Observability Patterns

import structlog

logger = structlog.get_logger()

logger.info("user_created", user_id=user.id, email=user.email, source="api")
logger.error("payment_failed", order_id=order.id, error=str(e), amount=amount)

import pino from "pino";

const logger = pino({ level: "info", transport: { target: "pino-pretty" } });

logger.info({ userId: user.id, action: "login" }, "User logged in");
logger.error({ err, orderId: order.id }, "Payment processing failed");

from opentelemetry import trace, metrics
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter

trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(
    BatchSpanProcessor(OTLPSpanExporter(endpoint="http://otel-collector:4317"))
)

tracer = trace.get_tracer(__name__)
meter = metrics.get_meter(__name__)

request_counter = meter.create_counter("http_requests_total", description="Total HTTP requests")
request_duration = meter.create_histogram("http_request_duration_seconds")

@tracer.start_as_current_span("process_order")
def process_order(order_id: str):
    request_counter.add(1, {"method": "POST", "endpoint": "/orders"})
    with tracer.start_as_current_span("validate_order"):
        validate(order_id)
    with tracer.start_as_current_span("charge_payment"):
        charge(order_id)

import { NodeSDK } from "@opentelemetry/sdk-node";
import { OTLPTraceExporter } from "@opentelemetry/exporter-trace-otlp-grpc";

const sdk = new NodeSDK({
  traceExporter: new OTLPTraceExporter({ url: "http://otel-collector:4317" }),
  instrumentations: [getNodeAutoInstrumentations()],
});
sdk.start();

# Counter - monotonically increasing (requests, errors)
http_requests_total = Counter("http_requests_total", "Total requests", ["method", "status", "path"])

# Histogram - distribution (latency, sizes)
request_duration = Histogram("request_duration_seconds", "Request latency",
    buckets=[0.01, 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0])

# Gauge - current value (connections, queue size)
active_connections = Gauge("active_connections", "Current active connections")

# FastAPI example
@app.get("/health")
async def health():
    checks = {
        "database": await check_db(),
        "redis": await check_redis(),
        "disk": check_disk_space(),
    }
    status = "healthy" if all(checks.values()) else "degraded"
    code = 200 if status == "healthy" else 503
    return JSONResponse({"status": status, "checks": checks}, status_code=code)

@app.get("/ready")
async def readiness():
    """Kubernetes readiness probe - can this instance serve traffic?"""
    return {"ready": True}

@app.get("/live")
async def liveness():
    """Kubernetes liveness probe - is the process alive?"""
    return {"alive": True}

import sentry_sdk

sentry_sdk.init(
    dsn="https://key@sentry.io/project",
    traces_sample_rate=0.1,
    profiles_sample_rate=0.1,
    environment="production",
)

# Automatic exception capture + manual context
with sentry_sdk.push_scope() as scope:
    scope.set_tag("order_id", order.id)
    scope.set_context("payment", {"amount": amount, "currency": "USD"})
    sentry_sdk.capture_exception(e)

Error Budget = 1 - SLO = 1 - 0.999 = 0.1%
Monthly budget = 30 days * 24h * 60min * 0.001 = 43.2 minutes

groups:
  - name: api-alerts
    rules:
      - alert: HighErrorRate
        expr: rate(http_requests_total{status=~"5.."}[5m]) / rate(http_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "Error rate above 5% for 5 minutes"

      - alert: HighLatency
        expr: histogram_quantile(0.99, rate(request_duration_seconds_bucket[5m])) > 1
        for: 10m
        labels:
          severity: warning