How do you protect revenue and reputation when your platform is under pressure?
Turn performance risk into evidence: run repeatable load campaigns, quantify supported load vs. infrastructure size, and forecast operational cost with confidence – without “guess-and-overprovision.”
Can you make a go/no-go release decision with confidence?
Platforms fail under load in ways that only appear when every layer is stressed at once. By the time a peak event exposes the gap, the cost is real — and already paid.
Poor performance isn’t just technical – it’s a business liability. Here’s how QALIPSIS helps leaders make smarter, faster, and safer decisions.
What will your platform do when a million users arrive at once?
- A salary-day surge, a flash sale, a product launch — every predictable high-traffic event can expose weaknesses invisible at normal volumes. By the time an incident is declared, the damage is done: sessions dropped, transactions abandoned, support queues flooded, and engineering pulled away from roadmap work.
- QALIPSIS runs load campaigns that reproduce the exact traffic shape of those events — steep ramp-up, sustained maximum, tail-off — across the full system stack. Scenarios validate API availability, messaging throughput, and data consistency simultaneously, so a bottleneck anywhere in the chain surfaces before it reaches real users.
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Why does it take days to find which service caused the incident?
- When a performance incident surfaces, the first question is always which service caused it. Without precise data from a load run that mirrors production conditions, the investigation is archaeology — combing through logs and metrics from a system already under distress, with engineers spending days narrowing down what went wrong where.
- QALIPSIS captures events and meters at the exact point in the scenario where failures occur, tagged by campaign, scenario, step, and zone. Results are accessible via the GUI or REST API, giving teams a precise starting point for resolution rather than a full-system audit.
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How many releases shipped without a real performance check?
- Performance testing tends to become the gate that holds releases hostage: it runs late in the cycle, takes days to complete, and produces results that are hard to act on under pressure. Skipped once, it gets skipped again — and risk accumulates silently across releases until something breaks in production.
- QALIPSIS scenarios live alongside application code and execute automatically through CI/CD pipelines. Smoke tests run on every build; full load suites run on a nightly or weekly schedule. Any breach of an assertion threshold fails the build automatically with a report identifying exactly what failed and where — quality gates enforced without a manual step.
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Are you overprovisioning because the last peak scared you?
- Infrastructure spending is often driven by incident memory. Teams overprovision defensively after a difficult peak, or underprovision and discover the limit in production. Neither approach produces a clear answer to how much infrastructure is actually needed for the next growth step — or what the cost of that headroom will be.
- Repeatable load campaigns under progressively increasing load produce concrete correlation between infrastructure configuration and supported concurrent capacity. Cluster mode scales load injection by adding factory nodes, making it possible to test at the scale you plan to operate before committing to the infrastructure cost.
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Why are users in some regions converting less than others?
- A service deployed in a single region adds latency for every user outside that geography — and that latency shows up as session abandonment and conversion drop, not as an error anyone reports. The problem accumulates quietly until it is large enough to be visible in business metrics, long after the architectural decision that caused it.
- Factories can be deployed in the zones your organisation controls and assigned zone eligibility. Campaigns distribute load across zones and export metrics tagged by zone, giving teams visibility into regional performance differences under realistic concurrent load — before they affect customers.
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QALIPSIS: Built for bold businesses that scale
With QALIPSIS, you can:
Prevent downtime before it happens
Optimize customer experience with real-time insights
Scale infrastructure cost-effectively
Ensure readiness for global markets
Advanced analysis dashboards
What you need to know
What QALIPSIS lets you do: Execute load campaigns that validate behavior (latency, failure rates, availability, data consistency) under pressure, using scenarios and assertions that represent real business flows.
What QALIPSIS lets you do: Reproduce realistic peak-traffic patterns using built-in execution profiles – staged ramp-ups, accelerating injection, progressing volume, or fully custom curves – so you can model the exact load shape you expect in production.
Within those scenarios, verify steps assert latency budgets, response correctness, and data consistency per minion under load. Assertion failures are captured as distinct events in the campaign report, giving you a clear, per-step breakdown of what degraded and where.
Export events and meters to your observability stack to correlate QALIPSIS findings with your own infrastructure telemetry. The result is a documented, repeatable verdict on your system’s peak readiness – run it on demand or schedule it before every release.
What QALIPSIS lets you do: Run load and E2E scenarios as regular Gradle tasks inside your existing CI/CD pipeline – with ready-made examples for Jenkins, GitHub Actions, GitLab CI/CD, and Travis CI. Autostart mode executes campaigns eagerly and tears down all nodes on completion, so pipelines stay clean.
QALIPSIS produces JUnit-compatible XML reports that CI platforms can consume for pass/fail gating, plus optional email notifications filtered by campaign status (successful, failed, warning).
Campaigns can also be scheduled via the REST API on hourly, daily, or monthly cadences for recurring regression runs outside the release cycle. The result is a repeatable performance gate that runs unattended alongside your existing build and deploy steps.
What QALIPSIS lets you do: Monitor and manage campaigns via GUI or REST API and access campaign reports (results, execution time, errors). Live reporting can provide real-time progress/results before your test ends.
What QALIPSIS lets you do: Run QALIPSIS through CI/CD workflows using Gradle tasks (examples exist for common CI systems). Tests can be executed nightly to keep the feedback loop short and not alter your teams velocity.
What QALIPSIS lets you do: Run repeatable load campaigns with configurable injection profiles (staged ramp-ups, accelerating volume, custom curves) and runtime tuning via minion-count and speed-factor overrides – so you can systematically sweep across load levels without rewriting scenarios.
In cluster mode, you scale injection capacity itself by adding factory nodes dynamically; factories can be geographically distributed across zones to simulate realistic traffic origins.
Campaign reports capture per-scenario and per-step success/failure counts, while exported events and meters let you correlate QALIPSIS load data with your own infrastructure telemetry.
Schedule campaigns on recurring cadences to track how capacity thresholds shift over time as your system evolves. The result is a documented, reproducible mapping between load levels and system behavior that turns provisioning from guesswork into data-driven decisions.
What QALIPSIS lets you do: Deploy factories in zones you control and configure zone eligibility so campaigns can run across eligible factories.