Zero-Risk Infrastructure Chaos Engineering
Prove your system's availability ceiling mathematically — without touching production.
Existing chaos tools inject real faults into your infrastructure.
FaultRay uses pure mathematical simulation.
Six pillars of zero-risk chaos engineering
Network, process, resource, dependency, and latency chaos engines powered by Monte Carlo, Markov chains, and queuing theory.
From single-node failures to cascading multi-region outages. Every scenario is generated from your topology YAML.
The only tool that separates Software, Hardware, and Theoretical limits to reveal your true availability ceiling.
Claude-driven root cause analysis and actionable improvement recommendations ranked by impact and cost.
Generate audit-ready Digital Operational Resilience Act reports with evidence trails and risk assessments.
Automatically incorporate CVE data and NVD feeds to simulate vulnerability-triggered cascading failures.
FaultRay takes a fundamentally different approach
| Recommended FaultRay | Gremlin | Steadybit | AWS FIS | |
|---|---|---|---|---|
| Approach | Mathematical Simulation | Real Fault Injection | Real Fault Injection | Real Fault Injection |
| Production Risk | Zero | High | Medium | High |
| Setup Time | 5 minutes | Days | Hours | Hours |
| Scenarios | 150+ auto-generated | Manual configuration | Template-based | AWS services only |
| Availability Proof | 3-Layer Mathematical | No | No | No |
| Starting Cost | Free / OSS | $10,000+/yr | $5,000+/yr | Pay per use |
The only tool that proves your availability ceiling
Mathematical upper bound assuming perfect software and ideal hardware
Constrained by physical components: disk MTBF, network gear, power systems
Your actual ceiling: deploy pipelines, config errors, dependency failures
Most teams chase hardware nines while their software layer caps availability at 4 nines. FaultRay reveals exactly where your bottleneck lives so you invest in the right layer.
faultray analyze --topology infra.yaml --output 3-layer
From zero to availability proof in 3 steps
$ pip install faultraytopology:
name: my-saas-platform
regions:
- name: us-east-1
zones: [a, b, c]
services:
- name: api-gateway
replicas: 3
dependencies: [auth, database]
- name: auth
replicas: 2
dependencies: [database, cache]
- name: database
type: rds-multi-az
replicas: 2
- name: cache
type: elasticache
replicas: 3$ faultray run --topology infra.yaml --scenarios all
Running 152 scenarios across 5 engines...
Completed in 8.3s | Pass: 147 | Fail: 5
$ faultray report --format html --output report.html
Report saved: report.html
$ faultray dashboard
Dashboard running at http://localhost:8550Start free. Scale as you grow.
Perfect for individual engineers and open source projects.
For engineering teams that need collaboration and CI integration.
For organizations needing AI analysis and compliance reports.
For enterprises with strict compliance and security requirements.