Chaos engineering basics in Microservices - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define the main goal of chaos engineering.

Microservices

chaos_engineering_goal = "[1]"

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Ato avoid any system testing

Bto increase system downtime intentionally

Cto improve system resilience by testing failures

Dto reduce system monitoring

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing chaos engineering with causing system downtime.

Thinking chaos engineering avoids testing.

The main goal of chaos engineering is to improve system resilience by intentionally testing failures in a controlled way.

2fill in blank

medium

Complete the code to identify a common tool used in chaos engineering for microservices.

Microservices

common_chaos_tool = "[1]"

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AChaos Monkey

BKubernetes

CDocker

DPrometheus

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing Kubernetes or Docker which are container tools, not chaos tools.

Selecting Prometheus which is a monitoring tool.

Chaos Monkey is a popular tool used to randomly terminate instances in microservices to test system resilience.

3fill in blank

hard

Fix the error in the code that simulates a failure injection in a microservice.

Microservices

def inject_failure(service):
    if service.status == 'healthy':
        service.status = '[1]'
    return service.status

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Afailed

Brunning

Cstarting

Didle

Attempts:

3 left

💡 Hint

Common Mistakes

Setting status to 'running' or 'starting' which means the service is healthy.

Using 'idle' which does not indicate failure.

To simulate failure, the service status should be set to 'failed'.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps microservice names to their failure status if they are unhealthy.

Microservices

failure_map = {service.name: service.status for service in services if service.status [1] '[2]'}

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A!=

B==

Cfailed

Dhealthy

Attempts:

3 left

💡 Hint

Common Mistakes

Using '==' with 'healthy' which selects healthy services instead of failures.

Using '!=' with 'failed' which would select healthy services.

The comprehension filters services whose status is not equal to 'healthy', mapping their names to their status.

5fill in blank

hard

Fill all three blanks to create a function that triggers chaos experiments only if the system is stable and the experiment is approved.

Microservices

def trigger_chaos(system_status, experiment_approved):
    if system_status [1] 'stable' and experiment_approved [2] True:
        return '[3]'
    else:
        return 'Do not run experiment'

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A==

B!=

CRun experiment

DFalse

Attempts:

3 left

💡 Hint

Common Mistakes

Using '!=' which would invert the logic.

Returning 'False' or other strings instead of 'Run experiment'.

The function checks if the system status equals 'stable' and the experiment is approved (True), then returns 'Run experiment'.