Elixir & Phoenix: Scalable Backend Development · 课时

使用 Telemetry 与指标进行监控

将 Telemetry 集成到应用中以生成指标,并深入了解应用的运行时行为。

第 2 / 4 课11 个步骤

使用 Telemetry 与指标进行监控 是 CoddyKit 上的免费 Elixir & Phoenix: Scalable Backend Development 课时。 这是第 2 节课,共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Elixir & Phoenix: Scalable Backend Development 学习路径的一部分,你的进度在网页和 CoddyKit 应用中同步。 Elixir & Phoenix: Scalable Backend Development 课程共包含 4 节课。

本课时的部分内容尚未翻译,以英文显示。

What is Elixir Telemetry?

In Elixir, Telemetry is a powerful, low-level event dispatching library. It helps you understand what's happening inside your running application.

  • It's built into Elixir/OTP, making it a standard way to observe systems.
  • Think of it as a central nervous system for your app's events.
  • It enables you to collect metrics, trace operations, and monitor performance.

It's crucial for building observable and maintainable applications.

Events: The Core of Telemetry

Telemetry works by emitting events. An event is a signal that something notable has happened in your application.

  • Each event has a unique name (a list of atoms, e.g., [:my_app, :user, :login]).
  • Events can carry measurements (numeric values like duration) and metadata (additional context like user ID).
  • You don't emit events directly; instead, you use functions that wrap your code.

Measuring Duration with Telemetry.span

One common use of Telemetry is to measure how long an operation takes. This is done using :telemetry.span/3.

  • It executes a given function and measures its execution time.
  • It emits two events: one when the span starts and one when it ends.
  • The end event includes the duration as a measurement.

This is great for profiling function calls or database queries.

Emitting Discrete Events with Telemetry.execute

Sometimes, you just want to signal that an action occurred, without necessarily measuring its duration. For this, use :telemetry.execute/3.

  • It emits a single event with specified measurements and metadata.
  • Useful for tracking things like cache hits/misses, background job completions, or specific API calls.
  • It's a simpler, more direct way to emit a single point-in-time event.

Code: Emitting a Telemetry Span

Let's see :telemetry.span/3 in action. This example simulates a 'processing' task and measures its duration.

We define a simple module and call a function that wraps its work in a span.

defmodule MyApp.Worker do
  require Logger

  def process_data(data) do
    Logger.info("Starting data processing...")
    :telemetry.span(
      [:my_app, :worker, :process_data],
      %{input_length: byte_size(data)},
      fn ->
        # Simulate some work
        :timer.sleep(100)
        result = String.upcase(data)
        {:ok, result}
      end
    )
  end
end

# --- Main execution for CoddyKit ---
Logger.info("Calling MyApp.Worker.process_data...")
{:ok, result} = MyApp.Worker.process_data("hello elixir")
IO.puts("Processed result: #{result}")
IO.puts("\n(No Telemetry output yet - we need a handler!)")

Attaching Telemetry Handlers

Emitting events is only half the story! To do something useful with them, you need to attach handlers.

  • A handler is a function that gets called whenever a specific Telemetry event is emitted.
  • You attach a handler using :telemetry.attach/4, specifying the event name and your handler function.
  • Handlers allow you to react to events: log them, send them to a metrics system, or trigger other actions.

They are the listeners of your application's internal signals.

Handler Function Structure

A Telemetry handler function must accept four arguments:

  1. event_name: The name of the event (e.g., [:my_app, :user, :login]).
  2. measurements: A map of numeric values associated with the event (e.g., %{duration: 123456}).
  3. metadata: A map of additional context (e.g., %{user_id: 123}).
  4. config: Any custom configuration passed during attachment.

Your handler logic will use these arguments to process the event.

Code: Attaching and Handling Events

Now let's add a handler to our previous example. This handler will simply log the event details.

