Observability for Multi-platform

Self-host uptime + status pages — not Datadog/APM. You run the container, backups, and alerting path. HTTP/TCP checks are the lane, not full distributed tracing.

Not PostHog/GA depth — no session replay/heatmaps on Hobby/self-host the way Cloud Business sells them. Self-host means you own updates, backups, and a growing DB. Vs Plausible (paid SaaS-first) and PostHog.

AGPL-3.0 — network copyleft on modifications you ship as a service. free cloud: one monitor / one page / 10m checks — fine for a side project, not a fleet. Vs Better Stack / Checkly-class SaaS, OpenStatus wins on OSS+IaC; you trade managed depth for license+self-host ops.

Config is YAML-only, with no UI for adding checks, which is great for GitOps and less great for non-engineers. It checks from wherever you run it, so you need a second location if you want to catch outages of that host itself. Suites are still marked alpha. A managed Gatus.io exists if you would rather not host it.

Its own README says it is not trying to replace Datadog or Atlassian Statuspage; checks run from your server only, so pair it with an external monitor. Smaller community than Uptime Kuma or Gatus, and the 4.x line moved fast.

AGPL-3.0, like the rest of Grafana's backends, so modified hosted versions must share source. Profiling has overhead and storage cost, so sample sensibly. You get the most out of it inside the Grafana stack; standalone it is less convenient.

You need ClickHouse, either self-run (ClickStack bundles it with the OTel collector) or ClickHouse Cloud, and ClickHouse is its own ops skill. Since joining ClickHouse, the direction follows ClickStack. Releases are split between app, CLI and other packages, which makes version tracking fiddly.

eBPF agents need privileged access and a recent Linux kernel on every node. Some features, such as AI root-cause analysis and SSO, are in Coroot Enterprise. It is opinionated about how it stores data (Prometheus plus ClickHouse), so it is another stack to run.

Traces can include prompts and completions, which may hold personal data, so configure content capture deliberately. The Traceloop SDK defaults point toward Traceloop's hosted platform; set your own exporter. It is instrumentation, not a UI, so you still need a backend.

It is a younger system than Prometheus, Loki or ClickHouse, and the README says the core is Apache-2.0 — some enterprise and cloud features are commercial. Grafana integration works but is less native than Mimir/Loki. Plan object-storage costs and compaction.

Data is kept in memory in-cluster for a short window, so it is for live debugging, not long-term retention. It needs a supported Linux kernel and privileged pods. Running the control plane yourself is more involved than using a hosted Pixie cloud. Release tags are split by component and some are old, so follow the docs for current versions.

The Alloy config syntax is its own language, so it is another thing to learn on top of OTel YAML. It is tuned for Grafana backends; for a pure OTel setup, the upstream Collector may be simpler. Migrating from Grafana Agent or Promtail takes conversion work.

A scaled Mimir is many components to operate, and object storage plus compactor tuning are real work. If you are below tens of millions of series, a single VictoriaMetrics or Prometheus with remote storage is simpler. AGPL-3.0 if you offer a modified version as a service.

Still 0.x. The eBPF agent needs root and a recent kernel. Interpreted languages get less detail than compiled ones. It overlaps with Grafana Pyroscope, which integrates more tightly if you are already on Grafana. Polar Signals runs the commercial cloud.

You run ClickHouse and PostgreSQL alongside it. The newest release is a release candidate, so pin a stable version for production. AGPL-3.0, and some features are reserved for the hosted and enterprise editions. Smaller community than SigNoz.

Auto-instrumentation shows you request flow but not your business attributes; you will still add manual spans for that. Some advanced eBPF instrumentation is in the commercial Odigos Enterprise. It is another operator to run in the cluster.

Still 0.x and much younger than Grafana, with far fewer plugins and data sources. Best suited to teams that want dashboards-as-code or embedding, not a full Grafana replacement today.

It only generates rules; Prometheus and Alertmanager still do the work, and you must choose good SLIs. The last release was April 2026, and the project status says internal refactoring is in progress. Single-maintainer project.

LogsQL is its own query language, so Loki or Elasticsearch users must relearn queries. The repo was split out from VictoriaMetrics in 2025, so the star count understates its age. Enterprise features and support come from VictoriaMetrics Inc.

AGPL-3.0, and some features are in the commercial Parseable Pro/Enterprise. Smaller ecosystem than Loki or OpenSearch, so fewer ready-made dashboards and integrations. Benchmarks on the site are the vendor's own.

Much of its community and older documentation is in Chinese. It is a separate alerting system next to Alertmanager or Grafana alerting, so pick one as your source of truth. The built-in AI features need your own model provider.

All configuration is YAML, and routing trees get hard to reason about at scale. There is no on-call scheduling or escalation; pair it with an incident tool for that. The UI is basic.

It covers a lot at once, so each part is shallower than a dedicated tool: Prometheus plus Grafana go deeper on metrics, Uptime Kuma is simpler for basic uptime. Change the default admin/hertzbeat login immediately. Java-based and heavier than a single Go binary. The new Next.js frontend is an alpha preview.