Projects
· Performance testing
Performance & scalability testing
Moving from one-off load tests to a structured performance practice aligned with business SLAs and peak events.
Strategy & objectives
Start with business expectations, not just tool configuration.
- Defined performance objectives with product and engineering: what fast enough means and where.
- Identified critical flows and components (search, checkout, APIs) to focus effort instead of testing “everything”.
- Agreed on metrics (latency, throughput, error rate) and SLOs that mattered to both tech and business stakeholders.
Scenarios, tooling & environment
Practical performance testing that fits into real release cycles.
- Designed load, stress and soak scenarios based on historical traffic patterns and expected growth.
- Used suitable tooling (e.g. Locust / JMeter / k6 ) depending on stacks and team skills.
- Worked with DevOps to provision realistic, isolated environments for regular performance runs where possible.
Integration into release process
Making performance checks a habit, not an afterthought.
- Scheduled regular performance runs ahead of big campaigns or feature launches with clear pass/fail criteria.
- Shared reports focused on decision-making: “can we launch?”, not just graphs of response times.
- Created feedback loops so findings informed architecture, caching and scaling decisions.
Impact & reuse
A pattern for making performance part of normal quality.
- Improved stability during peak events and reduced surprises like timeouts or cascading failures.
- Teams had a clearer picture of how close they were to limits, enabling smarter scaling and cost decisions.
- The same model (objectives → scenarios → runs → decisions) can be applied to any new product line.