Real-Time Log Metrics Aggregator | Dataford Interview Questions

Given a stream of log lines, implement a function that parses each line and returns rolling performance metrics over the last window_seconds. Each valid log line has the format "<timestamp> <service> <latency_ms> <status>", where timestamp is a non-decreasing integer. Ignore malformed lines. For each processed line, output the current metrics for that line's service: total requests in the window, error count (status >= 500), and average latency rounded down.

Constraints

1 <= len(logs) <= 10^5
1 <= window_seconds <= 10^6
Timestamps are non-decreasing integers
0 <= latency_ms <= 10^6
100 <= status <= 599 for valid lines

Function Signature

def aggregate_log_metrics(logs, window_seconds):

Your question is Real-Time Log Metrics Aggregator. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Constraints

1 <= len(logs) <= 10^5
1 <= window_seconds <= 10^6
Timestamps are non-decreasing integers
0 <= latency_ms <= 10^6
100 <= status <= 599 for valid lines

Function Signature

def aggregate_log_metrics(logs, window_seconds):

Your question is Real-Time Log Metrics Aggregator. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.