Open Source BSD Observability Tools

Grafana OSS is the leading open-source platform for visualization and observability. It enables teams to query, visualize, alert on, and explore telemetry data from multiple sources in a single interface. With support for 100+ data source plugins—including Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, and OpenTelemetry—Grafana helps teams correlate metrics, logs, and traces across applications and infrastructure. Users can build interactive dashboards with rich visualizations, template variables, and reusable panels to monitor systems and troubleshoot issues in real time. Grafana includes capabilities such as ad hoc data exploration, alerting, annotations, and flexible query support. Its extensible plugin ecosystem integrates with cloud platforms, databases, and developer tools—allowing teams to build observability workflows without vendor lock-in. The easiest way to get started with Grafana is with Grafana Cloud, our fully managed, full-stack observability platform.

twemproxy (pronounced "two-em-proxy"), aka nutcracker is a fast and lightweight proxy for memcached and redis protocol. It was built primarily to reduce the number of connections to the caching servers on the backend. This, together with protocol pipelining and sharding enables you to horizontally scale your distributed caching architecture. Fast and lightweight. Maintains persistent server connections. Keeps connection count on the backend caching servers low. Enables pipelining of requests and responses. Supports proxying to multiple servers. Supports multiple server pools simultaneously. Shard data automatically across multiple servers. Implements the complete memcached ascii and redis protocol. Easy configuration of server pools through a YAML file. Supports multiple hashing modes including consistent hashing and distribution. Can be configured to disable nodes on failures.

Kamon Telemetry is a set of libraries for instrumenting applications running on the JVM. With Kamon Telemetry you can collect metrics, propagate context across threads and services, and get distributed traces automatically. The best way to get started is by following our installation guides and taking it from there. Have fun with Kamon. Monitor your backend applications, fix performance issues, and get alerted when problems happen. All without being a monitoring expert. Everybody starts monitoring with logs because they are there by default. Just connect to your server and start tailing. But logs have a hard time showing you the overall response times for your application, or whether certain calls to the database are happening in sequence or parallel (among a million other things).

OpenClaw Opik Observability Plugin is an open-source plugin designed to add observability and monitoring capabilities to OpenClaw autonomous AI agents by exporting operational traces to the Opik observability platform. The project integrates directly with OpenClaw’s plugin architecture so that developers can capture detailed runtime information about how their agents behave while executing tasks. Each time an AI agent performs an action—such as calling a large language model, invoking a tool, accessing memory, or delegating to a sub-agent—the plugin records the full interaction and sends it to Opik for analysis and visualization. This allows developers to inspect inputs, outputs, token usage, latency, and execution flow across complex multi-step agent workflows. The goal of the project is to provide transparency into the internal reasoning and operational pipeline of agent systems so developers can diagnose failures, control costs, and improve reliability.

gRPC Go has support for "interceptors", i.e. middleware that is executed either on the gRPC Server before the request is passed onto the user's application logic, or on the gRPC client either around the user call. It is a perfect way to implement common patterns: auth, logging, tracing, metrics, validation, retries, rate limiting, and more, which can be great generic building blocks that make it easy to build multiple microservices. Especially for observability signals (logging, tracing, metrics) interceptors offer semi-auto-instrumentation that improves the consistency of your observability and allows great correlation techniques (e.g. exemplars and trace ID in logs). Demo-ed in examples. This repository offers ready-to-use middleware that implements gRPC interceptors with examples. In some cases, dedicated projects offer great interceptors, so this repository skips those, and we link them in the interceptors list.

Micrometer provides a simple facade over the instrumentation clients for the most popular observability systems, allowing you to instrument your JVM-based application code without vendor lock-in. Think SLF4J, but for observability. Micrometer provides vendor-neutral interfaces for timers, gauges, counters, distribution summaries, and long task timers with a dimensional data model that, when paired with a dimensional monitoring system, allows for efficient access to a particular named metric with the ability to drill down across its dimensions. Out-of-the-box instrumentation of caches, the class loader, garbage collection, processor utilization, thread pools, and more tailored to actionable insight. Micrometer is the instrumentation library powering the delivery of application observability from Spring Boot applications.

Fluent Bit is a super-fast, lightweight, and highly scalable logging and metrics processor and forwarder. It is the preferred choice for cloud and containerized environments. A robust, lightweight, and portable architecture for high throughput with low CPU and memory usage from any data source to any destination. Proven across distributed cloud and container environments. Highly available with I/O handlers to store data for disaster recovery. Granular management of data parsing and routing. Filtering and enrichment to optimize security and minimize cost. The lightweight, asynchronous design optimizes resource usage: CPU, memory, disk I/O, network. No more OOM errors! Integration with all your technology, cloud-native services, containers, streaming processors, and data backends. Fully event-driven design leverages the operating system API for performance and reliability. All operations to collect and deliver data are asynchronous.

cdviz is a developer-focused visualization and analysis tool designed to help engineers understand, monitor, and optimize codebases by providing insights into structure, performance, and execution patterns. It likely focuses on transforming complex code relationships into visual representations that improve comprehension and debugging efficiency. The system may include static analysis capabilities, enabling it to detect inefficiencies, dependencies, or architectural issues within a project. Its architecture suggests an emphasis on developer experience, providing clear and actionable insights rather than raw data. It is particularly useful for large or complex systems where understanding code interactions is critical. The tool may also integrate with development workflows, allowing continuous analysis and feedback. Overall, cdviz serves as a bridge between code complexity and human understanding through visualization.