We started noticing something in 2017
Most businesses couldn't actually tell if their systems were ready for real traffic.
A colleague of mine spent three weeks preparing for a product launch. Everything looked perfect in staging. Then launch day came and the site buckled under 200 concurrent users.
That pattern kept repeating. Companies would invest heavily in development but treat performance testing as an afterthought—something you do the week before going live, if there's time.
So we built Connectlogicpro around a different approach. Performance isn't a checkbox at the end. It's information you need throughout development to make better decisions about architecture, caching strategies, database queries.
Our team works from Taipei, and we've spent the past eight years testing systems across finance, e-commerce, and SaaS platforms. We've seen what breaks systems and what makes them resilient when traffic spikes hit.
What Actually Guides Our Work
Test Like Users Behave
We don't just hammer servers with uniform load. Real users browse, abandon carts, come back hours later, hit the same endpoint repeatedly when something breaks.
For an online retailer in 2024, we discovered their checkout failed specifically when users toggled between payment methods—something their previous load tests never caught.
Show the Full Picture
A test report that just says "system handled 1,000 users" tells you almost nothing. What were response times? Where did memory spike? Which database queries slowed down?
We provide timeline visualizations that show exactly when and where bottlenecks appear. One client found their API gateway was the issue, not their application servers—saved them from scaling the wrong infrastructure.
Build Knowledge Transfer
We're not interested in being the only people who understand your system's performance characteristics. Your team should learn to run these tests and interpret results.
After working with a fintech company for six months, their DevOps team now runs performance tests before every major release. They catch issues in staging that used to reach production.
Respect Development Constraints
We've worked in startups and enterprises. Sometimes the "right" architectural solution isn't realistic given timeline or budget. So we focus on improvements you can actually implement.
A SaaS platform couldn't rebuild their monolith, but they could add Redis caching to their most-hit endpoints. Response times dropped by 60% in two weeks.
Plan for Actual Traffic
Your system doesn't need to handle a million users if you're expecting 50,000. But it should handle those 50,000 comfortably with headroom for growth.
We helped an e-commerce site prepare for their annual sale. Rather than over-provisioning servers, we identified and fixed three specific bottlenecks. Their infrastructure costs stayed flat while handling 3x normal traffic.
Results From Recent Client Work
These numbers represent actual client projects from 2024 through early 2025. Most engagements start with a baseline assessment—we map current performance, identify bottlenecks, then work iteratively on improvements.
The 73% improvement varies significantly by system. Some clients see dramatic gains from database query optimization. Others benefit more from caching strategies or infrastructure adjustments. What matters is finding the specific constraints in your architecture.
Our retention rate reflects the ongoing nature of performance work. As your traffic grows and features change, new bottlenecks emerge. Most clients schedule quarterly testing cycles to stay ahead of issues.
How Our Team Actually Works
Henrik Torvalds leads our performance engineering team. Before joining us in 2019, he spent six years at a payment processor debugging why their system would randomly slow down during high-volume periods.
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Start with Questions
We don't assume we know your bottlenecks. First calls are about understanding your architecture, traffic patterns, and what you've already tried. Sometimes clients have done extensive optimization—we build on that rather than starting over.
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Test in Stages
Throwing maximum load at a system immediately doesn't reveal much. We gradually increase traffic while monitoring dozens of metrics. This shows exactly where and when things start degrading—which tells you what to fix first.
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Explain Trade-offs
Every optimization has costs. Caching improves speed but adds complexity. Horizontal scaling increases throughput but raises infrastructure expenses. We explain these trade-offs so you can make informed decisions based on your priorities.
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Document Everything
You shouldn't need us to understand test results. We provide detailed documentation of methodology, findings, and recommendations. Several clients use these reports as internal training materials for their engineering teams.