System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) · Pelajaran

Propagasi Konteks dan Bagasi

Pelajari propagasi konteks secara mendalam, yaitu konsep penting OpenTelemetry untuk menghubungkan operasi terdistribusi. Pelajari cara bagasi membawa data sembarang melintasi layanan.

Pelajaran 3 dari 411 langkah

Propagasi Konteks dan Bagasi adalah pelajaran System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) gratis di CoddyKit. Ini adalah pelajaran 3 dari 4. Kamu bisa membaca pelajaran lengkapnya di bawah secara gratis — lalu praktikkan langsung di browser dengan editor kode bawaan dan tutor AI 24/7. Ini adalah bagian dari jalur belajar System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry), dan progresmu tersinkronisasi di web dan aplikasi CoddyKit. Kursus System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) mencakup 4 pelajaran total.

Bagian dari pelajaran ini belum diterjemahkan dan ditampilkan dalam bahasa Inggris.

Linking Distributed Operations

In modern applications, a single user request often travels through many different services. Imagine an online store: your click goes to a frontend, then an order service, a payment service, and a shipping service.

How do we track this journey? If each service logs independently, it's like trying to follow a single thread in a tangled ball of yarn!

What is Context Propagation?

Context propagation is the magic that links these distributed operations together. It ensures that all parts of a request, no matter which service they touch, share a common understanding of that request.

Think of it like a relay race: the 'baton' (the context) is passed from one runner (service) to the next, linking all their efforts to a single goal.

The Trace Context Explained

The core of context propagation is the Trace Context. This usually contains two vital pieces of information:

  • Trace ID: A unique identifier for the entire request journey across all services.
  • Span ID: A unique identifier for the current operation within a service.

These IDs are crucial for OpenTelemetry to build a complete picture of your request's flow.

How Context Travels

Context doesn't just magically appear! OpenTelemetry uses 'propagators' to inject and extract this context.

Common ways context is propagated:

  • HTTP Headers: Standard headers like traceparent and tracestate.
  • gRPC Metadata: Similar to HTTP headers, but for gRPC calls.
  • Message Queue Properties: When sending messages between services.

These mechanisms ensure the Trace ID and Span ID follow the request.

Injecting Context Demo

When a service makes an outgoing call to another service, the current trace context needs to be 'injected' into the request. This example simulates adding trace context to headers.

import io.opentelemetry.api.trace.Span; 
import io.opentelemetry.api.trace.SpanContext;
import io.opentelemetry.context.Context;
import io.opentelemetry.context.propagation.TextMapSetter;
import java.util.HashMap;
import java.util.Map;

public class ContextInjector {

  public static void main(String[] args) {
    // Simulate an active span context
    SpanContext simulatedSpanContext =
        SpanContext.create(
            "0123456789abcdef0123456789abcdef", // Trace ID
            "fedcba9876543210", // Span ID
            io.opentelemetry.api.trace.TraceFlags.getDefault(),
            io.opentelemetry.api.trace.TraceState.getDefault());
    Span span = Span.wrap(simulatedSpanContext);
    Context context = Context.current().with(span);

    Map<String, String> headers = new HashMap<>();
    TextMapSetter<Map<String, String>> setter = Map::put;

    // OpenTelemetry usually handles this implicitly
    // Here, we simulate injecting context into headers
    // using a simplified representation.
    headers.put("traceparent", "00-" + simulatedSpanContext.getTraceId() + "-" + simulatedSpanContext.getSpanId() + "-01");
    
    System.out.println("Injected Headers:");
    headers.forEach((key, value) -> System.out.println(key + ": " + value));
  }
}

Extracting Context Demo

When a service receives an incoming request, it needs to 'extract' the trace context from the request. This allows it to continue the trace initiated by the upstream service.

import io.opentelemetry.api.trace.SpanContext;
import io.opentelemetry.context.Context;
import io.opentelemetry.context.propagation.TextMapGetter;
import io.opentelemetry.context.propagation.TextMapPropagator;
import io.opentelemetry.sdk.OpenTelemetrySdk;
import java.util.HashMap;
import java.util.Map;

public class ContextExtractor {

  public static void main(String[] args) {
    Map<String, String> incomingHeaders = new HashMap<>();
    incomingHeaders.put("traceparent", "00-112233445566778899aabbccddeeff00-aabbccddeeff0011-01");

    TextMapGetter<Map<String, String>> getter = new TextMapGetter<Map<String, String>>() {
      @Override
      public Iterable<String> keys(Map<String, String> carrier) {
        return carrier.keySet();
      }

      @Override
      public String get(Map<String, String> carrier, String key) {
        return carrier.get(key);
      }
    };

    // In a real app, OpenTelemetry.getGlobalPropagators() would be used
    TextMapPropagator propagator = OpenTelemetrySdk.builder().build()
        .getPropagators().getTextMapPropagator();

    Context extractedContext = propagator.extract(Context.current(), incomingHeaders, getter);
    SpanContext spanContext = Span.fromContext(extractedContext).getSpanContext();

    System.out.println("Extracted Trace ID: " + spanContext.getTraceId());
    System.out.println("Extracted Span ID: " + spanContext.getSpanId());
  }
}

Carrying Extra Data: Baggage

Beyond just trace and span IDs, sometimes you need to carry arbitrary key-value data across services that's relevant to the business logic, but not directly for tracing.

