tokio_metrics/

task.rs

use futures_util::task::{ArcWake, AtomicWaker};
use pin_project_lite::pin_project;
use std::future::Future;
use std::pin::Pin;
use std::sync::atomic::{AtomicU64, Ordering::SeqCst};
use std::sync::Arc;
use std::task::{Context, Poll};
use tokio_stream::Stream;

#[cfg(feature = "rt")]
use tokio::time::{Duration, Instant};

#[cfg(not(feature = "rt"))]
use std::time::{Duration, Instant};

/// Monitors key metrics of instrumented tasks.
///
/// ### Basic Usage
/// A [`TaskMonitor`] tracks key [metrics][TaskMetrics] of async tasks that have been
/// [instrumented][`TaskMonitor::instrument`] with the monitor.
///
/// In the below example, a [`TaskMonitor`] is [constructed][TaskMonitor::new] and used to
/// [instrument][TaskMonitor::instrument] three worker tasks; meanwhile, a fourth task
/// prints [metrics][TaskMetrics] in 500ms [intervals][TaskMonitor::intervals].
/// ```
/// use std::time::Duration;
///
/// #[tokio::main]
/// async fn main() {
///     // construct a metrics monitor
///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
///
///     // print task metrics every 500ms
///     {
///         let metrics_monitor = metrics_monitor.clone();
///         tokio::spawn(async move {
///             for interval in metrics_monitor.intervals() {
///                 // pretty-print the metric interval
///                 println!("{:?}", interval);
///                 // wait 500ms
///                 tokio::time::sleep(Duration::from_millis(500)).await;
///             }
///         });
///     }
///
///     // instrument some tasks and await them
///     // note that the same TaskMonitor can be used for multiple tasks
///     tokio::join![
///         metrics_monitor.instrument(do_work()),
///         metrics_monitor.instrument(do_work()),
///         metrics_monitor.instrument(do_work())
///     ];
/// }
///
/// async fn do_work() {
///     for _ in 0..25 {
///         tokio::task::yield_now().await;
///         tokio::time::sleep(Duration::from_millis(100)).await;
///     }
/// }
/// ```
///
/// ### What should I instrument?
/// In most cases, you should construct a *distinct* [`TaskMonitor`] for each kind of key task.
///
/// #### Instrumenting a web application
/// For instance, a web service should have a distinct [`TaskMonitor`] for each endpoint. Within
/// each endpoint, it's prudent to additionally instrument major sub-tasks, each with their own
/// distinct [`TaskMonitor`]s. [*Why are my tasks slow?*](#why-are-my-tasks-slow) explores a
/// debugging scenario for a web service that takes this approach to instrumentation. This
/// approach is exemplified in the below example:
/// ```no_run
/// // The unabridged version of this snippet is in the examples directory of this crate.
///
/// #[tokio::main]
/// async fn main() {
///     // construct a TaskMonitor for root endpoint
///     let monitor_root = tokio_metrics::TaskMonitor::new();
///
///     // construct TaskMonitors for create_users endpoint
///     let monitor_create_user = CreateUserMonitors {
///         // monitor for the entire endpoint
///         route: tokio_metrics::TaskMonitor::new(),
///         // monitor for database insertion subtask
///         insert: tokio_metrics::TaskMonitor::new(),
///     };
///
///     // build our application with two instrumented endpoints
///     let app = axum::Router::new()
///         // `GET /` goes to `root`
///         .route("/", axum::routing::get({
///             let monitor = monitor_root.clone();
///             move || monitor.instrument(async { "Hello, World!" })
///         }))
///         // `POST /users` goes to `create_user`
///         .route("/users", axum::routing::post({
///             let monitors = monitor_create_user.clone();
///             let route = monitors.route.clone();
///             move |payload| {
///                 route.instrument(create_user(payload, monitors))
///             }
///         }));
///
///     // print task metrics for each endpoint every 1s
///     let metrics_frequency = std::time::Duration::from_secs(1);
///     tokio::spawn(async move {
///         let root_intervals = monitor_root.intervals();
///         let create_user_route_intervals =
///             monitor_create_user.route.intervals();
///         let create_user_insert_intervals =
///             monitor_create_user.insert.intervals();
///         let create_user_intervals =
///             create_user_route_intervals.zip(create_user_insert_intervals);
///
///         let intervals = root_intervals.zip(create_user_intervals);
///         for (root_route, (create_user_route, create_user_insert)) in intervals {
///             println!("root_route = {:#?}", root_route);
///             println!("create_user_route = {:#?}", create_user_route);
///             println!("create_user_insert = {:#?}", create_user_insert);
///             tokio::time::sleep(metrics_frequency).await;
///         }
///     });
///
///     // run the server
///     let addr = std::net::SocketAddr::from(([127, 0, 0, 1], 3000));
///     axum::Server::bind(&addr)
///         .serve(app.into_make_service())
///         .await
///         .unwrap();
/// }
///
/// async fn create_user(
///     axum::Json(payload): axum::Json<CreateUser>,
///     monitors: CreateUserMonitors,
/// ) -> impl axum::response::IntoResponse {
///     let user = User { id: 1337, username: payload.username, };
///     // instrument inserting the user into the db:
///     let _ = monitors.insert.instrument(insert_user(user.clone())).await;
///     (axum::http::StatusCode::CREATED, axum::Json(user))
/// }
///
/// /* definitions of CreateUserMonitors, CreateUser and User omitted for brevity */
///
/// #
/// # #[derive(Clone)]
/// # struct CreateUserMonitors {
/// #     // monitor for the entire endpoint
/// #     route: tokio_metrics::TaskMonitor,
/// #     // monitor for database insertion subtask
/// #     insert: tokio_metrics::TaskMonitor,
/// # }
/// #
/// # #[derive(serde::Deserialize)] struct CreateUser { username: String, }
/// # #[derive(Clone, serde::Serialize)] struct User { id: u64, username: String, }
/// #
/// // insert the user into the database
/// async fn insert_user(_: User) {
///     /* implementation details elided */
///     tokio::time::sleep(std::time::Duration::from_secs(1)).await;
/// }
/// ```
///
/// ### Why are my tasks slow?
/// **Scenario:** You track key, high-level metrics about the customer response time. An alarm warns
/// you that P90 latency for an endpoint exceeds your targets. What is causing the increase?
///
/// #### Identifying the high-level culprits
/// A set of tasks will appear to execute more slowly if:
/// - they are taking longer to poll (i.e., they consume too much CPU time)
/// - they are waiting longer to be polled (e.g., they're waiting longer in tokio's scheduling
///   queues)
/// - they are waiting longer on external events to complete (e.g., asynchronous network requests)
///
/// The culprits, at a high level, may be some combination of these sources of latency. Fortunately,
/// you have instrumented the key tasks of each of your endpoints with distinct [`TaskMonitor`]s.
/// Using the monitors on the endpoint experiencing elevated latency, you begin by answering:
/// - [*Are my tasks taking longer to poll?*](#are-my-tasks-taking-longer-to-poll)
/// - [*Are my tasks spending more time waiting to be polled?*](#are-my-tasks-spending-more-time-waiting-to-be-polled)
/// - [*Are my tasks spending more time waiting on external events to complete?*](#are-my-tasks-spending-more-time-waiting-on-external-events-to-complete)
///
/// ##### Are my tasks taking longer to poll?
/// - **Did [`mean_poll_duration`][TaskMetrics::mean_poll_duration] increase?**   
///   This metric reflects the mean poll duration. If it increased, it means that, on average,
///   individual polls tended to take longer. However, this does not necessarily imply increased
///   task latency: An increase in poll durations could be offset by fewer polls.
/// - **Did [`slow_poll_ratio`][TaskMetrics::slow_poll_ratio] increase?**   
///   This metric reflects the proportion of polls that were 'slow'. If it increased, it means that
///   a greater proportion of polls performed excessive computation before yielding. This does not
///   necessarily imply increased task latency: An increase in the proportion of slow polls could be
///   offset by fewer or faster polls.
/// - **Did [`mean_slow_poll_duration`][TaskMetrics::mean_slow_poll_duration] increase?**   
///   This metric reflects the mean duration of slow polls. If it increased, it means that, on
///   average, slow polls got slower. This does not necessarily imply increased task latency: An
///   increase in average slow poll duration could be offset by fewer or faster polls.
///
/// If so, [*why are my tasks taking longer to poll?*](#why-are-my-tasks-taking-longer-to-poll)
///
/// ##### Are my tasks spending more time waiting to be polled?
/// - **Did [`mean_first_poll_delay`][TaskMetrics::mean_first_poll_delay] increase?**   
///   This metric reflects the mean delay between the instant a task is first instrumented and the
///   instant it is first polled. If it increases, it means that, on average, tasks spent longer
///   waiting to be initially run.
/// - **Did [`mean_scheduled_duration`][TaskMetrics::mean_scheduled_duration] increase?**   
///   This metric reflects the mean duration that tasks spent in the scheduled state. The
///   'scheduled' state of a task is the duration between the instant a task is awoken and the
///   instant it is subsequently polled. If this metric increases, it means that, on average, tasks
///   spent longer in tokio's queues before being polled.
/// - **Did [`long_delay_ratio`][TaskMetrics::long_delay_ratio] increase?**
///   This metric reflects the proportion of scheduling delays which were 'long'. If it increased,
///   it means that a greater proportion of tasks experienced excessive delays before they could
///   execute after being woken. This does not necessarily indicate an increase in latency, as this
///   could be offset by fewer or faster task polls.
/// - **Did [`mean_long_delay_duration`][TaskMetrics::mean_long_delay_duration] increase?**
///   This metric reflects the mean duration of long delays. If it increased, it means that, on
///   average, long delays got even longer. This does not necessarily imply increased task latency:
///   an increase in average long delay duration could be offset by fewer or faster polls or more
///   short schedules.
///
/// If so, [*why are my tasks spending more time waiting to be polled?*](#why-are-my-tasks-spending-more-time-waiting-to-be-polled)
///
/// ##### Are my tasks spending more time waiting on external events to complete?
/// - **Did [`mean_idle_duration`][TaskMetrics::mean_idle_duration] increase?**   
///   This metric reflects the mean duration that tasks spent in the idle state. The idle state is
///   the duration spanning the instant a task completes a poll, and the instant that it is next
///   awoken. Tasks inhabit this state when they are waiting for task-external events to complete
///   (e.g., an asynchronous sleep, a network request, file I/O, etc.). If this metric increases,
///   tasks, in aggregate, spent more time waiting for task-external events to complete.
///
/// If so, [*why are my tasks spending more time waiting on external events to complete?*](#why-are-my-tasks-spending-more-time-waiting-on-external-events-to-complete)
///
/// #### Digging deeper
/// Having [established the high-level culprits](#identifying-the-high-level-culprits), you now
/// search for further explanation...
///
/// ##### Why are my tasks taking longer to poll?
/// You observed that [your tasks are taking longer to poll](#are-my-tasks-taking-longer-to-poll).
/// The culprit is likely some combination of:
/// - **Your tasks are accidentally blocking.** Common culprits include:
///     1. Using the Rust standard library's [filesystem](https://doc.rust-lang.org/std/fs/) or
///        [networking](https://doc.rust-lang.org/std/net/) APIs.
///        These APIs are synchronous; use tokio's [filesystem](https://docs.rs/tokio/latest/tokio/fs/)
///        and [networking](https://docs.rs/tokio/latest/tokio/net/) APIs, instead.
///     3. Calling [`block_on`](https://docs.rs/tokio/latest/tokio/runtime/struct.Handle.html#method.block_on).
///     4. Invoking `println!` or other synchronous logging routines.   
///        Invocations of `println!` involve acquiring an exclusive lock on stdout, followed by a
///        synchronous write to stdout.
/// 2. **Your tasks are computationally expensive.** Common culprits include:
///     1. TLS/cryptographic routines
///     2. doing a lot of processing on bytes
///     3. calling non-Tokio resources
///
/// ##### Why are my tasks spending more time waiting to be polled?
/// You observed that [your tasks are spending more time waiting to be polled](#are-my-tasks-spending-more-time-waiting-to-be-polled)
/// suggesting some combination of:
/// - Your application is inflating the time elapsed between instrumentation and first poll.
/// - Your tasks are being scheduled into tokio's global queue.
/// - Other tasks are spending too long without yielding, thus backing up tokio's queues.
///
/// Start by asking: [*Is time-to-first-poll unusually high?*](#is-time-to-first-poll-unusually-high)
///
/// ##### Why are my tasks spending more time waiting on external events to complete?
/// You observed that [your tasks are spending more time waiting waiting on external events to
/// complete](#are-my-tasks-spending-more-time-waiting-on-external-events-to-complete). But what
/// event? Fortunately, within the task experiencing increased idle times, you monitored several
/// sub-tasks with distinct [`TaskMonitor`]s. For each of these sub-tasks, you [*you try to identify
/// the performance culprits...*](#identifying-the-high-level-culprits)
///
/// #### Digging even deeper
///
/// ##### Is time-to-first-poll unusually high?
/// Contrast these two metrics:
/// - **[`mean_first_poll_delay`][TaskMetrics::mean_first_poll_delay]**  
///   This metric reflects the mean delay between the instant a task is first instrumented and the
///   instant it is *first* polled.
/// - **[`mean_scheduled_duration`][TaskMetrics::mean_scheduled_duration]**  
///   This metric reflects the mean delay between the instant when tasks were awoken and the
///   instant they were subsequently polled.
///
/// If the former metric exceeds the latter (or increased unexpectedly more than the latter), then
/// start by investigating [*if your application is artificially delaying the time-to-first-poll*](#is-my-application-delaying-the-time-to-first-poll).
///
/// Otherwise, investigate [*if other tasks are polling too long without yielding*](#are-other-tasks-polling-too-long-without-yielding).
///
/// ##### Is my application delaying the time-to-first-poll?
/// You observed that [`mean_first_poll_delay`][TaskMetrics::mean_first_poll_delay] increased, more
/// than [`mean_scheduled_duration`][TaskMetrics::mean_scheduled_duration]. Your application may be
/// needlessly inflating the time elapsed between instrumentation and first poll. Are you
/// constructing (and instrumenting) tasks separately from awaiting or spawning them?
///
/// For instance, in the below example, the application induces 1 second delay between when `task`
/// is instrumented and when it is awaited:
/// ```rust
/// #[tokio::main]
/// async fn main() {
///     use tokio::time::Duration;
///     let monitor = tokio_metrics::TaskMonitor::new();
///
///     let task = monitor.instrument(async move {});
///
///     let one_sec = Duration::from_secs(1);
///     tokio::time::sleep(one_sec).await;
///
///     let _ = tokio::spawn(task).await;
///
///     assert!(monitor.cumulative().total_first_poll_delay >= one_sec);
/// }
/// ```
///
/// Otherwise, [`mean_first_poll_delay`][TaskMetrics::mean_first_poll_delay] might be unusually high
/// because [*your application is spawning key tasks into tokio's global queue...*](#is-my-application-spawning-more-tasks-into-tokio’s-global-queue)
///
/// ##### Is my application spawning more tasks into tokio's global queue?
/// Tasks awoken from threads *not* managed by the tokio runtime are scheduled with a slower,
/// global "injection" queue.
///
/// You may be notifying runtime tasks from off-runtime. For instance, Given the following:
/// ```ignore
/// #[tokio::main]
/// async fn main() {
///     for _ in 0..100 {
///         let (tx, rx) = oneshot::channel();
///         tokio::spawn(async move {
///             tx.send(());
///         })
///         
///         rx.await;
///     }
/// }
/// ```
/// One would expect this to run efficiently, however, the main task is run *off* the main runtime
/// and the spawned tasks are *on* runtime, which means the snippet will run much slower than:
/// ```ignore
/// #[tokio::main]
/// async fn main() {
///     tokio::spawn(async {
///         for _ in 0..100 {
///             let (tx, rx) = oneshot::channel();
///             tokio::spawn(async move {
///                 tx.send(());
///             })
///
///             rx.await;
///         }
///     }).await;
/// }
/// ```
/// The slowdown is caused by a higher time between the `rx` task being notified (in `tx.send()`)
/// and the task being polled.
///
/// ##### Are other tasks polling too long without yielding?
/// You suspect that your tasks are slow because they're backed up in tokio's scheduling queues. For
/// *each* of your application's [`TaskMonitor`]s you check to see [*if their associated tasks are
/// taking longer to poll...*](#are-my-tasks-taking-longer-to-poll)
///
/// ### Limitations
/// The [`TaskMetrics`] type uses [`u64`] to represent both event counters and durations (measured
/// in nanoseconds). Consequently, event counters are accurate for ≤ [`u64::MAX`] events, and
/// durations are accurate for ≤ [`u64::MAX`] nanoseconds.
///
/// The counters and durations of [`TaskMetrics`] produced by [`TaskMonitor::cumulative`] increase
/// monotonically with each successive invocation of [`TaskMonitor::cumulative`]. Upon overflow,
/// counters and durations wrap.
///
/// The counters and durations of [`TaskMetrics`] produced by [`TaskMonitor::intervals`] are
/// calculated by computing the difference of metrics in successive invocations of
/// [`TaskMonitor::cumulative`]. If, within a monitoring interval, an event occurs more than
/// [`u64::MAX`] times, or a monitored duration exceeds [`u64::MAX`] nanoseconds, the metrics for
/// that interval will overflow and not be accurate.
///
/// ##### Examples at the limits
/// Consider the [`TaskMetrics::total_first_poll_delay`] metric. This metric accurately reflects
/// delays between instrumentation and first-poll ≤ [`u64::MAX`] nanoseconds:
/// ```
/// use tokio::time::Duration;
///
/// #[tokio::main(flavor = "current_thread", start_paused = true)]
/// async fn main() {
///     let monitor = tokio_metrics::TaskMonitor::new();
///     let mut interval = monitor.intervals();
///     let mut next_interval = || interval.next().unwrap();
///
///     // construct and instrument a task, but do not `await` it
///     let task = monitor.instrument(async {});
///
///     // this is the maximum duration representable by tokio_metrics
///     let max_duration = Duration::from_nanos(u64::MAX);
///
///     // let's advance the clock by this amount and poll `task`
///     let _ = tokio::time::advance(max_duration).await;
///     task.await;
///
///     // durations ≤ `max_duration` are accurately reflected in this metric
///     assert_eq!(next_interval().total_first_poll_delay, max_duration);
///     assert_eq!(monitor.cumulative().total_first_poll_delay, max_duration);
/// }
/// ```
/// If the total delay between instrumentation and first poll exceeds [`u64::MAX`] nanoseconds,
/// [`total_first_poll_delay`][TaskMetrics::total_first_poll_delay] will overflow:
/// ```
/// # use tokio::time::Duration;
/// #
/// # #[tokio::main(flavor = "current_thread", start_paused = true)]
/// # async fn main() {
/// #    let monitor = tokio_metrics::TaskMonitor::new();
/// #
///  // construct and instrument a task, but do not `await` it
///  let task_a = monitor.instrument(async {});
///  let task_b = monitor.instrument(async {});
///
///  // this is the maximum duration representable by tokio_metrics
///  let max_duration = Duration::from_nanos(u64::MAX);
///
///  // let's advance the clock by 1.5x this amount and await `task`
///  let _ = tokio::time::advance(3 * (max_duration / 2)).await;
///  task_a.await;
///  task_b.await;
///
///  // the `total_first_poll_delay` has overflowed
///  assert!(monitor.cumulative().total_first_poll_delay < max_duration);
/// # }
/// ```
/// If *many* tasks are spawned, it will take far less than a [`u64::MAX`]-nanosecond delay to bring
/// this metric to the precipice of overflow:
/// ```
/// # use tokio::time::Duration;
/// #
/// # #[tokio::main(flavor = "current_thread", start_paused = true)]
/// # async fn main() {
/// #     let monitor = tokio_metrics::TaskMonitor::new();
/// #     let mut interval = monitor.intervals();
/// #     let mut next_interval = || interval.next().unwrap();
/// #
/// // construct and instrument u16::MAX tasks, but do not `await` them
/// let first_poll_count = u16::MAX as u64;
/// let mut tasks = Vec::with_capacity(first_poll_count as usize);
/// for _ in 0..first_poll_count { tasks.push(monitor.instrument(async {})); }
///
/// // this is the maximum duration representable by tokio_metrics
/// let max_duration = u64::MAX;
///
/// // let's advance the clock justenough such that all of the time-to-first-poll
/// // delays summed nearly equals `max_duration_nanos`, less some remainder...
/// let iffy_delay = max_duration / (first_poll_count as u64);
/// let small_remainder = max_duration % first_poll_count;
/// let _ = tokio::time::advance(Duration::from_nanos(iffy_delay)).await;
///
/// // ...then poll all of the instrumented tasks:
/// for task in tasks { task.await; }
///
/// // `total_first_poll_delay` is at the precipice of overflowing!
/// assert_eq!(
///     next_interval().total_first_poll_delay.as_nanos(),
///     (max_duration - small_remainder) as u128
/// );
/// assert_eq!(
///     monitor.cumulative().total_first_poll_delay.as_nanos(),
///     (max_duration - small_remainder) as u128
/// );
/// # }
/// ```
/// Frequent, interval-sampled metrics will retain their accuracy, even if the cumulative
/// metrics counter overflows at most once in the midst of an interval:
/// ```
/// # use tokio::time::Duration;
/// # use tokio_metrics::TaskMonitor;
/// #
/// # #[tokio::main(flavor = "current_thread", start_paused = true)]
/// # async fn main() {
/// #     let monitor = TaskMonitor::new();
/// #     let mut interval = monitor.intervals();
/// #     let mut next_interval = || interval.next().unwrap();
/// #
///  let first_poll_count = u16::MAX as u64;
///  let batch_size = first_poll_count / 3;
///
///  let max_duration_ns = u64::MAX;
///  let iffy_delay_ns = max_duration_ns / first_poll_count;
///
///  // Instrument `batch_size` number of tasks, wait for `delay` nanoseconds,
///  // then await the instrumented tasks.
///  async fn run_batch(monitor: &TaskMonitor, batch_size: usize, delay: u64) {
///      let mut tasks = Vec::with_capacity(batch_size);
///      for _ in 0..batch_size { tasks.push(monitor.instrument(async {})); }
///      let _ = tokio::time::advance(Duration::from_nanos(delay)).await;
///      for task in tasks { task.await; }
///  }
///
///  // this is how much `total_time_to_first_poll_ns` will
///  // increase with each batch we run
///  let batch_delay = iffy_delay_ns * batch_size;
///
///  // run batches 1, 2, and 3
///  for i in 1..=3 {
///      run_batch(&monitor, batch_size as usize, iffy_delay_ns).await;
///      assert_eq!(1 * batch_delay as u128, next_interval().total_first_poll_delay.as_nanos());
///      assert_eq!(i * batch_delay as u128, monitor.cumulative().total_first_poll_delay.as_nanos());
///  }
///
///  /* now, the `total_time_to_first_poll_ns` counter is at the precipice of overflow */
///  assert_eq!(monitor.cumulative().total_first_poll_delay.as_nanos(), max_duration_ns as u128);
///
///  // run batch 4
///  run_batch(&monitor, batch_size as usize, iffy_delay_ns).await;
///  // the interval counter remains accurate
///  assert_eq!(1 * batch_delay as u128, next_interval().total_first_poll_delay.as_nanos());
///  // but the cumulative counter has overflowed
///  assert_eq!(batch_delay as u128 - 1, monitor.cumulative().total_first_poll_delay.as_nanos());
/// # }
/// ```
/// If a cumulative metric overflows *more than once* in the midst of an interval,
/// its interval-sampled counterpart will also overflow.
#[derive(Clone, Debug)]
pub struct TaskMonitor {
    metrics: Arc<RawMetrics>,
}

