Ship with Confidence: Load-Tested Before Launch

A comprehensive pre-launch load testing engagement that simulates your expected launch traffic, identifies infrastructure gaps, and delivers a clear go/no-go report before you press the button.

Duration: 5 days Team: 1 Senior Load Testing Engineer

You might be experiencing...

Your product launches next month and you haven't tested whether the infrastructure can handle expected traffic
The last launch caused a 4-hour outage because load exceeded capacity by 3x — you need to prevent a repeat
Your CEO is asking for assurance that the system will hold up under press coverage or a Product Hunt launch
You've set up auto-scaling but don't know if it's configured correctly for launch traffic patterns

A pre-launch load test is the insurance policy that engineering teams owe themselves before any significant product launch. Launch day is the worst possible time to discover that your database connection pool is sized for 100 users when you’re expecting 10,000, or that your auto-scaling group takes 8 minutes to provision new instances while the press coverage spike lasts 5 minutes. These problems are trivially detectable with a well-designed load test.

The key design principle for pre-launch load testing is that you test above your expected peak, not at it. Launch traffic is notoriously unpredictable: a Product Hunt launch can deliver 10x expected traffic; a mention in a major tech outlet can spike traffic by 5x in under a minute. We test at 3x your expected peak as the standard safety margin, which means that even a significantly better-than-expected launch leaves headroom.

The go/no-go framework is designed to produce a clear, defensible recommendation. Engineering teams often face pressure to launch despite known risks — a go/no-go report with specific, quantified pass/fail criteria turns a vague feeling of readiness into an objective measurement. If the system passes, leadership has confidence backed by data. If it fails, the report specifies exactly what needs to be fixed and the estimated effort to fix it.

Engagement Phases

Days 1–2

Launch Traffic Modelling

We work with your product and growth teams to model expected launch traffic: peak concurrent users, traffic ramp profile (gradual vs spike), geographic distribution, and critical user journeys (signup, onboarding, key feature). We instrument test scenarios in k6 or Locust and configure infrastructure monitoring for the test period.

Days 3–4

Staged Load Test Execution

We run three load scenarios: steady-state at 1x expected peak, spike test at 3x peak (press coverage scenario), and sustained load at 1.5x peak for 2 hours (endurance scenario). We monitor infrastructure metrics, identify auto-scaling gaps, and validate CDN and caching behaviour under load.

Day 5

Go/No-Go Report & Remediation

We deliver a go/no-go readiness report against agreed pass/fail criteria (P99 < threshold, error rate < 0.1%, zero data loss). For any failed criteria, we provide specific remediation steps and estimated effort. If critical gaps are found, we assist with priority fixes and retest.

Deliverables

Launch traffic model with scenario definitions
Three load test execution reports (1x, 3x spike, endurance)
Go/no-go readiness report with pass/fail criteria results
Infrastructure gap register with remediation steps
Scaling policy configuration recommendations
k6/Locust test scripts for ongoing use

Before & After

MetricBeforeAfter
Launch readinessUnknownGo/no-go with data
Infrastructure gapsUnknown3 identified and fixed
Scaling policyDefault configurationOptimised for launch pattern

Tools We Use

k6 / Locust Auto-scaling configuration CDN validation

Frequently Asked Questions

What if the test finds critical issues close to the launch date?

That is the point — finding issues before launch, even close to the date, is better than finding them during launch. We prioritise the issues by severity and provide specific remediation steps with effort estimates. Many infrastructure issues (connection pool limits, auto-scaling thresholds, cache configuration) can be fixed in hours, not days. We stay available for re-testing after remediation.

How do you model traffic for a new product with no historical data?

We base the model on comparable product launches in your category, your marketing plan (channels, expected reach, conversion assumptions), and any pre-launch signups or beta user behaviour. We test against 3x your expected peak to build in a safety margin — launch traffic consistently surprises on the upside.

What does the go/no-go report actually contain?

The report specifies pass/fail criteria agreed before testing (e.g., P99 < 500ms at 2x peak, error rate < 0.1%, zero data loss), the actual measured result for each criterion, and a clear recommendation. It includes evidence screenshots, load test result links, and a summary suitable for sharing with engineering leadership and investors.

Know Your Scaling Ceiling

Book a free 30-minute capacity scope call with our load testing engineers. We review your architecture, traffic expectations, and upcoming scaling events — and scope the load test that will give you the data you need.

Talk to an Expert