Reference library

Observability & SRE

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

29 matches

How to Use Log Levels DEBUG INFO WARNING ERROR in Python

Demonstrates Python's logging levels (DEBUG, INFO, WARNING, ERROR) with basicConfig and a logger, showing how severity filtering controls output.

logging log-levels observability

Python

import logging

# Configure a mock logger to demonstrate log levels
logging.basicConfig(level=logging.DEBUG, format="%(levelname)s: %(message)s")
logger = logging.getLogger("mock_logger")

# Simulate events at each severity level
logger.debug("Detailed diagnostic info")
logger.info("General system operation")
logger.w…

13 0 Open

Observability & SRE easy

Mock Health Endpoint Liveness Check in Python

Simulate a liveness endpoint that reports service health with a configurable failure rate and uptime.

health check mock observability

Python

import time
import random


def liveness_check(service_name: str, failure_rate: float = 0.1) -> dict:
    """Mock health check that returns liveness status with a configurable failure rate."""
    healthy = random.random() > failure_rate
    response = {
        "service": service_name,
        "status": "alive" if he…

16 0 Open

Observability & SRE easy

Mocking a Metrics Gauge's set_value Method in Python

Demonstrates using unittest.mock.Mock with wraps to intercept a gauge's set_value call while verifying arguments and preserving real behavior.

unittest mocking metrics

Python

from unittest.mock import Mock

class MetricsGauge:
    def __init__(self, name):
        self.name = name
        self.value = 0.0

    def set_value(self, new_value):
        self.value = float(new_value)
        return self.value

# Usage demonstration with a mock
gauge = MetricsGauge("cpu_usage")
gauge_mock = Mock…

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):
…

14 0 Open

Observability & SRE easy

Track Success Rates and Latency in Python: SRE Metrics Helper

A beginner-friendly Python class to record request outcomes and latencies, then report success rate, average latency, and p99.

sre metrics latency

Python

import random
import time
from collections import defaultdict


class MetricsTracker:
    """Simple helper to track success rates and latencies for SRE beginners."""

    def __init__(self):
        self.successes = 0
        self.failures = 0
        self.latencies = []

    def record(self, success, latency_ms):
   …

14 0 Open

Browse by section

Each section groups closely related Python snippets.