Practice
1. A large-scale messaging platform needs to isolate failures to prevent cascading outages during regional network partitions. Which architectural component best limits the blast radius by decoupling service dependencies?
easy
Solution
Step 1: Identify failure isolation mechanism
Asynchronous message queues decouple services, buffering requests and preventing direct cascading failures during outages.Step 2: Evaluate alternatives
Synchronous REST calls (A) cause blocking and cascading failures; monolithic DB (C) is a single point of failure; direct TCP (D) lacks buffering and backpressure.Final Answer:
Option C -> Option CQuick Check:
Async queues buffer and isolate failures, limiting blast radius [check]
Hint: Async queues buffer failures, blocking calls cascade [check]
Common Mistakes:
2. In a Cache Aside pattern, at step 3 the application checks the cache and finds a miss. What happens next at step 4?
easy
Solution
Step 1: Understand Cache Aside flow
On cache miss, application queries DB and updates cache explicitly.Step 2: Eliminate other options
Cache Aside does not auto-load cache (A); it does not return null or stale data (C, D).Final Answer:
Option A -> Option AQuick Check:
Application loads DB and updates cache on miss [check]
Hint: Cache Aside: app loads DB and updates cache on miss [check]
Common Mistakes:
3. In the Pastebin system request flow, at Step 4 the Expiration Worker scans stored snippets to remove expired entries. What state does the worker observe for a snippet whose TTL just expired but is still being accessed by a user?
easy
Solution
Step 1: Trace Expiration Worker behavior at Step 4
The worker deletes expired snippets in batches; deletion is not instantaneous upon TTL expiry.Step 2: Understand user access during deletion
Until deletion completes, the snippet remains accessible; no locking or blocking occurs.Final Answer:
Option B -> Option BQuick Check:
Batch deletion delays snippet removal, keeping it accessible briefly [check]
Hint: Expiration deletion is batch-based, not instant [check]
Common Mistakes:
4. A public API receives unpredictable bursts of traffic that can overwhelm backend services. Which component is best suited to protect the system from overload?
easy
Solution
Step 1: Identify the protection mechanism against traffic bursts
Distributed cache (A) improves response time but doesn't limit request rate; load balancer (C) distributes load but can't prevent overload from bursts; message queue (D) buffers but can be overwhelmed if bursts are too large.Step 2: Recognize rate limiter role
Rate limiter (B) enforces quotas per client, directly preventing backend overload by rejecting or delaying excess requests.Final Answer:
Option B -> Option BQuick Check:
Rate limiter enforces quotas to prevent overload [check]
Hint: Rate limiter controls request bursts to protect backend [check]
Common Mistakes:
5. Without explicitly defining system constraints during your 45-minute design answer, what failure mode is most likely to occur in your final design?
medium
Solution
Step 1: Trace impact of missing constraints
Without constraints, design choices conflict and trade-offs are unclear, leading to incomplete or inconsistent design.Step 2: Exclude unrealistic outcomes
Automatic scaling or perfect design without iteration is unrealistic; architecture does not default automatically.Final Answer:
Option B -> Option BQuick Check:
Missing constraints -> conflicting design decisions [check]
Hint: Constraints prevent conflicting designs [check]
Common Mistakes: