Eliminate performance bottlenecks and design an architecture that grows with your business, before your next traffic spike becomes an outage.
The root cause of fragility is rarely a single bottleneck. It's an architecture designed for a different scale than the one you're at now.
Instrumented profiling and load simulation identify the bottlenecks the data reveals, not the ones the team suspects. You get a ranked list of real constraints.
Before adding infrastructure, we extract maximum performance from what you already have, typically 3–5× throughput improvement without changing your deployment topology.
With the low-hanging fruit captured, we design horizontal scaling for the next growth phase, implemented incrementally, load-tested at every stage, handed off with runbooks.
Current throughput, latency percentiles, and resource utilisation under realistic load. A ranked bottleneck inventory with measured impact on each one.
ReportA documented caching architecture covering application-level caching, HTTP headers, CDN, and invalidation patterns, designed for your specific data access patterns.
StrategyTarget architecture diagram with read/write separation, horizontal scaling policies, queue-based decoupling, and IaC templates, sized for 18–24 months of growth.
BlueprintBefore/after comparisons across baseline, post-optimisation, and post-scaling. Scripts and infrastructure included, so your team can re-run tests every release.
BenchmarkHorizontal scaling of what you already have, almost always. Microservices are a last resort, they introduce their own operational cost. Most teams get the throughput they need from caching, query optimisation, and stateless app tiers.
Usually yes. We design cloud-agnostic patterns but optimise for your existing provider first, a migration is rarely the shortest path to throughput.
Session state moves to a distributed store (Redis, Valkey) as part of the stateless tier work. Uploads go through S3-compatible object storage with signed URLs, no instance-local storage.
We address that in the Optimise phase before touching app-tier scaling. Query tuning, indexing, read replicas, and caching buy huge runway. Sharding is only considered when the data model genuinely requires it.
Profiling takes 1–2 weeks. Most clients see a measurable throughput improvement within 4–6 weeks of the optimise phase starting, well before any new infrastructure is added.