Snap is an open telemetry framework designed to simplify the collection, processing and publishing of system data through a single API. The goals of this project are to Empower systems to expose a consistent set of telemetry data, Simplify telemetry ingestion across ubiquitous storage systems, Provide powerful clustered control of telemetry workflows across small or large clusters and lot more.

Snap -  A powerful open telemetry framework

Apache NiFi supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic. Data flow can be tracked and modified at run time.  It automates the movement of data between disparate data sources and systems, making data ingestion fast, easy and secure. The project was created by the United States National Security Agency (NSA).
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It is data source agnostic, supporting disparate and distributed sources of differing formats, schemas, protocols, speeds and sizes such as machines, geo location devices, click streams, files, social feeds, log files and videos and more.

Apache NiFi supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic. Data flow can be tracked and modified at run time.  It automates the movement of data between disparate data sources and systems, making data ingestion fast, easy and secure. The project was created by the United States National Security Agency (NSA).

Apache NiFi - An easy to use, powerful, and reliable system to process and distribute data

Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure. Fluentd can be used to tail access/error logs and transport them reliably to remote systems. It can "grep" for events and send out alerts. It can function as middleware to enable asynchronous, scalable logging for user action events.
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Fluentd tries to structure data as JSON as much as possible: this allows Fluentd to unify all facets of processing log data: collecting, filtering, buffering, and outputting logs across multiple sources and destinations (Unified Logging Layer). The downstream data processing is much easier with JSON, since it has enough structure to be accessible while retaining flexible schemas.

Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure. Fluentd can be used to tail access/error logs and transport them reliably to remote systems. It can "grep" for events and send out alerts. It can function as middleware to enable asynchronous, scalable logging for user action events.

Fluentd - Unified Logging Layer

Fluent Bit is a fast Log Processor and Forwarder, it allows to collect log events or metrics from different sources, process them and deliver them to different backends such as Fluentd, Elasticsearch, Splunk, DataDog, Kafka, New Relic, Azure services, AWS services, Google services, NATS, InfluxDB or any custom HTTP end-point. It also comes with full SQL Stream Processing capabilities: data manipulation and analytics using SQL queries.

Fluent Bit - Fast and Lightweight Logs and Metrics processor

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Snap - A powerful open telemetry framework

Apache NiFi - An easy to use, powerful, and reliable system to process and distribute data

Fluentd - Unified Logging Layer

Fluent Bit - Fast and Lightweight Logs and Metrics processor

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Projects

Snap - A powerful open telemetry framework

Apache NiFi - An easy to use, powerful, and reliable system to process and distribute data

Fluentd - Unified Logging Layer

Fluent Bit - Fast and Lightweight Logs and Metrics processor

TechStack

Tagcloud