Observability Logging Baseline

Overview

Establish production-ready observability foundations using OpenTelemetry standards. Covers structured logging with message templates, RED/USE metrics, distributed tracing with W3C Trace Context, and correlation ID propagation across service boundaries.

When to Use

• Building any service requiring production-ready observability
• Establishing logging, metrics, and tracing patterns for new services
• Upgrading existing services from unstructured to structured observability
• Reviewing PRs that introduce or modify observability instrumentation
• Making architecture decisions involving monitoring and observability tooling

Core Workflow

1. Configure structured logging with message templates (not string interpolation)
2. Add correlation ID middleware to propagate request context
3. Set up OpenTelemetry SDK for metrics and tracing
4. Implement RED metrics (Rate, Errors, Duration) for HTTP endpoints
5. Enable W3C Trace Context propagation for distributed tracing
6. Configure OTLP exporter for vendor-portable telemetry export
7. Validate log output contains structured fields and correlation IDs

Core

When to use

• Any service requiring production-ready observability.
• New services establishing logging, metrics, and tracing patterns.
• Existing services upgrading from unstructured to structured observability.
• Any PR introducing or modifying observability instrumentation.
• Architecture decisions involving monitoring and observability tooling.

Defaults (strong preference)

• Use structured logging with message templates, not string interpolation.
• Prefer OpenTelemetry standards over vendor-specific SDKs.
• Implement RED metrics (Rate, Errors, Duration) for HTTP endpoints.
• Enable W3C Trace Context propagation for distributed tracing.
• Configure correlation IDs for request tracing across components.

Three Pillars of Observability

Rationale

• Structured logging enables searching, filtering, and alerting.
• OpenTelemetry provides vendor portability and industry standardisation.
• Correlation IDs enable distributed debugging across service boundaries.
• RED metrics provide consistent service health visibility.
• W3C Trace Context ensures interoperability across systems.

Review rules

• Reject string interpolation in log messages when structured templates are possible.
• Reject vendor-specific SDKs without OpenTelemetry abstraction layer.
• Reject custom metric naming when semantic conventions exist.
• Require correlation ID propagation for multi-component requests.
• Require log level justification for verbose production logging.

Load: structured-logging

Structured Logging Principles

Message Templates over String Interpolation:

// Correct: Message template with named placeholders
_logger.LogInformation("User {UserId} logged in from {IpAddress}", userId, ipAddress);

// Incorrect: String interpolation loses structure
_logger.LogInformation($"User {userId} logged in from {ipAddress}");

Why structure matters:

• Enables log aggregation queries: UserId = "12345"
• Preserves type information for analysis
• Supports alerting on specific field values
• Reduces log storage through deduplication

Correlation ID Pattern

Every request should carry a correlation ID:

// Middleware to propagate correlation ID
public class CorrelationIdMiddleware
{
    public async Task InvokeAsync(HttpContext context)
    {
        var correlationId = context.Request.Headers["X-Correlation-ID"].FirstOrDefault()
            ?? Guid.NewGuid().ToString();

        context.Items["CorrelationId"] = correlationId;
        context.Response.Headers["X-Correlation-ID"] = correlationId;

        using (_logger.BeginScope(new Dictionary<string, object>
        {
            ["CorrelationId"] = correlationId
        }))
        {
            await _next(context);
        }
    }
}

Log Level Semantics

Sensitive Data Handling

Never log:

• Passwords, API keys, or tokens
• Full credit card numbers
• Personal identification numbers
• Health or financial data (without explicit consent)

Redaction patterns:

// Mask sensitive fields
_logger.LogInformation("Payment processed for card ending {CardLast4}",
    cardNumber.Substring(cardNumber.Length - 4));

// Use redaction attributes
[LogPropertyIgnore]
public string Password { get; set; }

Load: metrics

RED Metrics (Golden Signals)

For every HTTP service, implement:

USE Metrics (Resources)

For infrastructure resources:

OpenTelemetry Metrics Setup

builder.Services.AddOpenTelemetry()
    .WithMetrics(metrics =>
    {
        metrics
            .AddAspNetCoreInstrumentation()
            .AddHttpClientInstrumentation()
            .AddRuntimeInstrumentation()
            .AddOtlpExporter();
    });

Metric Naming Conventions

Follow OpenTelemetry semantic conventions:

# Format: <namespace>.<metric_name>_<unit>
http.server.request.duration   (histogram, seconds)
http.server.active_requests    (gauge)
db.client.connections.usage    (gauge)

