github.com/iaas-resource-provision/iaas-rpc@v1.0.7-0.20211021023331-ed21f798c408/website/intro/use-cases.html.markdown (about)

     1  ---
     2  layout: "intro"
     3  page_title: "Use Cases"
     4  sidebar_current: "use-cases"
     5  description: |-
     6    Learn common use cases for Terraform including managing Heroku apps, self-service clusters, and multi-cloud deployments.
     7  ---
     8  
     9  # Use Cases
    10  
    11  This page lists a subset of use cases for [Terraform](/intro/index.html).
    12  
    13  ## Heroku App Setup
    14  
    15  Heroku is a popular PaaS for hosting web apps. Developers create an app, and then attach add-ons, such as a database, or email provider. One of the best features is the ability to elastically scale the number of dynos or workers. However, most non-trivial applications quickly need many add-ons and external services.
    16  
    17  You can use Terraform to codify the setup required for a Heroku application, ensuring that all the required add-ons are available, but it can go even further: configuring DNSimple to set a CNAME, or setting up Cloudflare as a CDN for the app. Best of all, Terraform can do all of this in under 30 seconds without using a web interface.
    18  
    19  ## Multi-Tier Applications
    20  
    21  A very common pattern is the N-tier architecture. The most common 2-tier architecture is
    22  a pool of web servers that use a database tier. Additional tiers get added for API servers,
    23  caching servers, routing meshes, etc. This pattern is used because the tiers can be scaled
    24  independently and provide a separation of concerns.
    25  
    26  Terraform is an ideal tool for building and managing these infrastructures. You can group resources in each tier together, and Terraform will automatically handle the dependencies between each tier. For example, Terraform will ensure the database tier is available before provisioning the web servers and that the load balancers are connected to the web nodes. You can then use Terraform to easily scale each tier by modifying the `count` configuration value. Because resource creation and provisioning is codified and automated, elastically scaling
    27  with load becomes trivial.
    28  
    29  ## Self-Service Clusters
    30  
    31  At a certain organizational size, it becomes very challenging for a centralized
    32  operations team to manage a large and growing infrastructure. Instead it becomes
    33  more attractive to make "self-serve" infrastructure, allowing product teams to
    34  manage their own infrastructure using tooling provided by the central operations team.
    35  
    36  You can use Terraform configuration to codify the knowledge of how to build and scale a service. You can then share these configurations throughout your organization, enabling customer teams to use Terraform to manage their services.
    37  
    38  ## Software Demos
    39  
    40  Modern software is increasingly networked and distributed. Although tools like
    41  [Vagrant](https://www.vagrantup.com/) exist to build virtualized environments
    42  for demos, it is still very challenging to demo software on real infrastructure
    43  which more closely matches production environments.
    44  
    45  Software writers can provide a Terraform configuration to create, provision and
    46  bootstrap a demo on cloud providers like AWS. This allows end users to easily demo the software on their own infrastructure, and even enables tweaking parameters like cluster size to more rigorously test tools at any scale.
    47  
    48  ## Disposable Environments
    49  
    50  It is common practice to have both a production and staging or QA environment.
    51  These environments are smaller clones of their production counterpart, but are
    52  used to test new applications before releasing in production. As the production
    53  environment grows larger and more complex, it becomes increasingly onerous to
    54  maintain an up-to-date staging environment.
    55  
    56  Using Terraform, the production environment can be codified and then shared with
    57  staging, QA or dev. These configurations can be used to rapidly spin up new
    58  environments to test in, and then be easily disposed of. Terraform can help tame
    59  the difficulty of maintaining parallel environments, and makes it practical
    60  to elastically create and destroy them.
    61  
    62  ## Software Defined Networking
    63  
    64  Software Defined Networking (SDN) is becoming increasingly prevalent in the
    65  datacenter, as it provides more control to operators and developers and
    66  allows the network to better support the applications running on top. Most SDN
    67  implementations have a control layer and infrastructure layer.
    68  
    69  You can use Terraform to codify the configuration for software defined networks.
    70  Terraform can then use this configuration to automatically set up and modify settings by interfacing with the control layer. This allows the configuration to be
    71  versioned and changes to be automated. For example, you can [use Terraform to configure AWS VPC](https://registry.terraform.io/providers/hashicorp/aws/latest/docs/resources/vpc).
    72  
    73  ## Resource Schedulers
    74  
    75  In large-scale infrastructures, static assignment of applications to machines
    76  becomes increasingly challenging. To solve that problem, there are a number
    77  of schedulers like Borg, Mesos, YARN, and Kubernetes. These can be used to
    78  dynamically schedule Docker containers, Hadoop, Spark, and many other software
    79  tools.
    80  
    81  Terraform is not limited to physical providers like AWS. Resource schedulers
    82  can be treated as a provider, enabling Terraform to request resources from them.
    83  This allows Terraform to be used in layers: to setup the physical infrastructure
    84  running the schedulers as well as provisioning onto the scheduled grid.
    85  
    86  ## Multi-Cloud Deployment
    87  
    88  It's often attractive to spread infrastructure across multiple clouds to increase fault-tolerance. By using only a single region or cloud provider, fault tolerance is limited by the availability of that provider. Multi-cloud deployment allows for more graceful recovery of the loss of a region or entire provider.
    89  
    90  Realizing multi-cloud deployments can be very challenging as many existing tools
    91  for infrastructure management are cloud-specific. Terraform is cloud-agnostic
    92  and allows a single configuration to be used to manage multiple providers, and
    93  to even handle cross-cloud dependencies. This simplifies management and orchestration, helping operators build large-scale multi-cloud infrastructures.