Can AI replace Datadog?

Build a closest honest personal substitute for Datadog in an empty repository.
Use Go, PostgreSQL, ClickHouse, a Next.js 15 dashboard, and Docker Compose; do not offer alternative stacks.
The core loop is: collect a bounded set of host metrics and log events into a self-hosted dashboard, run independent checks, alert through one channel, and publish an honest status page.
Make the first run work locally with one documented command.
Store all user data locally by default and make export straightforward.
Put secrets in .env, ship .env.example, and never commit credentials.
Implement HTTP, TCP, DNS, TLS-expiry, and heartbeat checks with explicit timeout and retry policies.
Run checks from one independently hosted worker and store raw results plus incident state transitions.
Send deduplicated alerts to email or one webhook destination with recovery notifications.
Create services, maintenance windows, incidents, subscribers, and a public status page.
Add bounded event ingestion for application errors with sampling and sensitive-field scrubbing.
Provide health checks, retention settings, exports, backups, and a test-alert function.
Include clear empty, loading, success, and recoverable error states.
Add input validation, safe filenames, and graceful handling of unavailable APIs.
Write focused tests for the core transformation and one end-to-end happy path.
Create a README with setup, architecture, permissions, data location, and backup steps.
Do not add accounts, billing, telemetry, analytics, or a hosted control plane.
Do not claim to reproduce proprietary data, network liquidity, regulated access, or frontier infrastructure.
Deliberately leave out a worldwide probe network.
Deliberately leave out phone, SMS, and managed on-call escalation.
Deliberately leave out unbounded logs, enterprise observability, and vendor-operated incident response.
Finish by running the tests and listing the exact commands used.