/// Provides an interface for constructing a [`TaskMonitor`] with specialized configuration
/// parameters.
#[derive(Clone, Debug, Default)]
pub struct TaskMonitorBuilder {
    slow_poll_threshold: Option<Duration>,
    long_delay_threshold: Option<Duration>,
}

impl TaskMonitorBuilder {
    /// Creates a new [`TaskMonitorBuilder`].
    pub fn new() -> Self {
        Self {
            slow_poll_threshold: None,
            long_delay_threshold: None,
        }
    }

    /// Specifies the threshold at which polls are considered 'slow'.
    pub fn with_slow_poll_threshold(&mut self, threshold: Duration) -> &mut Self {
        self.slow_poll_threshold = Some(threshold);

        self
    }

    /// Specifies the threshold at which schedules are considered 'long'.
    pub fn with_long_delay_threshold(&mut self, threshold: Duration) -> &mut Self {
        self.long_delay_threshold = Some(threshold);

        self
    }

    /// Consume the builder, producing a [`TaskMonitor`].
    pub fn build(self) -> TaskMonitor {
        TaskMonitor::create(
            self.slow_poll_threshold
                .unwrap_or(TaskMonitor::DEFAULT_SLOW_POLL_THRESHOLD),
            self.long_delay_threshold
                .unwrap_or(TaskMonitor::DEFAULT_LONG_DELAY_THRESHOLD),
        )
    }
}

pin_project! {
    /// An async task that has been instrumented with [`TaskMonitor::instrument`].
    #[derive(Debug)]
    pub struct Instrumented<T> {
        // The task being instrumented
        #[pin]
        task: T,

        // True when the task is polled for the first time
        did_poll_once: bool,

        // The instant, tracked as nanoseconds since `instrumented_at`, at which the future finished
        // its last poll.
        idled_at: u64,

        // State shared between the task and its instrumented waker.
        state: Arc<State>,
    }

    impl<T> PinnedDrop for Instrumented<T> {
        fn drop(this: Pin<&mut Self>) {
            this.state.metrics.dropped_count.fetch_add(1, SeqCst);
        }
    }
}

/// Key metrics of [instrumented][`TaskMonitor::instrument`] tasks.
#[non_exhaustive]
#[derive(Debug, Clone, Copy, Default)]
pub struct TaskMetrics {
    /// The number of tasks instrumented.
    ///
    /// ##### Examples
    /// ```
    /// #[tokio::main]
    /// async fn main() {
    ///     let monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // 0 tasks have been instrumented
    ///     assert_eq!(next_interval().instrumented_count, 0);
    ///
    ///     monitor.instrument(async {});
    ///
    ///     // 1 task has been instrumented
    ///     assert_eq!(next_interval().instrumented_count, 1);
    ///
    ///     monitor.instrument(async {});
    ///     monitor.instrument(async {});
    ///
    ///     // 2 tasks have been instrumented
    ///     assert_eq!(next_interval().instrumented_count, 2);
    ///
    ///     // since the last interval was produced, 0 tasks have been instrumented
    ///     assert_eq!(next_interval().instrumented_count, 0);
    /// }
    /// ```
    pub instrumented_count: u64,

