Lesson 1When to kill, restart, or throttle a process: safe kill practices, systemctl restart, and using cgroups and nice/reniceUnderstand when to kill, restart, or throttle a process and how to do it safely. Learn signal types, safe kill patterns, systemctl restart behavior, and how to apply cgroups and nice or renice to limit impact.
Choosing SIGTERM, SIGKILL, and othersUsing kill and pkill with safeguardsRestarting services with systemctlThrottling CPU with nice and reniceLimiting resources using cgroupsDocumenting and automating remediesLesson 2Analyzing swap usage and OOM events: dmesg, kernel OOM killer logs, and /var/log/kern.logInvestigate swap usage and Out Of Memory events using free, dmesg, kernel OOM logs, and /var/log/kern.log. Learn to recognize thrashing, tune swappiness, and decide when to add RAM or adjust limits.
Checking swap usage with free and /procRecognizing swap thrashing symptomsReading dmesg for OOM killer entriesParsing /var/log/kern.log detailsTuning swappiness and vm overcommitDeciding when to add RAM or adjust limitsLesson 3Identifying hot processes: ps, ps aux --sort, pgrep, pidstat and mapping PIDs to servicesLearn to quickly identify hot or misbehaving processes using ps, pgrep, pidstat, and sorting options. Map PIDs back to services, units, and containers to connect resource usage with responsible components.
Sorting ps output by CPU and memoryUsing pgrep and pkill name filtersMonitoring per-process stats with pidstatMapping PIDs to systemd unitsRelating PIDs to containers or cgroupsTracking short-lived bursty processesLesson 4Identifying recurring resource spikes: inspecting cron, systemd timers, at jobs, and application schedulersExplore methods to detect recurring CPU, memory, and I/O spikes by correlating metrics with scheduled tasks. Inspect cron, systemd timers, at jobs, and in-app schedulers to find and fix noisy or overlapping jobs.
Listing and reading user and system crontabsInspecting systemd timers and calendar unitsReviewing at jobs and one-off schedulesTracing app-level schedulers and workersCorrelating spikes with job execution timesRefining or staggering noisy recurring jobsLesson 5Memory troubleshooting: free, /proc/meminfo, smem, pmap and checking for memory leaksGain skills to troubleshoot memory issues using free, /proc/meminfo, smem, and pmap. Learn to distinguish cache from real pressure, find per-process usage, and recognize patterns that indicate memory leaks or fragmentation.
Interpreting free and available memoryReading /proc/meminfo key fieldsUsing smem for per-process breakdownsInspecting process maps with pmapSpotting memory leak growth patternsDifferentiating cache from real pressureLesson 6Integrating with monitoring data (Prometheus, Grafana) and using historical metrics to determine trendsLearn to combine local troubleshooting with Prometheus and Grafana data. Use historical metrics, dashboards, and alerts to identify trends, regressions, and slow drifts, and to validate the impact of performance fixes.
Reviewing key CPU and load dashboardsInspecting memory, cache, and swap panelsAnalyzing disk and network latency graphsUsing PromQL to slice historical metricsCorrelating deploys with metric changesValidating fixes with before and after viewsLesson 7Load vs CPU saturation: uptime, load average interpretation and relation to CPU coresClarify the meaning of system load averages and their relation to CPU cores and run queues. Learn to distinguish healthy high load from CPU saturation, and correlate load with I/O wait, context switches, and latency.
Reading uptime and load averagesRelating load to CPU core countsSeparating runnable and blocked tasksIdentifying CPU-bound saturation casesRecognizing I/O wait driven loadUsing vmstat and mpstat to confirmLesson 8Collecting live system metrics: top, htop, vmstat, mpstat, iostat and how to interpret outputsLearn to collect and interpret live Linux performance metrics using top, htop, vmstat, mpstat, and iostat. Understand CPU, memory, and I/O views, key fields, refresh intervals, and how to spot bottlenecks in real time.
Reading CPU usage in top and htopMonitoring memory and swap in topUsing vmstat for system-wide snapshotsAnalyzing CPU stats with mpstatChecking disk I/O patterns with iostatChoosing sampling intervals and filtersLesson 9Using perf, strace, and ltrace for deep process analysis and when to use eachUnderstand when and how to use perf, strace, and ltrace for deep process analysis. Learn to profile CPU hotspots, trace system calls, inspect library calls, and minimize overhead while capturing actionable diagnostics.
Profiling CPU hotspots with perf recordViewing perf reports and call graphsTracing syscalls with strace safelyFiltering noisy strace outputInspecting library calls using ltraceChoosing the right tool for each symptomLesson 10Using lightweight profiling and tracing tools (py-spy, gdb, flamegraphs) for Python appsFocus on lightweight profiling and tracing for Python applications using py-spy, gdb, and flamegraphs. Capture stack samples in production, locate hot code paths, and interpret flamegraphs without stopping services.
Sampling Python stacks with py-spyGenerating and reading flamegraphsAttaching gdb safely to live PythonHandling stripped or optimized buildsProfiling async and multithreaded codeReducing profiler overhead in production
