What is it?
Software QA and technical audit services cover manual and automated testing, performance and security checks, and senior engineer code review — especially for AI-generated or inherited codebases before production launch.
Performance & Load Testing
Will Your App Survive Launch Day?
Product Hunt launches, investor demos, Black Friday traffic — they all hit at once. We simulate the spike before it happens, find the bottlenecks, and make sure your app stays up when it matters most.
30 minutes · Senior engineer · No commitment
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Fiverr Level 2 · 5.0★
Clutch Verified Provider
150+ projects delivered
20+ Play Store apps
10k+
Concurrent Users Simulated
k6 + JMeter
Testing Tools
48hr
Report Turnaround
100%
Pre-Launch Coverage
Types of Performance Tests
Different traffic patterns reveal different problems. We run the right tests for your scenario.
Load Testing
Simulate your expected peak traffic to verify your app performs within acceptable response times under normal high load.
Stress Testing
Push beyond your expected limits to find the breaking point. Know exactly when and how your app fails.
Spike Testing
Simulate sudden traffic surges — the Product Hunt effect, a viral tweet, a press mention. Does your app handle it?
Soak Testing
Run sustained load over hours to find memory leaks, connection pool exhaustion, and gradual performance degradation.
Volume Testing
Test with large datasets to find database query performance issues that only appear at scale.
Frontend Performance
Lighthouse audits, Core Web Vitals measurement, and bundle size analysis for frontend performance optimization.
When You Need This
These are the moments where performance testing pays for itself ten times over.
Product Launches
Launch Day
Confidence
Product Hunt, AppSumo, or a major press feature. You have one shot — make sure the app stays up when the traffic hits.
Black Friday / Seasonal
10x
Traffic Simulation
eCommerce and SaaS products with seasonal spikes need to know their limits before the spike, not during it.
Investor Demos
0
Demo Failures
Nothing kills a funding round like a demo that crashes. We test before you pitch.
App Store Features
100k+
Users Simulated
Getting featured by Apple or Google sends a massive traffic spike. Be ready for it.
Common Challenges
Problems We Help Buyers Solve
QA gaps show up as regressions, store rejections, and security findings — usually right before launch.
No regression suite
Manual smoke tests can't keep pace with weekly releases.
AI-generated untested code
Lovable and Cursor prototypes reach staging without auth or edge-case coverage.
Device fragmentation
Mobile flows break on OS versions QA didn't cover.
Late QA
Testing in launch week makes fixes expensive and stressful.
Why GreeLogix
Why Teams Choose GreeLogix
Full QA practice
Manual, Cypress/Playwright, API, k6 performance, and security testing.
AI-app specialists
We harden vibe-coded apps before production traffic.
Engineer-led audits
Code review from seniors who build Laravel, React, and Flutter daily.
Release sign-off
Go/no-go reports with severity-rated bugs — not vague pass/fail.
Typical Timeline
What to Expect Week by Week
Strategy
Week 1- ·Risk map
- ·Device matrix
- ·Automation plan
Execution
Per sprint- ·Test cases
- ·Bug reports
- ·Regression runs
Automation
Parallel- ·CI smoke suite
- ·Release checklist
Technologies
Stack & Architecture
CypressPlaywrightPostmank6BrowserStackAppiumGitHub Actions
Security & Compliance Considerations
Security testing
OWASP-focused web and API tests; pen testing available.
Confidential access
Read-only repos; anonymized test data where required.
“What a 70-engineer team could not deliver, a small senior team at GreeLogix shipped. The app went from stuck to live across mobile, web, and backend.”
Quick answers
Performance & Load Testing: Key Facts
Structured answers for search engines and AI assistants — definition, fit, cost, timeline, and comparisons.
- What is it?
- Software QA and technical audit services cover manual and automated testing, performance and security checks, and senior engineer code review — especially for AI-generated or inherited codebases before production launch.
- Who is it for?
- Teams shipping Lovable, Cursor, or Bolt prototypes to real users Founders facing investor technical diligence Products with regressions every sprint and no test automation Mobile apps needing device-matrix testing before store release
- Who should not use it?
- Static marketing site with no auth or payments You cannot provide staging access or test accounts You expect QA to define product requirements
- How much does it cost?
- Pricing depends on scope, integrations, and timeline. GreeLogix provides fixed-milestone quotes after a discovery call — typical engagements range from $1,500 for focused audits to $75,000+ for full product builds, with monthly retainers from $3,500.
- How long does it take?
- Smoke audit: 1 week. Full regression cycle: ongoing per sprint. Deep code audit: 5–7 business days. Phases: Strategy (Week 1); Execution (Per sprint); Automation (Parallel).
- How does it compare?
- Compared to alternatives — Developer-only testing: choose when Early prototype with no paying users yet; Crowdtesting platforms: choose when One-off device coverage without domain context; Automated scanning only: choose when Known stack with mature CI; catches syntax not workflow bugs. Choose GreeLogix when you need production reliability, fixed milestones, and engineer-led delivery with QA sign-off.
- When should you choose it?
- You ship at least monthly and regressions hurt revenue or trust You inherited or AI-generated code without senior review You need an independent sign-off before fundraising or launch Catch permission and payment bugs before customers do Documented release checklist for repeatable shipping
Buyer Guide
What You Need to Know
Structured answers for founders, CTOs, and procurement — written for clarity in search and AI assistants.