    /// The number of tasks dropped.
    ///
    /// ##### Examples
    /// ```
    /// #[tokio::main]
    /// async fn main() {
    ///     let monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // 0 tasks have been dropped
    ///     assert_eq!(next_interval().dropped_count, 0);
    ///
    ///     let _task = monitor.instrument(async {});
    ///
    ///     // 0 tasks have been dropped
    ///     assert_eq!(next_interval().dropped_count, 0);
    ///
    ///     monitor.instrument(async {}).await;
    ///     drop(monitor.instrument(async {}));
    ///
    ///     // 2 tasks have been dropped
    ///     assert_eq!(next_interval().dropped_count, 2);
    ///
    ///     // since the last interval was produced, 0 tasks have been dropped
    ///     assert_eq!(next_interval().dropped_count, 0);
    /// }
    /// ```
    pub dropped_count: u64,

    /// The number of tasks polled for the first time.
    ///
    /// ##### Derived metrics
    /// - **[`mean_first_poll_delay`][TaskMetrics::mean_first_poll_delay]**  
    ///   The mean duration elapsed between the instant tasks are instrumented, and the instant they
    ///   are first polled.
    ///
    /// ##### Examples
    /// In the below example, no tasks are instrumented or polled in the first sampling interval;
    /// one task is instrumented (but not polled) in the second sampling interval; that task is
    /// awaited to completion (and, thus, polled at least once) in the third sampling interval; no
    /// additional tasks are polled for the first time within the fourth sampling interval:
    /// ```
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // no tasks have been constructed, instrumented, and polled at least once
    ///     assert_eq!(next_interval().first_poll_count, 0);
    ///
    ///     let task = metrics_monitor.instrument(async {});
    ///
    ///     // `task` has been constructed and instrumented, but has not yet been polled
    ///     assert_eq!(next_interval().first_poll_count, 0);
    ///
    ///     // poll `task` to completion
    ///     task.await;
    ///
    ///     // `task` has been constructed, instrumented, and polled at least once
    ///     assert_eq!(next_interval().first_poll_count, 1);
    ///
    ///     // since the last interval was produced, 0 tasks have been constructed, instrumented and polled
    ///     assert_eq!(next_interval().first_poll_count, 0);
    ///
    /// }
    /// ```
    pub first_poll_count: u64,

    /// The total duration elapsed between the instant tasks are instrumented, and the instant they
    /// are first polled.
    ///
    /// ##### Derived metrics
    /// - **[`mean_first_poll_delay`][TaskMetrics::mean_first_poll_delay]**   
    ///   The mean duration elapsed between the instant tasks are instrumented, and the instant they
    ///   are first polled.
    ///
    /// ##### Examples
    /// In the below example, 0 tasks have been instrumented or polled within the first sampling
    /// interval, a total of 500ms elapse between the instrumentation and polling of tasks within
    /// the second sampling interval, and a total of 350ms elapse between the instrumentation and
    /// polling of tasks within the third sampling interval:
    /// ```
    /// use tokio::time::Duration;
    ///
    /// #[tokio::main(flavor = "current_thread", start_paused = true)]
    /// async fn main() {
    ///     let monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // no tasks have yet been created, instrumented, or polled
    ///     assert_eq!(monitor.cumulative().total_first_poll_delay, Duration::ZERO);
    ///     assert_eq!(next_interval().total_first_poll_delay, Duration::ZERO);
    ///
    ///     // constructs and instruments a task, pauses a given duration, then awaits the task
    ///     async fn instrument_pause_await(monitor: &tokio_metrics::TaskMonitor, pause: Duration) {
    ///         let task = monitor.instrument(async move {});
    ///         tokio::time::sleep(pause).await;
    ///         task.await;
    ///     }
    ///
    ///     // construct and await a task that pauses for 500ms between instrumentation and first poll
    ///     let task_a_pause_time = Duration::from_millis(500);
    ///     instrument_pause_await(&monitor, task_a_pause_time).await;
    ///
    ///     assert_eq!(next_interval().total_first_poll_delay, task_a_pause_time);
    ///     assert_eq!(monitor.cumulative().total_first_poll_delay, task_a_pause_time);
    ///
    ///     // construct and await a task that pauses for 250ms between instrumentation and first poll
    ///     let task_b_pause_time = Duration::from_millis(250);
    ///     instrument_pause_await(&monitor, task_b_pause_time).await;
    ///
    ///     // construct and await a task that pauses for 100ms between instrumentation and first poll
    ///     let task_c_pause_time = Duration::from_millis(100);
    ///     instrument_pause_await(&monitor, task_c_pause_time).await;
    ///
    ///     assert_eq!(
    ///         next_interval().total_first_poll_delay,
    ///         task_b_pause_time + task_c_pause_time
    ///     );
    ///     assert_eq!(
    ///         monitor.cumulative().total_first_poll_delay,
    ///         task_a_pause_time + task_b_pause_time + task_c_pause_time
    ///     );
    /// }
    /// ```
    ///
    /// ##### When is this metric recorded?
    /// The delay between instrumentation and first poll is not recorded until the first poll
    /// actually occurs:
    /// ```
    /// # use tokio::time::Duration;
    /// #
    /// # #[tokio::main(flavor = "current_thread", start_paused = true)]
    /// # async fn main() {
    /// #     let monitor = tokio_metrics::TaskMonitor::new();
    /// #     let mut interval = monitor.intervals();
    /// #     let mut next_interval = || interval.next().unwrap();
    /// #
    /// // we construct and instrument a task, but do not `await` it
    /// let task = monitor.instrument(async {});
    ///
    /// // let's sleep for 1s before we poll `task`
    /// let one_sec = Duration::from_secs(1);
    /// let _ = tokio::time::sleep(one_sec).await;
    ///
    /// // although 1s has now elapsed since the instrumentation of `task`,
    /// // this is not reflected in `total_first_poll_delay`...
    /// assert_eq!(next_interval().total_first_poll_delay, Duration::ZERO);
    /// assert_eq!(monitor.cumulative().total_first_poll_delay, Duration::ZERO);
    ///
    /// // ...and won't be until `task` is actually polled
    /// task.await;
    ///
    /// // now, the 1s delay is reflected in `total_first_poll_delay`:
    /// assert_eq!(next_interval().total_first_poll_delay, one_sec);
    /// assert_eq!(monitor.cumulative().total_first_poll_delay, one_sec);
    /// # }
    /// ```
    ///
    /// ##### What if first-poll-delay is very large?
    /// The first-poll-delay of *individual* tasks saturates at `u64::MAX` nanoseconds. However, if
    /// the *total* first-poll-delay *across* monitored tasks exceeds `u64::MAX` nanoseconds, this
    /// metric will wrap around:
    /// ```
    /// use tokio::time::Duration;
    ///
    /// #[tokio::main(flavor = "current_thread", start_paused = true)]
    /// async fn main() {
    ///     let monitor = tokio_metrics::TaskMonitor::new();
    ///
    ///     // construct and instrument a task, but do not `await` it
    ///     let task = monitor.instrument(async {});
    ///
    ///     // this is the maximum duration representable by tokio_metrics
    ///     let max_duration = Duration::from_nanos(u64::MAX);
    ///
    ///     // let's advance the clock by double this amount and await `task`
    ///     let _ = tokio::time::advance(max_duration * 2).await;
    ///     task.await;
    ///
    ///     // the time-to-first-poll of `task` saturates at `max_duration`
    ///     assert_eq!(monitor.cumulative().total_first_poll_delay, max_duration);
    ///
    ///     // ...but note that the metric *will* wrap around if more tasks are involved
    ///     let task = monitor.instrument(async {});
    ///     let _ = tokio::time::advance(Duration::from_nanos(1)).await;
    ///     task.await;
    ///     assert_eq!(monitor.cumulative().total_first_poll_delay, Duration::ZERO);
    /// }
    /// ```
    pub total_first_poll_delay: Duration,

    /// The total number of times that tasks idled, waiting to be awoken.
    ///
    /// An idle is recorded as occurring if a non-zero duration elapses between the instant a
    /// task completes a poll, and the instant that it is next awoken.
    ///
    /// ##### Derived metrics
    /// - **[`mean_idle_duration`][TaskMetrics::mean_idle_duration]**   
    ///   The mean duration of idles.
    ///
    /// ##### Examples
    /// ```
    /// #[tokio::main(flavor = "current_thread", start_paused = true)]
    /// async fn main() {
    ///     let monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = monitor.intervals();
    ///     let mut next_interval = move || interval.next().unwrap();
    ///     let one_sec = std::time::Duration::from_secs(1);
    ///
    ///     monitor.instrument(async {}).await;
    ///
    ///     assert_eq!(next_interval().total_idled_count, 0);
    ///     assert_eq!(monitor.cumulative().total_idled_count, 0);
    ///
    ///     monitor.instrument(async move {
    ///         tokio::time::sleep(one_sec).await;
    ///     }).await;
    ///
    ///     assert_eq!(next_interval().total_idled_count, 1);
    ///     assert_eq!(monitor.cumulative().total_idled_count, 1);
    ///
    ///     monitor.instrument(async {
    ///         tokio::time::sleep(one_sec).await;
    ///         tokio::time::sleep(one_sec).await;
    ///     }).await;
    ///
    ///     assert_eq!(next_interval().total_idled_count, 2);
    ///     assert_eq!(monitor.cumulative().total_idled_count, 3);
    /// }
    /// ```
    pub total_idled_count: u64,

    /// The total duration that tasks idled.
    ///
    /// An idle is recorded as occurring if a non-zero duration elapses between the instant a
    /// task completes a poll, and the instant that it is next awoken.
    ///
    /// ##### Derived metrics
    /// - **[`mean_idle_duration`][TaskMetrics::mean_idle_duration]**   
    ///   The mean duration of idles.
    ///
    /// ##### Examples
    /// ```
    /// #[tokio::main(flavor = "current_thread", start_paused = true)]
    /// async fn main() {
    ///     let monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = monitor.intervals();
    ///     let mut next_interval = move || interval.next().unwrap();
    ///     let one_sec = std::time::Duration::from_secs(1);
    ///     let two_sec = std::time::Duration::from_secs(2);
    ///
    ///     assert_eq!(next_interval().total_idle_duration.as_nanos(), 0);
    ///     assert_eq!(monitor.cumulative().total_idle_duration.as_nanos(), 0);
    ///
    ///     monitor.instrument(async move {
    ///         tokio::time::sleep(one_sec).await;
    ///     }).await;
    ///
    ///     assert_eq!(next_interval().total_idle_duration, one_sec);
    ///     assert_eq!(monitor.cumulative().total_idle_duration, one_sec);
    ///
    ///     monitor.instrument(async move {
    ///         tokio::time::sleep(two_sec).await;
    ///     }).await;
    ///
    ///     assert_eq!(next_interval().total_idle_duration, two_sec);
    ///     assert_eq!(monitor.cumulative().total_idle_duration, one_sec + two_sec);
    /// }
    /// ```
    pub total_idle_duration: Duration,

    /// The total number of times that tasks were awoken (and then, presumably, scheduled for
    /// execution).
    ///
    /// ##### Definition
    /// This metric is equal to [`total_short_delay_duration`][TaskMetrics::total_short_delay_duration]
    /// \+ [`total_long_delay_duration`][TaskMetrics::total_long_delay_duration].
    ///
    /// ##### Derived metrics
    /// - **[`mean_scheduled_duration`][TaskMetrics::mean_scheduled_duration]**   
    ///   The mean duration that tasks spent waiting to be executed after awakening.
    ///
    /// ##### Examples
    /// In the below example, a task yields to the scheduler a varying number of times between
    /// sampling intervals; this metric is equal to the number of times the task yielded:
    /// ```
    /// #[tokio::main]
    /// async fn main(){
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///
    ///     // [A] no tasks have been created, instrumented, and polled more than once
    ///     assert_eq!(metrics_monitor.cumulative().total_scheduled_count, 0);
    ///
    ///     // [B] a `task` is created and instrumented
    ///     let task = {
    ///         let monitor = metrics_monitor.clone();
    ///         metrics_monitor.instrument(async move {
    ///             let mut interval = monitor.intervals();
    ///             let mut next_interval = move || interval.next().unwrap();
    ///
    ///             // [E] `task` has not yet yielded to the scheduler, and
    ///             // thus has not yet been scheduled since its first `poll`
    ///             assert_eq!(next_interval().total_scheduled_count, 0);
    ///
    ///             tokio::task::yield_now().await; // yield to the scheduler
    ///
    ///             // [F] `task` has yielded to the scheduler once (and thus been
    ///             // scheduled once) since the last sampling interval
    ///             assert_eq!(next_interval().total_scheduled_count, 1);
    ///
    ///             tokio::task::yield_now().await; // yield to the scheduler
    ///             tokio::task::yield_now().await; // yield to the scheduler
    ///             tokio::task::yield_now().await; // yield to the scheduler
    ///
    ///             // [G] `task` has yielded to the scheduler thrice (and thus been
    ///             // scheduled thrice) since the last sampling interval
    ///             assert_eq!(next_interval().total_scheduled_count, 3);
    ///
    ///             tokio::task::yield_now().await; // yield to the scheduler
    ///
    ///             next_interval
    ///         })
    ///     };
    ///
    ///     // [C] `task` has not yet been polled at all
    ///     assert_eq!(metrics_monitor.cumulative().first_poll_count, 0);
    ///     assert_eq!(metrics_monitor.cumulative().total_scheduled_count, 0);
    ///
    ///     // [D] poll `task` to completion
    ///     let mut next_interval = task.await;
    ///
    ///     // [H] `task` has been polled 1 times since the last sample
    ///     assert_eq!(next_interval().total_scheduled_count, 1);
    ///
    ///     // [I] `task` has been polled 0 times since the last sample
    ///     assert_eq!(next_interval().total_scheduled_count, 0);
    ///
    ///     // [J] `task` has yielded to the scheduler a total of five times
    ///     assert_eq!(metrics_monitor.cumulative().total_scheduled_count, 5);
    /// }
    /// ```
    #[doc(alias = "total_delay_count")]
    pub total_scheduled_count: u64,

