Datadog plugins

Profile, monitor, and optimize application performance across the full stack — from frontend Core Web Vitals and React/Next.js rendering to backend caching, load testing, and distributed tracing with OpenTelemetry. Automate performance baselines, observability setup, and incident investigation for production systems.

Analyze and resolve errors across distributed systems with root cause analysis, log correlation, and multi-agent code review. Debug test failures, search logs for anomalies, and improve error handling patterns.

Set up full-stack observability with Prometheus/Grafana dashboards, distributed tracing (Jaeger/Tempo), SLO frameworks, and alerting, plus performance optimization across services, databases, and networks.

Systematically trace errors from stack traces to distributed traces, perform root-cause analysis, and generate fixes with automated observability steps. Also audits error-handling patterns and logging setup across your codebase, producing actionable recommendations for structured logging, alerts, and monitoring service integration.

Set up, monitor, and optimize production systems with distributed tracing, SLI/SLO management, incident response, and performance profiling using Prometheus, Grafana, OpenTelemetry, and other observability tools.

Triage errors, stack traces, and observability data to generate ranked hypotheses and recommend debugging strategies. Automate environment setup, optimize build/test loops, and create project-specific git hooks to reduce friction.

Automate production incident response with structured runbooks, triage workflows, multi-agent debugging, and blameless postmortems, integrating with observability tools like Sentry, Datadog, and Kubernetes for root cause analysis and automated resolution.

Debug and trace distributed systems across microservices by configuring environments, analyzing logs for error patterns, and troubleshooting production incidents with Kubernetes and observability tools.

Streamlines engineering workflows with structured standups, code review, architecture decisions, incident response, debugging, deployment verification, technical debt management, and documentation — all integrated with Slack, Linear, Jira, Notion, GitHub, PagerDuty, Datadog, and Databricks.

Orchestrates and optimizes multi-agent teams for complex workflows, handling task decomposition, state coordination, error recovery, performance monitoring, and knowledge extraction across distributed agents.

Run load, stress, and soak tests on APIs using k6, Artillery, Gatling, or wrk to measure performance, identify bottlenecks, and validate scalability under realistic traffic patterns.

Generate OpenTelemetry integration code, instrumentation, context propagation config, and sampling strategy for distributed tracing in microservices, with support for Jaeger, Zipkin, or Datadog backends.

Manage the full Guidewire InsuranceSuite lifecycle: configure CI/CD pipelines, execute PolicyCenter/ClaimCenter/BillingCenter workflows via REST API, debug Cloud errors, monitor performance, handle security and RBAC, and orchestrate multi-environment deployments and upgrades.

Set up synthetic monitoring to proactively track application performance, uptime, API health, and SSL certificates with multi-location probes, alert rules, dashboards, and incident response playbooks.

Manage Glean enterprise search integration: index documents, configure permissions, set up CI/CD connectors, monitor search quality, debug API issues, and automate deployment workflows.

Implement Real User Monitoring (RUM) to capture Core Web Vitals, page load times, and custom performance events, with auto-generated integration code and dashboards for Google Analytics, Datadog RUM, and New Relic.

Collect infrastructure performance metrics across compute, storage, network, containers, load balancers, and databases, with agent configurations, dashboards, and alert rules powered by Prometheus, Datadog, or CloudWatch.

Creates intelligent alerting rules for Prometheus, Grafana, and Datadog with automated threshold calculations, routing, escalation policies, and runbooks to streamline performance monitoring and SLO management.

Automate APM dashboard creation across Grafana, Datadog, and New Relic, incorporating golden signals, request/resource metrics, and alert rules for performance monitoring.

Manage and monitor Datadog resources (monitors, logs, APM traces, dashboards, security signals, SLOs) via CLI commands and specialized agents, enabling observability workflows for infrastructure, applications, and CI/CD pipelines.

Set up comprehensive monitoring and observability for your applications, including APM instrumentation, custom metrics, alerting, centralized logging, distributed tracing, infrastructure monitoring, and dashboards using tools like New Relic, Datadog, Prometheus, Grafana, Elasticsearch, and AWS.

Generate analytics reports and dashboard configurations from project data, covering code quality, velocity, build health, and dependencies. Outputs structured summaries with scores and multi-platform dashboard configs.

Guides through setting up monitoring and alerting for application and infrastructure metrics with dashboard generation, following best practices for layout, color coding, and SLA targets.

Audit, plan, and instrument mobile app observability across iOS, Android, React Native, and Flutter — covering crash reporting, performance monitoring, session replay, and distributed tracing with actionable gap analysis and vendor-agnostic rollout strategies.

Delegate observability infrastructure: set up OpenTelemetry distributed tracing, Prometheus/Grafana monitoring dashboards, Datadog alerting, structured logging pipelines, and SLO incident runbooks

Manage site reliability with incident response workflows, Prometheus-based monitoring and alerting, and SRE templates for SLOs, error budgets, and distributed system resilience patterns.

Set up enterprise-grade monitoring, observability, and alerting for B2B applications, including APM, distributed tracing, logging, metrics, and SLA compliance with Prometheus, Grafana, Datadog, and cloud-native infrastructure.

Build, evaluate, secure, and monitor reliable LLM and AI-agent applications with observability, guardrails, evaluation datasets, cost analysis, and regression testing.

Manage the full incident lifecycle in Rootly: create and triage incidents, route alerts, manage on-call shifts, generate postmortems, and check service health — all from Claude Code.

Automates the end-to-end software engineering lifecycle with AI agents: from ticket creation and PRD writing to TDD, parallel implementation, code review, PR management, and post-mortem analysis, enforcing quality gates at every stage.

Structures product discovery workflows for ideation, experiment design, assumption validation, feature prioritization, and user interview organization, with outputs in Markdown.

Generate Google-SRE-style blameless postmortems from an incident tracker URL (Jira or Azure DevOps). Automatically gathers evidence from Slack, Datadog, related issues, and pull requests, reconstructs a chronological timeline with evidence tags, and writes a markdown postmortem with sections like impact, root cause, timeline, and action items.

Query Datadog logs, metrics, traces, dashboards, alerts, SLOs, and incidents through natural conversation in Claude Code, with preconfigured MCP server setup and toolset management.