A high-performance observability data pipeline.
- logs
- metrics
- observability
- forwarder
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A high-performance observability data pipeline.
Agent for collecting, processing, aggregating, and writing metrics, logs, and other arbitrary data.
Logstash - transport and process your logs, events, or other data
Asynchronous Python framework for event-driven services. A thin client for Kafka, RabbitMQ, NATS, Redis and MQTT with full access to native broker features, plus AsyncAPI docs, in-memory tests and observability out of the box.
A network event stream processing system, in Clojure.
Open source framework for processing, monitoring, and alerting on time series data
The fastest unified streaming SQL Engine in a single C++ binary. ⚡ Millisecond latency. 100+ GB/s throughput. Continuously compute stateful context from streams, logs, metrics, events, and CDC.
Evaluation code for various unsupervised automated metrics for Natural Language Generation.
This library provides a set of F# helpers for string manipulations, logging, collection data structures, file operations, text processing, security, async, parsing, diagnostics, configuration files and Json serialization.
Daggy - Data Aggregation Utility and C/C++ developer library for data streams catching
Small, Fast event processing and monitoring for Erlang/OTP applications.
Elixir library to log custom application metrics, in a well-structured, human and machine readable format, for use by downstream log processing systems (Librato, Reimann, etc...)
Observability stack for Stacks blockchain nodes and signers - dashboards, alerts, and log processing