I started writing the happy path first and the interviewer let me get through maybe half of it before asking about retries.
Start by clarifying requirements and constraints, then outline a modular design with separate components for fetching, retrying, content-type inspection, and parsing. Walk through the flow, emphasizing error handling, concurrency, and trade-offs like retry strategy and timeout handling.
Pro tip: Mention that you would use exponential backoff with jitter for retries to avoid thundering herd problems, and that you'd inspect the Content-Type header before parsing to avoid unnecessary work and errors.
Ask about expected scale, concurrency needs, retry limits, timeout durations, and whether the crawler should respect robots.txt. Confirm the output format for parsed results and errors.
Propose a modular design: a fetcher with retry logic, a content-type inspector, a JSON parser, and an orchestrator that manages concurrency and aggregates results. Consider using a thread pool or async I/O.
Describe making HTTP GET requests with a timeout, and on failure (network error or 5xx), retry with exponential backoff and jitter up to a max retry count. Handle 4xx errors as non-retryable.
Check the Content-Type header; if it's application/json, attempt to parse the body as JSON. If parsing fails or content type is not JSON, record an error for that URL.
Collect parsed JSON objects or error messages per URL, and return them to the caller in a structured format (e.g., a list of results with status). Discuss how to handle partial failures.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by framing retries as a trade-off between reliability and resource consumption, then walk through a decision process that considers error type, idempotency, and system load. Explain how you'd set retry counts based on acceptable failure rates and latency budgets, and when to use exponential backoff versus immediate retries based on the nature of the failure.
Pro tip: Mention that you'd instrument retries with metrics and logs to tune parameters over time, and that you'd consider jitter to avoid thundering herds—this shows you think about production realities beyond textbook answers.
Determine if the error is transient (e.g., network blip, temporary overload) or persistent (e.g., bad request, auth failure). Only transient errors are worth retrying.
Check if the operation is idempotent; if not, retries could cause duplicate actions. For non-idempotent operations, consider using idempotency keys or avoiding retries.
Calculate the maximum retries that keep the overall failure rate within acceptable limits, considering the probability of success per attempt and the impact on latency and resources.
Use exponential backoff with jitter for most transient errors to reduce load and avoid synchronized retries. Use immediate retries only for very short-lived, known blips where latency is critical and the system can handle the load.
Instrument retries with metrics (count, success rate, latency) and logs. Continuously tune retry counts and backoff parameters based on observed behavior and system changes.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by categorizing HTTP status codes into retryable (e.g., 5xx, 429) and non-retryable (e.g., 4xx except 429), then explain how to implement retry logic with exponential backoff and jitter. Finally, describe a testing strategy that covers both unit tests with mocked responses and integration tests with fault injection to validate retry behavior.
Pro tip: Mention that retry logic should be idempotent and consider using a circuit breaker to prevent cascading failures. Also, highlight the importance of logging retries for observability and debugging.
Explain that 5xx errors (server errors) and 429 (Too Many Requests) are generally retryable, while 4xx errors (client errors) except 429 are not. Also consider network errors (timeouts, connection resets) as retryable.
Describe using exponential backoff with jitter to avoid thundering herd, and set a maximum number of retries. Mention that retries should only be attempted for idempotent operations or when the operation is safe to repeat.
Discuss using libraries or custom code to wrap HTTP calls with retry logic. Ensure that the retry mechanism respects the Retry-After header for 429 responses and has a timeout to prevent indefinite retries.
Outline unit tests that mock HTTP responses to simulate retryable and non-retryable failures, verifying that retries occur only when appropriate. Use integration tests with tools like WireMock or Toxiproxy to inject faults and validate backoff timing and maximum retry limits.
Emphasize the need for logging and metrics to track retry attempts and success rates. Use this data to adjust retry parameters and identify non-retryable errors that might be misclassified.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.