    /// The total duration that tasks spent waiting to be polled after awakening.
    ///
    /// ##### Definition
    /// This metric is equal to [`total_short_delay_count`][TaskMetrics::total_short_delay_count]
    /// \+ [`total_long_delay_count`][TaskMetrics::total_long_delay_count].
    ///
    /// ##### Derived metrics
    /// - **[`mean_scheduled_duration`][TaskMetrics::mean_scheduled_duration]**   
    ///   The mean duration that tasks spent waiting to be executed after awakening.
    ///
    /// ##### Examples
    /// ```
    /// use tokio::time::Duration;
    ///
    /// #[tokio::main(flavor = "current_thread")]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // construct and instrument and spawn a task that yields endlessly
    ///     tokio::spawn(metrics_monitor.instrument(async {
    ///         loop { tokio::task::yield_now().await }
    ///     }));
    ///
    ///     tokio::task::yield_now().await;
    ///
    ///     // block the executor for 1 second
    ///     std::thread::sleep(Duration::from_millis(1000));
    ///
    ///     tokio::task::yield_now().await;
    ///
    ///     // `endless_task` will have spent approximately one second waiting
    ///     let total_scheduled_duration = next_interval().total_scheduled_duration;
    ///     assert!(total_scheduled_duration >= Duration::from_millis(1000));
    ///     assert!(total_scheduled_duration <= Duration::from_millis(1100));
    /// }
    /// ```
    #[doc(alias = "total_delay_duration")]
    pub total_scheduled_duration: Duration,

    /// The total number of times that tasks were polled.
    ///
    /// ##### Definition
    /// This metric is equal to [`total_fast_poll_count`][TaskMetrics::total_fast_poll_count]
    /// \+ [`total_slow_poll_count`][TaskMetrics::total_slow_poll_count].
    ///
    /// ##### Derived metrics
    /// - **[`mean_poll_duration`][TaskMetrics::mean_poll_duration]**   
    ///   The mean duration of polls.
    ///
    /// ##### Examples
    /// In the below example, a task with multiple yield points is await'ed to completion; this
    /// metric reflects the number of `await`s within each sampling interval:
    /// ```
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///
    ///     // [A] no tasks have been created, instrumented, and polled more than once
    ///     assert_eq!(metrics_monitor.cumulative().first_poll_count, 0);
    ///
    ///     // [B] a `task` is created and instrumented
    ///     let task = {
    ///         let monitor = metrics_monitor.clone();
    ///         metrics_monitor.instrument(async move {
    ///             let mut interval = monitor.intervals();
    ///             let mut next_interval = move || interval.next().unwrap();
    ///
    ///             // [E] task is in the midst of its first poll
    ///             assert_eq!(next_interval().total_poll_count, 0);
    ///
    ///             tokio::task::yield_now().await; // poll 1
    ///
    ///             // [F] task has been polled 1 time
    ///             assert_eq!(next_interval().total_poll_count, 1);
    ///
    ///             tokio::task::yield_now().await; // poll 2
    ///             tokio::task::yield_now().await; // poll 3
    ///             tokio::task::yield_now().await; // poll 4
    ///
    ///             // [G] task has been polled 3 times
    ///             assert_eq!(next_interval().total_poll_count, 3);
    ///
    ///             tokio::task::yield_now().await; // poll 5
    ///
    ///             next_interval                   // poll 6
    ///         })
    ///     };
    ///
    ///     // [C] `task` has not yet been polled at all
    ///     assert_eq!(metrics_monitor.cumulative().total_poll_count, 0);
    ///
    ///     // [D] poll `task` to completion
    ///     let mut next_interval = task.await;
    ///
    ///     // [H] `task` has been polled 2 times since the last sample
    ///     assert_eq!(next_interval().total_poll_count, 2);
    ///
    ///     // [I] `task` has been polled 0 times since the last sample
    ///     assert_eq!(next_interval().total_poll_count, 0);
    ///
    ///     // [J] `task` has been polled 6 times
    ///     assert_eq!(metrics_monitor.cumulative().total_poll_count, 6);
    /// }
    /// ```
    pub total_poll_count: u64,

    /// The total duration elapsed during polls.
    ///
    /// ##### Definition
    /// This metric is equal to [`total_fast_poll_duration`][TaskMetrics::total_fast_poll_duration]
    /// \+ [`total_slow_poll_duration`][TaskMetrics::total_slow_poll_duration].
    ///
    /// ##### Derived metrics
    /// - **[`mean_poll_duration`][TaskMetrics::mean_poll_duration]**   
    ///   The mean duration of polls.
    ///
    /// #### Examples
    /// ```
    /// use tokio::time::Duration;
    ///
    /// #[tokio::main(flavor = "current_thread", start_paused = true)]
    /// async fn main() {
    ///     let monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = monitor.intervals();
    ///     let mut next_interval = move || interval.next().unwrap();
    ///
    ///     assert_eq!(next_interval().total_poll_duration, Duration::ZERO);
    ///
    ///     monitor.instrument(async {
    ///         tokio::time::advance(Duration::from_secs(1)).await; // poll 1 (1s)
    ///         tokio::time::advance(Duration::from_secs(1)).await; // poll 2 (1s)
    ///         ()                                                  // poll 3 (0s)
    ///     }).await;
    ///
    ///     assert_eq!(next_interval().total_poll_duration, Duration::from_secs(2));
    /// }
    /// ```
    pub total_poll_duration: Duration,

    /// The total number of times that polling tasks completed swiftly.
    ///
    /// Here, 'swiftly' is defined as completing in strictly less time than
    /// [`slow_poll_threshold`][TaskMonitor::slow_poll_threshold].
    ///
    /// ##### Derived metrics
    /// - **[`mean_fast_poll_duration`][TaskMetrics::mean_fast_poll_duration]**   
    ///   The mean duration of fast polls.
    ///
    /// ##### Examples
    /// In the below example, 0 polls occur within the first sampling interval, 3 fast polls occur
    /// within the second sampling interval, and 2 fast polls occur within the third sampling
    /// interval:
    /// ```
    /// use std::future::Future;
    /// use std::time::Duration;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // no tasks have been constructed, instrumented, or polled
    ///     assert_eq!(next_interval().total_fast_poll_count, 0);
    ///
    ///     let fast = Duration::ZERO;
    ///
    ///     // this task completes in three fast polls
    ///     let _ = metrics_monitor.instrument(async {
    ///         spin_for(fast).await; // fast poll 1
    ///         spin_for(fast).await; // fast poll 2
    ///         spin_for(fast)        // fast poll 3
    ///     }).await;
    ///
    ///     assert_eq!(next_interval().total_fast_poll_count, 3);
    ///
    ///     // this task completes in two fast polls
    ///     let _ = metrics_monitor.instrument(async {
    ///         spin_for(fast).await; // fast poll 1
    ///         spin_for(fast)        // fast poll 2
    ///     }).await;
    ///
    ///     assert_eq!(next_interval().total_fast_poll_count, 2);
    /// }
    ///
    /// /// Block the current thread for a given `duration`, then (optionally) yield to the scheduler.
    /// fn spin_for(duration: Duration) -> impl Future<Output=()> {
    ///     let start = tokio::time::Instant::now();
    ///     while start.elapsed() <= duration {}
    ///     tokio::task::yield_now()
    /// }
    /// ```
    pub total_fast_poll_count: u64,

    /// The total duration of fast polls.
    ///
    /// Here, 'fast' is defined as completing in strictly less time than
    /// [`slow_poll_threshold`][TaskMonitor::slow_poll_threshold].
    ///
    /// ##### Derived metrics
    /// - **[`mean_fast_poll_duration`][TaskMetrics::mean_fast_poll_duration]**   
    ///   The mean duration of fast polls.
    ///
    /// ##### Examples
    /// In the below example, no tasks are polled in the first sampling interval; three fast polls
    /// consume a total of 3μs time in the second sampling interval; and two fast polls consume a
    /// total of 2μs time in the third sampling interval:
    /// ```
    /// use std::future::Future;
    /// use std::time::Duration;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // no tasks have been constructed, instrumented, or polled
    ///     let interval = next_interval();
    ///     assert_eq!(interval.total_fast_poll_duration, Duration::ZERO);
    ///
    ///     let fast = Duration::from_micros(1);
    ///
    ///     // this task completes in three fast polls
    ///     let task_a_time = time(metrics_monitor.instrument(async {
    ///         spin_for(fast).await; // fast poll 1
    ///         spin_for(fast).await; // fast poll 2
    ///         spin_for(fast)        // fast poll 3
    ///     })).await;
    ///
    ///     let interval = next_interval();
    ///     assert!(interval.total_fast_poll_duration >= fast * 3);
    ///     assert!(interval.total_fast_poll_duration <= task_a_time);
    ///
    ///     // this task completes in two fast polls
    ///     let task_b_time = time(metrics_monitor.instrument(async {
    ///         spin_for(fast).await; // fast poll 1
    ///         spin_for(fast)        // fast poll 2
    ///     })).await;
    ///
    ///     let interval = next_interval();
    ///     assert!(interval.total_fast_poll_duration >= fast * 2);
    ///     assert!(interval.total_fast_poll_duration <= task_b_time);
    /// }
    ///
    /// /// Produces the amount of time it took to await a given async task.
    /// async fn time(task: impl Future) -> Duration {
    ///     let start = tokio::time::Instant::now();
    ///     task.await;
    ///     start.elapsed()
    /// }
    ///
    /// /// Block the current thread for a given `duration`, then (optionally) yield to the scheduler.
    /// fn spin_for(duration: Duration) -> impl Future<Output=()> {
    ///     let start = tokio::time::Instant::now();
    ///     while start.elapsed() <= duration {}
    ///     tokio::task::yield_now()
    /// }
    /// ```
    pub total_fast_poll_duration: Duration,

    /// The total number of times that polling tasks completed slowly.
    ///
    /// Here, 'slowly' is defined as completing in at least as much time as
    /// [`slow_poll_threshold`][TaskMonitor::slow_poll_threshold].
    ///
    /// ##### Derived metrics
    /// - **[`mean_slow_poll_duration`][`TaskMetrics::mean_slow_poll_duration`]**   
    ///   The mean duration of slow polls.
    ///
    /// ##### Examples
    /// In the below example, 0 polls occur within the first sampling interval, 3 slow polls occur
    /// within the second sampling interval, and 2 slow polls occur within the third sampling
    /// interval:
    /// ```
    /// use std::future::Future;
    /// use std::time::Duration;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // no tasks have been constructed, instrumented, or polled
    ///     assert_eq!(next_interval().total_slow_poll_count, 0);
    ///
    ///     let slow = 10 * metrics_monitor.slow_poll_threshold();
    ///
    ///     // this task completes in three slow polls
    ///     let _ = metrics_monitor.instrument(async {
    ///         spin_for(slow).await; // slow poll 1
    ///         spin_for(slow).await; // slow poll 2
    ///         spin_for(slow)        // slow poll 3
    ///     }).await;
    ///
    ///     assert_eq!(next_interval().total_slow_poll_count, 3);
    ///
    ///     // this task completes in two slow polls
    ///     let _ = metrics_monitor.instrument(async {
    ///         spin_for(slow).await; // slow poll 1
    ///         spin_for(slow)        // slow poll 2
    ///     }).await;
    ///
    ///     assert_eq!(next_interval().total_slow_poll_count, 2);
    /// }
    ///
    /// /// Block the current thread for a given `duration`, then (optionally) yield to the scheduler.
    /// fn spin_for(duration: Duration) -> impl Future<Output=()> {
    ///     let start = tokio::time::Instant::now();
    ///     while start.elapsed() <= duration {}
    ///     tokio::task::yield_now()
    /// }
    /// ```
    pub total_slow_poll_count: u64,