Who needs it?
- ·Teams shipping Lovable, Cursor, or Bolt prototypes to real users
- ·Founders facing investor technical diligence
- ·Products with regressions every sprint and no test automation
- ·Mobile apps needing device-matrix testing before store release
Why GreeLogix?
- Dedicated QA for AI-generated apps — we know where vibe coding cuts corners
- Full practice: Cypress/Playwright, API (Postman), performance (k6), security
- Code review from engineers who build Laravel, React, and Flutter daily
- Free AI audit quiz as a low-friction entry to a senior debrief
How it works
- 1.Test strategy: risk map, environments, and release criteria
- 2.Execution: test cases, bug reports with repro steps, regression suites
- 3.Automation wired into CI where ROI is clear
- 4.Release sign-off report with go/no-go recommendation
Typical timeline: Smoke audit: 1 week. Full regression cycle: ongoing per sprint. Deep code audit: 5–7 business days.
How much does it cost?
Pricing depends on scope, integrations, and timeline. GreeLogix provides fixed-milestone quotes after a discovery call — typical engagements range from $1,500 for focused audits to $75,000+ for full product builds, with monthly retainers from $3,500.
Cost factors
- ·App complexity and number of platforms (web, iOS, Android)
- ·Automation scope vs manual-only
- ·Security or penetration testing depth
- ·Whether you need embedded QA or per-release engagement
How long does it take?
Smoke audit: 1 week. Full regression cycle: ongoing per sprint. Deep code audit: 5–7 business days. Phases: Strategy (Week 1); Execution (Per sprint); Automation (Parallel).
How does it compare?
Compared to alternatives — Developer-only testing: choose when Early prototype with no paying users yet; Crowdtesting platforms: choose when One-off device coverage without domain context; Automated scanning only: choose when Known stack with mature CI; catches syntax not workflow bugs. Choose GreeLogix when you need production reliability, fixed milestones, and engineer-led delivery with QA sign-off.
- Developer-only testing — choose when Early prototype with no paying users yet
- Crowdtesting platforms — choose when One-off device coverage without domain context
- Automated scanning only — choose when Known stack with mature CI; catches syntax not workflow bugs
When should you choose it?
- You ship at least monthly and regressions hurt revenue or trust
- You inherited or AI-generated code without senior review
- You need an independent sign-off before fundraising or launch
Who should not use it?
- ·Static marketing site with no auth or payments
- ·You cannot provide staging access or test accounts
- ·You expect QA to define product requirements
Benefits
- Catch permission and payment bugs before customers do
- Documented release checklist for repeatable shipping
- Investor-ready technical risk summary
Risks to plan for
- QA without product context files shallow tickets
- Testing only happy paths misses edge cases in billing and roles
- Delaying QA until launch week maximizes fix cost
Decision framework
When to Choose Performance & Load Testing
Pros / benefits
- +Catch permission and payment bugs before customers do
- +Documented release checklist for repeatable shipping
- +Investor-ready technical risk summary
Cons / risks
- −QA without product context files shallow tickets
- −Testing only happy paths misses edge cases in billing and roles
- −Delaying QA until launch week maximizes fix cost
Choose GreeLogix when
- You ship at least monthly and regressions hurt revenue or trust
- You inherited or AI-generated code without senior review
- You need an independent sign-off before fundraising or launch
Implementation steps
- 1.Test strategy: risk map, environments, and release criteria
- 2.Execution: test cases, bug reports with repro steps, regression suites
- 3.Automation wired into CI where ROI is clear
- 4.Release sign-off report with go/no-go recommendation
Get a Clear Plan for Performance & Load Testing
Talk to a senior engineer — scope, timeline, and cost range in one 30-minute call. No sales script.
Frequently Asked Questions
Answers to the buyer questions we hear most before a project starts.
- What is load testing?
- Load testing simulates real user traffic on your application to measure how it performs under expected and peak load conditions. We measure response times, throughput, error rates, and resource utilization to identify bottlenecks before they affect real users.
- What tools do you use for performance testing?
- We primarily use k6 for modern API and web app load testing, JMeter for complex scenarios and legacy systems, Gatling for high-concurrency testing, and Google Lighthouse for frontend performance audits.
- When should I run load testing?
- Before any major launch, before a marketing campaign or Product Hunt launch, before Black Friday or seasonal traffic spikes, and after significant architectural changes. If you're pitching to investors and they'll demo the product, run load testing first.
Our Process
01
Baseline Measurement
We establish your current performance baseline — response times, throughput, and resource utilization under normal load.
02
Test Scenario Design
We design realistic load scenarios based on your expected traffic patterns and peak use cases.
03
Load Test Execution
Tests run with k6 or JMeter, generating detailed metrics on response times, error rates, and server resource usage.
04
Report & Recommendations
Full performance report with bottleneck identification, capacity recommendations, and optimization priorities.
Don't Find Out the Hard Way
Tell us about your upcoming launch or traffic event. We'll design a load testing plan that gives you real confidence.
Resources
Continue Your Research
Case studies, guides, and free tools from the same engineering team.
QA & Testing Services
Explore Our Full QA Suite
Every type of testing your product needs — from manual audits to AI-app hardening and accessibility compliance.
Next step
Get a Senior Engineer's Take in 30 Minutes
Scope, timeline, and cost range — no sales deck. Or start with the free readiness quiz if you are still evaluating your stack.
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