Reference library

Observability & SRE

Structured logging, metrics, tracing, health checks, and SLO-friendly instrumentation.

3 matches

How to Build a Metrics Counter with Increment and Snapshot in Python

A simple dict-backed MetricsCounter class that increments named counters and returns a snapshot of the current values.

class MetricsCounter:
    def __init__(self):
        self._metrics = {}

    def increment(self, key, delta=1):
        self._metrics[key] = self._metrics.get(key, 0) + delta

    def snapshot(self):
        return dict(self._metrics)


if __name__ == "__main__":
    counter = MetricsCounter()
    counter.increment("…

13 0 Open

Observability & SRE medium

How to Group Alerts by Time Window in Python

Group alert occurrences that fall within a sliding time window per alert key, reducing noise and summarizing bursts into single events.

alerts grouping monitoring

Python

from collections import defaultdict
from datetime import datetime, timedelta

def group_alerts(alerts, window_minutes=10):
    """Group alerts that occur within the same time window."""
    alerts_by_key = defaultdict(list)
    
    for alert in alerts:
        key = alert["key"]
        timestamp = alert["timestamp"]…

12 0 Open

Observability & SRE medium

How to Track Cache Hit Ratio in Python

Simulate an LRU cache with hit/miss tracking and compute a real-time hit ratio from random access patterns.

cache lru hit-ratio

Python

import random
import time
from collections import OrderedDict

class LRUCache:
    def __init__(self, capacity: int):
        self.cache = OrderedDict()
        self.capacity = capacity
        self.hits = 0
        self.misses = 0

    def get(self, key):
        if key in self.cache:
            self.hits += 1
     …

13 0 Open

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