AWS Fault Injection Service vs Krkn
AWS Fault Injection Service
aws.amazon.comKrkn
krkn-chaos.devSide by side
| Figure | AWS Fault Injection Service | Krkn |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 1 | 1 |
| Spec score · Chaos Engineering Platforms | 8.2 (#6) | 8.5 (#5) |
| Integrations | FIS can be accessed through the AWS Management Console, CLI, SDKs, CloudFormation, and HTTPS API, and its APIs can be used in CI/CD pipelines and custom tooling. | The documentation describes integrations with Prometheus, Elasticsearch, Grafana, Slack, S3, and CI/CD systems such as Jenkins and GitHub Actions. |
| Monitoring | FIS supports Amazon CloudWatch metrics for monitoring experiments and shows experiment progress and action details through its console and APIs. | Cerberus monitors Kubernetes and OpenShift health and exposes a go/no-go signal, reports, and a metrics API. |
| Purpose | AWS FIS runs fault injection experiments on AWS workloads to help teams improve application performance, observability, and resilience. | Krkn injects deliberate failures into Kubernetes clusters to test their resilience. |
| Rollback | FIS supports automatically rolling back or stopping an experiment when specified conditions are met. | Krkn’s rollback system persists changes to the filesystem before a scenario so it can restore targeted Kubernetes objects or subsystems. |
Plans
AWS Fault Injection Service
- AWS Fault Injection Service$0.10, paid once
In their own words
AWS Fault Injection Service
AWS Fault Injection Service has no write-up on Specifiction yet; its figures are above.
Krkn
Krkn injects deliberate failures into Kubernetes clusters so teams can examine resilience under disruption. Its 20-plus scenarios cover pods, containers, nodes, networks, applications, resources, storage and time. The recommended krknctl command-line tool discovers, runs and coordinates scenarios; other choices include pre-built containers, a browser dashboard and a standalone Python program. Krkn evaluates Prometheus metrics against SLO pass/fail criteria and can review metrics during and after scenarios. Dashboard integrations include Elasticsearch and Grafana, and telemetry can be sent to S3 or Elasticsearch. Cerberus monitors Kubernetes and OpenShift health, providing a go/no-go signal, reports and a metrics API; it can also report failures in Slack. Krkn-AI uses evolutionary algorithms against user-defined objectives to identify experiments. Krkn says it saves recovery state and can restore a cluster, but some disruptive scenarios may leave the target unrecoverable. It is intended for resilience measurement, not security provision, and does not currently adhere to compliance standards. Requirements include Kubernetes or OpenShift 1.21+, cluster-admin kubeconfig access, and Docker 20.10+ or Podman 4.0+.