You're probably here because your mobile roadmap suddenly got bigger than your team. Maybe product wants a new customer app before peak season. Maybe your operations team needs a field app that works offline. Maybe leadership now expects AI inside the app too,...
Your team probably already has the ingredients for AI. A web app that creaks a little under peak load. A mobile app with decent engagement but too many support tickets. A back office full of spreadsheets, rules, approvals, and “we'll fix that later” workflows....
Load testing applies a controlled, expected workload to a system to see whether it can sustain normal and peak demand while meeting latency, throughput, and stability objectives. In practice, teams judge it with concrete signals like p50, p95, and p99 response times,...
You've added servers, hired another squad, and still watched response times climb while releases become harder to coordinate. The product works for its original audience, but every new market, integration, workflow, or AI feature adds another gear to the machine....
Your software product is doing well. A few customers have become many, each with its own users, settings, permissions, integrations, and expectations. The uncomfortable question arrives when the original deployment model starts to strain: should every customer receive...
Your team has shipped the new customer portal, connected several internal APIs, added a mobile companion app, and given a language model access to business data. The login works, the CI pipeline is green, and the demo looks polished. Then a user changes an object ID...