This is where Baggage comes in! It's a collection of key-value pairs that travel alongside the trace context.

Baggage vs. Trace Context

It's important to understand the difference:

  • Trace Context: Essential for linking spans and building the trace graph. It's structural.
  • Baggage: Carries application-specific data. Examples include a user_id, tenant_id, or an A/B test variant. It's informational.

Baggage is propagated using the same mechanisms as trace context (e.g., HTTP headers), often in a header like baggage.

Using Baggage Demo

Here's how you can add an item to Baggage in one part of your application and retrieve it in another, potentially downstream, service. This data travels with the request.

import io.opentelemetry.api.baggage.Baggage;
import io.opentelemetry.context.Context;

public class BaggageUsage {

  public static void main(String[] args) {
    // --- Service A: Add to Baggage ---
    System.out.println("--- Service A ---");
    Context contextWithBaggage = Baggage.current()
        .toBuilder()
        .put("user.id", "12345")
        .put("ab.test.group", "variantA")
        .build()
        .make   Current(); // Make this baggage active in current context

    System.out.println("Added user.id: " + Baggage.current().getEntryValue("user.id"));
    System.out.println("Added ab.test.group: " + Baggage.current().getEntryValue("ab.test.group"));
    
    // Simulate passing context (and thus baggage) to Service B
    // In a real app, this would be via HTTP headers, etc.
    callServiceB(contextWithBaggage);
  }

  public static void callServiceB(Context parentContext) {
    // --- Service B: Retrieve from Baggage ---
    System.out.println("\n--- Service B ---");
    // Activate the context from Service A
    try (io.opentelemetry.context.Scope scope = parentContext.makeCurrent()) {
      Baggage currentBaggage = Baggage.current();
      System.out.println("Retrieved user.id: " + currentBaggage.getEntryValue("user.id"));
      System.out.println("Retrieved ab.test.group: " + currentBaggage.getEntryValue("ab.test.group"));
    }
  }
}

Context Propagation Check

You're debugging a distributed system. A user reports an issue, and you have their user_id. You want to see all logs and traces related to this user across multiple services.

Context & Baggage Summary

You've learned how context propagation is fundamental to distributed tracing, using Trace IDs and Span IDs to link operations across services.

You also explored Baggage, a powerful mechanism to carry custom, application-specific data (like a user_id or A/B test group) alongside your trace context, enriching your observability data.

These concepts are vital for building a complete and actionable view of your distributed applications!

Gratis untuk memulai

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Kursus
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Pelajaran
48

Pertanyaan yang Sering Diajukan

Apakah pelajaran “Propagasi Konteks dan Bagasi” gratis?

Ya — teks lengkap “Propagasi Konteks dan Bagasi” gratis dibaca di sini di web. Untuk praktiknya secara interaktif (editor kode bawaan dan tutor AI 24/7) dan buka sisa kursus System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry), upgrade ke CoddyKit PRO. Kursus System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) mencakup 4 pelajaran total.

Apa yang akan aku pelajari di “Propagasi Konteks dan Bagasi”?

Pelajari propagasi konteks secara mendalam, yaitu konsep penting OpenTelemetry untuk menghubungkan operasi terdistribusi. Pelajari cara bagasi membawa data sembarang melintasi layanan. Kamu berlatih System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) dengan kode praktik yang langsung kamu jalankan di browser, dan tutor AI 24/7 menjawab pertanyaanmu saat kamu mengerjakan pelajaran ini.

Apakah aku perlu pengalaman untuk memulai System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry)?

Tidak diperlukan pengalaman sebelumnya. System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) di CoddyKit dirancang untuk pemula hingga pelajar tingkat lanjut, jadi kamu bisa memulai di sini atau dari awal dan belajar sesuai kecepatan kamu sendiri. Ini adalah pelajaran 3 dari 4.

Berapa lama pelajaran “Propagasi Konteks dan Bagasi” memakan waktu?

Sebagian besar pelajaran CoddyKit memakan waktu sekitar 5–10 menit. Setiap pelajaran ringkas dan interaktif, jadi kamu membuat kemajuan stabil dan melanjutkan dari tempat kamu tinggalkan di web dan aplikasi.

Bisakah aku menulis dan menjalankan kode dalam pelajaran System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) ini?

Ya. Setiap pelajaran System Observability: Logging, Metrics & Tracing (ELK + OpenTelemetry) menyertakan editor kode bawaan, jadi kamu menulis dan menjalankan kode nyata langsung di browser dan mendapatkan umpan balik AI instan — tidak diperlukan penyiapan lokal.

Semua pelajaran dalam kursus ini

  1. Teknik Instrumentasi Otomatis
  2. Praktik Terbaik Instrumentasi Manual
  3. Propagasi Konteks dan Bagasi
  4. Atribut Span, Peristiwa, dan Status
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