Reference library

Observability & SRE

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

6 matches

Generate Synthetic SRE Metrics and Calculate Availability in Python

Create realistic service metrics with random latency, error rate, and request counts, then compute availability and summarize the stream for SLO checks.

sre synthetic-data metrics

Python

from datetime import datetime, timedelta
import random

def generate_service_metrics(service_name: str, minutes: int = 30) -> list[dict]:
    """Generate synthetic SRE metrics for a service across recent minutes."""
    metrics = []
    now = datetime.now()
    
    for i in range(minutes):
        timestamp = now - t…

14 0 Open

Observability & SRE medium

How to Build a Burn Rate Alert with Multiple Time Windows in Python

Track token consumption and trigger alerts when the burn rate exceeds a threshold across multiple time windows using deque and time-based sliding windows.

burn-rate alerts time-windows

Python

import time
from collections import deque

class BurnRateAlert:
    def __init__(self, windows_seconds=(60, 300, 900), threshold_rate=0.8):
        self.windows = {w: deque() for w in windows_seconds}
        self.threshold_rate = threshold_rate
        self.previous_tokens = None

    def record_sample(self, current_…

16 0 Open

Observability & SRE easy

How to Build a Consumer Lag Gauge in Python

Simulate Kafka consumer lag with a Python class that tracks lag over time and reports health and averages.

consumer-lag kafka monitoring

Python

import time
import random
from collections import deque


class ConsumerLagGauge:
    """Mock consumer lag gauge measuring how far behind a consumer is."""

    def __init__(self, producer_rate=10, consumer_rate=7, initial_lag=0):
        self.producer_rate = producer_rate
        self.consumer_rate = consumer_rate
  …

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 easy

Python Observability Data Helper for Beginners

A beginner-friendly Python helper to log events, record metrics, summarize observability data, and export it as JSON.

observability logging metrics

Python

import json
from datetime import datetime
from collections import defaultdict


class ObservabilityDataHelper:
    """Helper for exploring basic observability data patterns."""

    def __init__(self):
        self.events = []
        self.metrics = defaultdict(list)

    def log_event(self, service, level, message):
…

14 0 Open

Observability & SRE medium

Summary Quantile Mock Sketch in Python

Build a memory-efficient sketch that stores sorted bins of data points to answer approximate quantile queries like median without keeping all values in memory.

quantile sketch statistics

Python

import random
import statistics
from collections import Counter

class SummaryQuantileSketch:
    """
    A simple sketch that stores a fixed-size summary of data (min, max, deciles)
    using sorted bins, then answers approximate quantile queries.
    """
    def __init__(self, bins=10):
        self.bins = bins
    …

13 0 Open

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