    /// The total duration of slow polls.
    ///
    /// Here, 'slowly' is defined as completing in at least as much time as
    /// [`slow_poll_threshold`][TaskMonitor::slow_poll_threshold].
    ///
    /// ##### Derived metrics
    /// - **[`mean_slow_poll_duration`][`TaskMetrics::mean_slow_poll_duration`]**   
    ///   The mean duration of slow polls.
    ///
    /// ##### Examples
    /// In the below example, no tasks are polled in the first sampling interval; three slow polls
    /// consume a total of
    /// 30 × [`DEFAULT_SLOW_POLL_THRESHOLD`][TaskMonitor::DEFAULT_SLOW_POLL_THRESHOLD]
    /// time in the second sampling interval; and two slow polls consume a total of
    /// 20 × [`DEFAULT_SLOW_POLL_THRESHOLD`][TaskMonitor::DEFAULT_SLOW_POLL_THRESHOLD] time in the
    /// third sampling interval:
    /// ```
    /// use std::future::Future;
    /// use std::time::Duration;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // no tasks have been constructed, instrumented, or polled
    ///     let interval = next_interval();
    ///     assert_eq!(interval.total_slow_poll_duration, Duration::ZERO);
    ///
    ///     let slow = 10 * metrics_monitor.slow_poll_threshold();
    ///
    ///     // this task completes in three slow polls
    ///     let task_a_time = time(metrics_monitor.instrument(async {
    ///         spin_for(slow).await; // slow poll 1
    ///         spin_for(slow).await; // slow poll 2
    ///         spin_for(slow)        // slow poll 3
    ///     })).await;
    ///
    ///     let interval = next_interval();
    ///     assert!(interval.total_slow_poll_duration >= slow * 3);
    ///     assert!(interval.total_slow_poll_duration <= task_a_time);
    ///
    ///     // this task completes in two slow polls
    ///     let task_b_time = time(metrics_monitor.instrument(async {
    ///         spin_for(slow).await; // slow poll 1
    ///         spin_for(slow)        // slow poll 2
    ///     })).await;
    ///
    ///     let interval = next_interval();
    ///     assert!(interval.total_slow_poll_duration >= slow * 2);
    ///     assert!(interval.total_slow_poll_duration <= task_b_time);
    /// }
    ///
    /// /// Produces the amount of time it took to await a given async task.
    /// async fn time(task: impl Future) -> Duration {
    ///     let start = tokio::time::Instant::now();
    ///     task.await;
    ///     start.elapsed()
    /// }
    ///
    /// /// Block the current thread for a given `duration`, then (optionally) yield to the scheduler.
    /// fn spin_for(duration: Duration) -> impl Future<Output=()> {
    ///     let start = tokio::time::Instant::now();
    ///     while start.elapsed() <= duration {}
    ///     tokio::task::yield_now()
    /// }
    /// ```
    pub total_slow_poll_duration: Duration,

    /// The total count of tasks with short scheduling delays.
    ///
    /// This is defined as tasks taking strictly less than
    /// [`long_delay_threshold`][TaskMonitor::long_delay_threshold] to be executed after being
    /// scheduled.
    ///
    /// ##### Derived metrics
    /// - **[`mean_short_delay_duration`][TaskMetrics::mean_short_delay_duration]**   
    ///   The mean duration of short scheduling delays.
    pub total_short_delay_count: u64,

    /// The total count of tasks with long scheduling delays.
    ///
    /// This is defined as tasks taking
    /// [`long_delay_threshold`][TaskMonitor::long_delay_threshold] or longer to be executed
    /// after being scheduled.
    ///
    /// ##### Derived metrics
    /// - **[`mean_long_delay_duration`][TaskMetrics::mean_long_delay_duration]**   
    ///   The mean duration of short scheduling delays.
    pub total_long_delay_count: u64,

    /// The total duration of tasks with short scheduling delays.
    ///
    /// This is defined as tasks taking strictly less than
    /// [`long_delay_threshold`][TaskMonitor::long_delay_threshold] to be executed after being
    /// scheduled.
    ///
    /// ##### Derived metrics
    /// - **[`mean_short_delay_duration`][TaskMetrics::mean_short_delay_duration]**   
    ///   The mean duration of short scheduling delays.
    pub total_short_delay_duration: Duration,

    /// The total number of times that a task had a long scheduling duration.
    ///
    /// Here, a long scheduling duration is defined as taking longer to start execution after
    /// scheduling than [`long_delay_threshold`][TaskMonitor::long_delay_threshold].
    ///
    /// ##### Derived metrics
    /// - **[`mean_long_delay_duration`][TaskMetrics::mean_long_delay_duration]**   
    ///   The mean duration of short scheduling delays.
    pub total_long_delay_duration: Duration,
}

/// Tracks the metrics, shared across the various types.
#[derive(Debug)]
struct RawMetrics {
    /// A task poll takes longer than this, it is considered a slow poll.
    slow_poll_threshold: Duration,

    /// A scheduling delay of at least this long will be considered a long delay
    long_delay_threshold: Duration,

    /// Total number of instrumented tasks.
    instrumented_count: AtomicU64,

    /// Total number of instrumented tasks polled at least once.
    first_poll_count: AtomicU64,

    /// Total number of times tasks entered the `idle` state.
    total_idled_count: AtomicU64,

    /// Total number of times tasks were scheduled.
    total_scheduled_count: AtomicU64,

    /// Total number of times tasks were polled fast
    total_fast_poll_count: AtomicU64,

    /// Total number of times tasks were polled slow
    total_slow_poll_count: AtomicU64,

    /// Total number of times tasks had long delay,
    total_long_delay_count: AtomicU64,

    /// Total number of times tasks had little delay
    total_short_delay_count: AtomicU64,

    /// Total number of times tasks were dropped
    dropped_count: AtomicU64,

    /// Total amount of time until the first poll
    total_first_poll_delay_ns: AtomicU64,

    /// Total amount of time tasks spent in the `idle` state.
    total_idle_duration_ns: AtomicU64,

    /// Total amount of time tasks spent in the waking state.
    total_scheduled_duration_ns: AtomicU64,

    /// Total amount of time tasks spent being polled below the slow cut off.
    total_fast_poll_duration_ns: AtomicU64,

    /// Total amount of time tasks spent being polled above the slow cut off.
    total_slow_poll_duration: AtomicU64,

    /// Total amount of time tasks spent being polled below the long delay cut off.
    total_short_delay_duration_ns: AtomicU64,

    /// Total amount of time tasks spent being polled at or above the long delay cut off.
    total_long_delay_duration_ns: AtomicU64,
}

#[derive(Debug)]
struct State {
    /// Where metrics should be recorded
    metrics: Arc<RawMetrics>,

    /// Instant at which the task was instrumented. This is used to track the time to first poll.
    instrumented_at: Instant,

    /// The instant, tracked as nanoseconds since `instrumented_at`, at which the future
    /// was last woken.
    woke_at: AtomicU64,

    /// Waker to forward notifications to.
    waker: AtomicWaker,
}

impl TaskMonitor {
    /// The default duration at which polls cross the threshold into being categorized as 'slow' is
    /// 50μs.
    #[cfg(not(test))]
    pub const DEFAULT_SLOW_POLL_THRESHOLD: Duration = Duration::from_micros(50);
    #[cfg(test)]
    pub const DEFAULT_SLOW_POLL_THRESHOLD: Duration = Duration::from_millis(500);

    /// The default duration at which schedules cross the threshold into being categorized as 'long'
    /// is 50μs.
    #[cfg(not(test))]
    pub const DEFAULT_LONG_DELAY_THRESHOLD: Duration = Duration::from_micros(50);
    #[cfg(test)]
    pub const DEFAULT_LONG_DELAY_THRESHOLD: Duration = Duration::from_millis(500);

    /// Constructs a new task monitor.
    ///
    /// Uses [`Self::DEFAULT_SLOW_POLL_THRESHOLD`] as the threshold at which polls will be
    /// considered 'slow'.
    ///
    /// Uses [`Self::DEFAULT_LONG_DELAY_THRESHOLD`] as the threshold at which scheduling will be
    /// considered 'long'.
    pub fn new() -> TaskMonitor {
        TaskMonitor::with_slow_poll_threshold(Self::DEFAULT_SLOW_POLL_THRESHOLD)
    }

    /// Constructs a builder for a task monitor.
    pub fn builder() -> TaskMonitorBuilder {
        TaskMonitorBuilder::new()
    }

    /// Constructs a new task monitor with a given threshold at which polls are considered 'slow'.
    ///
    /// ##### Selecting an appropriate threshold
    /// TODO. What advice can we give here?
    ///
    /// ##### Examples
    /// In the below example, low-threshold and high-threshold monitors are constructed and
    /// instrument identical tasks; the low-threshold monitor reports4 slow polls, and the
    /// high-threshold monitor reports only 2 slow polls:
    /// ```
    /// use std::future::Future;
    /// use std::time::Duration;
    /// use tokio_metrics::TaskMonitor;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let lo_threshold = Duration::from_micros(10);
    ///     let hi_threshold = Duration::from_millis(10);
    ///
    ///     let lo_monitor = TaskMonitor::with_slow_poll_threshold(lo_threshold);
    ///     let hi_monitor = TaskMonitor::with_slow_poll_threshold(hi_threshold);
    ///
    ///     let make_task = || async {
    ///         spin_for(lo_threshold).await; // faster poll 1
    ///         spin_for(lo_threshold).await; // faster poll 2
    ///         spin_for(hi_threshold).await; // slower poll 3
    ///         spin_for(hi_threshold).await  // slower poll 4
    ///     };
    ///
    ///     lo_monitor.instrument(make_task()).await;
    ///     hi_monitor.instrument(make_task()).await;
    ///
    ///     // the low-threshold monitor reported 4 slow polls:
    ///     assert_eq!(lo_monitor.cumulative().total_slow_poll_count, 4);
    ///     // the high-threshold monitor reported only 2 slow polls:
    ///     assert_eq!(hi_monitor.cumulative().total_slow_poll_count, 2);
    /// }
    ///
    /// /// Block the current thread for a given `duration`, then (optionally) yield to the scheduler.
    /// fn spin_for(duration: Duration) -> impl Future<Output=()> {
    ///     let start = tokio::time::Instant::now();
    ///     while start.elapsed() <= duration {}
    ///     tokio::task::yield_now()
    /// }
    /// ```
    pub fn with_slow_poll_threshold(slow_poll_cut_off: Duration) -> TaskMonitor {
        Self::create(slow_poll_cut_off, Self::DEFAULT_LONG_DELAY_THRESHOLD)
    }

    fn create(slow_poll_cut_off: Duration, long_delay_cut_off: Duration) -> TaskMonitor {
        TaskMonitor {
            metrics: Arc::new(RawMetrics {
                slow_poll_threshold: slow_poll_cut_off,
                first_poll_count: AtomicU64::new(0),
                total_idled_count: AtomicU64::new(0),
                total_scheduled_count: AtomicU64::new(0),
                total_fast_poll_count: AtomicU64::new(0),
                total_slow_poll_count: AtomicU64::new(0),
                total_long_delay_count: AtomicU64::new(0),
                instrumented_count: AtomicU64::new(0),
                dropped_count: AtomicU64::new(0),
                total_first_poll_delay_ns: AtomicU64::new(0),
                total_scheduled_duration_ns: AtomicU64::new(0),
                total_idle_duration_ns: AtomicU64::new(0),
                total_fast_poll_duration_ns: AtomicU64::new(0),
                total_slow_poll_duration: AtomicU64::new(0),
                total_short_delay_duration_ns: AtomicU64::new(0),
                long_delay_threshold: long_delay_cut_off,
                total_short_delay_count: AtomicU64::new(0),
                total_long_delay_duration_ns: AtomicU64::new(0),
            }),
        }
    }

    /// Produces the duration greater-than-or-equal-to at which polls are categorized as slow.
    ///
    /// ##### Examples
    /// In the below example, [`TaskMonitor`] is initialized with [`TaskMonitor::new`];
    /// consequently, its slow-poll threshold equals [`TaskMonitor::DEFAULT_SLOW_POLL_THRESHOLD`]:
    /// ```
    /// use tokio_metrics::TaskMonitor;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = TaskMonitor::new();
    ///
    ///     assert_eq!(
    ///         metrics_monitor.slow_poll_threshold(),
    ///         TaskMonitor::DEFAULT_SLOW_POLL_THRESHOLD
    ///     );
    /// }
    /// ```
    pub fn slow_poll_threshold(&self) -> Duration {
        self.metrics.slow_poll_threshold
    }

    /// Produces the duration greater-than-or-equal-to at which scheduling delays are categorized
    /// as long.
    pub fn long_delay_threshold(&self) -> Duration {
        self.metrics.long_delay_threshold
    }

