Service mesh concept in Microservices - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a service mesh component that manages communication between microservices.

Microservices

service_mesh = [1]('linker')

Drag options to blanks, or click blank then click option'

AProxy

BGateway

CLoadBalancer

DSidecar

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'Proxy' alone without the sidecar pattern.

Confusing 'Gateway' with internal service communication.

Using 'LoadBalancer' which is for traffic distribution, not mesh.

The Sidecar pattern is used in service mesh to manage communication by running alongside each microservice.

2fill in blank

medium

Complete the code to enable secure communication between services in a service mesh.

Microservices

service_mesh.enable_tls([1]=True)

Drag options to blanks, or click blank then click option'

Aencryption

Bmutual_authentication

Cmutual_tls

Dinsecure

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'encryption' alone without mutual verification.

Confusing 'mutual_authentication' which is not a direct parameter.

Setting 'insecure' to True disables security.

Mutual TLS (mTLS) is used in service mesh to secure communication by authenticating both client and server.

3fill in blank

hard

Fix the error in the code to correctly configure traffic routing in a service mesh.

Microservices

service_mesh.route_traffic(source='frontend', destination=[1])

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Abackend-service

Bfrontend-service

Cdatabase

Dcache

Attempts:

3 left

💡 Hint

Common Mistakes

Routing traffic back to frontend causing loops.

Routing to database directly instead of backend service.

Routing to cache which is not the main service endpoint.

The destination should be the backend-service to route traffic from frontend to backend correctly.

4fill in blank

hard

Fill both blanks to create a policy that limits requests and retries in a service mesh.

Microservices

policy = [1](max_requests=100, retry=[2])

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ARateLimiter

B3

C5

DRetryPolicy

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'RetryPolicy' for rate limiting.

Setting retry count too high or as a string.

Confusing max_requests with retry count.

The RateLimiter controls request limits, and 3 retries is a common retry count.

5fill in blank

hard

Fill all three blanks to define a service mesh configuration that includes observability and fault injection.

Microservices

config = {
  '[1]': True,
  'fault_injection': {'delay': [2], 'percentage': [3]
}

Drag options to blanks, or click blank then click option'

Aobservability

B'100ms'

C10

Dlogging

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'logging' instead of observability.

Setting delay without units or as a number only.

Confusing percentage with delay value.

Observability enables monitoring, 100ms delay simulates latency, and 10% fault injection rate tests resilience.