Open-source Google Cloud Observability alternatives

Grafana is a visualization and observability platform that lets you query, chart and alert on data wherever it is stored. It does not hold your data itself; it connects to sources such as Prometheus, Loki, Elasticsearch, InfluxDB, MySQL and PostgreSQL and brings their results together in shared dashboards.

Dashboards can be made reusable with template variables that appear as dropdowns, and a single graph may mix queries against different data sources. Explore views support ad-hoc queries, side-by-side comparison of time ranges and a jump from metrics to logs while keeping label filters. Alert rules are defined visually, and notifications go to systems like Slack, PagerDuty, VictorOps and OpsGenie. Panel plugins add further visualization types.

Grafana is AGPL-3.0 licensed, written in Go and TypeScript, and can be installed on your own servers; Grafana Labs also runs a hosted offering. It is common in DevOps and SRE teams as the dashboard layer on top of Prometheus-style monitoring, and a public demo site lets you try it first.

Prometheus is a systems and service monitoring tool and time series database, and a project of the Cloud Native Computing Foundation. It collects metrics from configured targets at set intervals, evaluates rule expressions, shows the results and can fire alerts when conditions are met.

Its data model is multi-dimensional: a time series is identified by a metric name plus key and value labels, and PromQL is the query language built to exploit that structure. Collection uses an HTTP pull model, with a gateway available for pushing metrics from short-lived batch jobs, and targets are found through service discovery or static configuration. Single server nodes are autonomous with no dependence on distributed storage, and hierarchical and horizontal federation is supported.

Prometheus is written in Go under the Apache-2.0 license and ships as precompiled binaries and Docker images on Quay.io and Docker Hub, or can be built from source. It has no hosted service of its own and is typically run next to exporters and a dashboarding tool such as Grafana, which suits cloud-native and Kubernetes environments.

Sentry is a debugging platform that helps developers detect, trace and fix problems in their applications. It collects crash reports and errors from running software, groups them into issues, and adds the context needed to understand what happened, alongside performance monitoring for slow requests and transactions.

Integration happens through official SDKs covering web, mobile, desktop, server and game platforms, from JavaScript, Python and PHP to Go, Rust, Java, Kotlin, Swift, Flutter, Unity, Unreal Engine and Godot. The server itself is a Python application built on Django, and topics also mention CSP report collection and application performance monitoring.

Sentry is source available, and its license is listed as 'Other' on GitHub rather than a standard open-source license. It can be run on your own infrastructure, and the company also operates the hosted service at sentry.io. It is used by engineering teams of all sizes as a first stop when something breaks in production.

SigNoz is an observability platform, open source and built on OpenTelemetry. It aims to replace a fragmented monitoring stack with a single place for logs, metrics, traces, alerts, exceptions and dashboards, and it presents itself as useful for both engineering teams and their AI agents.

The APM view follows how each service performs, covering latency, error rate, throughput, Apdex, the busiest endpoints, and calls to databases and external services. Log management supports ingesting, searching and correlating logs with traces and metrics through a visual query builder. Dashboards can be built with a query builder, PromQL or ClickHouse SQL, infrastructure monitoring covers Kubernetes clusters, pods, nodes and host resources, and LLM and AI observability traces prompts, tool calls, tokens, latency and cost.

You can choose how to run it. SigNoz Cloud is fully managed, with a 30-day free trial and usage-based pricing that starts at $49. Enterprise options cover cloud, bring-your-own-cloud and self-hosted deployments with extra support and controls. The free Community edition runs in your own infrastructure via Docker, Kubernetes or Linux. The repository license is listed as 'Other' on GitHub.

Loki is a log aggregation system from Grafana, described as Prometheus for logs. It is horizontally scalable, highly available and multi-tenant. Instead of indexing the contents of log lines, it indexes a set of labels for each log stream and stores the compressed log text, which the project says makes it simpler to operate and cheaper to run. It is written in Go and released under the AGPL-3.0 license.

