Performance work
done with precision
Coredev Nexus works with organizations that need reliable answers about how their systems behave under pressure — not estimates, not assumptions.
Founded in 2024, we focus specifically on performance testing and optimization, treating it as an engineering discipline rather than a checkbox step before release.
Three principles that shape every engagement
Performance problems rarely have a single cause. Our work is structured to find the actual bottleneck, not the nearest one.
Measurement before opinion
Every engagement begins with instrumented baselines. We capture response times, throughput, error rates, and resource curves under defined load profiles before drawing any conclusions about where problems exist.
Root cause, not symptom
Slow response times are a symptom. The cause might be a missing index, a blocking query, an undersized connection pool, or a cascade of synchronous calls. We trace the chain rather than patching the surface.
Transferable findings
Deliverables are written for engineers, not executives. Every report includes reproducible test scripts, annotated profiler output, and specific code or configuration changes — not generic recommendations.
Specialists who work on one thing
Teodor Vaszilenko leads our performance engineering practice. His background spans distributed systems, database query planning, and JVM tuning across financial and logistics platforms. He joined Coredev Nexus to build a team focused exclusively on performance — not as a feature of a broader consulting offer, but as the entire practice.
The rest of the team comes from infrastructure, backend development, and QA automation backgrounds. Each person was chosen because they had already done performance work seriously in a previous role, not because they were willing to learn it here.
What working with us actually looks like
Most engagements follow a consistent four-stage structure. The scope of each stage depends on what we find, not on a predetermined timeline.
Environment and baseline audit
We review your stack, deployment configuration, and existing monitoring. Then we run controlled load scenarios to establish a documented baseline — what the system does under normal and elevated traffic before any changes.
Profiling and bottleneck identification
With baseline data in hand, we run targeted profiling sessions. This means flame graphs, slow query logs, thread dumps, and memory allocation traces — whatever the runtime requires to expose where time and resources are actually spent.
Optimization and verification
Changes are implemented incrementally and re-tested after each one. We do not batch all optimizations and re-run at the end — that approach makes it impossible to attribute improvements to specific changes.
Handoff and documentation
You receive the full test suite, profiling artifacts, a written report with numbered findings, and a runbook for reproducing the tests independently. The goal is that your team can continue without us.
| Deliverable | Format | Who uses it | Typical size |
|---|---|---|---|
| Performance baseline report | PDF + raw data export | Engineering leads, architects | 15–30 pages |
| Load test script suite | k6 or Gatling scripts in Git repo | QA engineers, DevOps | Varies by scenario count |
| Bottleneck findings log | Numbered markdown document | Backend developers | 8–20 findings |
| Monitoring runbook | Grafana dashboard + annotations | On-call engineers | Deployed to your instance |
| Post-optimization comparison | Side-by-side metric charts | All stakeholders | 4–8 pages |