    /// Produces an instrumented façade around a given async task.
    ///
    /// ##### Examples
    /// Instrument an async task by passing it to [`TaskMonitor::instrument`]:
    /// ```
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///
    ///     // 0 tasks have been instrumented, much less polled
    ///     assert_eq!(metrics_monitor.cumulative().first_poll_count, 0);
    ///
    ///     // instrument a task and poll it to completion
    ///     metrics_monitor.instrument(async {}).await;
    ///
    ///     // 1 task has been instrumented and polled
    ///     assert_eq!(metrics_monitor.cumulative().first_poll_count, 1);
    ///
    ///     // instrument a task and poll it to completion
    ///     metrics_monitor.instrument(async {}).await;
    ///
    ///     // 2 tasks have been instrumented and polled
    ///     assert_eq!(metrics_monitor.cumulative().first_poll_count, 2);
    /// }
    /// ```
    /// An aync task may be tracked by multiple [`TaskMonitor`]s; e.g.:
    /// ```
    /// #[tokio::main]
    /// async fn main() {
    ///     let monitor_a = tokio_metrics::TaskMonitor::new();
    ///     let monitor_b = tokio_metrics::TaskMonitor::new();
    ///
    ///     // 0 tasks have been instrumented, much less polled
    ///     assert_eq!(monitor_a.cumulative().first_poll_count, 0);
    ///     assert_eq!(monitor_b.cumulative().first_poll_count, 0);
    ///
    ///     // instrument a task and poll it to completion
    ///     monitor_a.instrument(monitor_b.instrument(async {})).await;
    ///
    ///     // 1 task has been instrumented and polled
    ///     assert_eq!(monitor_a.cumulative().first_poll_count, 1);
    ///     assert_eq!(monitor_b.cumulative().first_poll_count, 1);
    /// }
    /// ```
    /// It is also possible (but probably undesirable) to instrument an async task multiple times
    /// with the same [`TaskMonitor`]; e.g.:
    /// ```
    /// #[tokio::main]
    /// async fn main() {
    ///     let monitor = tokio_metrics::TaskMonitor::new();
    ///
    ///     // 0 tasks have been instrumented, much less polled
    ///     assert_eq!(monitor.cumulative().first_poll_count, 0);
    ///
    ///     // instrument a task and poll it to completion
    ///     monitor.instrument(monitor.instrument(async {})).await;
    ///
    ///     // 2 tasks have been instrumented and polled, supposedly
    ///     assert_eq!(monitor.cumulative().first_poll_count, 2);
    /// }
    /// ```
    pub fn instrument<F>(&self, task: F) -> Instrumented<F> {
        self.metrics.instrumented_count.fetch_add(1, SeqCst);
        Instrumented {
            task,
            did_poll_once: false,
            idled_at: 0,
            state: Arc::new(State {
                metrics: self.metrics.clone(),
                instrumented_at: Instant::now(),
                woke_at: AtomicU64::new(0),
                waker: AtomicWaker::new(),
            }),
        }
    }

    /// Produces [`TaskMetrics`] for the tasks instrumented by this [`TaskMonitor`], collected since
    /// the construction of [`TaskMonitor`].
    ///
    /// ##### See also
    /// - [`TaskMonitor::intervals`]:
    ///     produces [`TaskMetrics`] for user-defined sampling intervals, instead of cumulatively
    ///
    /// ##### Examples
    /// In the below example, 0 polls occur within the first sampling interval, 3 slow polls occur
    /// within the second sampling interval, and 2 slow polls occur within the third sampling
    /// interval; five slow polls occur across all sampling intervals:
    /// ```
    /// use std::future::Future;
    /// use std::time::Duration;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///
    ///     // initialize a stream of sampling intervals
    ///     let mut intervals = metrics_monitor.intervals();
    ///     // each call of `next_interval` will produce metrics for the last sampling interval
    ///     let mut next_interval = || intervals.next().unwrap();
    ///
    ///     let slow = 10 * metrics_monitor.slow_poll_threshold();
    ///
    ///     // this task completes in three slow polls
    ///     let _ = metrics_monitor.instrument(async {
    ///         spin_for(slow).await; // slow poll 1
    ///         spin_for(slow).await; // slow poll 2
    ///         spin_for(slow)        // slow poll 3
    ///     }).await;
    ///
    ///     // in the previous sampling interval, there were 3 slow polls
    ///     assert_eq!(next_interval().total_slow_poll_count, 3);
    ///     assert_eq!(metrics_monitor.cumulative().total_slow_poll_count, 3);
    ///
    ///     // this task completes in two slow polls
    ///     let _ = metrics_monitor.instrument(async {
    ///         spin_for(slow).await; // slow poll 1
    ///         spin_for(slow)        // slow poll 2
    ///     }).await;
    ///
    ///     // in the previous sampling interval, there were 2 slow polls
    ///     assert_eq!(next_interval().total_slow_poll_count, 2);
    ///
    ///     // across all sampling interval, there were a total of 5 slow polls
    ///     assert_eq!(metrics_monitor.cumulative().total_slow_poll_count, 5);
    /// }
    ///
    /// /// Block the current thread for a given `duration`, then (optionally) yield to the scheduler.
    /// fn spin_for(duration: Duration) -> impl Future<Output=()> {
    ///     let start = tokio::time::Instant::now();
    ///     while start.elapsed() <= duration {}
    ///     tokio::task::yield_now()
    /// }
    /// ```
    pub fn cumulative(&self) -> TaskMetrics {
        self.metrics.metrics()
    }

    /// Produces an unending iterator of metric sampling intervals.
    ///
    /// Each sampling interval is defined by the time elapsed between advancements of the iterator
    /// produced by [`TaskMonitor::intervals`]. The item type of this iterator is [`TaskMetrics`],
    /// which is a bundle of task metrics that describe *only* events occurring within that sampling
    /// interval.
    ///
    /// ##### Examples
    /// In the below example, 0 polls occur within the first sampling interval, 3 slow polls occur
    /// within the second sampling interval, and 2 slow polls occur within the third sampling
    /// interval; five slow polls occur across all sampling intervals:
    /// ```
    /// use std::future::Future;
    /// use std::time::Duration;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///
    ///     // initialize a stream of sampling intervals
    ///     let mut intervals = metrics_monitor.intervals();
    ///     // each call of `next_interval` will produce metrics for the last sampling interval
    ///     let mut next_interval = || intervals.next().unwrap();
    ///
    ///     let slow = 10 * metrics_monitor.slow_poll_threshold();
    ///
    ///     // this task completes in three slow polls
    ///     let _ = metrics_monitor.instrument(async {
    ///         spin_for(slow).await; // slow poll 1
    ///         spin_for(slow).await; // slow poll 2
    ///         spin_for(slow)        // slow poll 3
    ///     }).await;
    ///
    ///     // in the previous sampling interval, there were 3 slow polls
    ///     assert_eq!(next_interval().total_slow_poll_count, 3);
    ///
    ///     // this task completes in two slow polls
    ///     let _ = metrics_monitor.instrument(async {
    ///         spin_for(slow).await; // slow poll 1
    ///         spin_for(slow)        // slow poll 2
    ///     }).await;
    ///
    ///     // in the previous sampling interval, there were 2 slow polls
    ///     assert_eq!(next_interval().total_slow_poll_count, 2);
    ///
    ///     // across all sampling intervals, there were a total of 5 slow polls
    ///     assert_eq!(metrics_monitor.cumulative().total_slow_poll_count, 5);
    /// }
    ///
    /// /// Block the current thread for a given `duration`, then (optionally) yield to the scheduler.
    /// fn spin_for(duration: Duration) -> impl Future<Output=()> {
    ///     let start = tokio::time::Instant::now();
    ///     while start.elapsed() <= duration {}
    ///     tokio::task::yield_now()
    /// }
    /// ```
    pub fn intervals(&self) -> impl Iterator<Item = TaskMetrics> {
        let latest = self.metrics.clone();
        let mut previous: Option<TaskMetrics> = None;

        std::iter::from_fn(move || {
            let latest: TaskMetrics = latest.metrics();
            let next = if let Some(previous) = previous {
                TaskMetrics {
                    instrumented_count: latest
                        .instrumented_count
                        .wrapping_sub(previous.instrumented_count),
                    dropped_count: latest.dropped_count.wrapping_sub(previous.dropped_count),
                    total_poll_count: latest
                        .total_poll_count
                        .wrapping_sub(previous.total_poll_count),
                    total_poll_duration: sub(
                        latest.total_poll_duration,
                        previous.total_poll_duration,
                    ),
                    first_poll_count: latest
                        .first_poll_count
                        .wrapping_sub(previous.first_poll_count),
                    total_idled_count: latest
                        .total_idled_count
                        .wrapping_sub(previous.total_idled_count),
                    total_scheduled_count: latest
                        .total_scheduled_count
                        .wrapping_sub(previous.total_scheduled_count),
                    total_fast_poll_count: latest
                        .total_fast_poll_count
                        .wrapping_sub(previous.total_fast_poll_count),
                    total_short_delay_count: latest
                        .total_short_delay_count
                        .wrapping_sub(previous.total_short_delay_count),
                    total_slow_poll_count: latest
                        .total_slow_poll_count
                        .wrapping_sub(previous.total_slow_poll_count),
                    total_long_delay_count: latest
                        .total_long_delay_count
                        .wrapping_sub(previous.total_long_delay_count),
                    total_first_poll_delay: sub(
                        latest.total_first_poll_delay,
                        previous.total_first_poll_delay,
                    ),
                    total_idle_duration: sub(
                        latest.total_idle_duration,
                        previous.total_idle_duration,
                    ),
                    total_scheduled_duration: sub(
                        latest.total_scheduled_duration,
                        previous.total_scheduled_duration,
                    ),
                    total_fast_poll_duration: sub(
                        latest.total_fast_poll_duration,
                        previous.total_fast_poll_duration,
                    ),
                    total_short_delay_duration: sub(
                        latest.total_short_delay_duration,
                        previous.total_short_delay_duration,
                    ),
                    total_slow_poll_duration: sub(
                        latest.total_slow_poll_duration,
                        previous.total_slow_poll_duration,
                    ),
                    total_long_delay_duration: sub(
                        latest.total_long_delay_duration,
                        previous.total_long_delay_duration,
                    ),
                }
            } else {
                latest
            };

            previous = Some(latest);

            Some(next)
        })
    }
}

impl RawMetrics {
    fn metrics(&self) -> TaskMetrics {
        let total_fast_poll_count = self.total_fast_poll_count.load(SeqCst);
        let total_slow_poll_count = self.total_slow_poll_count.load(SeqCst);

        let total_fast_poll_duration =
            Duration::from_nanos(self.total_fast_poll_duration_ns.load(SeqCst));
        let total_slow_poll_duration =
            Duration::from_nanos(self.total_slow_poll_duration.load(SeqCst));

        let total_poll_count = total_fast_poll_count + total_slow_poll_count;
        let total_poll_duration = total_fast_poll_duration + total_slow_poll_duration;

        TaskMetrics {
            instrumented_count: self.instrumented_count.load(SeqCst),
            dropped_count: self.dropped_count.load(SeqCst),

            total_poll_count,
            total_poll_duration,
            first_poll_count: self.first_poll_count.load(SeqCst),
            total_idled_count: self.total_idled_count.load(SeqCst),
            total_scheduled_count: self.total_scheduled_count.load(SeqCst),
            total_fast_poll_count: self.total_fast_poll_count.load(SeqCst),
            total_slow_poll_count: self.total_slow_poll_count.load(SeqCst),
            total_short_delay_count: self.total_short_delay_count.load(SeqCst),
            total_long_delay_count: self.total_long_delay_count.load(SeqCst),
            total_first_poll_delay: Duration::from_nanos(
                self.total_first_poll_delay_ns.load(SeqCst),
            ),
            total_idle_duration: Duration::from_nanos(self.total_idle_duration_ns.load(SeqCst)),
            total_scheduled_duration: Duration::from_nanos(
                self.total_scheduled_duration_ns.load(SeqCst),
            ),
            total_fast_poll_duration: Duration::from_nanos(
                self.total_fast_poll_duration_ns.load(SeqCst),
            ),
            total_slow_poll_duration: Duration::from_nanos(
                self.total_slow_poll_duration.load(SeqCst),
            ),
            total_short_delay_duration: Duration::from_nanos(
                self.total_short_delay_duration_ns.load(SeqCst),
            ),
            total_long_delay_duration: Duration::from_nanos(
                self.total_long_delay_duration_ns.load(SeqCst),
            ),
        }
    }
}

impl Default for TaskMonitor {
    fn default() -> TaskMonitor {
        TaskMonitor::new()
    }
}

