Recognizing Patterns and Selecting Algorithms Questions
Ability to recognize problem patterns and know which algorithm/data structure is appropriate. Includes pattern matching like 'this looks like a sliding window problem' or 'this is a backtracking problem'.
HardTechnical
86 practiced
Capacity prediction/forecasting: choose an approach to predict CPU and traffic with daily/weekly seasonality and occasional outages. Compare SARIMA/ARIMA, Prophet, and LSTM-based models for SRE capacity planning. Describe feature engineering, cross-validation strategy, and how you'd evaluate forecasts relative to SLOs.
HardTechnical
96 practiced
You must find the most frequent (heavy-hitter) error messages in a massive log stream with tight memory. Compare algorithms: Space-Saving (Misra-Gries), Count-Min Sketch + heap, and reservoir/sample-based approaches. For each, explain accuracy guarantees, memory/time complexity, and suitability for SRE real-time dashboards.
MediumTechnical
75 practiced
Design (describe data structures and algorithm; pseudo-code acceptable) a streaming system in Python that receives events (timestamp, user_id) and continuously reports the top-k most active users in the last 24 hours. Memory cannot hold all events; explain how you would evict old events and how to merge per-shard summaries into a global top-k.
MediumTechnical
65 practiced
For performing health checks across a service dependency graph, when would you use BFS versus DFS? Discuss implications on memory, parallelism, shortest-path detection to failing components, and how branching factor and depth affect the choice in SRE tooling.
HardTechnical
73 practiced
Implement consistent hashing with virtual nodes in Python. Provide a class with methods: add_node(node_id), remove_node(node_id), and get_node(key). The implementation should place virtual nodes on a 32-bit hash ring and use bisect/search to locate node for a key. Ensure minimal remapping when nodes are added/removed.
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