Practice
1. In a gRPC streaming call, at step 4 the server-side stream handler checks the client connection status before sending a message. What happens if the client has disconnected at this step?
easy
Solution
Step 1: Understand server stream handler behavior
When client disconnects, server detects cancellation via context and stops streaming.Step 2: Trace server reaction at step 4
Server cancels the stream and frees resources immediately; it does not buffer or retry indefinitely.Final Answer:
Option A -> Option AQuick Check:
Client disconnect -> server cancels stream and frees resources [check]
Hint: Disconnected client -> server cancels stream immediately [check]
Common Mistakes:
2. In a server-side service discovery flow, at step 4 the API Gateway queries the service registry for available instances. What happens if the registry returns stale data at this step?
easy
Solution
Step 1: Trace API Gateway behavior at step 4
The API Gateway relies on the registry response to route requests; stale data leads to routing to unavailable instances.Step 2: Eliminate other options
The API Gateway retries the request until fresh data is received is incorrect as retries are not automatic; The API Gateway falls back to client-side discovery automatically is false since fallback is not built-in; The API Gateway caches the stale data but marks instances as unhealthy is incorrect because caching stale data without health checks causes failures.Final Answer:
Option A -> Option AQuick Check:
API Gateway routes based on stale registry data causing failures [check]
Hint: Stale registry data routes to dead instances causing failures [OK]
Common Mistakes:
3. If the Road Graph Service's update pipeline fails to process live traffic changes, what is the exact failure observed in ETA computation?
medium
Solution
Step 1: Understand Road Graph update pipeline failure impact
Without updates, live traffic data is stale; system must handle this gracefully.Step 2: Trace failure effect on ETA computation
Routing Engine does not silently use stale data (A) or crash (B); it returns errors (C) to avoid misleading ETAs; no automatic backup switch (D).Final Answer:
Option B -> Option BQuick Check:
Update pipeline failure causes routing errors, not silent stale data use [check]
Hint: Update failure triggers routing errors, not silent stale data use [check]
Common Mistakes:
4. At 10x scale, which Kafka component is most lik
medium
Solution
Step 1: Identify scaling bottleneck
Consumers handle message processing and scale with load.Step 2: Assess component impact
At 10x scale, consumers need to scale out to handle increased throughput.Final Answer:
Option B -> Option BQuick Check:
Consumers scale with load; brokers and producers less impacted [check]
Hint: Consumers scale most at high load [OK]
Common Mistakes:
5. Without a latency percentile monitoring system, what exactly breaks in detecting performance issues in a distributed service?
medium
Solution
Step 1: Role of latency percentile monitoring
Latency percentiles detect tail latency spikes that average latency misses, enabling targeted alerts.Step 2: Failure without percentile monitoring
Without it, only average latency is visible, which can spike due to outliers or noise, causing false alarms and missing tail issues.Final Answer:
Option D -> Option DQuick Check:
Without percentiles, average latency spikes cause false alarms [check]
Hint: No percentiles -> false alarms from average spikes [OK]
Common Mistakes: