Anti-patterns (distributed monolith, chatty services) in Microservices - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a distributed monolith in microservices architecture?

A distributed monolith is a system where microservices are tightly coupled and depend heavily on each other, causing the system to behave like a single monolithic application despite being split into services.

beginner

Why are chatty services considered an anti-pattern?

Chatty services make many small calls between microservices, increasing network overhead, latency, and complexity, which can degrade system performance and reliability.

intermediate

How does a distributed monolith affect scalability?

Because services are tightly coupled, scaling one service often requires scaling others, reducing the benefits of microservices and making the system harder to scale independently.

intermediate

What is a common cause of chatty services?

Poor service boundaries and design that require frequent synchronous communication between services for small pieces of data or operations.

intermediate

Name one strategy to avoid a distributed monolith.

Design clear service boundaries with high cohesion and low coupling, and use asynchronous communication patterns where possible.

What best describes a distributed monolith?

A Microservices communicating only asynchronously

B Microservices tightly coupled behaving like a monolith

C A single large monolithic application

D Completely independent microservices with no communication

A distributed monolith occurs when microservices are tightly coupled and behave like a single monolith.

Why are chatty services problematic?

A They reduce network calls

B They simplify debugging

C They improve service independence

D They increase latency and network overhead

Chatty services cause many small calls, increasing latency and network overhead.

Which practice helps avoid distributed monoliths?

A Clear service boundaries and asynchronous communication

B Tight coupling between services

C Frequent synchronous calls between services

D Sharing databases between services

Clear boundaries and async communication reduce tight coupling and avoid distributed monoliths.

What is a sign of chatty services in a system?

A Few, large service calls

B No communication between services

C Many small, frequent service calls

D Services deployed on the same server

Chatty services make many small, frequent calls increasing overhead.

How does a distributed monolith impact deployment?

A Deploying one service often requires deploying others

B Services can be deployed independently without issues

C Deployment is fully automated and simple

D It reduces deployment time

Tight coupling means deploying one service often requires deploying others, reducing independence.

Explain what a distributed monolith is and why it is considered an anti-pattern in microservices.

Think about how microservices should be independent but sometimes behave like one big app.

Describe chatty services and discuss their impact on system performance.

Imagine many tiny phone calls between friends instead of fewer longer calls.

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