Lesson 1Backend Node.js instrumentation: automatic vs manual tracing, HTTP middleware, capturing spans for middleware, business logic and downstream callsDis section detail Node.js backend instrumentation, comparing automatic and manual tracing, and showing how to capture spans for HTTP middleware, business logic, and downstream calls to databases, caches, and external services for full request visibility.
Choosing automatic versus manual instrumentationTracing Express and Koa middleware chainsCapturing spans for core business operationsInstrumenting outbound HTTP and gRPC clientsHandling async context and promise boundariesLesson 2Database instrumentation: PostgreSQL query timings, slow query logging, connection pool metrics, statement-level tracingDis section focus on PostgreSQL instrumentation, including query timing, slow query logging, connection pool metrics, and statement-level tracing, so you fit identify bottlenecks, tune queries, and understand database impact on end-user latency.
Enabling query timing and latency histogramsConfiguring slow query thresholds and loggingMonitoring connection pool size and saturationTracing prepared statements and ORM queriesTagging queries with tenant and feature dataLesson 3Frontend instrumentation: metrics to capture (page load, Core Web Vitals, TTFB, FID, LCP, CLS), measuring single-page application routing and synthetic transactionsDis section cover browser performance instrumentation, including Core Web Vitals, SPA routing, and synthetic transactions, enabling you to capture consistent frontend metrics, detect regressions, and link client behavior to backend performance.
Capturing Core Web Vitals in productionMeasuring TTFB, FID, LCP, CLS, and long tasksInstrumenting SPA route changes and virtual viewsModeling synthetic user flows in the frontendTagging frontend metrics with release versionsLesson 4Logging and metrics correlation: structured logs, log enrichment with trace IDs, centralized log ingestion pointsDis section explain how to correlate logs and metrics using structured logging, trace and span identifiers, and centralized ingestion. You go learn to build queries and dashboards dat connect events, performance, and user impact.
Designing structured log schemas and fieldsEnriching logs with trace and span identifiersCentralizing log ingestion and parsing rulesLinking metrics, logs, and traces in dashboardsDefining retention and access control policiesLesson 5Backend Java (Spring Boot) instrumentation: agent-based tracing, configuring spans for controllers, filters, database calls and external HTTP/gRPCDis section describe Java Spring Boot instrumentation using agents and configuration, covering spans for controllers, filters, database calls, and external HTTP or gRPC requests, to achieve consistent, low-friction tracing across Java services.
Deploying Java agents in different environmentsConfiguring controller and filter span boundariesTracing JDBC, JPA, and reactive database callsInstrumenting outbound HTTP and gRPC clientsCustom spans for business and domain eventsLesson 6Distributed tracing design: trace context propagation, sampling strategies, span naming conventions and metadata/taggingDis section explain distributed tracing design, including trace context propagation, sampling strategies, span naming, and tagging. You go learn how to create consistent, low-overhead traces dat support debugging, SLOs, and dependency analysis.
Propagating W3C trace context across servicesDesigning head and tail sampling strategiesDefining span naming rules and hierarchiesStandardizing tags for teams and environmentsManaging trace volume and retention policiesLesson 7Frontend instrumentation: error collection (JS exceptions, source maps, unhandled promise rejections) and session/trace correlationDis section address frontend error instrumentation, including JavaScript exceptions, source maps, unhandled promise rejections, and session correlation, so you fit quickly diagnose client-side failures and link dem to backend traces.
Capturing runtime JS errors and stack tracesUploading and managing source maps securelyHandling unhandled rejections and console errorsGrouping and prioritizing frontend error eventsLinking sessions to backend traces and logsLesson 8Synthetic monitoring and RUM: configuring synthetic checkout journeys and browser Real User MonitoringDis section explain how to design and configure synthetic journeys and Real User Monitoring, so you fit measure availability, performance, and user experience across key flows such as checkout, login, and account management in production and staging.
Designing critical synthetic user journeysConfiguring browser and API synthetic checksSetting SLAs and alert thresholds for syntheticsImplementing browser RUM beacons and samplingCorrelating RUM sessions with backend tracesLesson 9Infrastructure instrumentation: Kubernetes metrics (node, pod, container), kubelet/cadvisor, kube-state metrics and cloud provider metricsDis section cover infrastructure instrumentation for Kubernetes and cloud platforms, including node, pod, and container metrics, kubelet and kube-state metrics, and cloud provider telemetry, enabling capacity planning and incident triage.
Collecting node, pod, and container metricsScraping kubelet and cAdvisor endpointsUsing kube‑state metrics for cluster healthIntegrating cloud provider metrics and quotasBuilding SLOs for infrastructure resources
