Antithesis

Antithesis is an autonomous software testing platform that runs a complete distributed system inside a deterministic simulator, stresses it with injected faults and unusual inputs, and reports the bugs it finds with a root cause analysis and an exact reproduction. It is built for engineering teams working on systems that cannot fail, such as databases, event streaming, capital markets infrastructure, blockchains and ledgers, and for teams whose code is increasingly written by AI agents.

The foundation is a custom deterministic hypervisor that runs the whole system on a single CPU core and works with any x86 binary packaged in containers orchestrated by Docker Compose or Kubernetes. Because every run is 100% deterministic, Antithesis can rewind time, try alternate execution paths and reproduce any bug perfectly. A feedback-guided exploration algorithm synthesises input data and injects clock, scheduling, network and storage faults to reach code paths such as exception handling and leader election.

Users describe how the system should behave with properties, using SDKs for C, C++, Go, Java, JavaScript, .NET, Python and Rust or a low-level fallback API. When a property fails, Antithesis delivers unified, ordered traces of the distributed execution, custom artifacts such as data files or core dumps, automated root cause analysis and a time-travelling debugger. Skills, CLIs and APIs let coding agents onboard a project, write Docker Compose or Kubernetes manifests, build a specification and call Antithesis in their loop.

Antithesis runs fast enough for CI, the local development loop or an agent skill, and onboarding can take as little as a day. It is sold through sales contact and via AWS Marketplace Private Offers; there is no free or open-source edition, though the open-source property-based testing tools Hegel and Bombadil are published separately. Execution environments can run in a customer's own AWS VPC, but no fully on-premise option exists. Containerised dependencies such as Postgres, Redis, Kafka and NATS are supported; other software needs a mock.

Use cases

• Testing market-making and trading infrastructure that depends on in-order delivery and state machine replication
• Verifying databases, event streaming, blockchains, ledgers and other distributed systems
• Gating pull requests authored by coding agents
• Automated quality gate inside an agentic coding loop
• Testing systems that rely on multicast networking