Avoid:

• Custom prefixes: myapp_request_count
• Inconsistent units: latency_ms vs duration_seconds
• Vendor-specific names: datadog.custom.metric

Load: tracing

Distributed Tracing Concepts

W3C Trace Context

Standard headers for context propagation:

traceparent: 00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01
tracestate: vendor1=value1,vendor2=value2

OpenTelemetry Tracing Setup

builder.Services.AddOpenTelemetry()
    .WithTracing(tracing =>
    {
        tracing
            .AddAspNetCoreInstrumentation()
            .AddHttpClientInstrumentation()
            .AddSqlClientInstrumentation()
            .AddOtlpExporter();
    });

Span Naming Conventions

Sampling Strategies

// Probability-based sampling
tracing.SetSampler(new TraceIdRatioBasedSampler(0.1)); // 10% sampling

Load: enforcement

Review Heuristic: Logging Changes

• If PR adds logging, verify message templates are used (not interpolation).
• If PR adds request handlers, verify correlation ID propagation exists.
• If PR logs user data, verify sensitive field redaction.
• If PR changes log levels, verify production volume impact assessed.

Review Heuristic: Metrics Changes

• If PR adds metrics, verify semantic convention compliance.
• If PR measures latency, verify histogram is used (not gauge/average).
• If PR adds counters, verify appropriate labels without high cardinality.
• If PR uses vendor SDK, verify OpenTelemetry abstraction considered.

Review Heuristic: Tracing Changes

• If PR crosses service boundaries, verify context propagation.
• If PR adds manual spans, verify naming follows conventions.
• If PR changes sampling, verify production volume considered.
• If PR adds span attributes, verify no sensitive data included.

Anti-Patterns to Reject

Load: advanced

Observability in Kubernetes

Container-friendly logging:

// JSON output for container log aggregation
builder.Host.UseSerilog((context, config) =>
{
    config
        .WriteTo.Console(new JsonFormatter())
        .Enrich.WithProperty("ServiceName", "my-api");
});

Resource attributes for K8s:

.ConfigureResource(resource =>
{
    resource
        .AddService("my-api")
        .AddAttributes(new Dictionary<string, object>
        {
            ["k8s.namespace.name"] = Environment.GetEnvironmentVariable("K8S_NAMESPACE"),
            ["k8s.pod.name"] = Environment.GetEnvironmentVariable("K8S_POD_NAME")
        });
});

Exporter Configuration

OTLP (recommended for portability):

.AddOtlpExporter(options =>
{
    options.Endpoint = new Uri("http://otel-collector:4317");
    options.Protocol = OtlpExportProtocol.Grpc;
});

Direct vendor export (when needed):

// Jaeger, Zipkin, or vendor-specific exporters
// Only use when OTLP collector is not available
.AddJaegerExporter()

Cost and Performance Considerations

Incremental Adoption Path

1. Phase 1: Structured Logging

   • Convert string interpolation to message templates
   • Add correlation ID middleware
   • Configure JSON output for aggregation

2. Phase 2: Metrics

   • Add OpenTelemetry metrics SDK
   • Implement RED metrics for HTTP endpoints
   • Configure OTLP exporter

3. Phase 3: Tracing

   • Add OpenTelemetry tracing SDK
   • Enable automatic instrumentation
   • Configure sampling for production

4. Phase 4: Refinement

   • Add custom spans for business operations
   • Tune sampling strategies
   • Establish alerting on key signals

Minimal Validation Checklist

Use this checklist to verify observability is correctly configured:

Structured Logging Validation

• Log entry contains structured fields (not just message string)
• Correlation ID present in all request-scoped logs
• Log level appropriate for message type
• No PII or sensitive data in logs

Sample log entry to verify:

{
  "timestamp": "2024-01-15T10:30:45.123Z",
  "level": "Information",
  "message": "User logged in successfully",
  "properties": {
    "UserId": "usr_12345",
    "IpAddress": "192.168.1.100",
    "CorrelationId": "abc-123-def-456",
    "ServiceName": "auth-api"
  }
}

Validation command:

# Check log output format
curl -s http://localhost:5000/api/health | jq .
# Then check application logs for structured output

# Verify correlation ID propagation
curl -H "X-Correlation-ID: test-123" http://localhost:5000/api/users/1
# Check logs contain "CorrelationId": "test-123"

