Complete Serverless Observability | Datadog

Complete Serverless Observability

Detect and resolve performance issues in your serverless environment

All your functions in one place

Aggregate critical serverless metrics in one place for a birds-eye view.

  • Optimize performance by filtering to functions that are generating errors, high latency, or cold starts
  • Leverage tags to group functions by cloud region, allocated memory, environment, and more
  • Identify high-level function issues, then pivot to invocation traces and logs with one click

Trace across any infrastructure

Detect and resolve incidents spanning all of your service architecture, whether serverless functions, containers, or VMs.

  • Trace microservice calls across your stack to get end-to-end visibility into customer requests
  • Automatically map out upstream and downstream dependencies like API Gateway, Amazon SNS, or DynamoDB
  • Get greater service customization via integrations like, Serverless Framework, Terraform and SAM

Complete serverless functions observability

Simplify serverless function incident diagnosis.

  • Isolate an individual customer request and drill down to the associated logs and metrics for the full story
  • Alert your on-call teams with machine learning-based anomaly, outlier, and forecasting monitors
  • Search and filter using tags like service, customer, or error code to troubleshoot ephemeral functions

Track business metrics with no additional overhead

Collect custom business metrics from serverless functions without adding any resource overhead to invocations.

  • Reduce silos with a single source of truth for dev, ops, and business teams
  • Collect metrics directly from your functions to track data like a count of items in a cart, or value of item in a cart
  • Visualize and analyze key business data through customizable dashboards
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Analyze critical serverless metrics

Address underprovisioned or misconfigured serverless functions for performance and cost benefits.

  • Alert on memory, timeout, and allocated concurrency metrics to avoid poor end user experiences
  • Correlate metrics with cold starts to identify patterns of customer-facing latency
  • Identify which functions are producing errors and what types of errors are plaguing individual Lambda functions

Resources