Notice how :telemetry.attach/4 links our handler function to the specific event name.

defmodule MyApp.WorkerWithHandler do
  require Logger

  # Define our simple handler function
  def handle_event(event_name, measurements, metadata, _config) do
    Logger.info("\n--- Telemetry Event Received ---")
    Logger.info("Event: #{inspect(event_name)}")
    Logger.info("Measurements: #{inspect(measurements)}")
    Logger.info("Metadata: #{inspect(metadata)}")
    Logger.info("------------------------------")
  end

  # Function that emits a Telemetry event
  def process_data(data) do
    Logger.info("Starting data processing...")
    :telemetry.span(
      [:my_app, :worker, :process_data],
      %{input_length: byte_size(data)},
      fn ->
        :timer.sleep(100)
        result = String.upcase(data)
        {:ok, result}
      end
    )
  end
end

# --- Main execution for CoddyKit ---
# Attach the handler *before* emitting events
:telemetry.attach(
  "my-worker-handler",
  [:my_app, :worker, :process_data], # Event name to listen for
  &MyApp.WorkerWithHandler.handle_event/4, # Our handler function
  nil # Optional config
)
Logger.info("Telemetry handler 'my-worker-handler' attached.")

# Perform some work, which will now trigger the handler
{:ok, result} = MyApp.WorkerWithHandler.process_data("hello world")
IO.puts("Processed result: #{result}")

# Clean up: detach the handler (good practice in tests/scripts)
:telemetry.detach("my-worker-handler")
Logger.info("Telemetry handler 'my-worker-handler' detached.")

Telemetry as a Metrics Source

Telemetry is not a metrics system itself, but it's an excellent source for them. By attaching handlers, you can feed events into dedicated metrics libraries.

  • Libraries like telemetry_metrics can aggregate Telemetry events into counters, gauges, and histograms.
  • These aggregated metrics are then often exported to monitoring systems like Prometheus or Datadog.
  • This separation keeps Telemetry lightweight and flexible, allowing you to choose your preferred metrics backend.

Quick Check: Telemetry Handlers

You've learned about emitting and handling Telemetry events. Let's test your understanding.

Recap: Telemetry for Observability

In this lesson, we explored Elixir's Telemetry library:

  • Telemetry is an event dispatching system for internal application observability.
  • It uses events with unique names, measurements, and metadata.
  • :telemetry.span/3 measures code execution duration.
  • :telemetry.execute/3 emits discrete, point-in-time events.
  • Handlers are functions attached via :telemetry.attach/4 to process events.
  • Telemetry events are a prime source for building application metrics.

Mastering Telemetry is key to understanding and monitoring your Elixir applications effectively!

免费开始

用 AI 导师学习 Elixir — 免费

在浏览器中编写并运行真实代码,获得全天候 AI 导师的即时帮助,并在网页或应用中继续学习。

课程
12
课程
48

常见问题解答

「使用 Telemetry 与指标进行监控」课时是免费的吗?

是的 — 「使用 Telemetry 与指标进行监控」的完整文本可在网页上免费阅读。要进行交互式练习(内置代码编辑器和全天候 AI 导师)并解锁 Elixir & Phoenix: Scalable Backend Development 课程的其余内容,请升级到 CoddyKit PRO。 Elixir & Phoenix: Scalable Backend Development 课程共包含 4 节课。

「使用 Telemetry 与指标进行监控」这节课中我会学到什么?

将 Telemetry 集成到应用中以生成指标,并深入了解应用的运行时行为。 你通过在浏览器中直接运行的动手代码来练习 Elixir & Phoenix: Scalable Backend Development,全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Elixir & Phoenix: Scalable Backend Development 需要有经验吗?

无需任何先前经验。CoddyKit 上的 Elixir & Phoenix: Scalable Backend Development 课程适合初学者到高级学习者,你可以从这里开始或从头开始,按照自己的节奏学习。 这是第 2 节课,共 4 节。

「使用 Telemetry 与指标进行监控」课时需要多长时间?

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动,所以你能稳步进步,并在网页和应用中从离开的地方继续。

我能在这节 Elixir & Phoenix: Scalable Backend Development 课中编写并运行代码吗?

能。每节 Elixir & Phoenix: Scalable Backend Development 课都包含内置代码编辑器,你可以在浏览器中直接编写并运行真实代码,并获得即时 AI 反馈 — 无需本地设置。

此课程中的所有课时

  1. Elixir 基准测试与性能分析
  2. 使用 Telemetry 与指标进行监控
  3. 错误处理与结构化日志记录
  4. 使用 OpenTelemetry 进行分布式追踪
← 返回 Elixir & Phoenix: Scalable Backend Development