Examples for the Pulumi Automation API https://pkg.go.dev/github.com/pulumi/pulumi/sdk/v3/go/auto?tab=doc
Go
automation-api-examples
This repo provides full end to end examples and walk-throughs for the Pulumi Automation API. The Automation API is available for Go, Node.js, Python and C#.
Use Automation API with an inline Pulumi program. Inline programs are self contained in a single main.go and support full debugging capabilities. In this demo we deploy the same static S3 website adapted from the Pulumi examples repo.
This example shows how to use Automation API with an existing traditional CLI-driven Pulumi program. We add an Automation API deployment program to our Fargate program that deploys a web service via a Fargate task behind a load balancer.
This example shows how to refactor your infrastructure to get the best of both worlds, a debuggable inline program that can still be driven by the Pulumi CLI for convenience (one-off deployments, inspecting the stack, retrieving outputs, etc). In this example we deploy an S3 static website. The automation/main.go is fully debuggable, including the shared deployment function. The stack can also be managed via the CLI program in cli/main.go.
This example shows how to use Automation API to tame the complexity of multiple stacks with dependent stack outputs. We decompose our S3 static website into two stacks, one that manages the bucket, and another that manages the index.html file. Both of these are defined as inline programs, and are deployed and destroyed together via a single main.go
This application demonstrates how to run Automation API in an HTTP server to expose infrastructure as RESTful resources. In our case, we've defined and exposed a static website site that exposes all of the CRUD operations plus list. Users can hit our REST endpoint and create custom static websites by specifying the content field in the POST body. All of our infrastructure is defined in inline programs that are constructed and altered on the fly based on input parsed from user-specified POST bodies.
This example provisions an AWS Aurora SQL database and executes a database "migration" using the resulting connection info. This migration creates a table, inserts a few rows of data, and reads the data back to verify the setup. This is all done in a single program using an inline Pulumi program. With Automation API you can orchestrate complex workflows that go beyond infrastructure provisioning and into application management, database setup, etc.
Use Automation API with an inline Pulumi program. Inline programs are self-contained in a single index.ts and support full debugging capabilities. In this demo we deploy the same static S3 website adapted from the Pulumi examples repo. This example uses typescript with ts-node as an execution environment.
Use Automation API with an inline Pulumi program. Inline programs are self-contained in a single index.ts and support full debugging capabilities. In this demo we deploy the same static S3 website adapted from the Pulumi examples repo. This example uses typescript compiled into javascript via tsc and executed via node.
Use Automation API with an inline Pulumi program. Inline programs are self-contained in a single index.js and support full debugging capabilities. In this demo we deploy the same static S3 website adapted from the Pulumi examples repo. This example uses plain javascript executed via node.
This example shows how to use Automation API with an existing traditional CLI-driven Pulumi program. We add an Automation API deployment program to our existing CLI-driven S3 website program. This example uses typescript with ts-node as an execution environment.
This example shows how to use Automation API in typescript with an existing traditional CLI-driven Pulumi program written in a different language, in this case go. We add an Automation API deployment program to our Fargate program that deploys a web service via a Fargate task behind a load balancer. This automation program uses typescript with ts-node as an execution environment.
This application demonstrates how to run Automation API in an HTTP server to expose infrastructure as RESTful resources. In our case, we've defined and exposed a static website site that exposes all of the CRUD operations plus list. Users can hit our REST endpoint and create custom static websites by specifying the content field in the POST body. All of our infrastructure is defined in inline programs that are constructed and altered on the fly based on input parsed from user specified POST bodies.
This example provisions an AWS Aurora SQL database and executes a database "migration" using the resulting connection info. This migration creates a table, inserts a few rows of data, and reads the data back to verify the setup. This is all done in a single program using an inline Pulumi program. With Automation API you can orchestrate complex workflows that go beyond infrastructure provisioning and into application management, database setup, etc.
This example shows how to use Automation API with an existing traditional CLI-driven Pulumi program alongside some mocha-based integration tests to ensure that the infrastructure was set up properly. This example uses typescript with ts-node as an execution environment, with mocha being used to run the tests.
Use Automation API with an inline Pulumi program. Inline programs are self contained in a single main.py and support full debugging capabilities. In this demo we deploy the same static S3 website adapted from the Pulumi examples repo.
This example shows how to use Automation API in python with an existing traditional CLI-driven Pulumi program written in a different language, in this case go. We add an Automation API deployment program to our Fargate program that deploys a web service via a Fargate task behind a load balancer.
This example provisions an AWS Aurora SQL database and executes a database "migration" using the resulting connection info. This migration creates a table, inserts a few rows of data, and reads the data back to verify the setup. This is all done in a single program using an inline Pulumi program. With Automation API you can orchestrate complex workflows that go beyond infrastructure provisioning and into application management, database setup, etc.
This example shows how to use Automation API with an existing traditional CLI-driven Pulumi program. We add an Automation API deployment program to our existing CLI-driven app described in the aws-py-voting-app example.
This application demonstrates how to run Automation API in an HTTP server to expose infrastructure as RESTful resources. In our case, we've defined and exposed a static website site that exposes all of the CRUD operations plus list. Users can hit our REST endpoint and create custom static websites by specifying the content field in the POST body. All of our infrastructure is defined in inline programs that are constructed and altered on the fly based on input parsed from user specified POST bodies.
Use Automation API with an inline Pulumi program. Inline programs are self contained in a .NET console application and support full debugging capabilities. In this demo we deploy the same static S3 website adapted from the Pulumi examples repo.
This example shows how to use Automation API with an existing traditional CLI-driven Pulumi program. We add an Automation API deployment program to our existing CLI-driven S3 website program.
This example shows how to use Automation API in dotnet with an existing traditional CLI-driven Pulumi program written in a different language, in this case go. We add an Automation API deployment program to our Fargate program that deploys a web service via a Fargate task behind a load balancer.
This example provisions an AWS Aurora SQL database and executes a database "migration" using the resulting connection info. This migration creates a table, inserts a few rows of data, and reads the data back to verify the setup. This is all done in a single program using an inline Pulumi program. With Automation API you can orchestrate complex workflows that go beyond infrastructure provisioning and into application management, database setup, etc.