Parallel running in Microservices - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Parallel Running in Microservices

In a microservices environment, what is the primary purpose of parallel running during a system upgrade?

A To deploy multiple microservices on the same server to save resources

B To split a microservice into smaller parts to improve scalability

C To run microservices in parallel threads within the same process for faster execution

D To run the old and new versions simultaneously to compare outputs and ensure correctness before full switch-over

💡 Hint

Think about how to safely transition from an old system to a new one without disrupting users.

Parallel running means operating both old and new systems at the same time to verify the new system works correctly before fully switching over.

❓ Architecture

intermediate

Designing Parallel Running for a Payment Microservice

You want to implement parallel running for a payment microservice to migrate from version 1 to version 2. Which architectural component is essential to route requests to both versions simultaneously?

A API Gateway with traffic splitting capability

B Database replication service

C Load balancer that only sends traffic to the new version

D Service registry without routing features

💡 Hint

Consider how incoming requests can be sent to two different service versions at the same time.

An API Gateway with traffic splitting can send requests to both old and new versions simultaneously, enabling parallel running.

❓ scaling

advanced

Scaling Challenges in Parallel Running

When running two versions of a microservice in parallel, what is a key challenge related to system resources?

A Resource contention leading to increased CPU and memory usage

B Decreased database load because of parallel writes

C Reduced network latency due to duplicated services

D Automatic scaling of only the old version without affecting the new

💡 Hint

Think about what happens when two systems run side by side on the same infrastructure.

Running two versions simultaneously doubles resource usage, causing contention and higher CPU and memory consumption.

❓ tradeoff

advanced

Trade-offs of Parallel Running vs Blue-Green Deployment

Which is a major trade-off when choosing parallel running over blue-green deployment for microservices?

A Parallel running eliminates the need for monitoring; blue-green requires extensive monitoring

B Parallel running is faster to deploy but risks data loss; blue-green is slower but safer

C Parallel running requires more resources but allows direct output comparison; blue-green uses fewer resources but switches instantly

D Parallel running only works for stateless services; blue-green works for all services

💡 Hint

Consider resource usage and how the two methods handle traffic during deployment.

Parallel running runs both versions simultaneously, using more resources but enabling output comparison. Blue-green switches traffic instantly, using fewer resources but less direct comparison.

❓ estimation

expert

Estimating Capacity for Parallel Running in Microservices

You have a microservice cluster handling 10,000 requests per second with 20 nodes. You want to run parallel running with the new version alongside the old. How many nodes do you need to maintain the same throughput without degradation?

A 20 nodes because parallel running does not affect node count

B 40 nodes to handle double the load

C 30 nodes assuming 50% load increase due to overhead

D 10 nodes since load is split between versions

💡 Hint

Think about how running two versions simultaneously affects total load and capacity.

Parallel running doubles the load because both versions handle the full traffic, so you need double the nodes to maintain throughput.