Linux Performance Tuning
Develop the skills to identify Linux bottlenecks and validate targeted performance improvements through a learning path centred on Linux Performance Tuning. Explore concepts, guided practice and an applied project.
Build practical Linux Performance Tuning skills.
Skills and knowledge developed in this course.
- Measurement method and workload baselines
- CPU utilisation, scheduling and profiling
- Memory pressure and virtual memory
- Storage latency and I/O paths
- Network performance diagnosis
- cgroups, limits and workload contention
- Kernel tunables and tuning profiles
- Evidence-based optimisation report
About this course
Use measurement to distinguish CPU saturation, memory pressure, storage latency and network constraints. Build a baseline, form a hypothesis, change one variable and compare results under a repeatable workload.
Who this is for
Experienced Linux administrators, SREs and performance engineers investigating slow services.
Before you start
Linux administration, process and filesystem knowledge, and basic statistics for comparing measurements.
Produce a reproducible Linux performance investigation and before-and-after report
Run a controlled workload, locate its limiting resource, apply a justified change and report throughput, latency, resource use and regression checks.
Course content
Course-specific syllabus and practical exercises. Lab release, access arrangements and final delivery scope are confirmed before enrolment.
01Measurement method and workload baselines
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- Define throughput, latency percentiles, saturation and error rate.
- Control warm-up, test duration, workload shape and measurement overhead.
Practical exerciserecord a reproducible baseline before making a tuning change.
02CPU utilisation, scheduling and profiling
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- Interpret load average, runnable tasks and per-core CPU activity.
- Use tools such as mpstat, pidstat and perf where lab permissions permit.
Practical exercisedistinguish a compute-bound workload from a runnable-task queue.
03Memory pressure and virtual memory
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- Interpret cache, resident memory, page faults, reclaim and swap activity.
- Use free, vmstat and process memory evidence to test a memory-pressure hypothesis.
Practical exercisecompare a healthy working set with a constrained workload.
04Storage latency and I/O paths
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- Analyse throughput, queueing and latency with iostat and process-level evidence.
- Distinguish buffered I/O, writeback and workload access patterns.
Practical exerciseisolate an I/O-bound scenario and assess its filesystem and device path.
05Network performance diagnosis
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- Review socket statistics, retransmissions, interface errors and connection limits.
- Use ss and controlled traffic tests to distinguish bandwidth from latency constraints.
Practical exerciseinvestigate an application slowdown caused by a network bottleneck.
06cgroups, limits and workload contention
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- Relate resource limits and scheduling controls to service behaviour.
- Compare CPU and memory isolation using systemd-managed test workloads.
Practical exercisemeasure competing services before and after a justified resource-control change.
07Kernel tunables and tuning profiles
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- Read existing sysctl values and explain persistence and rollback.
- Evaluate a supported tuning profile against a measured requirement.
Practical exercisechange one approved parameter in the lab and verify both benefit and side effects.
08Evidence-based optimisation report
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- Repeat measurements and distinguish a real improvement from noise.
- Record the hypothesis, environment, changed values and rollback conditions.
Practical exercisepresent the before-and-after performance investigation with regression checks.
Technical references
These primary vendor, project or standards sources inform this independent IT Purview outline. Reference pages checked 25 October 2026; current provider documentation and exam objectives take precedence when versions change.
From understanding to application.
Progress by learning milestone. The schedule is agreed around your starting level and learning goals.
- 01Learning milestone 1 In progress
Create a trustworthy baseline
Module 1: workload and measurement
Define success criteria and repeatable test conditions. - 02Learning milestone 2 In progress
Locate the limiting resource
Modules 2–5: CPU, memory, storage and network
Identify the bottleneck with correlated evidence. - 03Learning milestone 3 In progress
Apply a targeted change
Modules 6–7: resource controls and tunables
Validate one change and retain a rollback path. - 04Learning milestone 4 In progress
Report the outcome
Module 8 and the investigation project
Show measured gains, limitations and regression results.
Career outlook after this learning path
Typical roles this roadmap can support, with broad salary ranges by relevant work experience.
| Role | 0–3 years | 3–7 years | 7–12+ years |
|---|---|---|---|
| Linux / Unix Administrator | ₹5–11 LPA | ₹12–24 LPA | ₹25–45 LPA |
Ranges are indicative India-market compensation estimates in ₹ lakh per annum, not a salary promise. They reflect broad market guides and vary by location, employer, skills and role scope; the experience bands refer to relevant work experience, not time since training. Completing this course does not guarantee employment, a role, compensation or career progression. View market reference ↗