Amazon Fault Injection Simulator
AWS Fault Injection Simulator (FIS) is a fully managed service for running fault injection experiments on AWS. It allows you to improve an application's performance, observability, and resiliency by identifying and fixing weaknesses through controlled chaos engineering experiments.
Solid contracts, transparent operations, and an easy start — typically complete on four or five facets with one clear soft spot.
API Evangelist profiles Amazon Fault Injection Simulator the way a machine reads it — 71 machine-readable artifacts across 6 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Amazon Fault Injection Simulator scores 69.4/100 (strong), with a separate agent-readiness read of 48/100 (agent ready). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Amazon Fault Injection Simulator
Each block below is one kind of artifact we hold for Amazon Fault Injection Simulator. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 6
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
Amazon Fault Injection Simulator Actions API
Discover available FIS fault injection actions
Amazon Fault Injection Simulator Experiment Templates API
Create and manage fault injection experiment templates
Amazon Fault Injection Simulator Experiments API
Start, stop, and monitor fault injection experiments
Amazon Fault Injection Simulator Safety Levers API
Manage safety levers for experiment control
Amazon Fault Injection Simulator Tagging API
Manage tags on FIS resources
Amazon Fault Injection Simulator Target Resource Types API
Discover available target resource types
Postman Collections 1
A runnable collection turns the contract into something a developer can execute in seconds. We profile them because the fastest way to trust an API is to make a real call against it.
Ready-to-run Postman collections for exercising this provider's APIs.
Open Collections 1
Open, tool-agnostic collections carry the same runnable value as Postman without locking you to one client — the portable, forkable form of the same exercise.
Open, tool-agnostic API collections (OpenAPI-derived and Bruno).
AWS Fault Injection Simulator API
OPEN COLLECTIONArazzo Workflows 7
Real integrations are rarely a single call. Arazzo describes the multi-step sequences — auth, then create, then confirm — so both a human and an agent can follow the choreography, not just the endpoints.
Multi-step API workflows described with the Arazzo specification.
AWS FIS Discover Action Detail
List the available FIS actions and fetch the full detail of the first action returned.
ARAZZOAWS FIS Discover Target Resource Type
List the supported target resource types and fetch the full detail of the first one returned.
ARAZZOAWS FIS Find and Stop Running Experiment
List experiments for a template, and if the first one is still active, stop it and confirm the stop.
ARAZZOAWS FIS List Then Get Experiment Template
List experiment templates and fetch the full definition of the first one returned.
ARAZZOAWS FIS Run Experiment to Completion
Create an experiment template, start an experiment from it, and poll until the experiment reaches a terminal state.
ARAZZOAWS FIS Start Then Stop Experiment
Start an experiment from an existing template, confirm it is running, stop it, and poll until it is fully stopped.
ARAZZOAWS FIS Update Template Then Run
Fetch an existing experiment template, update its description, and start an experiment from the revised template.
ARAZZOScroll within the panel for all 7 ·
Pricing Plans 1
Pricing is part of the interface. Machine-readable plans tell you what a tier costs and includes before you commit — one of the six things the Kin Score reads for commercial clarity.
Published pricing tiers and plan structures.
Rate Limits 1
Rate limits are the difference between a demo that works and a production integration that doesn't fall over. Publishing them is an operational-transparency signal — and a hard requirement for any agent that plans its own throughput.
Documented rate limits and quota policies.
Amazon Fault Injection Simulator Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals let a buyer model the financial operations of an API before it's live. We profile them for the same reason we profile pricing: the money is part of the contract.
Cost, billing, and metering signals for API financial operations.
Features 8
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Managed Fault Injection
Fully managed service requiring no agent installation with pre-built fault injection actions for EC2, RDS, ECS, EKS, and more.
Pre-built Scenarios
Ready-to-use resilience scenarios for AZ failures, power interruptions, network disruptions, and cross-region connectivity issues.
Safety Controls
CloudWatch alarm-based stop conditions and safety levers prevent unintended impact during live testing.
