Health check endpoints in HLD - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Purpose of Health Check Endpoints

What is the primary purpose of a health check endpoint in a distributed system?

A To provide detailed logs of system errors to developers

B To manage database schema migrations automatically

C To allow external systems to verify if a service is running and responsive

D To store user authentication tokens securely

💡 Hint

Think about what external systems need to know to decide if a service is healthy.

Health check endpoints are designed to let other systems or load balancers know if a service is alive and responsive, so they can route traffic accordingly.

❓ Architecture

intermediate

Designing a Health Check Endpoint

Which design best describes a simple health check endpoint that returns HTTP 200 OK only if the service and its database are reachable?

A Endpoint checks service status and database connectivity, returns HTTP 200 OK if both are healthy, else HTTP 503

B Endpoint returns HTTP 200 OK without checking any dependencies

C Endpoint returns HTTP 500 Internal Server Error if the service is healthy

D Endpoint only checks database connectivity and ignores service status

💡 Hint

Consider what components must be healthy for the service to be considered healthy.

A robust health check endpoint verifies both the service itself and critical dependencies like the database. It returns HTTP 200 OK only if all checks pass, otherwise HTTP 503 to indicate unavailability.

❓ scaling

advanced

Scaling Health Check Endpoints in Microservices

In a microservices architecture with hundreds of services, what is the best approach to efficiently perform health checks without overwhelming the system?

A Each service only checks its own health and ignores dependencies

B Each service performs health checks on all other services synchronously on every request

C Disable health checks to reduce network traffic

D Use a centralized health aggregator that periodically polls each service's health endpoint asynchronously and caches results

💡 Hint

Think about reducing load and avoiding synchronous calls across many services.

A centralized health aggregator asynchronously polls each service's health endpoint and caches the results. This reduces network load and avoids cascading delays or failures.

❓ tradeoff

advanced

Tradeoffs in Health Check Endpoint Complexity

What is a key tradeoff when designing a health check endpoint that performs deep checks (e.g., database, cache, external APIs) versus a simple ping check?

A Deep checks increase response time and risk false negatives, while simple checks may miss critical failures

B Simple checks provide detailed error logs, deep checks do not

C Deep checks always improve performance, simple checks cause system crashes

D Deep checks reduce network traffic, simple checks increase it

💡 Hint

Consider the balance between thoroughness and speed.

Deep health checks provide more accurate status but can slow down responses and cause false alarms if dependencies are slow. Simple checks are fast but might miss issues.

❓ estimation

expert

Estimating Load on Health Check Endpoints

A service has 100 instances behind a load balancer. The load balancer performs health checks every 10 seconds. Each health check request consumes 5ms CPU time on the instance. Estimate the total CPU time spent per second on health checks across all instances.

A 5 ms per second

B 50 ms per second

C 500 ms per second

D 1000 ms per second

💡 Hint

Calculate how many health checks happen per second and multiply by CPU time per check.

Each instance receives 1 health check every 10 seconds, so 0.1 checks per second per instance. For 100 instances, total checks per second = 100 * 0.1 = 10. Each check uses 5ms CPU, so total CPU time = 10 * 5ms = 50ms per second.