5 repository-uri
Reads metrics or message payloads from message brokers using standard protocols.
Distinct from Message Queue Integrations: Distinct from Message Queue Integrations: focuses on the consumption of metrics from queues.
Explore 5 awesome GitHub repositories matching data & databases · Message Queue Metric Consumption. Refine with filters or upvote what's useful.
Vector is a high-performance observability data pipeline designed to collect, transform, and route logs, metrics, and traces across distributed infrastructure. It functions as a modular engine that decouples data ingestion from processing and transmission, utilizing a component-based architecture to connect diverse sources to multiple destinations. The project distinguishes itself through a focus on reliability and flow control. It implements backpressure-aware data movement to prevent data loss during traffic spikes and utilizes disk-backed event buffering to ensure durability during network
Streams processed metric data into database instances using gRPC with support for authentication and compression.
Telegraf is a modular, cross-platform telemetry pipeline designed to collect, process, and route metrics from diverse infrastructure, applications, and hardware. It functions as a server-side middleware that normalizes heterogeneous data into a unified format, enabling consistent monitoring across complex environments. By utilizing a plugin-driven architecture, the agent manages the entire lifecycle of telemetry data from initial ingestion to final transmission. The project distinguishes itself through a declarative, configuration-driven execution model that allows users to define complex dat
Reads metrics or message payloads from message brokers and distributed queue services using standard protocols.
VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term storage and analysis of metric, log, and trace data. It functions as a unified backend for monitoring ecosystems, offering full compatibility with industry-standard protocols and query languages. The system is built to handle massive data volumes through a distributed architecture that supports horizontal scaling and efficient data lifecycle management. The platform distinguishes itself through a storage engine that utilizes consistent hashing for data sharding and log-struct
Streams metric data to message queues using remote write protocols with support for compression and authentication.
FastStream is an asynchronous Python framework designed for building event-driven microservices. It provides a unified abstraction layer for interacting with various message brokers, enabling developers to manage event production and consumption through a consistent interface while maintaining access to native provider-specific features. The framework centers on a decorator-based routing model that binds application logic directly to broker topics, supported by a built-in dependency injection container that resolves resources at runtime. The framework distinguishes itself through its deep int
Specifies the starting point for message processing upon connection, such as retrieving only new messages or replaying historical data.
KafkaJS is a pure JavaScript client for Apache Kafka, providing the necessary tools to produce and consume messages from a Kafka cluster without requiring native dependencies or external addons. It functions as a comprehensive integration library for Node.js applications to engage in distributed message processing and real-time event streaming. The project is distinguished by its native implementation of the Kafka wire protocol, avoiding C++ dependencies. It features a security client supporting SSL, TLS, and SASL authentication, alongside transactional capabilities that allow for atomic mess
Determines whether to start reading from the earliest or latest message when no committed offset exists.