Announcement
Vector: High-Performance Observability Data Pipeline
Explore Vector, a high-performance observability data pipeline that collects, transforms, and routes all your logs, metrics, and traces to any destination. Designed for scalability and reliability.
Project Introduction
Summary
This project delivers a high-performance, vendor-neutral data pipeline specifically built for collecting, transforming, and routing all types of observability data (logs, metrics, traces). It aims to provide a single source of truth for data pipelines, improving efficiency and control.
Problem Solved
Managing observability data from diverse sources, formats, and destinations is complex, resource-intensive, and often unreliable. This project provides a single, high-performance tool to simplify this entire workflow.
Core Features
Unified Data Collection
Efficiently collect data from a wide array of sources including files, sockets, APIs, and popular platforms.
In-Stream Transformation
Process and transform data in flight using powerful built-in functions for parsing, filtering, sampling, and enrichment.
Flexible Data Routing
Route transformed data to multiple destinations like object storage, databases, monitoring systems, and data warehouses.
Reliable Delivery
Handle backpressure and ensure data delivery with robust buffering, retries, and acknowledgments.
Tech Stack
Use Cases
Vector can be deployed in various scenarios where efficient and reliable data collection, transformation, and routing are critical.
Unified Data Aggregation
Details
Aggregate logs, metrics, and traces from applications, containers, and infrastructure nodes into a unified stream.
User Value
Centralize observability data management, simplifying monitoring and troubleshooting across distributed systems.
Conditional Data Routing
Details
Route specific data types (e.g., security logs) to a dedicated SIEM system, while sending operational logs to an analytics platform, and metrics to a time-series database.
User Value
Ensure data lands in the most appropriate system for analysis and storage, optimizing cost and accessibility.
Data Transformation and Masking
Details
Filter out sensitive information (e.g., PII) from logs before sending them to external systems or long-term storage.
User Value
Enhance data privacy and compliance by processing data in-stream according to predefined rules.
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