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Elster OS Documentation

Overview

Elster OS is a modular, highly configurable operating system based on the Linux Foundation's DANOS project. It provides a distributed computing environment specifically designed for researchers who need to develop and deploy compute tasks requiring massive amounts of disparate computing hardware.

Elster OS is built for researchers and organizations that require flexible, scalable computing resources.

Core Concept

At its heart, Elster OS embraces a distributed computing model where workloads can be efficiently spread across multiple nodes. The system leverages the robust foundation of DANOS while extending its capabilities to support complex scientific and research computing environments.

Key features include:

  • Modular Architecture: Components can be added, removed, or modified based on specific research requirements
  • Distributed Computing Framework: Efficiently manages resources across multiple machines
  • Advanced Workload Distribution: Intelligent task allocation based on available resources and priority
  • Configurable System Spaces: Flexible partitioning between local and cloud resources
  • Vyatta Configuration Interface: Powerful command-line configuration system inherited from DANOS

Installation

System Requirements

Client:

  • CPU: 64-bit multi-core processor (4+ cores recommended)
  • RAM: Minimum 4GB
  • Storage: 10GB available space (SSD recommended)
  • Network: Gigabit Ethernet or faster connection

Server:

  • CPU: 64-bit multi-core server processor (8+ cores recommended)
  • RAM: Minimum 16GB (32GB+ recommended)
  • Storage: 100GB available space (SSD required)
  • Network: Gigabit Ethernet or faster connection, multiple NICs recommended

Client Installation

  1. Download the client installer from the official download page (opens in a new tab)
  2. Create installation media:
sudo dd if=elster-os-client.iso of=/dev/sdX bs=4M status=progress

  1. Boot from installation media and follow the on-screen instructions

  2. Install Image

install image
  1. Basic configuration:
configure
set system hostname client-name
set interfaces ethernet eth0 address dhcp
commit
save
exit
  1. Connect to server nodes:
configure
set service daos-client config server-group server-hostname
set service daos-client config interface enp1s0
set service daos-client mount-points /share pool-id <pool-uuid>
set service daos-client mount-points /share container-id <container-uuid>
commit
save
exit

Server Installation

  1. Download the server installer from the official download page (opens in a new tab)
  2. Create installation media (similar to client installation)
  3. Boot from installation media and follow the on-screen instructions
  4. Basic configuration:
configure
set system hostname server-name
set daos-server config interface enp1s0
set daos-server pool data container share
commit
save
exit

Deployment Options

Client

Elster OS client installations provide researchers with a flexible environment to develop and submit computing jobs to the wider cluster.

The client deployment is ideal for individual researchers and development workstations.

  • Configurable local/cloud system spaces via the Vyatta config shell
    • Dynamically allocate resources between local computation and cloud-based resources
    • Seamlessly transition workloads between environments based on resource availability
  • Optimized resource management for distributed workloads
    • Intelligent scheduling of jobs based on priority and resource requirements
    • Real-time monitoring of resource utilization across all connected nodes
  • Seamless integration with server nodes
    • Automatic discovery of available computing resources
    • Transparent job submission and result retrieval

Download Client (opens in a new tab)

Server

Elster OS server installations form the backbone of the computing cluster, providing the processing power needed for intensive research workloads.

Server deployments are designed for data centers and high-performance computing environments.

  • Easy deployment of system partitions
    • Create virtual environments tailored to specific computational needs
    • Isolate workloads for security and resource management
  • Advanced workload distribution capabilities
    • Automatically balance computing jobs across available hardware
    • Prioritize critical tasks while maintaining overall system efficiency
  • High-performance cluster management
    • Centralized monitoring and administration of all nodes
    • Automated scaling based on demand and resource availability

Download Server (opens in a new tab)

Documentation Resources

Support

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