Reference library

Observability & SRE

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

3 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 easy

How to Process System Metrics (RSS, CPU) in Python

Simulate and aggregate RSS and CPU system metrics to compute averages and maximums for monitoring dashboards.

metrics rss cpu

Python

import random
import time
from collections import namedtuple

Metric = namedtuple("Metric", ["name", "value", "unit"])


def generate_metrics(num_metrics: int = 5) -> list:
    """Simulate a batch of system metrics."""
    metrics = []
    for i in range(num_metrics):
        rss = random.randint(50, 500)  # MB
      …

12 0 Open

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