Reference library

Observability & SRE

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

5 matches

Check if a Timestamp Falls in a Daily Maintenance Window in Python

A small Python function that returns True when a datetime falls inside a daily maintenance window, and a demo printing yes/no for sample timestamps.

maintenance datetime scheduling

Python

from datetime import datetime, timedelta
from zoneinfo import ZoneInfo


def in_maintenance_window(now: datetime, start_hour: int = 2, duration_hours: int = 4) -> bool:
    """Return True if 'now' falls inside the daily maintenance window."""
    day_start = now.replace(hour=start_hour, minute=0, second=0, microsecond…

15 0 Open

Observability & SRE easy

Generate Mock CPU and Memory Metrics in Python

Build a mock_host_metrics() generator that outputs realistic CPU and memory usage percentages for monitoring demos and tests.

mock metrics monitoring

Python

import time
import random


def mock_host_metrics():
    """Generate mock CPU and memory metrics for a host."""
    cpu_percent = round(random.uniform(10.0, 95.0), 1)
    memory_percent = round(random.uniform(20.0, 90.0), 1)
    memory_used_mb = round(random.uniform(512, 8192), 1)

    return {
        "timestamp": in…

15 0 Open

Observability & SRE easy

Generate Synthetic CPU Utilization Metrics in Python

Creates realistic time-series CPU utilization samples with timestamps, noise, and output as structured JSON for observability demos and testing.

observability metrics time-series

Python

from datetime import datetime, timedelta
import random
import json


def generate_metric_samples(base_value, noise, count=60, interval_minutes=1):
    """Generate realistic CPU utilization samples for a given time window."""
    timestamps = []
    values = []

    now = datetime.utcnow()
    start_time = now - timede…

14 0 Open

Observability & SRE easy

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

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

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