Observability & SRE
Structured logging, metrics, tracing, health checks, and SLO-friendly instrumentation.
How to Add Metadata Attributes to a Span in Python
Create a lightweight dataclass-based Span mock that stores key-value metadata attributes for tracing or event logging.
from dataclasses import dataclass, field
from typing import Dict, Any
@dataclass
class Span:
name: str
attributes: Dict[str, Any] = field(default_factory=dict)
def set_attribute(self, key: str, value: Any) -> None:
self.attributes[key] = value
def get_attribute(self, key: str) -> Any…How to Build a Burn Rate Alert with Multiple Time Windows in Python
Track token consumption and trigger alerts when the burn rate exceeds a threshold across multiple time windows using deque and time-based sliding windows.
import time
from collections import deque
class BurnRateAlert:
def __init__(self, windows_seconds=(60, 300, 900), threshold_rate=0.8):
self.windows = {w: deque() for w in windows_seconds}
self.threshold_rate = threshold_rate
self.previous_tokens = None
def record_sample(self, current_…How to Build a Consumer Lag Gauge in Python
Simulate Kafka consumer lag with a Python class that tracks lag over time and reports health and averages.
import time
import random
from collections import deque
class ConsumerLagGauge:
"""Mock consumer lag gauge measuring how far behind a consumer is."""
def __init__(self, producer_rate=10, consumer_rate=7, initial_lag=0):
self.producer_rate = producer_rate
self.consumer_rate = consumer_rate
…How to Build a Metrics Counter with Increment and Snapshot in Python
A simple dict-backed MetricsCounter class that increments named counters and returns a snapshot of the current values.
class MetricsCounter:
def __init__(self):
self._metrics = {}
def increment(self, key, delta=1):
self._metrics[key] = self._metrics.get(key, 0) + delta
def snapshot(self):
return dict(self._metrics)
if __name__ == "__main__":
counter = MetricsCounter()
counter.increment("…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.
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…How to Build an HTTP Server Request Duration Histogram in Python
Create a small HTTP server that times each GET request, buckets the duration, and prints a histogram on shutdown.
import time
import random
from collections import Counter
from http.server import HTTPServer, BaseHTTPRequestHandler
class HistogramHandler(BaseHTTPRequestHandler):
response_times = Counter()
def do_GET(self):
start = time.perf_counter()
time.sleep(random.uniform(0.001, 0.1))
duratio…How to Calculate Apdex Score from Latency Data in Python
Generate simulated latency samples and compute the Apdex score to gauge user satisfaction with an application's performance.
import random
import statistics
def generate_latencies(count=100, base=100, stddev=30):
return [max(0, random.gauss(base, stddev)) for _ in range(count)]
def apdex(latencies, threshold=200):
satisfied = sum(1 for lat in latencies if lat < threshold)
tolerating = sum(1 for lat in latencies if lat >= thres…How to Calculate Percentile Latency in Python
Generate mock latency samples with occasional spikes and compute 50th, 90th, 95th, and 99th percentile values in milliseconds.
import random
import statistics
def generate_latency_samples(n=1000):
"""Generate realistic mock latency data (ms) with occasional spikes."""
samples = []
for _ in range(n):
# Normal case: ~50ms with jitter
base = random.gauss(50, 5)
# 2% spike chance: slow downstream or GC pause
…How to Calculate SLO Error Budget in Python
Simulate an SLO error budget by computing allowed downtime from a target availability percentage and mocking monthly incidents.
```python
import random
def calculate_error_budget(total_seconds: int, target_availability: float) -> float:
return (1.0 - target_availability) * total_seconds
def simulate_monthly_availability(seconds_in_month: int, budget_seconds: float) -> float:
# Mock: randomly consume a fraction of the error budget i…How to Check Service Readiness Dependencies in Python
This code simulates a readiness check for external dependencies (database, cache, queue) with mock availability data and reports readiness status.
import sys
from datetime import datetime
def check_dependencies(config):
results = []
for dep, required in config.items():
available = mock_availability(dep)
status = "READY" if available >= required else "NOT READY"
results.append((dep, available, required, status))
return result…How to Check Uptime with a Synthetic HTTP Mock in Python
Run a mock HTTP server locally and probe it with urllib to measure synthetic uptime and response times, perfect for testing monitoring logic without external dependencies.
import http.server
import threading
import time
import urllib.request
class MockHandler(http.server.BaseHTTPRequestHandler):
def do_GET(self):
if self.path == "/health":
self.send_response(200)
self.send_header("Content-Type", "application/json")
self.end_headers()
…How to Compute SRE Metrics Like Error Rate and Availability in Python
Tracks log events in a sliding time window and calculates error rate per second and availability percentage using an easy-to-follow class.
