AWS Lambda cold starts (the time it takes for AWS to assign a worker to a request) are a major frustration point of many serverless programmers. In this article, we will take a look at the problem of latency-critical serverless applications, and how Provisioned Concurrency impacts the status-quo. Concurrency Model of AWS Lambda Despite being serverless, AWS Lambda uses lightweight containers to process incoming requests. Every container, or worker, can process only a single request at any given time.
A big part of our vision with Pulumi is to bring application developers and infrastructure teams closer together in the cloud. That includes both providing infrastructure teams with better software engineering tools, as well as providing developers with easier access to cloud infrastructure. We are often inspired by looking at great software engineering experiences in other development stacks and applying them to the cloud infrastructure space. Whether it be general-purpose languages and rich IDEs, testing and package management, or components and rich APIs, at Pulumi, we’ve repeatedly applied successful development tools and practices to the challenges of building and scaling modern cloud infrastructure.
Azure Functions is a managed service for serverless applications in the Azure cloud. More broadly, Azure Functions is a runtime with multiple hosting possibilities. KEDA (Kubernetes-based Event-Driven Autoscaling) is an emerging option to host this runtime in Kubernetes.
In the first part of this post, I compare KEDA with cloud-based scaling and outline the required components. In the second part, I define infrastructure as code to deploy a sample KEDA application to an Azure Kubernetes Service (AKS) cluster.
The result is a fully working example and a high-level idea of how it works. Kubernetes expertise is not required!
In this post, we’ll take a look at 10 “pearls”—bite-sized code snippets—that demonstrate using Pulumi to build serverless applications with Azure Functions and infrastructure as code. These pearls are organized into four categories, each demonstrating a unique scenario:
- Function App Deployment: Deploy an existing Azure Functions application using infrastructure as code.
- Cloud Event Handling: Leverage a variety of event sources available to Azure Functions with lightweight event handlers.
- Data Flows with Function Bindings: Take advantage of function bindings—declarative connectors to Azure services.
Today, I will build a serverless application with both the data store and the HTTP endpoint located close to end users to ensure prompt response time. The entire application runs on top of managed Azure services and is defined as a single Pulumi program in TypeScript.
Guest Author: Chris Toomey, Solution Architect Lead @ Mapbox
With 8 billion+ connected IoT devices and 2 billion GPS-equipped smartphones already online, logistics businesses are tracking assets at every step in the supply chain. At this scale and complexity, it is imperative to have a flexible way to ingest, process, and act upon this data, without sacrificing security or best practices.
Amazon Web Services provides an incredible platform for developers to build cloud-native applications, and is used by millions of customers of all sizes. The building block services that AWS offers enable teams to offload undifferentiated heavy-lifting to AWS. To maximally benefit from these services though, cloud engineering teams must learn how to compose all of these building blocks together to build and deliver their own applications. Today, this is still too hard. Getting from your laptop to a production-ready AWS deployment frequently takes days or weeks instead of minutes or hours. And AWS building block services frequently leave you to re-implement (and re-discover) best-practices instead of providing these as smart defaults.
Pulumi Crosswalk for AWS is a new open source library of infrastructure-as-code components that make it easier to get from zero to production on AWS, easier to adopt AWS best practices by default, and easier to evolve your AWS infrastructure as your application needs mature.
Today’s guest post is from Mikhail Shilkov, a Microsoft Azure MVP and early Pulumi user and contributor - enjoy!
Serverless compute services, like Azure Functions, offer an amazing power to application developers to leverage: highly available, automatically scaled, low-ceremony, pay-per-value functions created in several lines of code.
Creating serverless applications just got even easier! You can now protect your application APIs in just three easy steps. We’ve already posted about how easy it is to create serverless apps in Pulumi. Now, we’re helping you simplify protecting those apps with API Gateway and Lambda authorizers.
With Pulumi’s new AWSX package, you can quickly define a Lambda and an AWS Lambda authorizer to protect it. We’re once again harnessing the power of Lambdas as Lambdas to allow developers to focus on writing code.
Today, we will walkthrough creating a simple serverless app using AWS and Pulumi. We will simplify implementing the OAuth protocol by using Auth0 and AWS Lambda authorizers to authorize users. Auth0 provides a universal authentication and authorization platform for applications. It has become an extremely popular platform for user management because Auth0 makes OAuth easy.