Here at Pulumi, everyone on our engineering team is a Gopher. Go has quickly become the “language of the cloud,” and so when we chose to build our open-source pulumi/pulumi engine and SaaS backend, we chose Go. As such, we are very excited to welcome Go to the family of supported infrastructure as code languages as part of Pulumi 2.0. What is Pulumi? Go has become the lingua franca of cloud-native infrastructure development.
Scheduling events has long been an essential part of automation; many tasks need to run at specific times or intervals. You could be checking StackOverflow for new questions every 20 minutes or compiling a report that is emailed every other Friday at 4:00 pm. Today, many of these tasks can be efficiently accomplished in the cloud. While each cloud has its flavor of scheduled functions, this post steps you through an example using AWS CloudWatch with the help of Pulumi.
We are excited to announce the release of Audit Logs on Pulumi for Enterprise organizations. Audit logs enable you to track the activity of users within an organization. They attempt to answer what a user did, when they did it and where. They help answer these questions by recording user actions. Pulumi’s audit logs allow you to account for the activity your users are taking within your organization. These logs are available to organizations with an Enterprise level subscription.
In an earlier article, we introduced examples of Policy as Code to prevent two of the most common causes of data breaches. Policies are the guardrails of infrastructure. They control access, set limits, and manage how infrastructure operates. In many systems, policies are created by clicking on a GUI, making it difficult to replicate or version. Pulumi implements policy by writing it in Typescript, which ensures that you can write policies using software development practices such as automated testing, deployment, and version control.
AWS Step Functions lets you build applications by connecting AWS services. Daisy-chaining steps into a workflow simplifies application development by creating a state machine diagram which shows how services are connected to each other in your application. We’ll go into the details of creating a lambda function, IAM roles and policies, and creating a workflow. Once we have the example deployed, we’ll walk through the process of adding another function and step to the workflow. Included in the walkthrough is a discussion of one of the aspects of the Pulumi programming model. The goal of this article is to provide a foundation for building your application using serverless workflows.
Modern applications have brought many benefits and improvements, including the ability to scale and rapid iterations to update software. However, this has come at the cost of complexity. Modern infrastructure is composed of many resources that require detailed configuration to work correctly and securely. Even managed solutions from cloud service providers need additional configuration to ensure that services are secure and free of defects. Cloud providers, such as AWS, do allow you to create policies to ensure that applications are secure, but they are specific to resources that are already deployed. A significant benefit of Policy as Code is the ability to verify and spot problems before deploying your infrastructure.
Google Cloud Run is the latest addition to the serverless compute family. While it may look similar to existing services of public cloud, the feature set makes Cloud Run unique: Docker as a deployment package enables using any language, runtime, framework, or library that can respond to an HTTP request. Automatic scaling, including scale to zero, means you pay for what you consume with no fixed cost and no management overhead.
Whether it’s an IoT installation, a website, or a mobile app, modern software systems generate a trove of usage and performance data. While it can be daunting to collect and manage, surfacing data empowers the business to make informed product investments. In this article, we’ll explore the following: An overview of the traditional Redshift analytics stack on AWS, the use cases it excels at, and where it falls apart.
Pulumi has many resource providers that allow you to interact with your favorite cloud or resource. There are times when a provider may not deliver on the specific task that you want to accomplish. Dynamic Providers can be a powerful tool to help accomplish your infrastructure tasks.
The Amazon Web Services (AWS) Cloud ecosystem is large and vibrant, so vast and vibrant that at times, it can be challenging to know where best to start! In the case of containers, Abby Fuller tweeted a descriptive summary about using AWS container services.
