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Observability & SRE

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

3 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 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 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):
…

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