Software Performance
Develop the skills to measure and improve a representative software workload through a learning path centred on Software Performance. Explore concepts, guided practice and an applied project.
Build practical Software Performance skills.
Skills and knowledge developed in this course.
- Performance model
- Profiling
- Optimization
- Benchmark project
- Applied project: Measure and improve a representative software workload
- Software Performance — validation and review
About this course
This course develops practical capability in Software Performance. Its course-specific content covers Performance model, Profiling, Optimization, Benchmark project, followed by an applied project focused on measure and improve a representative software workload. The lessons include concrete configuration, design, testing or operational decisions appropriate to the subject.
Who this is for
Administrators, developers and practitioners who work with Software Performance or plan to take on responsibilities in this area.
Before you start
Working knowledge of software architecture & engineering and practical familiarity with the named platform or subject. Review the course topics before enrolment to confirm the lab starting point.
Measure and improve a representative software workload
Deliver measure and improve a representative software workload. Use the module outcomes to state requirements, demonstrate a working result, test an expected failure or boundary case, and document assumptions and follow-up work.
Course content
Course-specific syllabus and practical exercises. Lab release, access arrangements and final delivery scope are confirmed before enrolment.
01Performance model
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- Latency, throughput and saturation
- Workload profile and service objectives
Practical exerciseApply performance model to the measure and improve a representative software workload and capture the validation evidence.
02Profiling
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- CPU, memory, database and network signals
- Hot-path and allocation evidence
Practical exerciseApply profiling to the measure and improve a representative software workload and capture the validation evidence.
03Optimization
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- Algorithm and query improvements
- Caching and concurrency trade-offs
Practical exerciseApply optimization to the measure and improve a representative software workload and capture the validation evidence.
04Benchmark project
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- Establish a reproducible baseline
- Measure a change and explain any regressions
Practical exerciseApply benchmark project to the measure and improve a representative software workload and capture the validation evidence.
05Applied project: Measure and improve a representative software workload
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- Define inputs, assumptions and acceptance criteria for: Measure and improve a representative software workload.
- Implement the project using performance model, profiling, optimization, benchmark project.
Practical exerciseMeasure and improve a representative software workload.
06Software Performance — validation and review
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- Demonstrate the completed project against its acceptance criteria.
- Exercise an invalid-input or failure scenario and document the observed result.
Practical exercisepresent the project evidence, limitations and a repeatable handover.
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
Set the context
Performance model · Profiling
Establish the Software Performance scope, baseline concepts and operating assumptions. - 02Learning milestone 2 In progress
Build the working skills
Optimization · Benchmark project
Apply the core Software Performance techniques in the course lab and record the result. - 03Learning milestone 3 In progress
Validate and handle exceptions
Check expected behavior, investigate a failure case and capture evidence for measure and improve a representative software workload. - 04Learning milestone 4 In progress
Deliver the applied project
Complete measure and improve a representative software workload, explain key decisions and identify a practical next step.
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 |
|---|---|---|---|
| SRE / Observability Engineer | ₹8–14 LPA | ₹18–32 LPA | ₹35–58 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 ↗