from collections import deque
from datetime import datetime, timedelta
from typing import Dict, Deque
class LogMetrics:
"""Simple observability helper to track log events and calculate SRE metrics."""
def __init__(self, window_seconds: int = 60):
self.window_seconds = window_seconds
self.eve…How to Create a Deep Health Check Database in Python
Setup a SQLite-backed health check database, insert mock data with response times and statuses, and generate a report ordered by most recent check.
import sqlite3
from datetime import datetime, timedelta
from pathlib import Path
DB_PATH = Path("deep_health_check.db")
def setup_database():
conn = sqlite3.connect(DB_PATH)
cursor = conn.cursor()
cursor.execute("""
CREATE TABLE IF NOT EXISTS health_checks (
id INTEGER PRIMARY KEY AU…How to Create a Deployment Environment Tag in Python
Generate a standardized deployment tag string by combining service and environment names with an f-string.
def mock_env_tag(service, environment):
return f"{service}-{environment}"
if __name__ == "__main__":
service = "api-gateway"
environment = "production"
tag = mock_env_tag(service, environment)
print(f"Deployment tag: {tag}")How to Create a Mock OpenTelemetry Trace in Python
Create a mock OpenTelemetry trace in memory to test span creation, attributes, and parent-child relationships without exporting to a backend.
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter
def create_mock_trace():
tracer_provider = TracerProvider()
span_exporter =…How to Create a StatsD UDP Metric Mock Server in Python
Run a lightweight mock UDP server that captures StatsD metrics over a short window for local testing.
import socket
import threading
import time
def start_mock_statsd_server(host="127.0.0.1", port=8125, timeout=3):
"""Run a mock StatsD UDP server that captures metrics for a short window."""
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
sock.bind((host, port))
sock.settimeout(timeout)
me…How to Create a TCP DNS Mock Server in Python
This code creates a mock TCP DNS server that listens on a specified port, accepts probe connections, and returns a fixed DNS response header to simulate a live DNS service for testing and observability.
import socket
import threading
def handle_client(client_socket, address):
print(f"[+] Connection from {address}")
try:
while True:
data = client_socket.recv(1024)
if not data:
break
print(f"[*] Received {len(data)} bytes (TCP DNS probe)")
…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.
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…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.
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…How to Flush Metrics on Graceful Shutdown in Python
Register an atexit handler to automatically flush collected metrics when a Python process exits gracefully.
import atexit
import time
import random
class MetricsCollector:
def __init__(self):
self._metrics = []
atexit.register(self.flush)
def record(self, name, value):
self._metrics.append((name, value, time.time()))
def flush(self):
print(f"Flushing {len(self._metrics)} metri…How to Generate and Propagate W3C Trace Context Headers in Python
Generate and propagate W3C traceparent and tracestate headers for distributed tracing in Python, with mock service headers.
import uuid
def generate_w3c_traceparent(trace_id=None, parent_id=None, flags="01"):
if trace_id is None:
trace_id = uuid.uuid4().hex[:32]
if parent_id is None:
parent_id = uuid.uuid4().hex[:16]
return f"00-{trace_id}-{parent_id}-{flags}"
def create_mock_headers(service_name, trace_id=N…How to Group Alerts by Time Window in Python
Group alert occurrences that fall within a sliding time window per alert key, reducing noise and summarizing bursts into single events.
from collections import defaultdict
from datetime import datetime, timedelta
def group_alerts(alerts, window_minutes=10):
"""Group alerts that occur within the same time window."""
alerts_by_key = defaultdict(list)
for alert in alerts:
key = alert["key"]
timestamp = alert["timestamp"]…How to Implement Tail Sampling in Python
Sample the slowest subset of calls (tail) for latency analysis using a deque with a random ratio gate.
import random
import time
from collections import deque
class TailSampler:
def __init__(self, tail_ratio=0.1, max_samples=100):
self.tail_ratio = tail_ratio
self.max_samples = max_samples
self.samples = deque(maxlen=max_samples)
self.total_calls = 0
def record(self, latency_ms…How to Implement an Error Budget Policy in Python
This code implements a mock error budget policy that decides whether to freeze deployments based on a simulated error rate and monthly freeze limits.
from datetime import datetime, timedelta
class ErrorBudgetPolicy:
FREEZE_WINDOW_HOURS = 24
MAX_FREEZES_PER_MONTH = 3
def __init__(self, budget_percentage=99.9):
self.budget_percentage = budget_percentage
self.freeze_count = 0
self.last_freeze_start = None
self.freeze_enabl…Browse by section
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Observability & SRE — Python code examples
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