01
Evidence, not guesswork
Profiling and load tests find the real bottleneck — we fix causes, not symptoms.
Services — Quality & support
Fast is a feature. We engineer it.
Load testing, profiling, and tuning across the stack — from database queries to Core Web Vitals — so your system stays fast at 10x the traffic you have today.
Why enterprises choose this service.
02
Full-stack scope
Frontend vitals, API latency, database plans, and infrastructure — one engagement, whole picture.
03
Baselines that stick
Performance budgets wired into CI so regressions get caught at merge time, not in production.
04
Capacity answers
Concrete numbers: what breaks first, at what load, and what it costs to fix.
How we deliver.
Step 01
Baseline
Instrument the stack and measure real user experience and system behavior under current load.
Step 02
Load test
Realistic scenario tests to find breaking points, saturation curves, and the first bottleneck.
Step 03
Optimize
Targeted fixes — queries, caching, code paths, infrastructure — verified by re-test after each change.
Step 04
Guard
Performance budgets and automated tests in CI, plus dashboards that keep the gains visible.
Technology we use.
k6JMeterGatlingGrafanaPrometheusOpenTelemetryPostgreSQLRedisCDN tuning
Frequently asked questions.
Our app is slow but we do not know why. Where do we start?
With a two-week baseline: instrumentation plus profiling usually identifies the top three bottlenecks — and they are rarely where teams expect.
Can you help before a big launch or seasonal peak?
Yes — pre-peak load testing with a capacity plan is one of our most common engagements; start at least six weeks before the date.
Do you optimize Core Web Vitals for SEO?
Yes — LCP, CLS, and INP optimization with field-data verification, typically alongside backend latency work.
Will fixes require a rewrite?
Rarely. Most gains come from query tuning, caching, and configuration; we flag any architectural limits honestly with options.
Related services.
In depth
Performance engineering: latency is a feature, capacity is a plan
Slow is the new down. Users abandon sluggish apps, and cloud bills balloon when inefficiency hides behind autoscaling. Performance engineering treats speed as a designed property: budgets set at architecture time, load models built from real traffic, and bottlenecks found by profiling — not guessing.
Our toolkit: k6 and JMeter load suites wired into CI, distributed tracing to pinpoint the slow hop, database and query tuning, cache strategy, and front-end optimization against Core Web Vitals. Capacity planning turns Black Friday and open-enrollment peaks from emergencies into line items.
We engage before launches, after incidents, and as ongoing discipline alongside QA automation and infrastructure management. Deliverables are numbers: p95 latency down, throughput up, cost per transaction reduced — with the test harness left behind so gains persist.
Budgets before builds
Latency and throughput targets set at design time and enforced in CI.
Profile, don’t speculate
Tracing and profiling find the real bottleneck — fixes target evidence.
Peaks as line items
Capacity models that make seasonal spikes a plan, not a war room.