Chaos engineering basics in Microservices - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is chaos engineering?

Chaos engineering is the practice of intentionally introducing failures into a system to test its resilience and improve its ability to handle unexpected problems.

beginner

Why do we perform chaos engineering in microservices?

Because microservices are distributed and complex, chaos engineering helps find hidden weaknesses before real failures happen, ensuring the system stays reliable.

beginner

Name a common type of failure introduced in chaos engineering experiments.

Examples include shutting down a service, increasing latency, or causing network partitions to see how the system reacts.

beginner

What is the main goal of chaos engineering?

The main goal is to build confidence that the system can withstand turbulent conditions and continue to operate correctly.

intermediate

How should chaos experiments be conducted safely?

Start small, run experiments in controlled environments or during low traffic, monitor carefully, and have quick rollback plans.

What does chaos engineering primarily test in a system?

A System resilience to failures

B User interface design

C Database schema correctness

D Code style consistency

Chaos engineering focuses on testing how well a system handles failures and unexpected conditions.

Which of the following is NOT a typical chaos experiment?

A Changing user passwords

B Shutting down a microservice

C Introducing network delays

D Simulating high CPU usage

Changing user passwords is unrelated to chaos engineering experiments.

When is the best time to run chaos experiments?

A During peak traffic without monitoring

B In a controlled environment with monitoring

C Without informing the team

D Only after system failure

Experiments should be done carefully with monitoring to avoid unintended damage.

What is a key benefit of chaos engineering in microservices?

A Increases deployment speed

B Reduces code complexity

C Enhances UI responsiveness

D Improves system resilience

Chaos engineering helps improve how well microservices handle failures.

Which statement best describes a chaos engineering experiment?

A Randomly breaking parts of the system without observation

B Monitoring system logs passively

C Carefully planned failure injection to test system behavior

D Writing unit tests for code functions

Chaos experiments are planned and observed to learn about system weaknesses.

Explain what chaos engineering is and why it is important for microservices.

Think about how breaking things on purpose helps systems get stronger.

Describe best practices to safely conduct chaos engineering experiments.

Consider how to avoid causing real harm while testing failures.

Practice

1. What is the main goal of chaos engineering in microservices?

easy

A. To reduce the number of developers needed

B. To increase the number of microservices in a system

C. To find and fix weaknesses before real failures occur

D. To speed up the deployment process

Solution

1. Step 1: Understand chaos engineering purpose

   Chaos engineering is about testing systems by intentionally causing failures to find weaknesses.

2. Step 2: Identify the main goal

   The goal is to find and fix weaknesses before they cause real problems in production.

3. Final Answer:

   To find and fix weaknesses before real failures occur -> Option C

4. Quick Check:

   Chaos engineering goal = Find and fix weaknesses [OK]

Hint: Chaos engineering tests failures to improve system stability [OK]

Common Mistakes:

• Thinking chaos engineering increases microservices count
• Confusing chaos engineering with deployment speedup
• Assuming chaos engineering reduces developer count

2. Which of the following is a correct way to start chaos engineering experiments?

easy

A. Start with complex multi-service failures immediately

B. Begin with simple, controlled failure tests

C. Run chaos tests only after a system crash

D. Avoid monitoring during chaos experiments

Solution

1. Step 1: Review best practice for chaos experiments

   Best practice is to start small with simple, controlled failures to understand system behavior.

2. Step 2: Identify the correct starting approach

   Starting with simple tests helps safely learn and improve system resilience gradually.

3. Final Answer:

   Begin with simple, controlled failure tests -> Option B

4. Quick Check:

   Start chaos with simple tests = Begin with simple, controlled failure tests [OK]

Hint: Start chaos tests simple and controlled, not complex [OK]

Common Mistakes:

• Starting with complex failures too soon
• Running chaos only after failures happen
• Ignoring monitoring during tests

3. Consider a microservice system where a chaos experiment randomly kills one instance every 5 minutes. What is the expected immediate effect on system availability?

medium

A. System availability remains stable if redundancy exists

B. System availability drops to zero immediately

C. System crashes permanently after first kill

D. System automatically scales down instances

Solution

1. Step 1: Analyze the chaos experiment impact

   Killing one instance every 5 minutes tests resilience but does not remove all instances.

2. Step 2: Consider system redundancy

   If the system has redundant instances, killing one does not reduce availability immediately.

3. Final Answer:

   System availability remains stable if redundancy exists -> Option A

4. Quick Check:

   Redundancy keeps availability stable during chaos [OK]

Hint: Redundancy keeps system available despite instance failures [OK]

Common Mistakes:

• Assuming system crashes immediately after one instance killed
• Thinking availability drops to zero instantly
• Believing system scales down automatically

4. A chaos experiment script intended to shut down a microservice instance sometimes fails silently without stopping the instance. What is the most likely cause?

medium

A. The network is too fast for the script

B. The microservice is designed to never stop

C. The chaos experiment is running on a different system

D. The script lacks proper error handling and logging

Solution

1. Step 1: Identify why script fails silently

   Silent failures usually happen when errors are not caught or logged properly.

2. Step 2: Evaluate other options

   Microservices can be stopped; network speed does not cause silent failure; running on different system would cause errors, not silent failure.

3. Final Answer:

   The script lacks proper error handling and logging -> Option D

4. Quick Check:

   Silent failure = Missing error handling [OK]

Hint: Check error handling if chaos script fails silently [OK]

Common Mistakes:

• Assuming microservice cannot be stopped
• Blaming network speed for silent failure
• Ignoring script environment mismatch

5. You want to design a chaos engineering experiment to test how your microservices handle database latency spikes. Which approach best fits this goal?

hard

A. Inject artificial latency into database calls during tests

B. Disable monitoring tools to avoid false alerts

C. Increase the number of database replicas without testing

D. Randomly kill microservice instances during peak hours

Solution

1. Step 1: Understand the goal of testing database latency spikes

   The goal is to see how microservices behave when database responses are slow.

2. Step 2: Choose the best chaos experiment approach

   Injecting artificial latency simulates slow database calls directly, matching the goal.

3. Step 3: Evaluate other options

   Killing instances tests availability, not latency; increasing replicas without testing doesn't simulate latency; disabling monitoring hides important data.

4. Final Answer:

   Inject artificial latency into database calls during tests -> Option A

5. Quick Check:

   Test latency by injecting delays = Inject artificial latency into database calls during tests [OK]

Hint: Inject delays to test latency, not kill instances [OK]

Common Mistakes:

• Confusing instance failure with latency testing
• Adding replicas without testing effects
• Turning off monitoring during chaos