Lambda Monitoring

Overview

Monitor AWS Lambda functions using CloudWatch native integration, X-Ray distributed tracing, and Lambda Insights for enhanced performance visibility. This solution requires zero external agents — it leverages built-in AWS capabilities.

Key observability features:

• Invocation metrics (duration, errors, throttles, concurrency)
• X-Ray traces for downstream call visibility
• Lambda Insights for memory, CPU, and network metrics
• Structured logging with embedded metric format (EMF)
• Cost-per-invocation tracking

Needs refresh

This entry leads with Lambda Insights and native CloudWatch metrics. It predates the current recommendation and does not cover:

• CloudWatch Application Signals for Lambda, which provides service-level latency, error rate, and dependency mapping
• The AWS-managed OpenTelemetry Lambda layers for OTLP export
• Transaction Search for trace-level analysis

The steps below still work and Lambda Insights remains useful for memory and cold-start analysis. Prefer Application Signals as the starting point for new functions.

Prerequisites

• AWS Lambda function(s) deployed
• IAM execution role with AWSXRayDaemonWriteAccess (for tracing)
• Lambda Insights layer ARN for your region
• CloudWatch Logs enabled (default)

Architecture

┌───────────────────────────────────────────────────┐
│                Lambda Function                     │
│                                                   │
│  ┌────────────────┐  ┌──────────────────────────┐│
│  │ Function Code  │  │ Lambda Insights Extension ││
│  │ + X-Ray SDK    │  │ (Lambda Layer)            ││
│  └───────┬────────┘  └────────────┬─────────────┘│
└──────────┼─────────────────────────┼──────────────┘
           │                         │
     ┌─────▼─────┐            ┌─────▼──────┐
     │  X-Ray    │            │ CloudWatch │
     │  Traces   │            │ Metrics +  │
     │           │            │ Logs       │
     └───────────┘            └────────────┘

Deploy

Step 1: Enable X-Ray tracing

aws lambda update-function-configuration \
  --function-name my-function \
  --tracing-config Mode=Active

Step 2: Add Lambda Insights layer

aws lambda update-function-configuration \
  --function-name my-function \
  --layers "arn:aws:lambda:us-west-2:580247275435:layer:LambdaInsightsExtension:52"

Step 3: Add IAM permissions

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "xray:PutTraceSegments",
        "xray:PutTelemetryRecords"
      ],
      "Resource": "*"
    }
  ]
}

Step 4: Add structured logging (optional but recommended)

In your function code, emit metrics via Embedded Metric Format:

from aws_lambda_powertools import Logger, Metrics, Tracer

logger = Logger()
metrics = Metrics(namespace="MyApp")
tracer = Tracer()

@logger.inject_lambda_context
@metrics.log_metrics
@tracer.capture_lambda_handler
def handler(event, context):
    metrics.add_metric(name="OrderProcessed", unit="Count", value=1)
    # your logic here

Validate

1. Invoke your function:

   aws lambda invoke --function-name my-function output.json

2. Check CloudWatch metrics: Navigate to CloudWatch > Metrics > AWS/Lambda.

3. Check X-Ray traces: Navigate to CloudWatch > X-Ray traces > Trace map.

4. Check Lambda Insights: Navigate to CloudWatch > Insights > Lambda Insights.

Troubleshoot

Symptom	Likely Cause	Fix
No traces in X-Ray	Tracing not set to Active	Check function config
Lambda Insights no data	Layer not attached	Verify layer ARN matches region
High duration reported	Cold starts	Enable provisioned concurrency or SnapStart
Missing custom metrics	EMF format error	Validate JSON structure in logs

Related Solutions

• EKS Application Signals — Trace requests from Lambda to EKS
• Kafka on EC2 — Monitor Kafka consumers triggered by Lambda