Reference library

Observability & SRE

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

6 matches

Export Metrics with OTLP Mock in Python

Simulates system metric collection and exports them as an OTLP-like JSON payload using only Python's standard library.

from dataclasses import dataclass, asdict
import json
import random
import time


@dataclass
class Metric:
    name: str
    value: float
    timestamp: int
    unit: str = "1"


def collect_system_metrics() -> list[Metric]:
    """Mock metric collection for OTLP export simulation."""
    now = int(time.time())
    re…

12 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 Do Structured JSON Line Logging in Python

Create a simple JSON-lines logger that writes one JSON object per line to stdout with timestamp, level, message, and custom context fields.

logging json observability

Python

import json
import sys
from datetime import datetime

class JsonLineLogger:
    def __init__(self, stream=sys.stdout):
        self.stream = stream

    def log(self, level, message, **context):
        record = {
            "timestamp": datetime.utcnow().isoformat() + "Z",
            "level": level,
            "me…

15 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 Ship Logs to an Aggregator Endpoint in Python

Ship batched log entries to a mock HTTP aggregator endpoint with proper error handling and response status.

logging requests json

Python

import json
import requests
from datetime import datetime, timezone

LOG_ENTRIES = [
    {"timestamp": "2024-01-15T10:00:00Z", "level": "INFO", "message": "Server started"},
    {"timestamp": "2024-01-15T10:00:05Z", "level": "WARN", "message": "High memory usage"},
    {"timestamp": "2024-01-15T10:00:10Z", "level": "E…

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

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