Performance Testing

Find out where your system breaks before your users do

We build load, stress, spike, and soak test scripts in JMeter, k6, or Gatling against your real workload model, instrument the full stack with APM, and hand you an SLA verdict backed by evidence — not a guess.

US, Canada & UK overlapWorking hours planned around your team, not just ours.
One point of contactA named lead owns the engagement end to end — no ticket queue.
NDA on every engagementSigned before we see a single ticket or line of test data.
Scale up or down monthlyNo multi-year lock-in — resize the team as the release calendar changes.

Who this is for

Engineering teams heading into a launch, peak season, or high-stakes event without hard numbers on what their system can actually handle under real traffic.

Especially useful if your last performance issue in production was diagnosed after the fact from monitoring alerts, rather than caught before release.

What you get

  • Load, stress, spike, and soak test scripts built in JMeter, k6, or Gatling against your highest-traffic user journeys or API endpoints
  • A documented workload model and target SLAs (response time, throughput, error rate) agreed with your team before scripting starts
  • Full-stack observability wired into every test run using your existing APM (Datadog, New Relic, Dynatrace) or a Grafana/Prometheus stack we stand up
  • A baseline performance report plus root-cause analysis for anything that fails the agreed SLA
  • An executive summary (pass/fail against SLA) and a technical report with tuning recommendations
  • Version-controlled test scripts and dashboards handed over so your team can rerun them after future releases
  • One retest pass after your team applies the recommended fixes

What's not included

Scoped this way on purpose, so the estimate stays accurate and nothing shows up as a surprise mid-engagement.

  • Making the actual code or infrastructure fixes — we identify and explain bottlenecks; implementation is your team’s or a separate engagement
  • Load generation against environments or production systems we don’t have explicit sign-off to test
  • Ongoing, continuous performance monitoring — this is a project-based engagement; monitoring can be scoped separately
  • Testing beyond the endpoints and journeys agreed at kickoff — added scope gets its own estimate

Timeline & process

  1. 1
    Week 1

    Workload modeling & SLA definition

    Review traffic logs and architecture, then agree on SLAs and which journeys or endpoints matter most.

  2. 2
    Week 2

    Environment setup & script development

    Provision test environment access, instrument APM, and write parameterised load scripts.

  3. 3
    Week 3

    Test execution

    Run baseline, load, stress, spike, and soak tests with live monitoring, flagging anomalies as they surface.

  4. 4
    Week 4

    Analysis, reporting & retest

    Deliver the SLA verdict and root-cause report, then retest after fixes land.

What we need from you

  • Access to a staging or production-equivalent environment we can safely load-test
  • Recent production traffic data or analytics, if available, so our workload model reflects real usage
  • Read access to APM or monitoring tools already in place, or agreement on which tool to stand up
  • A technical point of contact available during test execution windows to help triage anomalies live

Proof, not promises

Find out what your system can actually handle

Twenty minutes, no slide deck. Send us your architecture and traffic profile and we’ll tell you where the risk is and roughly what a test cycle would take.

Book a 20-minute scoping call

Contact Us

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