Metrics Validation

• RED metrics exposed for HTTP endpoints
• Metric names follow semantic conventions
• Labels have bounded cardinality
• Metrics endpoint accessible

Sample metric names to verify:

http_server_request_duration_seconds_bucket{method="GET",route="/api/users/{id}",status="200",le="0.1"}
http_server_request_duration_seconds_count{method="GET",route="/api/users/{id}",status="200"}
http_server_active_requests{method="GET"}

Validation command:

# Check metrics endpoint
curl -s http://localhost:5000/metrics | grep http_server

# Verify histogram buckets exist
curl -s http://localhost:5000/metrics | grep "_bucket"

# Check for high-cardinality labels (should NOT see user IDs, request IDs, etc.)
curl -s http://localhost:5000/metrics | grep -E "user_id|request_id"
# Should return nothing

Trace Propagation Validation

• W3C traceparent header propagated
• Spans created for HTTP requests
• Database operations create child spans
• Cross-service traces connected

Sample trace header:

traceparent: 00-0af7651916cd43dd8448eb211c80319c-b7ad6b7169203331-01
tracestate: myvendor=value

Validation command:

# Verify trace context propagation
# Make request with traceparent header
curl -H "traceparent: 00-12345678901234567890123456789012-1234567890123456-01" \
     -v http://localhost:5000/api/users/1 2>&1 | grep -i traceparent

# Check response includes traceparent
# Verify downstream services receive same trace ID

# Check OTLP exporter connectivity
curl -s http://localhost:4317/health  # gRPC health check
curl -s http://localhost:4318/health  # HTTP health check

Quick Validation Script

#!/bin/bash
# validate-observability.sh

SERVICE_URL="${1:-http://localhost:5000}"
ERRORS=0

echo "=== Observability Validation ==="
echo "Service: $SERVICE_URL"
echo ""

# Test 1: Metrics endpoint
echo "1. Checking metrics endpoint..."
if curl -sf "$SERVICE_URL/metrics" > /dev/null; then
  echo "   ✓ Metrics endpoint accessible"

  # Check for RED metrics
  if curl -sf "$SERVICE_URL/metrics" | grep -q "http_server_request_duration"; then
    echo "   ✓ Duration metric present"
  else
    echo "   ✗ Duration metric missing"
    ((ERRORS++))
  fi
else
  echo "   ✗ Metrics endpoint not accessible"
  ((ERRORS++))
fi

# Test 2: Correlation ID propagation
echo ""
echo "2. Checking correlation ID propagation..."
CORRELATION_ID="test-$(date +%s)"
RESPONSE=$(curl -sf -H "X-Correlation-ID: $CORRELATION_ID" "$SERVICE_URL/api/health" -i 2>&1)
if echo "$RESPONSE" | grep -qi "x-correlation-id"; then
  echo "   ✓ Correlation ID returned in response"
else
  echo "   ✗ Correlation ID not propagated"
  ((ERRORS++))
fi

# Test 3: Trace context
echo ""
echo "3. Checking trace context propagation..."
TRACE_ID="12345678901234567890123456789012"
RESPONSE=$(curl -sf -H "traceparent: 00-$TRACE_ID-1234567890123456-01" \
                "$SERVICE_URL/api/health" -i 2>&1)
if echo "$RESPONSE" | grep -qi "traceparent"; then
  echo "   ✓ Trace context propagated"
else
  echo "   ⚠ Trace context not in response headers (may be logged internally)"
fi

# Summary
echo ""
echo "=== Summary ==="
if [ $ERRORS -eq 0 ]; then
  echo "✓ All validations passed"
  exit 0
else
  echo "✗ $ERRORS validation(s) failed"
  exit 1
fi

Evidence Template

# Observability Validation Evidence

**Service**: [service-name]
**Date**: YYYY-MM-DD
**Validator**: [name]

## Logging

- [x] Structured logging configured
- [x] Correlation ID middleware active
- [x] Log level: Information (production)

**Sample log entry:**
[paste actual log entry here]

## Metrics

- [x] Metrics endpoint: /metrics
- [x] RED metrics present
- [x] No high-cardinality labels

**Metrics output:**

```text
[paste relevant metrics here]
```

## Tracing

- [x] OpenTelemetry SDK configured
- [x] W3C Trace Context propagation
- [x] Sampling: 10% (production)

**Trace verification:**
[paste trace ID and verification steps]

Red Flags - STOP

These statements indicate observability anti-patterns:

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