Distributed tracing (Jaeger, Zipkin) in Microservices - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is distributed tracing in microservices?

Distributed tracing is a method to track and observe requests as they flow through multiple microservices, helping to understand system behavior and diagnose issues.

beginner

Name two popular distributed tracing tools.

Jaeger and Zipkin are two widely used open-source distributed tracing tools.

intermediate

What is a 'span' in distributed tracing?

A span represents a single unit of work or operation within a trace, such as a request to a microservice or a database call.

intermediate

How does distributed tracing help in debugging microservices?

It shows the path of a request across services with timing details, helping identify slow or failing components quickly.

beginner

What is the role of a trace ID in distributed tracing?

A trace ID uniquely identifies a single request as it travels through multiple services, linking all spans together.

Which of the following best describes a 'trace' in distributed tracing?

A A log file of errors

B A single operation within a service

C A collection of spans representing a single request journey

D A database query

A trace is made up of multiple spans that together represent the full path of a request.

What is the primary purpose of Jaeger and Zipkin?

A To monitor network traffic

B To deploy microservices

C To store user data

D To trace requests across microservices

Jaeger and Zipkin help track requests as they move through microservices.

Which component in distributed tracing represents a single operation or work unit?

A Span

B Service mesh

C Trace ID

D Log entry

A span is a single operation within a trace.

How does distributed tracing improve system observability?

A By encrypting data

B By showing request flow and timing across services

C By reducing server load

D By caching responses

It provides visibility into how requests move and perform across services.

What unique identifier links all spans of a single request in distributed tracing?

A Trace ID

B User ID

C Session ID

D Service ID

Trace ID connects all spans belonging to the same request.

Explain how distributed tracing works in a microservices environment using Jaeger or Zipkin.

Think about how a request travels and how tracing tools capture each step.

Describe the benefits of using distributed tracing for debugging and monitoring microservices.

Consider how tracing helps find problems quickly.

Practice

1. What is the main purpose of distributed tracing tools like Jaeger or Zipkin in microservices?

easy

A. To track and visualize requests as they flow through multiple services

B. To store large amounts of user data securely

C. To replace load balancers in service communication

D. To encrypt network traffic between microservices

Solution

1. Step 1: Understand the role of distributed tracing

   Distributed tracing tools help monitor how requests move through different microservices by collecting timing and metadata.

2. Step 2: Identify the main function of Jaeger and Zipkin

   They visualize and analyze traces made of spans to find bottlenecks or errors in service chains.

3. Final Answer:

   To track and visualize requests as they flow through multiple services -> Option A

4. Quick Check:

   Distributed tracing = track requests flow [OK]

Hint: Distributed tracing = tracking requests across services [OK]

Common Mistakes:

• Confusing tracing with data storage
• Thinking tracing replaces load balancers
• Assuming tracing encrypts traffic

2. Which of the following is the correct way to propagate trace context between microservices using HTTP headers?

easy

A. Add Cookie header with span ID

B. Add Authorization header with trace ID

C. Add X-B3-TraceId and X-B3-SpanId headers to the outgoing request

D. Add Content-Type header with trace ID value

Solution

1. Step 1: Recall standard trace context headers

   Distributed tracing uses specific headers like X-B3-TraceId and X-B3-SpanId to pass trace info between services.

2. Step 2: Identify correct header usage

   Headers like Authorization, Content-Type, or Cookie are unrelated to tracing context propagation.

3. Final Answer:

   Add X-B3-TraceId and X-B3-SpanId headers to the outgoing request -> Option C

4. Quick Check:

   Trace context headers = X-B3-TraceId, X-B3-SpanId [OK]

Hint: Trace context uses X-B3 headers, not auth or content-type [OK]

Common Mistakes:

• Using unrelated HTTP headers for trace context
• Forgetting to propagate span ID
• Confusing trace ID with authentication tokens

3. Given the following trace spans collected by Zipkin, what is the total time taken by the root request?

Span A (root): start=0ms, duration=50ms
Span B (child of A): start=10ms, duration=20ms
Span C (child of A): start=35ms, duration=10ms

medium

A. 50ms

B. 40ms

C. 30ms

D. 60ms

Solution

1. Step 1: Understand root span duration

   The root span duration represents the total time of the entire request, including child spans.

2. Step 2: Analyze given spans

   Span A starts at 0ms and lasts 50ms, so total time is 50ms regardless of child spans.

3. Final Answer:

   50ms -> Option A

4. Quick Check:

   Root span duration = total request time = 50ms [OK]

Hint: Root span duration = total request time [OK]

Common Mistakes:

• Adding child spans durations incorrectly
• Ignoring root span duration
• Confusing start times with total duration

4. You notice that your distributed tracing data in Jaeger shows many missing spans for some services. What is the most likely cause?

medium

A. The network latency is too low

B. The services have too many CPU cores

C. The database is down

D. The services are not propagating the trace context headers correctly

Solution

1. Step 1: Identify cause of missing spans

   If spans are missing, it usually means trace context was not passed properly between services.

2. Step 2: Eliminate unrelated causes

   CPU cores, database status, or low network latency do not cause missing trace spans.

3. Final Answer:

   The services are not propagating the trace context headers correctly -> Option D

4. Quick Check:

   Missing spans = trace context not propagated [OK]

Hint: Missing spans? Check trace context propagation [OK]

Common Mistakes:

• Blaming unrelated system resources
• Ignoring header propagation
• Assuming network latency causes missing spans

5. You want to design a distributed tracing system for a microservices architecture with 100 services and high request volume. Which approach best ensures scalability and minimal overhead?

hard

A. Trace every request fully and store all spans in a single central database

B. Use sampling to trace only a subset of requests and propagate trace context with lightweight headers

C. Disable trace context propagation and log spans locally in each service

D. Use synchronous calls to the tracing backend for every span creation

Solution

1. Step 1: Consider scalability needs

   Tracing every request fully in a large system causes high overhead and storage issues.

2. Step 2: Identify best practice for high volume tracing

   Sampling reduces load by tracing only some requests, and lightweight headers keep propagation efficient.

3. Step 3: Eliminate poor options

   Disabling propagation loses trace linkage; synchronous calls add latency; central DB can bottleneck.

4. Final Answer:

   Use sampling to trace only a subset of requests and propagate trace context with lightweight headers -> Option B

5. Quick Check:

   Sampling + lightweight headers = scalable tracing [OK]

Hint: Sampling + lightweight headers = scalable tracing [OK]

Common Mistakes:

• Tracing all requests causing overhead
• Ignoring trace context propagation
• Using synchronous calls causing latency