We are very excited to announce that we have partnered with GitHub to offer our users better protection for their Pulumi Access Tokens.

By default, Pulumi users manage the state of their cloud infrastructure deployments using https://app.pulumi.com. This service provides state storage, concurrency control, audit history and access controls for both individuals and teams working with Pulumi. Each user and service account can generate one or more Pulumi Access Tokens to be used to authenticate with this service. These access tokens can be used on both local development machines, as well as in CI/CD systems for automated infrastructure deployments. These access tokens are sensitive secrets which should never be shared publicly, and in particular should never be committed to source control.

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Most cloud infrastructure projects involve working with existing cloud resources — either building on top of existing resources or adopting existing resources under management with a new and more robust infrastructure provisioning solution.

Whether you are adopting resources that were deployed manually using your cloud provider’s console or CLI — or migrating existing infrastructure from tools like Terraform or CloudFormation — Pulumi makes it easy to adopt and manage your existing resources.

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Kubernetes clusters from the managed offerings of AWS EKS, Azure AKS, and GCP GKE all vary in configuration, management, and resource properties. This variance creates unnecessary complexity in cluster provisioning and app deployments, as well as for CI/CD and testing.

Additionally, if you wanted to deploy the same app across multiple clusters for specific use cases or test scenarios across providers, subtleties such as LoadBalancer outputs and cluster connection settings can be a nuisance to manage.

In this post, we’ll see how to use Pulumi to deploy the kuard app across EKS, AKS, GKE and a local Kubernetes cluster, such as Docker Desktop or a self-managed cluster. We’ll spin up the clusters in each provider, launch the app, and manage both cluster and app using the TypeScript programming language.

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Every non-trivial application relies on configuration values that may depend on the current execution environment. Some of these values contain sensitive information that shouldn’t be shared publicly. In general, the fewer parties that have access to those secret values, the safer the application will be—in fact, in an ideal world, no one would be granted direct access to those secrets.

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Managed Kubernetes offerings greatly reduce the overhead required in administering Kubernetes. However, the cluster is only one of the components under management, as app lifecycles are self-driven tasks that vary by workloads.

In Kubernetes, node groups are a useful mechanism for creating pools of resources that can enforce scheduling requirements. They also provide a utility for shifting workloads around during cluster management and updates.

In this post, we’ll see how to use Pulumi for Day 2 Kubernetes administration. We’ll spin up a new EKS cluster with two node groups and a given workload. Then we’ll add one more node group with an updated configuration, and migrate the workload over to it with zero downtime using code and kubectl.

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Pulumi recently added support for managing DigitalOcean resources. This article will show you how to deploy some load balanced Droplets on DigitalOcean using Pulumi.

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Last Wednesday, we invited members of our local Seattle community to Pulumi HQ for the July Pulumi Up meetup. The evening began with some networking time wherein our guests met some Pulumi engineers and users they may have only ever interacted with over Pulumi’s Community Slack while enjoying free pizza and beverages. This month’s meetup featured two talks by Pulumi engineers. Application code isn’t the only code that can have APIs Unfortunately, due to travel issues, Paul Stack wasn’t able to join us in person, but graciously agreed to present remotely… from Europe… at 4:00 in the morning.

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The Amazon Elastic File System Container Storage Interface (CSI) Driver implements the CSI specification for container orchestrators to manage the lifecycle of Amazon EFS filesystems. The CSI specification defines an interface along with the minimum operational and packaging recommendations for a storage provider to implement a CSI compatible plugin. The interface declares the RPCs that a plugin must expose. The CSI drivers are the right mechanism to work with, when using a cloud storage component with Kubernetes workloads.

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Testing your infrastructure using familiar tools like Node.js’s Mocha framework allows you to ensure configuration is correct before provisioning, and that the resulting infrastructure has certain desirable properties afterwards. This can enforce team standards, ensure security guidelines are being followed, and so much more. Because Pulumi uses general purpose languages, you can just embed tests alongside your infrastructure-as-code definitions themselves, using a familiar authoring style and reporting experience. In this post, we’ll explore the ins and outs of unit testing your infrastructure.

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Kubernetes Ingress is an API object that allows you manage external (or) internal HTTP[s] access to Kubernetes services running in a cluster. Amazon Elastic Load Balancing Application Load Balancer (ALB) is a popular AWS service that load balances incoming traffic at the application layer across multiple targets, such as Amazon EC2 instances, in a region. ALB supports multiple features including host or path based routing, TLS (Transport layer security) termination, WebSockets, HTTP/2, AWS WAF (web application firewall) integration, integrated access logs, and health checks.

The AWS ALB Ingress controller is a Kubernetes SIG-AWS subproject - it was the second sub-project added to SIG-AWS after the aws-authenticator subproject. The ALB Ingress controller triggers the creation of an ALB and the necessary supporting AWS resources whenever a Kubernetes user declares an Ingress resource on the cluster. TargetGroups are created for each backend specified in the Ingress resource. Listeners are created for every port specified as Ingress resource annotation. When no port is specified, sensible defaults (80 or 443) are used. Rules are created for each path specified in your ingress resource. This ensures that traffic to a specific path is routed to the correct TargetGroup.

In this post, we will work through a simple example of running ALB based Kubernetes Ingresses with Pulumi EKS, AWS, and AWSX packages.

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