Armada

sandbox

First Research Pass

GitHub Repository Official Website

Content Lifecycle & Evolution State

1

Initial Seed

Metadata Loaded

2

First Research

Automated Gathering

3

Tech Writing

Content Structured

4

Approval

Editorial Verified

First Research Pass Completed: Initial facts, key features, and documentation links have been gathered. Detailed technical writing and synthesis are currently in queue.

Overview

Armada is a multi-Kubernetes cluster batch job meta-scheduler designed to handle massive-scale workloads. Built on top of Kubernetes, Armada enables organizations to distribute millions of batch jobs per day across tens of thousands of nodes spanning multiple clusters, making it an ideal solution for high-throughput computational workloads.

Key Features

Multi-cluster orchestration to schedule jobs across many Kubernetes clusters seamlessly
High-throughput queueing capable of handling millions of queued jobs
Advanced batch scheduling including fair queuing, gang scheduling, preemption, and resource limits
Enterprise-grade reliability with secure, highly available components designed for production use
Support for external storage backends (e.g., PostgreSQL and Redis) for high-throughput batch job queueing and scheduling

Use Cases

High-Performance Computing (HPC) such as Machine Learning Training, Scientific Computing, and Financial Modeling. Data Processing Pipelines like ETL Workloads, Data Analytics, and Backup/Archival. CI/CD and Development for Build Systems, Integration Testing, and Deployment Automation.

Getting Started

Users can try Armada locally by following the quickstart guide on the Armada project website.

Recent Updates

Armada is actively maintained as a CNCF Sandbox project and used in production environments, such as G-Research where it processes millions of jobs daily.

Did You Know?

G-Research, a leading quantitative research company, uses Armada in production to process millions of jobs per day and manage tens of thousands of nodes.