SRE and advanced troubleshooting: Linux performance, SLOs and incident management
Diagnose a slow or failing Linux server one resource at a time, trace processes down to the kernel, then drive reliability with SLOs, on-call, blameless postmortems and automation.
A MasterLinux course · Original text
What you will learn
- Measure and cap toil, write an error budget policy and alert on burn rate
- Apply the USE and RED methods and the first-60-seconds checklist to a slow server
- Read load, steal time, cgroup throttling and a perf profile to find what is eating the CPU
- Understand the page cache, swap, memory pressure (PSI) and the OOM killer's decisions
- Measure disk latency with iostat, find the guilty process and choose the I/O scheduler
- Diagnose the network with ss, nstat and sar - retransmissions, queues, CLOSE-WAIT, a full conntrack table
- Trace a process with strace, ltrace and lsof, and discover eBPF with bpftrace
- Tune kernel and process limits - ulimit, prlimit, fs.file-max, vm.max_map_count, TasksMax
- Run an incident with clear roles, severity levels and controlled communication
- Write blameless postmortems based on real public incidents, and turn runbooks into safe automation
Course content
12 lessons · 9 h 50 minSection 1 — SRE culture
Section 2 — Linux performance
Section 3 — Tracing and the kernel
Section 4 — Incidents and reliability
- On-call and incident management: severity, roles, communication and team health 45 min
- Blameless postmortems: contributing factors, useful actions and lessons from public incidents 50 min
- From runbooks to safe automation: dry run, lock, log and safeguards 50 min
- Final project: an end-to-end incident, from diagnosis to postmortem 1 h 30 min
Requirements
- The “Fundamentals” course (included) or solid hands-on experience with the Linux command line
- Able to administer a Debian, Ubuntu or Rocky server (packages, services, logs)
- Recommended - the “Monitoring and observability” course (Prometheus, Grafana, alerts)
Who is this course for?
- System administrators and operations engineers who want to become SREs
- DevOps engineers who carry the pager and want to diagnose faster
- Back-end developers who want to understand why their application is slow in production