impl TaskMetrics {
    /// The mean duration elapsed between the instant tasks are instrumented, and the instant they
    /// are first polled.
    ///
    /// ##### Definition
    /// This metric is derived from [`total_first_poll_delay`][TaskMetrics::total_first_poll_delay]
    /// ÷ [`first_poll_count`][TaskMetrics::first_poll_count].
    ///
    /// ##### Interpretation
    /// If this metric increases, it means that, on average, tasks spent longer waiting to be
    /// initially polled.
    ///
    /// ##### See also
    /// - **[`mean_scheduled_duration`][TaskMetrics::mean_scheduled_duration]**   
    ///   The mean duration that tasks spent waiting to be executed after awakening.
    ///
    /// ##### Examples
    /// In the below example, no tasks are instrumented or polled within the first sampling
    /// interval; in the second sampling interval, 500ms elapse between the instrumentation of a
    /// task and its first poll; in the third sampling interval, a mean of 750ms elapse between the
    /// instrumentation and first poll of two tasks:
    /// ```
    /// use std::time::Duration;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // no tasks have yet been created, instrumented, or polled
    ///     assert_eq!(next_interval().mean_first_poll_delay(), Duration::ZERO);
    ///
    ///     // constructs and instruments a task, pauses for `pause_time`, awaits the task, then
    ///     // produces the total time it took to do all of the aforementioned
    ///     async fn instrument_pause_await(
    ///         metrics_monitor: &tokio_metrics::TaskMonitor,
    ///         pause_time: Duration
    ///     ) -> Duration
    ///     {
    ///         let before_instrumentation = tokio::time::Instant::now();
    ///         let task = metrics_monitor.instrument(async move {});
    ///         tokio::time::sleep(pause_time).await;
    ///         task.await;
    ///         before_instrumentation.elapsed()
    ///     }
    ///
    ///     // construct and await a task that pauses for 500ms between instrumentation and first poll
    ///     let task_a_pause_time = Duration::from_millis(500);
    ///     let task_a_total_time = instrument_pause_await(&metrics_monitor, task_a_pause_time).await;
    ///
    ///     // the `mean_first_poll_delay` will be some duration greater-than-or-equal-to the
    ///     // pause time of 500ms, and less-than-or-equal-to the total runtime of `task_a`
    ///     let mean_first_poll_delay = next_interval().mean_first_poll_delay();
    ///     assert!(mean_first_poll_delay >= task_a_pause_time);
    ///     assert!(mean_first_poll_delay <= task_a_total_time);
    ///
    ///     // construct and await a task that pauses for 500ms between instrumentation and first poll
    ///     let task_b_pause_time = Duration::from_millis(500);
    ///     let task_b_total_time = instrument_pause_await(&metrics_monitor, task_b_pause_time).await;
    ///
    ///     // construct and await a task that pauses for 1000ms between instrumentation and first poll
    ///     let task_c_pause_time = Duration::from_millis(1000);
    ///     let task_c_total_time = instrument_pause_await(&metrics_monitor, task_c_pause_time).await;
    ///
    ///     // the `mean_first_poll_delay` will be some duration greater-than-or-equal-to the
    ///     // average pause time of 500ms, and less-than-or-equal-to the combined total runtime of
    ///     // `task_b` and `task_c`
    ///     let mean_first_poll_delay = next_interval().mean_first_poll_delay();
    ///     assert!(mean_first_poll_delay >= (task_b_pause_time + task_c_pause_time) / 2);
    ///     assert!(mean_first_poll_delay <= (task_b_total_time + task_c_total_time) / 2);
    /// }
    /// ```
    pub fn mean_first_poll_delay(&self) -> Duration {
        mean(self.total_first_poll_delay, self.first_poll_count)
    }

    /// The mean duration of idles.
    ///
    /// ##### Definition
    /// This metric is derived from [`total_idle_duration`][TaskMetrics::total_idle_duration] ÷
    /// [`total_idled_count`][TaskMetrics::total_idled_count].
    ///
    /// ##### Interpretation
    /// The idle state is the duration spanning the instant a task completes a poll, and the instant
    /// that it is next awoken. Tasks inhabit this state when they are waiting for task-external
    /// events to complete (e.g., an asynchronous sleep, a network request, file I/O, etc.). If this
    /// metric increases, it means that tasks, in aggregate, spent more time waiting for
    /// task-external events to complete.
    ///
    /// ##### Examples
    /// ```
    /// #[tokio::main]
    /// async fn main() {
    ///     let monitor = tokio_metrics::TaskMonitor::new();
    ///     let one_sec = std::time::Duration::from_secs(1);
    ///
    ///     monitor.instrument(async move {
    ///         tokio::time::sleep(one_sec).await;
    ///     }).await;
    ///
    ///     assert!(monitor.cumulative().mean_idle_duration() >= one_sec);
    /// }
    /// ```
    pub fn mean_idle_duration(&self) -> Duration {
        mean(self.total_idle_duration, self.total_idled_count)
    }

    /// The mean duration that tasks spent waiting to be executed after awakening.
    ///
    /// ##### Definition
    /// This metric is derived from
    /// [`total_scheduled_duration`][TaskMetrics::total_scheduled_duration] ÷
    /// [`total_scheduled_count`][`TaskMetrics::total_scheduled_count`].
    ///
    /// ##### Interpretation
    /// If this metric increases, it means that, on average, tasks spent longer in the runtime's
    /// queues before being polled.
    ///
    /// ##### See also
    /// - **[`mean_first_poll_delay`][TaskMetrics::mean_first_poll_delay]**   
    ///   The mean duration elapsed between the instant tasks are instrumented, and the instant they
    ///   are first polled.
    ///
    /// ##### Examples
    /// ```
    /// use tokio::time::Duration;
    ///
    /// #[tokio::main(flavor = "current_thread")]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // construct and instrument and spawn a task that yields endlessly
    ///     tokio::spawn(metrics_monitor.instrument(async {
    ///         loop { tokio::task::yield_now().await }
    ///     }));
    ///
    ///     tokio::task::yield_now().await;
    ///
    ///     // block the executor for 1 second
    ///     std::thread::sleep(Duration::from_millis(1000));
    ///
    ///     // get the task to run twice
    ///     // the first will have a 1 sec scheduling delay, the second will have almost none
    ///     tokio::task::yield_now().await;
    ///     tokio::task::yield_now().await;
    ///
    ///     // `endless_task` will have spent approximately one second waiting
    ///     let mean_scheduled_duration = next_interval().mean_scheduled_duration();
    ///     assert!(mean_scheduled_duration >= Duration::from_millis(500), "{}", mean_scheduled_duration.as_secs_f64());
    ///     assert!(mean_scheduled_duration <= Duration::from_millis(600), "{}", mean_scheduled_duration.as_secs_f64());
    /// }
    /// ```
    pub fn mean_scheduled_duration(&self) -> Duration {
        mean(self.total_scheduled_duration, self.total_scheduled_count)
    }

    /// The mean duration of polls.
    ///
    /// ##### Definition
    /// This metric is derived from [`total_poll_duration`][TaskMetrics::total_poll_duration] ÷
    /// [`total_poll_count`][TaskMetrics::total_poll_count].
    ///
    /// ##### Interpretation
    /// If this metric increases, it means that, on average, individual polls are tending to take
    /// longer. However, this does not necessarily imply increased task latency: An increase in poll
    /// durations could be offset by fewer polls.
    ///
    /// ##### See also
    /// - **[`slow_poll_ratio`][TaskMetrics::slow_poll_ratio]**   
    ///   The ratio between the number polls categorized as slow and fast.
    /// - **[`mean_slow_poll_duration`][TaskMetrics::mean_slow_poll_duration]**   
    ///   The mean duration of slow polls.
    ///
    /// ##### Examples
    /// ```
    /// use std::time::Duration;
    ///
    /// #[tokio::main(flavor = "current_thread", start_paused = true)]
    /// async fn main() {
    ///     let monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = monitor.intervals();
    ///     let mut next_interval = move || interval.next().unwrap();
    ///  
    ///     assert_eq!(next_interval().mean_poll_duration(), Duration::ZERO);
    ///  
    ///     monitor.instrument(async {
    ///         tokio::time::advance(Duration::from_secs(1)).await; // poll 1 (1s)
    ///         tokio::time::advance(Duration::from_secs(1)).await; // poll 2 (1s)
    ///         ()                                                  // poll 3 (0s)
    ///     }).await;
    ///  
    ///     assert_eq!(next_interval().mean_poll_duration(), Duration::from_secs(2) / 3);
    /// }
    /// ```
    pub fn mean_poll_duration(&self) -> Duration {
        mean(self.total_poll_duration, self.total_poll_count)
    }

    /// The ratio between the number polls categorized as slow and fast.
    ///
    /// ##### Definition
    /// This metric is derived from [`total_slow_poll_count`][TaskMetrics::total_slow_poll_count] ÷
    /// [`total_poll_count`][TaskMetrics::total_poll_count].
    ///
    /// ##### Interpretation
    /// If this metric increases, it means that a greater proportion of polls took excessively long
    /// before yielding to the scheduler. This does not necessarily imply increased task latency:
    /// An increase in the proportion of slow polls could be offset by fewer or faster polls.
    /// However, as a rule, *should* yield to the scheduler frequently.
    ///
    /// ##### See also
    /// - **[`mean_poll_duration`][TaskMetrics::mean_poll_duration]**   
    ///   The mean duration of polls.
    /// - **[`mean_slow_poll_duration`][TaskMetrics::mean_slow_poll_duration]**   
    ///   The mean duration of slow polls.
    ///
    /// ##### Examples
    /// Changes in this metric may be observed by varying the ratio of slow and slow fast within
    /// sampling intervals; for instance:
    /// ```
    /// use std::future::Future;
    /// use std::time::Duration;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // no tasks have been constructed, instrumented, or polled
    ///     let interval = next_interval();
    ///     assert_eq!(interval.total_fast_poll_count, 0);
    ///     assert_eq!(interval.total_slow_poll_count, 0);
    ///     assert!(interval.slow_poll_ratio().is_nan());
    ///
    ///     let fast = Duration::ZERO;
    ///     let slow = 10 * metrics_monitor.slow_poll_threshold();
    ///
    ///     // this task completes in three fast polls
    ///     metrics_monitor.instrument(async {
    ///         spin_for(fast).await;   // fast poll 1
    ///         spin_for(fast).await;   // fast poll 2
    ///         spin_for(fast);         // fast poll 3
    ///     }).await;
    ///
    ///     // this task completes in two slow polls
    ///     metrics_monitor.instrument(async {
    ///         spin_for(slow).await;   // slow poll 1
    ///         spin_for(slow);         // slow poll 2
    ///     }).await;
    ///
    ///     let interval = next_interval();
    ///     assert_eq!(interval.total_fast_poll_count, 3);
    ///     assert_eq!(interval.total_slow_poll_count, 2);
    ///     assert_eq!(interval.slow_poll_ratio(), ratio(2., 3.));
    ///
    ///     // this task completes in three slow polls
    ///     metrics_monitor.instrument(async {
    ///         spin_for(slow).await;   // slow poll 1
    ///         spin_for(slow).await;   // slow poll 2
    ///         spin_for(slow);         // slow poll 3
    ///     }).await;
    ///
    ///     // this task completes in two fast polls
    ///     metrics_monitor.instrument(async {
    ///         spin_for(fast).await; // fast poll 1
    ///         spin_for(fast);       // fast poll 2
    ///     }).await;
    ///
    ///     let interval = next_interval();
    ///     assert_eq!(interval.total_fast_poll_count, 2);
    ///     assert_eq!(interval.total_slow_poll_count, 3);
    ///     assert_eq!(interval.slow_poll_ratio(), ratio(3., 2.));
    /// }
    ///
    /// fn ratio(a: f64, b: f64) -> f64 {
    ///     a / (a + b)
    /// }
    ///
    /// /// Block the current thread for a given `duration`, then (optionally) yield to the scheduler.
    /// fn spin_for(duration: Duration) -> impl Future<Output=()> {
    ///     let start = tokio::time::Instant::now();
    ///     while start.elapsed() <= duration {}
    ///     tokio::task::yield_now()
    /// }
    /// ```
    pub fn slow_poll_ratio(&self) -> f64 {
        self.total_slow_poll_count as f64 / self.total_poll_count as f64
    }

    /// The ratio of tasks exceeding [`long_delay_threshold`][TaskMonitor::long_delay_threshold].
    ///
    /// ##### Definition
    /// This metric is derived from [`total_long_delay_count`][TaskMetrics::total_long_delay_count] ÷
    /// [`total_scheduled_count`][TaskMetrics::total_scheduled_count].
    pub fn long_delay_ratio(&self) -> f64 {
        self.total_long_delay_count as f64 / self.total_scheduled_count as f64
    }

    /// The mean duration of fast polls.
    ///
    /// ##### Definition
    /// This metric is derived from
    /// [`total_fast_poll_duration`][TaskMetrics::total_fast_poll_duration] ÷
    /// [`total_fast_poll_count`][TaskMetrics::total_fast_poll_count].
    ///
    /// ##### Examples
    /// In the below example, no tasks are polled in the first sampling interval; three fast polls
    /// consume a mean of
    /// ⅜ × [`DEFAULT_SLOW_POLL_THRESHOLD`][TaskMonitor::DEFAULT_SLOW_POLL_THRESHOLD] time in the
    /// second sampling interval; and two fast polls consume a total of
    /// ½ × [`DEFAULT_SLOW_POLL_THRESHOLD`][TaskMonitor::DEFAULT_SLOW_POLL_THRESHOLD] time in the
    /// third sampling interval:
    /// ```
    /// use std::future::Future;
    /// use std::time::Duration;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // no tasks have been constructed, instrumented, or polled
    ///     assert_eq!(next_interval().mean_fast_poll_duration(), Duration::ZERO);
    ///
    ///     let threshold = metrics_monitor.slow_poll_threshold();
    ///     let fast_1 = 1 * Duration::from_micros(1);
    ///     let fast_2 = 2 * Duration::from_micros(1);
    ///     let fast_3 = 3 * Duration::from_micros(1);
    ///
    ///     // this task completes in two fast polls
    ///     let total_time = time(metrics_monitor.instrument(async {
    ///         spin_for(fast_1).await; // fast poll 1
    ///         spin_for(fast_2)        // fast poll 2
    ///     })).await;
    ///
    ///     // `mean_fast_poll_duration` ≈ the mean of `fast_1` and `fast_2`
    ///     let mean_fast_poll_duration = next_interval().mean_fast_poll_duration();
    ///     assert!(mean_fast_poll_duration >= (fast_1 + fast_2) / 2);
    ///     assert!(mean_fast_poll_duration <= total_time / 2);
    ///
    ///     // this task completes in three fast polls
    ///     let total_time = time(metrics_monitor.instrument(async {
    ///         spin_for(fast_1).await; // fast poll 1
    ///         spin_for(fast_2).await; // fast poll 2
    ///         spin_for(fast_3)        // fast poll 3
    ///     })).await;
    ///
    ///     // `mean_fast_poll_duration` ≈ the mean of `fast_1`, `fast_2`, `fast_3`
    ///     let mean_fast_poll_duration = next_interval().mean_fast_poll_duration();
    ///     assert!(mean_fast_poll_duration >= (fast_1 + fast_2 + fast_3) / 3);
    ///     assert!(mean_fast_poll_duration <= total_time / 3);
    /// }
    ///
    /// /// Produces the amount of time it took to await a given task.
    /// async fn time(task: impl Future) -> Duration {
    ///     let start = tokio::time::Instant::now();
    ///     task.await;
    ///     start.elapsed()
    /// }
    ///
    /// /// Block the current thread for a given `duration`, then (optionally) yield to the scheduler.
    /// fn spin_for(duration: Duration) -> impl Future<Output=()> {
    ///     let start = tokio::time::Instant::now();
    ///     while start.elapsed() <= duration {}
    ///     tokio::task::yield_now()
    /// }
    /// ```
    pub fn mean_fast_poll_duration(&self) -> Duration {
        mean(self.total_fast_poll_duration, self.total_fast_poll_count)
    }