Because Loki reuses the labels familiar from Prometheus, you can move between metrics and logs using the same label sets, and it has native support in Grafana. It works especially well for Kubernetes pod logs, since metadata such as pod labels is scraped and indexed automatically. A typical stack has three parts: Alloy as the collection agent, Loki for storage and queries, and Grafana for exploration. Alloy replaces Promtail, which is considered feature complete. Unlike Prometheus, Loki receives logs by push.

Jaeger is a tracing system for distributed applications, created at Uber Technologies and donated to the Cloud Native Computing Foundation, where it graduated in October 2019. It records how requests flow through services so teams can monitor and troubleshoot distributed systems. It is written in Go and released under the Apache-2.0 license. The README announces Jaeger v2.

A Docker-based quick start gets a local instance running in seconds, while the documentation covers production deployments and operations. Because Jaeger reuses many components from the OpenTelemetry Collector, the project works to keep configuration compatible between releases and publishes deprecation guidelines for when options change. It is an open project with open governance, welcoming contributions that do not always require code. The repository topics include distributed tracing, observability and OpenTelemetry, and community support runs on Slack.

OpenObserve, often shortened to O2, is open-source observability software spanning logs, metrics, traces and analytics, real user monitoring on web, Android and iOS, session replay, pipelines, SLOs and AI and LLM observability. It is pitched as a lower-cost option next to Datadog, Splunk and Elasticsearch for teams that want complete observability without the complexity or price.

Its architecture uses Parquet columnar storage and an S3-native design, which the project says can cut storage costs by up to 140 times compared with Elasticsearch, with petabyte-scale capacity. Topics reference OpenTelemetry, Prometheus, Jaeger and Kibana, showing the standards and tools it interoperates with. The README has sections on architecture, comparisons, production readiness, security and compliance, and an enterprise edition.

OpenObserve is AGPL-3.0 licensed, with a hosted cloud option and a self-hosted deployment, and documentation and a Slack community are provided. It suits engineering teams looking to consolidate logging, metrics and tracing in one tool while keeping storage costs under control.

VictoriaMetrics is a monitoring solution and time series database built for performance, cost efficiency and scale. It stores metrics, works with the Prometheus ecosystem and query language, and its topics also list support for InfluxDB, Graphite and OpenTSDB data formats, along with Grafana for dashboards, which makes it a common drop-in backend for existing monitoring setups.

It is offered as a single-node version and a cluster version, both under the Apache License 2.0, with downloadable binaries, container images published to Docker Hub and Quay, and the source code. The project publishes case studies from well-known companies, a quick start and key concepts guide, community channels on Slack, X and YouTube, and a fast-moving changelog. Enterprise support and enterprise releases with long-term support are available, and they can be evaluated with a free trial license. The maintainers also mention security certifications for their development practices.

Written in Go, VictoriaMetrics suits platform and SRE teams that want to store large volumes of metrics efficiently, replacing or extending Prometheus long-term storage. It can be deployed on your own infrastructure, including Kubernetes, and the company offers a managed cloud service as well.

HyperDX is an open-source observability platform for working out why production is broken. It brings logs, metrics, traces, errors and session replays into one place, and works as a search and visualization layer on top of ClickHouse and OpenTelemetry, which the authors compare to Kibana for ClickHouse. It is a core component of ClickStack.

It is schema agnostic and can sit on top of an existing ClickHouse schema. Searching uses full-text and property syntax such as level:err, with SQL as an option, events can be compared with event deltas, high-cardinality events can be charted on dashboards, and alerts can be set up in a few clicks. Live tail shows the newest logs and traces, JSON strings can be queried natively, OpenTelemetry works out of the box, and APM views cover HTTP requests down to database queries.

One deployment option is ClickStack, a bundle of ClickHouse, HyperDX, an OpenTelemetry Collector and MongoDB, and HyperDX can instead be pointed at your own ClickHouse instance. It can also be used with ClickHouse Cloud. The project is MIT licensed and written in TypeScript.