Elixir & Phoenix: Scalable Backend Development · 강의

Telemetry와 메트릭을 활용한 모니터링

애플리케이션에 Telemetry를 통합해 메트릭을 내보내고 런타임 동작을 파악합니다.

Telemetry와 메트릭을 활용한 모니터링은(는) CoddyKit의 무료 Elixir & Phoenix: Scalable Backend Development 강의입니다. 이것은 4개 중 2번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 Elixir & Phoenix: Scalable Backend Development 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. Elixir & Phoenix: Scalable Backend Development 강의에는 총 4개의 강의가 포함되어 있습니다.

이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.

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:

event_name: The name of the event (e.g., [:my_app, :user, :login]).
measurements: A map of numeric values associated with the event (e.g., %{duration: 123456}).
metadata: A map of additional context (e.g., %{user_id: 123}).
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!

자주 묻는 질문

“Telemetry와 메트릭을 활용한 모니터링” 강의는 무료인가요?

네 — “Telemetry와 메트릭을 활용한 모니터링” 전체 내용을 이 웹사이트에서 무료로 읽을 수 있습니다. 인터랙티브하게 실습하려면(내장 코드 에디터와 24/7 AI 튜터), CoddyKit PRO로 업그레이드하면 Elixir & Phoenix: Scalable Backend Development 강의 전체를 잠금 해제할 수 있습니다. Elixir & Phoenix: Scalable Backend Development 강의에는 총 4개의 강의가 포함되어 있습니다.

“Telemetry와 메트릭을 활용한 모니터링”에서 뭘 배우나요?

애플리케이션에 Telemetry를 통합해 메트릭을 내보내고 런타임 동작을 파악합니다. 브라우저에서 직접 실행하는 실습 코드로 Elixir & Phoenix: Scalable Backend Development을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.

Elixir & Phoenix: Scalable Backend Development을(를) 시작하는 데 경험이 필요한가요?

사전 경험은 필요하지 않습니다. CoddyKit의 Elixir & Phoenix: Scalable Backend Development은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 2번째 강의입니다.

“Telemetry와 메트릭을 활용한 모니터링” 강의는 얼마나 걸리나요?

대부분의 CoddyKit 강의는 약 5~10분이 소요됩니다. 각 강의는 간결하고 인터랙티브하여 꾸준한 진행이 가능하며, 웹과 앱에서 중단한 부분부터 바로 시작할 수 있습니다.

이 Elixir & Phoenix: Scalable Backend Development 강의에서 코드를 작성하고 실행할 수 있나요?

네. 모든 Elixir & Phoenix: Scalable Backend Development 강의에는 내장 코드 에디터가 포함되어 있으므로, 브라우저에서 바로 실제 코드를 작성하고 실행한 후 즉시 AI 피드백을 받을 수 있습니다 — 로컬 설정이 필요 없습니다.

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