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Observability & SRE

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

5 matches

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 medium

How to Build a Python Latency Histogram with Mock Buckets

This code implements a mock latency histogram that records request durations into configurable buckets and outputs counts, total, and average latency.

histogram latency metrics

Python

import time
import random
from collections import Counter


class LatencyHistogram:
    def __init__(self, buckets):
        self.buckets = sorted(buckets)
        self.counts = Counter()
        self.total = 0
        self.sum_latency = 0

    def record(self, latency_ms):
        for i, boundary in enumerate(self.bu…

13 0 Open

Observability & SRE easy

How to Do Structured JSON Logging in Python

Create a custom logging formatter that outputs each log entry as a single JSON line with timestamp, level, logger name, and message.

logging json observability

Python

import json
import logging
from datetime import datetime


class JsonFormatter(logging.Formatter):
    def format(self, record):
        log_entry = {
            "timestamp": datetime.utcnow().isoformat() + "Z",
            "level": record.levelname,
            "logger": record.name,
            "message": record.ge…

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

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