Open-source Dynatrace alternatives

Netdata is a real-time infrastructure monitoring platform. You install an agent on servers, containers or Kubernetes nodes and it starts collecting metrics every second, showing them on dashboards without lengthy setup. Its origin story is a frustration with monitoring tools that offered few metrics at low resolution and cost too much to run.

The project highlights zero-configuration deployment, machine-learning-based anomaly detection and automated analysis, and an efficient agent that uses few resources. Data stays distributed on the monitored machines instead of being shipped to one central store. Integrations cover databases such as MySQL, PostgreSQL and MongoDB, plus Docker and Kubernetes, and the topics list mentions export paths to Prometheus, Grafana and InfluxDB. Netdata also advertises AI-assisted troubleshooting and an MCP interface.

The agent is GPL-3.0 licensed and written largely in Go, and Netdata Cloud offers a hosted layer for viewing many nodes together. It suits operations teams and lean engineering groups that want deep visibility quickly rather than building a metrics stack from several separate tools.

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.

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.

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.

Pinpoint is an APM tool, short for application performance management, built for large-scale distributed systems. Inspired by Google's Dapper, it traces transactions as they move across the components of a distributed application so teams can see how the system is structured and where problems or bottlenecks arise.

Its ServerMap visualizes application topology and how components connect, while real-time monitoring and code-level visibility into each transaction help diagnose slow or failing requests. Agents can be installed without changing application code, and the project says their overhead on resource usage is low. Agents are available for Java, PHP and Python applications.

Pinpoint is written in Java and licensed under Apache-2.0. You deploy and operate the Pinpoint components yourself, with a quick-start guide, an installation guide and a Kubernetes deployment option provided, and a live demo is available online for a first look.

Coroot is an open-source observability and application performance monitoring tool. Its pitch is that collecting metrics, logs and traces is not enough on its own, so it turns the data into actionable insights, including AI-powered root cause analysis, predefined inspections and a service map.

It gathers metrics, logs, traces and continuous profiles automatically with eBPF, so legacy and third-party services can be observed without code changes, and it is also vendor-neutral through OpenTelemetry instrumentation. Features include a service map, application health summaries, SLO tracking and alerting, distributed tracing, log pattern clustering with logs-to-traces correlation using ClickHouse, and one-click profiling that drills down to the line of code. Predefined inspections audit each application without configuration.

Coroot is written in Go and licensed under Apache-2.0, with a live demo, documentation and a separate Coroot Enterprise edition. Topics include database monitoring, microservices and Prometheus. It suits SRE and platform teams that want observability for Kubernetes and Linux workloads without manually instrumenting every service.

Odigos is an open-source distributed tracing solution aimed at Kubernetes environments and virtual machines. Its core promise is instant tracing without changing application code, which helps platform engineers, DevOps professionals and SREs improve observability quickly.

It builds on OpenTelemetry and eBPF to instrument applications automatically, covering languages such as Go, Java, .NET, Node.js and Python according to the repository topics, and it can emit traces, metrics and logs. The data can be sent to many observability back ends, so it fits into existing monitoring stacks. Documentation, a demo video and a Slack community are linked from the README. It is written in Go.

Odigos is licensed under Apache-2.0 and installed into your own cluster. It suits teams that want OpenTelemetry coverage across many services without rolling out SDKs and code changes service by service.

Uptrace is an open-source application performance monitoring platform. It collects distributed traces, metrics and logs through OpenTelemetry and presents them in a single interface, so teams can monitor applications and troubleshoot problems without switching between separate tracing, metrics and logging tools.

The interface includes a query builder, a service graph, faceted filters, chart annotations and many prebuilt dashboards that appear automatically as metrics arrive. Alerting rules send notifications through email, Slack, WebHook or AlertManager. Data can be ingested via OpenTelemetry, Prometheus, Vector, FluentBit and CloudWatch, Grafana can use Uptrace as a Tempo or Prometheus data source, and single sign-on works through OpenID Connect.

Uptrace is written in Go with a Vue front end, stores telemetry in ClickHouse and keeps metadata such as alerts in PostgreSQL. It is licensed under AGPL-3.0 and can be self-hosted with Docker, and a cloud demo needs no login. The project says it is meant to cut monitoring costs, which suits engineering teams comparing self-hosted APM options with commercial observability suites.

Easy-Monitor is an enterprise-grade performance monitoring and online fault-diagnosis solution for Node.js applications. It is aimed at teams running Node.js services in production who need visibility into process and system metrics to diagnose performance and stability problems, rather than guessing from logs alone.

Version 3.0 supports Linux, macOS and Windows, and covers performance monitoring of Node.js process and system metrics, error log display with npm dependency security risk alerts, customizable intelligent alerting, and real-time export of a running process's state for diagnosis. The 3.0 architecture split the project into several sub-modules hosted under a separate X-Profiler organization, including a console, management and transit services, and the underlying performance-log generation and collection plugins.

The console frontend is built with Vue.js and the iView UI framework, while the monitoring backend uses the Egg.js framework, with its UI design referencing the AliNode console. It is released under the BSD-2-Clause license, with usage documentation hosted on Yuque and a DingTalk group for community support.