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# Service deployment platform

## Context

You have applied the \[\[Microservice architecture]] pattern and architected your system as a set of services. Each service is deployed as a set of service instances for throughput and availability.

## Problem

How are services packaged and deployed?

## Forces

* Services are written using a variety of languages, frameworks, and framework versions
* Each service consists of multiple service instances for throughput and availability
* Service must be independently deployable and scalable
* Service instances need to be isolated from one another
* You need to be able to quickly build and deploy a service
* You need to be able to constrain the resources (CPU and memory) consumed by a service
* You need to monitor the behavior of each service instance
* You want deployment to reliable
* You must deploy the application as cost-effectively as possible

## Solution

Use a deployment platform, which is automated infrastructure for application deployment. It provides a service abstraction, which is a named, set of highly available (e.g. load balanced) service instances.

## Examples

* \[\[Docker orchestration]] frameworks including \[\[Docker swarm]] mode and \[\[Kubernetes]]
* \[\[Serverless]] platforms such as \[\[AWS Lambda]]
* \[\[PaaS]] including \[\[Cloud Foundry]] and \[\[AWS Elastic Beanstalk]]

## Related patterns

* Some deployment platforms provide a \[\[Service Registry]] and \[\[Server-Side discovery]]
* Internally, a deployment platform might use use containers or virtual machines to deploy a service. Docker orchestration frameworks are, of course, explicitly container-based