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Telemetry and Observability. Powered by AI.

Your virtual Observability Engineer.

HoundOS reads your code the way a site-reliability engineer would, proposes the SLOs and SLIs that fit it, opens the OpenTelemetry pull requests that measure them — and keeps everything aligned as the code changes, including its own merged work.

BetaJava, JavaScript, Python, Go, Rust

HoundOS

The unit of trust is the agreed contract

Every other capability exists to propose that contract, implement it, verify it, or defend it. Nothing re-points, rewrites or silently retires an SLI you have agreed. HoundOS detects and surfaces; you decide.

How it works

  1. 1

    First value, in minutes

    Install the GitHub App, pick a repo. Services are detected from your manifests — monorepos and workspace layouts included — and analysed into a gap report with recommended SLOs. Zero configuration.

  2. 2

    Agree the contract

    Review recommendations per service, per user-journey flow and per dependency. Edit targets and windows, enable or disable SLIs, then agree the set. It is versioned; further edits re-open it as a draft.

  3. 3

    Implementation as pull requests

    Select agreed SLIs and HoundOS opens instrumentation PRs against your repo. Every changeset passes a compile gate before it reaches you, and conflicting sibling changes converge invisibly.

  4. 4

    Operation in your own backend

    Telemetry flows to your Grafana. Dashboards and alert policies are provisioned from the contract, and arrival is verified per service — so you know the signal is really there.

  5. 5

    Continuous adherence

    Every push triggers drift assessment. If a change breaks the instrumentation behind an agreed SLI, HoundOS surfaces it with the fix rather than letting the contract quietly decay.

  6. 6

    Maturity you can show

    Scores track the observability maturity and quality of the estate over time, so the state of coverage is legible to the people who fund it.

Who it is for

Service owners and tech leads

Credible SLOs without hiring an SRE team — grounded in observability-engineering practice rather than in whatever the last incident suggested.

Platform and SRE leads

Consistency and coverage across many repositories, and an authority to argue with when someone asks why a target is infeasible for the deployed topology.

Engineering leadership

The maturity of the estate visible as scores, and the cost of observability decisions legible rather than buried in a vendor bill.

Point it at a repository

The gap report costs you one GitHub App install and a few minutes. The contract is yours either way.