Open Source BSD Observability Tools

Grafana Open Source is a leading open-source visualization and observability platform that lets you query, visualize, alert on, and explore your data—regardless of where it’s stored. With support for 100+ data source plugins (such as Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, OpenTelemetry, and more), you can unify metrics, logs, traces, and other observability signals in one place. Grafana OSS empowers you to build dynamic, reusable dashboards with rich visualizations, template variables, interactive filtering, and cross-panel linking. Its Explore mode enables ad-hoc queries and side-by-side comparisons of time ranges, queries, and data sources. Grafana also includes built-in alerting, allowing you to define threshold-based rules and send notifications to external systems (e.g. Slack, PagerDuty, OpsGenie). Backed by a strong community and open governance, Grafana OSS is free to use, modify, and deploy under the AGPL-3.0 license.

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.

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).

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.

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.