Operations Management

Monitoring Frontend Performance with Amazon CloudWatch RUM - Real User Monitoring

Simply embed a JavaScript snippet to collect page load times, Web Vitals, JS errors, and HTTP errors in real time. This article explains how to visualize frontend quality using session replay and custom events.

約 3 分で読めます

Overview of CloudWatch RUM

CloudWatch RUM (Real User Monitoring) is a service that monitors web application frontend performance in real time. By simply embedding a JavaScript snippet in your page, it automatically collects page load times, Web Vitals (LCP, FID, CLS), JavaScript errors, and HTTP errors from actual users' browsers. Unlike Synthetic Monitoring (CloudWatch Synthetics), which runs scripted periodic synthetic tests, RUM collects data from real user sessions. You can configure a sampling rate to control data collection volume - collecting 100% of all sessions or reducing to 10% to save costs.

Web Vitals and Performance Analysis

RUM automatically collects Google's Core Web Vitals (LCP: Largest Contentful Paint, FID: First Input Delay, CLS: Cumulative Layout Shift) and displays per-page performance scores on a dashboard. Waterfall analysis of page loads visualizes the time spent in each phase: DNS resolution, TCP connection, TLS handshake, TTFB (Time to First Byte), and content download. Performance comparisons by browser, OS, and region help identify issues that occur only in specific environments. You can also send custom events to track user actions such as button clicks, form submissions, and page transitions.

Error Tracking and X-Ray Integration

JavaScript errors (unhandled exceptions, Promise rejections) and HTTP errors (4xx, 5xx responses) are automatically captured, with error frequency, affected session counts, and stack traces displayed on the dashboard. When X-Ray integration is enabled, you can obtain end-to-end traces from frontend requests through backend API Gateway, Lambda, and DynamoDB. You can trace whether an error in a user's browser originated from a specific backend service in a single trace, dramatically improving root cause identification. Cognito integration lets you identify authenticated user sessions and analyze specific users' experiences in detail. For practical guidance on frontend monitoring, related books on Amazon are also a useful reference.

CloudWatch RUM Pricing

CloudWatch RUM pricing is pay-per-use based on the number of events collected. It costs approximately $1.00 per 100,000 events. A single page view generates multiple events (page load, Web Vitals, errors, etc.), so estimate costs at roughly 5-10 events per page view. Lowering the sampling rate reduces costs, but there is a trade-off with statistical accuracy. If X-Ray tracing is enabled, X-Ray charges (approximately $0.000005 per trace) apply separately.

Summary

CloudWatch RUM is a service that monitors frontend performance and errors in real time simply by embedding a JavaScript snippet. With automatic Web Vitals collection, waterfall analysis, and end-to-end tracing via X-Ray integration, you can quickly identify and resolve user experience issues.

Related Services

Amazon CloudWatch RUMA real user monitoring service that collects client-side performance and error data from web applicationsAmazon CloudWatchA service that provides monitoring, log management, and alarms for AWS resources and applicationsAmazon CloudFrontA CDN service that delivers content at high speed from edge locations around the world

Related Articles

Building a Unified Observability Dashboard with Amazon Managed GrafanaLearn how to build a multi-source observability dashboard by integrating CloudWatch, Prometheus, and OpenSearch data sources.Automating SSL/TLS Certificate Management with AWS Certificate Manager - From Issuance to RotationLearn how ACM handles free public certificate issuance, DNS validation, automatic renewal, and deployment to ALB and CloudFront.Getting Started with Full-Stack Web App Development on AWS Amplify - Git-Connected Deploys and Backend SetupSet up automatic per-branch deployment environments with GitHub integration, and define authentication, APIs, and storage in TypeScript using Backend Gen 2. Also supports Next.js SSR.

More on This Topic

How AWS Keeps Time Internally - Amazon Time Sync Service and Leap Second Smearing DesignLearn how Amazon Time Sync Service works, how GPS and atomic clocks provide high-precision time sources, the design decision to absorb leap seconds through smearing, and why time synchronization matters in distributed systems.Centralizing SaaS Audit Logs with AWS AppFabric - OCSF Standardization and Security Lake IntegrationLearn how AppFabric collects audit logs from SaaS applications, standardizes them to OCSF format, and builds analysis pipelines.Implementing Feature Flags with AWS AppConfig - Safe Configuration Deployment and RollbackRoll out configuration changes independently from code deployments using Linear and Exponential strategies. Ensure safety with automatic rollback triggered by CloudWatch alarms.Architecture Review - Systematically Evaluate Workloads with the AWS Well-Architected ToolLearn about architecture reviews using the AWS Well-Architected Tool. Covers evaluation based on the six pillars, improvement planning, and custom lens usage.Audit Log Design and Operations - Complete API Activity Recording with CloudTrailLearn how to design audit logs using AWS CloudTrail, including recording API activity, long-term storage in S3, and compliance automation through integration with AWS Config.Lessons from AWS Incident Reports (COE) - How Past Major Outages Shaped Design PrinciplesAnalyze the root causes of past major incidents including the S3 outage, us-east-1 DNS failure, and Kinesis outage from AWS's published Correction of Errors (COE) and incident reports, and explain how they changed AWS's design principles.Tag Design Determines Operations - Trivia and Practical Naming Conventions for AWS Resource Tagging StrategyWe explain why AWS resource tags are not just labels but the foundation for cost allocation, access control, and automation, covering tag key naming conventions, how to use the 50-tag limit, and governance through tag policies.Why AWS Service Quotas Exist - Multi-Tenant Design That Protects Shared InfrastructureExplain how AWS service quotas (formerly service limits) are not mere restrictions but a design to protect other customers in a multi-tenant environment, covering the noisy neighbor problem, soft vs hard limits, and what happens behind quota increase requests.

Similar Articles and Services

AWS X-RayA tracing service that tracks and visualizes requests end-to-end across distributed applications, identifying latency and error bottlenecks between microservicesAWS X-RayTrace requests through distributed applications and identify performance bottlenecksDistributed Tracing with AWS X-Ray - Performance Analysis for MicroservicesVisualize the full request path across microservices with service maps, narrow down problem traces with filter expressions, and integrate with OpenTelemetry.The Integration Power of the AWS Observability Stack - Operational Transparency Through CloudWatch, X-Ray, and CloudTrailThis article examines the integration level of the AWS observability stack centered on CloudWatch, X-Ray, and CloudTrail, comparing it with Azure Monitor and GCP Cloud Logging to explain how the three pillars of metrics, traces, and logs drive differences in operational quality.