Fine-grained Targeting
Tag-based resource targeting scopes experiments to specific environments, applications, or resource subsets.
Multi-account Support
Run experiments across multiple AWS accounts using target account configurations.
CI/CD Integration
API and CLI access enables automated resilience testing in deployment pipelines.
Real-time Visibility
Console and API provide real-time status of executing actions, affected resources, and triggered stop conditions.
IAM Security
Fine-grained IAM controls restrict which users can create, run, or view experiments and affected resources.
Scroll within the panel for all 8 ·
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Amazon Fis Context
JSON-LDSpectral Rules 3
Governance rulesets we run against this provider's specs — the automated checks behind parts of the score. Profiling them makes the quality bar explicit and re-runnable, not a matter of opinion.
JSON Schema 10
Standalone JSON Schema definitions describe the data models behind the API. We profile them so the shapes are validatable on their own — useful long after a single request is forgotten.
Standalone JSON Schema definitions for this provider's data models.
Action
JSON SCHEMAExperiment
JSON SCHEMAExperimentState
JSON SCHEMAExperimentTemplateAction
JSON SCHEMAExperimentTemplate
JSON SCHEMAExperimentTemplateStopCondition
JSON SCHEMAExperimentTemplateTarget
JSON SCHEMASafetyLever
JSON SCHEMASafetyLeverState
JSON SCHEMATargetResourceType
JSON SCHEMAScroll within the panel for all 10 ·
JSON Structure 10
JSON Structure captures the data shapes in a form built for tooling — a complement to JSON Schema that keeps the model machine-legible.
JSON Structure definitions describing this provider's data shapes.
Amazon Fis Action Structure
JSON STRUCTUREAmazon Fis Experiment State Structure
JSON STRUCTUREAmazon Fis Experiment Structure
JSON STRUCTUREAmazon Fis Experiment Template Action Structure
JSON STRUCTUREAmazon Fis Experiment Template Stop Condition Structure
JSON STRUCTUREAmazon Fis Experiment Template Structure
JSON STRUCTUREAmazon Fis Experiment Template Target Structure
JSON STRUCTUREAmazon Fis Safety Lever State Structure
JSON STRUCTUREAmazon Fis Safety Lever Structure
JSON STRUCTUREAmazon Fis Target Resource Type Structure
JSON STRUCTUREScroll within the panel for all 10 ·
Examples 10
Real request and response payloads are what turn a spec from abstract into obvious — and they're one of the twelve things an agent needs to call an API correctly on the first try.
Example request and response payloads for these APIs.
Amazon Fis Action Example
EXAMPLEScroll within the panel for all 10 ·
Security Posture 4
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Agentic Access 1
An x-agentic-access contract marks which operations are safe for an agent to run on its own and which need a human in the loop. It is the difference between an API an agent can use and one it can use safely.
Recommended x-agentic-access execution contracts for AI agents.
Amazon Fault Injection Simulator Agentic Access
18 operations · 8 acting · 2 human-in-the-loop
AGENTICUse Cases 6
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
Application Resilience Testing
Validate application behavior under resource failures before they occur in production.
Chaos Engineering
Run structured fault injection experiments following chaos engineering principles.
Observability Validation
Verify that monitoring and alerting systems detect and respond to failures correctly.
Game Days
Conduct planned game day exercises simulating failure scenarios for team readiness.
Automated Pipeline Testing
Integrate resilience testing into CI/CD pipelines for continuous validation.
Multi-region Failover Testing
Test cross-region failover mechanisms and recovery time objectives.
Resources
Every other property we hold for Amazon Fault Injection Simulator — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 3
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Agent Surfaces 1
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 10
Pagination, idempotency, versioning, errors, and events
Scroll within the panel for all 10 ·
Build 2
SDKs, sample code, and the tooling you integrate with
Access & Security 4
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 3
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API
← All providers · Data indexed from github.com/api-evangelist/amazon-fault-injection-simulator · machine-readable index on apis.io