Anti-patterns (distributed monolith, chatty services) in Microservices - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to identify the anti-pattern where services are tightly coupled and deploy together.

Microservices

if system_architecture == '[1]':
    print("Warning: Services are tightly coupled and not independently deployable.")

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

Amonolithic

Bevent_driven

Cserverless

Ddistributed_monolith

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'monolithic' which is a single app, not distributed.

The distributed monolith anti-pattern occurs when microservices are tightly coupled and cannot be deployed independently.

2fill in blank

medium

Complete the code to detect an anti-pattern where services make too many small calls to each other.

Microservices

if service_calls_per_request > [1]:
    print("Warning: Chatty services detected, consider reducing inter-service calls.")

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

A10

B100

C50

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 5 which is too low, or 50/100 which is too high.

More than 10 calls per request often indicates chatty services, which can cause latency and complexity.

3fill in blank

hard

Fix the error in the code that wrongly identifies chatty services by comparing calls incorrectly.

Microservices

if total_calls_per_request [1] 10:
    print("Chatty services detected")

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

A>=

B<=

C==

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<=' which detects low calls instead of high.

We want to detect when calls are greater than or equal to 10 to flag chatty services.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps service names to their call counts, filtering only chatty services.

Microservices

chatty_services = {service: calls for service, calls in service_calls.items() if calls [1] [2]

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

A>

B10

C<

D5

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' which filters low call services.

This comprehension filters services with calls greater than 10, identifying chatty services.

5fill in blank

hard

Fill all three blanks to create a function that detects distributed monolith by checking if services share the same database and have high coupling.

Microservices

def is_distributed_monolith(services):
    shared_db = any(s['db'] == [1] for s in services)
    high_coupling = any(s['calls'] [2] [3] for s in services)
    return shared_db and high_coupling

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

A'central_db'

B>

C10

D'isolated_db'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'isolated_db' which means no shared database.

The function checks if any service uses the central shared database and makes more than 10 calls, indicating a distributed monolith.

Practice

1. Which of the following best describes a distributed monolith in microservices architecture?

easy

A. Services are fully independent and communicate rarely.

B. Services are tightly coupled and require coordinated deployment.

C. Services use asynchronous messaging to reduce latency.

D. Services are stateless and scale automatically.

Solution

1. Step 1: Understand distributed monolith characteristics

   A distributed monolith looks like microservices but behaves like a single app with tight coupling.

2. Step 2: Identify deployment and coupling issues

   Such services require coordinated deployment and cannot scale independently.

3. Final Answer:

   Services are tightly coupled and require coordinated deployment. -> Option B

4. Quick Check:

   Distributed monolith = tight coupling [OK]

Hint: Distributed monolith means tight coupling, not independence [OK]

Common Mistakes:

• Confusing distributed monolith with loosely coupled microservices
• Thinking distributed monolith scales independently
• Assuming distributed monolith uses asynchronous calls

2. Which syntax correctly describes a common symptom of chatty services in microservices communication?

easy

A. Service A uses event-driven messaging to notify Service B.

B. Service A calls Service B once per user request.

C. Service A calls Service B multiple times per user request.

D. Service A caches data to reduce calls to Service B.

Solution

1. Step 1: Define chatty services behavior

   Chatty services make many small calls between services per user request.

2. Step 2: Identify the correct syntax describing chatty calls

   Multiple calls per request indicate chatty communication.

3. Final Answer:

   Service A calls Service B multiple times per user request. -> Option C

4. Quick Check:

   Chatty services = many calls [OK]

Hint: Chatty means many calls, not just one [OK]

Common Mistakes:

• Choosing event-driven messaging as chatty behavior
• Assuming caching causes chatty services
• Thinking one call per request is chatty

3. Given a microservices system where Service A calls Service B 5 times and Service B calls Service C 3 times per user request, what is the total number of service calls triggered by one user request?

medium

A. 20

B. 15

C. 30

D. 8

Solution

1. Step 1: Calculate calls from Service A to B

   Service A calls Service B 5 times per request.

2. Step 2: Calculate calls from Service B to C triggered by A's calls

   Each of the 5 calls from A causes 3 calls from B to C, so 5 * 3 = 15 calls.

3. Step 3: Sum all calls

   Total calls = 5 (A->B) + 15 (B->C) = 20 calls.

4. Final Answer:

   20 -> Option A

5. Quick Check:

   5 + (5*3) = 20 [OK]

Hint: Multiply nested calls, then add all [OK]

Common Mistakes:

• Adding 5 + 3 instead of multiplying
• Ignoring nested calls from B to C
• Choosing sum as 18 instead of 20

4. You notice your microservices system has high latency due to many small synchronous calls between services. Which change would best fix this chatty service anti-pattern?

medium

A. Use asynchronous messaging or batch requests to reduce calls.

B. Combine tightly coupled services into a single service.

C. Add more synchronous calls to improve data freshness.

D. Increase the number of service instances to handle load.

Solution

1. Step 1: Identify chatty service problem

   Many small synchronous calls cause latency and network overhead.

2. Step 2: Choose solution to reduce call frequency

   Using asynchronous messaging or batching reduces calls and latency.

3. Final Answer:

   Use asynchronous messaging or batch requests to reduce calls. -> Option A

4. Quick Check:

   Reduce calls with async or batching [OK]

Hint: Reduce calls by batching or async messaging [OK]

Common Mistakes:

• Combining services creates distributed monolith
• Adding more sync calls worsens latency
• Scaling instances doesn't reduce call count

5. A company has a microservices system suffering from both distributed monolith and chatty services anti-patterns. Which combined approach best improves scalability and deployment independence?

hard

A. Merge all services into one large application to simplify deployment.

B. Increase hardware resources and add load balancers to handle traffic.

C. Use synchronous REST calls extensively to keep services tightly connected.

D. Refactor services to reduce dependencies and use asynchronous communication.

Solution

1. Step 1: Address distributed monolith by reducing dependencies

   Refactoring services to be loosely coupled allows independent deployment and scaling.

2. Step 2: Fix chatty services by adopting asynchronous communication

   Using async messaging reduces frequent synchronous calls and network overhead.

3. Step 3: Combine both improvements for better scalability and independence

   This combined approach solves both anti-patterns effectively.

4. Final Answer:

   Refactor services to reduce dependencies and use asynchronous communication. -> Option D

5. Quick Check:

   Loose coupling + async = scalable microservices [OK]

Hint: Loose coupling + async communication fixes both issues [OK]

Common Mistakes:

• Merging services worsens distributed monolith
• Adding hardware doesn't fix design flaws
• Using more sync calls increases chatty problems