    /// The average time taken for a task with a short scheduling delay to be executed after being
    /// scheduled.
    ///
    /// ##### Definition
    /// This metric is derived from
    /// [`total_short_delay_duration`][TaskMetrics::total_short_delay_duration] ÷
    /// [`total_short_delay_count`][TaskMetrics::total_short_delay_count].
    pub fn mean_short_delay_duration(&self) -> Duration {
        mean(
            self.total_short_delay_duration,
            self.total_short_delay_count,
        )
    }

    /// The mean duration of slow polls.
    ///
    /// ##### Definition
    /// This metric is derived from
    /// [`total_slow_poll_duration`][TaskMetrics::total_slow_poll_duration] ÷
    /// [`total_slow_poll_count`][TaskMetrics::total_slow_poll_count].
    ///
    /// ##### Interpretation
    /// If this metric increases, it means that a greater proportion of polls took excessively long
    /// before yielding to the scheduler. This does not necessarily imply increased task latency:
    /// An increase in the proportion of slow polls could be offset by fewer or faster polls.
    ///
    /// ##### See also
    /// - **[`mean_poll_duration`][TaskMetrics::mean_poll_duration]**   
    ///   The mean duration of polls.
    /// - **[`slow_poll_ratio`][TaskMetrics::slow_poll_ratio]**   
    ///   The ratio between the number polls categorized as slow and fast.
    ///
    /// ##### Interpretation
    /// If this metric increases, it means that, on average, slow polls got even slower. This does
    /// necessarily imply increased task latency: An increase in average slow poll duration could be
    /// offset by fewer or faster polls. However, as a rule, *should* yield to the scheduler
    /// frequently.
    ///
    /// ##### Examples
    /// In the below example, no tasks are polled in the first sampling interval; three slow polls
    /// consume a mean of
    /// 1.5 × [`DEFAULT_SLOW_POLL_THRESHOLD`][TaskMonitor::DEFAULT_SLOW_POLL_THRESHOLD] time in the
    /// second sampling interval; and two slow polls consume a total of
    /// 2 × [`DEFAULT_SLOW_POLL_THRESHOLD`][TaskMonitor::DEFAULT_SLOW_POLL_THRESHOLD] time in the
    /// third sampling interval:
    /// ```
    /// use std::future::Future;
    /// use std::time::Duration;
    ///
    /// #[tokio::main]
    /// async fn main() {
    ///     let metrics_monitor = tokio_metrics::TaskMonitor::new();
    ///     let mut interval = metrics_monitor.intervals();
    ///     let mut next_interval = || interval.next().unwrap();
    ///
    ///     // no tasks have been constructed, instrumented, or polled
    ///     assert_eq!(next_interval().mean_slow_poll_duration(), Duration::ZERO);
    ///
    ///     let threshold = metrics_monitor.slow_poll_threshold();
    ///     let slow_1 = 1 * threshold;
    ///     let slow_2 = 2 * threshold;
    ///     let slow_3 = 3 * threshold;
    ///
    ///     // this task completes in two slow polls
    ///     let total_time = time(metrics_monitor.instrument(async {
    ///         spin_for(slow_1).await; // slow poll 1
    ///         spin_for(slow_2)        // slow poll 2
    ///     })).await;
    ///
    ///     // `mean_slow_poll_duration` ≈ the mean of `slow_1` and `slow_2`
    ///     let mean_slow_poll_duration = next_interval().mean_slow_poll_duration();
    ///     assert!(mean_slow_poll_duration >= (slow_1 + slow_2) / 2);
    ///     assert!(mean_slow_poll_duration <= total_time / 2);
    ///
    ///     // this task completes in three slow polls
    ///     let total_time = time(metrics_monitor.instrument(async {
    ///         spin_for(slow_1).await; // slow poll 1
    ///         spin_for(slow_2).await; // slow poll 2
    ///         spin_for(slow_3)        // slow poll 3
    ///     })).await;
    ///
    ///     // `mean_slow_poll_duration` ≈ the mean of `slow_1`, `slow_2`, `slow_3`
    ///     let mean_slow_poll_duration = next_interval().mean_slow_poll_duration();
    ///     assert!(mean_slow_poll_duration >= (slow_1 + slow_2 + slow_3) / 3);
    ///     assert!(mean_slow_poll_duration <= total_time / 3);
    /// }
    ///
    /// /// Produces the amount of time it took to await a given task.
    /// async fn time(task: impl Future) -> Duration {
    ///     let start = tokio::time::Instant::now();
    ///     task.await;
    ///     start.elapsed()
    /// }
    ///
    /// /// Block the current thread for a given `duration`, then (optionally) yield to the scheduler.
    /// fn spin_for(duration: Duration) -> impl Future<Output=()> {
    ///     let start = tokio::time::Instant::now();
    ///     while start.elapsed() <= duration {}
    ///     tokio::task::yield_now()
    /// }
    /// ```
    pub fn mean_slow_poll_duration(&self) -> Duration {
        mean(self.total_slow_poll_duration, self.total_slow_poll_count)
    }

    /// The average scheduling delay for a task which takes a long time to start executing after
    /// being scheduled.
    ///
    /// ##### Definition
    /// This metric is derived from
    /// [`total_long_delay_duration`][TaskMetrics::total_long_delay_duration] ÷
    /// [`total_long_delay_count`][TaskMetrics::total_long_delay_count].
    pub fn mean_long_delay_duration(&self) -> Duration {
        mean(self.total_long_delay_duration, self.total_long_delay_count)
    }
}

impl<T: Future> Future for Instrumented<T> {
    type Output = T::Output;

    fn poll(self: Pin<&mut Self>, cx: &mut Context<'_>) -> Poll<Self::Output> {
        instrument_poll(cx, self, Future::poll)
    }
}

impl<T: Stream> Stream for Instrumented<T> {
    type Item = T::Item;

    fn poll_next(self: Pin<&mut Self>, cx: &mut Context<'_>) -> Poll<Option<Self::Item>> {
        instrument_poll(cx, self, Stream::poll_next)
    }
}

fn instrument_poll<T, Out>(
    cx: &mut Context<'_>,
    instrumented: Pin<&mut Instrumented<T>>,
    poll_fn: impl FnOnce(Pin<&mut T>, &mut Context<'_>) -> Poll<Out>,
) -> Poll<Out> {
    let poll_start = Instant::now();
    let this = instrumented.project();
    let idled_at = this.idled_at;
    let state = this.state;
    let instrumented_at = state.instrumented_at;
    let metrics = &state.metrics;
    /* accounting for time-to-first-poll and tasks-count */
    // is this the first time this task has been polled?
    if !*this.did_poll_once {
        // if so, we need to do three things:
        /* 1. note that this task *has* been polled */
        *this.did_poll_once = true;

        /* 2. account for the time-to-first-poll of this task */
        // if the time-to-first-poll of this task exceeds `u64::MAX` ns,
        // round down to `u64::MAX` nanoseconds
        let elapsed = (poll_start - instrumented_at)
            .as_nanos()
            .try_into()
            .unwrap_or(u64::MAX);
        // add this duration to `time_to_first_poll_ns_total`
        metrics.total_first_poll_delay_ns.fetch_add(elapsed, SeqCst);

        /* 3. increment the count of tasks that have been polled at least once */
        state.metrics.first_poll_count.fetch_add(1, SeqCst);
    }
    /* accounting for time-idled and time-scheduled */
    // 1. note (and reset) the instant this task was last awoke
    let woke_at = state.woke_at.swap(0, SeqCst);
    // The state of a future is *idling* in the interim between the instant
    // it completes a `poll`, and the instant it is next awoken.
    if *idled_at < woke_at {
        // increment the counter of how many idles occurred
        metrics.total_idled_count.fetch_add(1, SeqCst);

        // compute the duration of the idle
        let idle_ns = woke_at - *idled_at;

        // adjust the total elapsed time monitored tasks spent idling
        metrics.total_idle_duration_ns.fetch_add(idle_ns, SeqCst);
    }
    // if this task spent any time in the scheduled state after instrumentation,
    // and after first poll, `woke_at` will be greater than 0.
    if woke_at > 0 {
        // increment the counter of how many schedules occurred
        metrics.total_scheduled_count.fetch_add(1, SeqCst);

        // recall that the `woke_at` field is internally represented as
        // nanoseconds-since-instrumentation. here, for accounting purposes,
        // we need to instead represent it as a proper `Instant`.
        let woke_instant = instrumented_at + Duration::from_nanos(woke_at);

        // the duration this task spent scheduled is time time elapsed between
        // when this task was awoke, and when it was polled.
        let scheduled_ns = (poll_start - woke_instant)
            .as_nanos()
            .try_into()
            .unwrap_or(u64::MAX);

        let scheduled = Duration::from_nanos(scheduled_ns);

        let (count_bucket, duration_bucket) = // was the scheduling delay long or short?
            if scheduled >= metrics.long_delay_threshold {
                (&metrics.total_long_delay_count, &metrics.total_long_delay_duration_ns)
            } else {
                (&metrics.total_short_delay_count, &metrics.total_short_delay_duration_ns)
            };
        // update the appropriate bucket
        count_bucket.fetch_add(1, SeqCst);
        duration_bucket.fetch_add(scheduled_ns, SeqCst);

        // add `scheduled_ns` to the Monitor's total
        metrics
            .total_scheduled_duration_ns
            .fetch_add(scheduled_ns, SeqCst);
    }
    // Register the waker
    state.waker.register(cx.waker());
    // Get the instrumented waker
    let waker_ref = futures_util::task::waker_ref(state);
    let mut cx = Context::from_waker(&waker_ref);
    // Poll the task
    let inner_poll_start = Instant::now();
    let ret = poll_fn(this.task, &mut cx);
    let inner_poll_end = Instant::now();
    /* idle time starts now */
    *idled_at = (inner_poll_end - instrumented_at)
        .as_nanos()
        .try_into()
        .unwrap_or(u64::MAX);
    /* accounting for poll time */
    let inner_poll_duration = inner_poll_end - inner_poll_start;
    let inner_poll_ns: u64 = inner_poll_duration
        .as_nanos()
        .try_into()
        .unwrap_or(u64::MAX);
    let (count_bucket, duration_bucket) = // was this a slow or fast poll?
            if inner_poll_duration >= metrics.slow_poll_threshold {
                (&metrics.total_slow_poll_count, &metrics.total_slow_poll_duration)
            } else {
                (&metrics.total_fast_poll_count, &metrics.total_fast_poll_duration_ns)
            };
    // update the appropriate bucket
    count_bucket.fetch_add(1, SeqCst);
    duration_bucket.fetch_add(inner_poll_ns, SeqCst);
    ret
}

impl State {
    fn on_wake(&self) {
        let woke_at: u64 = match self.instrumented_at.elapsed().as_nanos().try_into() {
            Ok(woke_at) => woke_at,
            // This is highly unlikely as it would mean the task ran for over
            // 500 years. If you ran your service for 500 years. If you are
            // reading this 500 years in the future, I'm sorry.
            Err(_) => return,
        };

        // We don't actually care about the result
        let _ = self.woke_at.compare_exchange(0, woke_at, SeqCst, SeqCst);
    }
}

impl ArcWake for State {
    fn wake_by_ref(arc_self: &Arc<State>) {
        arc_self.on_wake();
        arc_self.waker.wake();
    }

    fn wake(self: Arc<State>) {
        self.on_wake();
        self.waker.wake();
    }
}

#[inline(always)]
fn to_nanos(d: Duration) -> u64 {
    debug_assert!(d <= Duration::from_nanos(u64::MAX));
    d.as_secs()
        .wrapping_mul(1_000_000_000)
        .wrapping_add(d.subsec_nanos() as u64)
}

#[inline(always)]
fn sub(a: Duration, b: Duration) -> Duration {
    let nanos = to_nanos(a).wrapping_sub(to_nanos(b));
    Duration::from_nanos(nanos)
}

#[inline(always)]
fn mean(d: Duration, count: u64) -> Duration {
    if let Some(quotient) = to_nanos(d).checked_div(count) {
        Duration::from_nanos(quotient)
    } else {
        Duration::ZERO
    }
}