AWS CloudWatch to Datadog Migration & Centralized Observability

**Migration Planning & Strategy**: Conducted comprehensive audit of all CloudWatch resources: 2,300+ log groups, 5,400+ metrics, and 380+ alarms across 8 AWS accounts. Created detailed migration plan prioritizing critical production services first, then staging, then development. Established success criteria: maintain 100% monitoring coverage, reduce costs by 40%+, and improve MTTD by 50%. Planned parallel running for 4 weeks to ensure no blind spots.

**Datadog Deployment**: Deployed Datadog Agent across 450+ EC2 instances, ECS tasks, and Lambda functions using Terraform and Ansible for automated installation. Configured AWS integration for automatic CloudWatch metric collection with selective filtering to reduce noise. Set up log forwarding from CloudWatch Logs to Datadog using Lambda forwarder with filtering rules to avoid ingesting unnecessary logs. Implemented APM instrumentation for 35+ microservices using dd-trace libraries.

**Unified Observability**: Created 80+ comprehensive Datadog dashboards replacing scattered CloudWatch dashboards, organizing by service ownership, infrastructure health, and business KPIs. Implemented distributed tracing providing end-to-end request visibility across microservices identifying bottlenecks within seconds. Configured log correlation linking traces to logs to metrics for seamless troubleshooting. Set up synthetic monitoring for critical user journeys with multi-region checks.

**Smart Alerting**: Redesigned alerting strategy using Datadog anomaly detection and forecasting reducing alerts from 380 to 85 high-value alerts. Configured composite monitors combining multiple signals to reduce false positives by 80%. Implemented dynamic thresholds adapting to traffic patterns automatically. Integrated alerts with PagerDuty, Slack, and Jira with intelligent routing based on severity and service ownership.