Lesson 1Node.js backend watching: auto vs hand tracking, HTTP middle steps, parts for middle, business rules, downstream callsThis part details adding watching to Node.js backends, comparing auto and hand-done tracking, and capturing parts for HTTP middle steps, business rules, and calls to other services, databases, caches for full view of requests.
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 watching: PostgreSQL query times, slow query records, connection group measures, query-level trackingThis part looks at adding watching to PostgreSQL databases, with query times, slow query records, connection group measures, and query-level tracking, to find blocks, improve queries, and see database effect on user wait times.
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 3Front watching: measures to catch (page load, key web measures, first byte time, first input delay, largest content paint, layout shifts), single-page app paths and fake actionsThis part covers browser speed watching, with key web measures, single-page app paths, and fake user actions, to catch steady front measures, spot slowdowns, and link front actions to backend speed.
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 4Linking logs and measures: ordered logs, log adding with track IDs, central log intake pointsThis part shows how to link logs and measures with ordered logs, adding track IDs to logs, and central points to take in logs. You learn to make searches and screens that join events, speed, and user effects.
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 5Java Spring Boot watching: agent tracking, setting parts for controllers, filters, database calls, outside HTTP/gRPCThis part describes adding watching to Java Spring Boot using agents and setup, covering parts for controllers, filters, database calls, and outside HTTP or gRPC calls, for steady, easy tracking 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 6Spread tracking setup: track info passing, sampling ways, part naming rules, info/taggingThis part explains spread tracking setup, with track info passing, sampling ways, part naming rules, and adding info/tags. You learn to make steady, low-cost tracks that help fixing, goals, and link checking.
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 7Front watching: error catching (JS errors, source maps, unhandled promise fails) and session/track linkingThis part handles front error watching, with JS errors, source maps, unhandled promise fails, and session/track linking, to quickly find client-side fails and link to backend tracks.
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 8Fake checks and real user watching: setting fake buy paths and browser real user watchingThis part explains setting fake checks and real user watching, to measure uptime, speed, user feel across key paths like buying, login, account handling in live and test setups.
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 9Basic setup watching: Kubernetes measures (node, pod, container), kubelet/cadvisor, kube-state measures, cloud measuresThis part covers basic setup watching for Kubernetes and cloud, with node, pod, container measures, kubelet/cadvisor, kube-state measures, cloud info, for planning space and sorting problems.
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
