68 lines
3.4 KiB
Plaintext
68 lines
3.4 KiB
Plaintext
---
|
|
layout: intro
|
|
page_title: Use Cases
|
|
sidebar_title: Use Cases
|
|
description: |-
|
|
This page lists some concrete use cases for Nomad, but the possible use cases
|
|
are much broader than what we cover.
|
|
---
|
|
|
|
# Use Cases
|
|
|
|
This page features Nomad's core use cases.
|
|
|
|
Note that the full range of potential use cases is broader than what is covered here.
|
|
|
|
## Docker Container Orchestration
|
|
|
|
Organizations are increasingly moving towards a Docker centric workflow for
|
|
application deployment and management. This transition requires new tooling
|
|
to automate placement, perform job updates, enable self-service for developers,
|
|
and to handle failures automatically. Nomad supports a [first-class Docker workflow](/docs/drivers/docker)
|
|
and integrates seamlessly with [Consul](/docs/integrations/consul-integration)
|
|
and [Vault](/docs/vault-integration) to enable a complete solution
|
|
while maximizing operational flexibility. Nomad is easy to use, can scale to
|
|
thousands of nodes in a single cluster, and can easily deploy across private data
|
|
centers and multiple clouds.
|
|
|
|
## Legacy Application Deployment
|
|
|
|
A virtual machine based application deployment strategy can lead to low hardware
|
|
utilization rates and high infrastructure costs. While a Docker-based deployment
|
|
strategy can be impractical for some organizations or use cases, the potential for
|
|
greater automation, increased resilience, and reduced cost is very attractive.
|
|
Nomad natively supports running legacy applications, static binaries, JARs, and
|
|
simple OS commands directly. Workloads are natively isolated at runtime and bin
|
|
packed to maximize efficiency and utilization (reducing cost). Developers and
|
|
operators benefit from API-driven automation and enhanced reliability for
|
|
applications through automatic failure handling.
|
|
|
|
## Microservices
|
|
|
|
Microservices and Service Oriented Architectures (SOA) are a design paradigm in
|
|
which many services with narrow scope, tight state encapsulation, and API driven
|
|
communication interact together to form a larger solution. However, managing hundreds
|
|
or thousands of services instead of a few large applications creates an operational
|
|
challenge. Nomad elegantly integrates with [Consul](/docs/integrations/consul-integration)
|
|
for automatic service registration and dynamic rendering of configuration files. Nomad
|
|
and Consul together provide an ideal solution for managing microservices, making it
|
|
easier to adopt the paradigm.
|
|
|
|
## Batch Processing Workloads
|
|
|
|
As data science and analytics teams grow in size and complexity, they increasingly
|
|
benefit from highly performant and scalable tools that can run batch workloads with
|
|
minimal operational overhead. Nomad can natively run batch jobs and [parameterized](https://www.hashicorp.com/blog/replacing-queues-with-nomad-dispatch) jobs.
|
|
Nomad's architecture enables easy scalability and an optimistically
|
|
concurrent scheduling strategy that can yield [thousands of container deployments per
|
|
second](https://www.hashicorp.com/c1m). Alternatives are overly complex and limited
|
|
in terms of their scheduling throughput, scalability, and multi-cloud capabilities.
|
|
|
|
## Multi-Region and Multi-Cloud Federated Deployments
|
|
|
|
Nomad is designed to natively handle multi-datacenter and multi-region deployments
|
|
and is cloud agnostic. This allows Nomad to schedule in private datacenters running
|
|
bare metal, OpenStack, or VMware alongside an AWS, Azure, or GCE cloud deployment.
|
|
This makes it easier to migrate workloads incrementally and to utilize the cloud
|
|
for bursting.
|