ACCELERATOR · TOOLING

Performance & FMEA Suite

Quantify system limits and failure modes before production discovers them for you.

An integrated performance-testing and failure-mode-and-effects-analysis toolkit that combines load generation, chaos experimentation and structured risk assessment into a single repeatable process. Built for teams operating in regulated industries where capacity planning and resilience evidence are not optional.

provenAvailable

Key Features

Scenario-Based Load Testing

Parameterised load-test suites modelling real-world traffic patterns including peak-day surges, batch overlaps and gradual ramp profiles, executable from CI/CD or on demand.

Chaos and Fault-Injection Experiments

Pre-built experiment packs for common failure scenarios such as dependency latency injection, pod eviction, zone failover and message queue back-pressure, integrated with safety abort conditions.

FMEA Risk Register

Structured failure-mode-and-effects-analysis templates that link identified risks to specific services, quantify severity and detection scores and track mitigation actions through to resolution.

Capacity and Resilience Reporting

Automated generation of capacity-planning reports and resilience evidence packs suitable for architecture review boards, regulators and operational-readiness assessments.

Use Cases

Pre-launch resilience assurance for a core-banking migration

Banking

Executed 14 failure scenarios and sustained-load tests across the end-to-end payment path, producing evidence that satisfied the bank's operational-readiness gate and PRA expectations.

Capacity planning for a Black Friday-scale retail platform

Retail

Modelled 10x traffic surges across checkout, inventory and payment services, identifying three auto-scaling bottlenecks that were resolved before the peak trading window.

FMEA-driven architecture review for a trading platform

Capital Markets

Conducted a structured FMEA across 22 services, identifying eight single-points-of-failure and producing a prioritised remediation roadmap adopted by the architecture review board.

Technical Stack

k6 / GatlingChaos Toolkit / Litmus ChaosGrafanaPrometheusTerraformPython

Deliverables

  • →
    Load-test suite and traffic profiles(k6 scripts and configuration)
  • →
    Chaos experiment library(Chaos Toolkit experiments and safety policies)
  • →
    FMEA risk register(Structured spreadsheet and linked Jira issues)
  • →
    Capacity and resilience evidence pack(PDF report and supporting data)

Expected Programme Outcomes

Time

4–8 weeks

saved on load-test and FMEA setup

Time

50–70%

faster capacity validation cycles

Risk & Compliance

45–65%

fewer undetected failure modes

Cost

3–6 months

of testing rework avoided

Cost

65–75%

faster capacity planning decisions

Prerequisites

  • →Non-production environment representative of production topology
  • →Observability stack in place (metrics, logs and traces)
  • →Identified critical user journeys or transaction flows to test

Proven in

Case studies that used this accelerator.

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