What Is Kubernetes? How the Control Loop Works
Understand Kubernetes through desired state, the control plane, nodes, Pods, workloads, and Services—what it automates, what remains yours, and how to inspect failure.
Practical, source-backed guides for instrumenting, operating, and improving production systems.
Understand Kubernetes through desired state, the control plane, nodes, Pods, workloads, and Services—what it automates, what remains yours, and how to inspect failure.
Understand Datadog AP1 pricing for Singapore with public rates, a transparent 30-day log model, worked cost examples, and the assumptions that change the estimate.
APM monitoring explained — distributed tracing mechanics, RED/USE metrics, sampling strategies, OpenTelemetry vs vendor agents, and how to choose an APM tool.
Monitor AWS RDS properly — CloudWatch vs Enhanced Monitoring vs Performance Insights, the metrics and alarms that matter, slow query setup, and cost traps.
Monitor Docker containers properly — docker stats limits, cAdvisor + Prometheus setup, the container metrics that matter, log collection, and restart-loop alerting.
Monitor Apache Kafka end to end — consumer lag (the one metric that matters), broker JMX metrics, under-replicated partitions, exporter setup, and alert rules.
Kubernetes monitoring architecture patterns compared — single-cluster Prometheus, agent-mode remote write, multi-cluster hub, and platform-based. Data flow, scaling, failure modes.
Monitor Kubernetes end to end — the 4 metric layers, kubectl/Prometheus/eBPF tool choices, the 10 alerts every cluster needs, and common failure patterns.
Monitor MySQL like an SRE — the 15 metrics that matter, slow query log setup, replication lag alerts, connection pool traps, and exporter configs.
Observability fundamentals explained — metrics/logs/traces and why pillars mislead, SLO-based alerting, OpenTelemetry instrumentation, and a maturity roadmap.
Monitor PostgreSQL like an SRE — pg_stat_statements setup, the metrics that matter, vacuum/bloat watch, replication lag, connection pools, and alert rules.
Learn Prometheus monitoring end to end — metric types, PromQL patterns, alerting rules, remote write, and production pitfalls like cardinality explosions.
Move from Datadog-native instrumentation to OpenTelemetry — per-language SDK swaps, Collector dual-export to keep Datadog running, semantic conventions, and pitfalls.
A field-tested Datadog migration plan — inventory, dual-write cutover, dashboard/alert field mapping, canary verification, and rollback. Week-by-week checklist.