Microservices Resilience and Fault Tolerance 3

Question 1

What problem does a cascading failure describe in a microservices system?

Accepted Answer

One service's failure propagating and overwhelming dependent services in a chain reaction

Answer

Cascading failures occur when one overloaded or failing service drags down others that depend on it, spreading the outage.

Question 2

Which technique limits the number of concurrent calls a service will accept to protect itself?

Accepted Answer

Rate limiting / concurrency limiting

Answer

Rate or concurrency limiting caps inbound load so a service is not overwhelmed beyond its capacity.

Question 3

What is the 'fail fast' principle in resilient design?

Accepted Answer

Detect failures quickly and return an error immediately rather than blocking

Answer

Failing fast returns errors promptly instead of holding resources on doomed calls, keeping the system responsive.

Question 4

When a circuit breaker is in the OPEN state, what happens to incoming requests?

Accepted Answer

They are short-circuited and fail immediately (or use a fallback) without calling the downstream

Answer

In OPEN state the breaker rejects calls instantly, giving the failing service time to recover and protecting the caller.

Question 5

Why can aggressive retries make an outage worse?

Accepted Answer

They add extra load to an already struggling service, amplifying the problem

Answer

Retries against a degraded service pile on more requests, increasing load and potentially deepening the outage.

Microservices Practice Test