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README.md
Provision a Nomad cluster in the Cloud
Use this repo to easily provision a Nomad sandbox environment on AWS or Azure with Packer and Terraform. Consul and Vault are also installed (colocated for convenience). The intention is to allow easy exploration of Nomad and its integrations with the HashiCorp stack. This is not meant to be a production ready environment. A demonstration of Nomad's Apache Spark integration is included.
Setup
Clone the repo and optionally use Vagrant to bootstrap a local staging environment:
$ git clone git@github.com:hashicorp/nomad.git
$ cd terraform
$ vagrant up && vagrant ssh
The Vagrant staging environment pre-installs Packer, Terraform, Docker and the Azure CLI.
Provision a cluster
- Follow the steps here to provision a cluster on AWS.
- Follow the steps here to provision a cluster on Azure.
Continue with the steps below after a cluster has been provisioned.
Test
Run a few basic status commands to verify that Consul and Nomad are up and running properly:
$ consul members
$ nomad server-members
$ nomad node-status
Unseal the Vault cluster (optional)
To initialize and unseal Vault, run:
$ vault init -key-shares=1 -key-threshold=1
$ vault unseal
$ export VAULT_TOKEN=[INITIAL_ROOT_TOKEN]
The vault init
command above creates a single
Vault unseal key for
convenience. For a production environment, it is recommended that you create at
least five unseal key shares and securely distribute them to independent
operators. The vault init
command defaults to five key shares and a key
threshold of three. If you provisioned more than one server, the others will
become standby nodes but should still be unsealed. You can query the active
and standby nodes independently:
$ dig active.vault.service.consul
$ dig active.vault.service.consul SRV
$ dig standby.vault.service.consul
See the Getting Started guide for an introduction to Vault.
Getting started with Nomad & the HashiCorp stack
Use the following links to get started with Nomad and its HashiCorp integrations:
Apache Spark integration
Nomad is well-suited for analytical workloads, given its performance characteristics and first-class support for batch scheduling. Apache Spark is a popular data processing engine/framework that has been architected to use third-party schedulers. The Nomad ecosystem includes a fork that natively integrates Nomad with Spark. A detailed walkthrough of the integration is included here.