AWS Open Source Blog
Category: Open Source
Deploy machine learning models to Amazon SageMaker using the ezsmdeploy Python package and a few lines of code
Customers on AWS deploy trained machine learning (ML) and deep learning (DL) models in production using Amazon SageMaker, and using other services such as AWS Lambda, AWS Fargate, AWS Elastic Beanstalk, and Amazon Elastic Compute Cloud (Amazon EC2) to name a few. Amazon SageMaker provides SDKs and a console-only workflow to deploy trained models, and […]
Why Jenkins still continuously serves developers
For an estimated 15 million developers, Jenkins is synonymous with countless iterations of collectible stickers of the iconic, non-assuming butler that have adorned their laptops all over the world. The butler is representative of the ubiquitous open source continuous integration (CI) technology that has quietly automated an endless set of development tasks for well over […]
What is Deno?
Deno 1.0, a runtime for JavaScript and TypeScript, rolled out in May with appealing features for JavaScript developers, including: Secure defaults: Explicit permission must be granted for your Deno applications in order to access disk, network, and runtime environments. Native TypeScript support: No tsconfig needed—Deno acts like a native TypeScript runtime. Under the hood Deno […]
Generate Python, Java, and .NET software libraries from a TypeScript source
As builders and developers, many of us are aware of the principle of Don’t Repeat Yourself (or DRY) and practice it every day. Entire runtimes and programming languages have been developed by taking that principle to an even higher level, with the core idea of writing software once and having it run on many different […]
Continuous delivery with server-side Swift on Amazon Linux 2
In January, I published an article describing how to use AWS tools to build, test, and release server-side Swift code on two platforms: Amazon Elastic Container Service (Amazon ECS) and Elastic Compute Cloud (Amazon EC2) running Ubuntu Linux. Recently Swift.org has released official support for the Amazon Linux 2 operating system. This article is a […]
Monitor AWS services used by Kubernetes with Prometheus and PromCat
AWS offers Amazon CloudWatch to provide observability of the operational health for your AWS resources and applications through logs, metrics, and events. CloudWatch is a great way to monitor and visualize AWS resources metrics and logs. Recently I’ve found that some customers are adopting Prometheus as their monitoring standard because it offers the ability to […]
Automating your ECS container architecture deployments with ECS ComposeX
This is a guest post by a third-party author. John Preston is an experienced solution architect who enjoys development and who has spent time working on and open sourcing the automation of AWS architecture deployments, including the ECS ComposeX open source project. In this post, John talks about the motivation for this project, and how […]
Deploy, track, and roll back RDS database code changes using open source tools Liquibase and Jenkins
Customers across industries and verticals deal with relational database code deployment. In most cases, developers rely on database administrators (DBAs) to perform the database code deployment. This works well when the number of databases and the amount of database code changes are low. As organizations scale, however, they deal with different database engines—including Oracle, SQL […]
Introducing Heapothesys, an open source Java GC latency benchmark with predictable allocation rates
The Amazon Corretto team introduces the open source Heapothesys benchmark, a synthetic workload that simulates fundamental application characteristics that affect garbage collector (GC) latency. The benchmark creates and tests GC load scenarios defined by object allocation rates, heap occupancy, and JVM flags, then reports the resulting JVM pauses. OpenJDK developers can thus produce reference points […]
Adopting machine learning in your microservices with DJL (Deep Java Library) and Spring Boot
Many AWS customers—startups and large enterprises—are on a path to adopt machine learning and deep learning in their existing applications. The reasons for machine learning adoption are dictated by the pace of innovation in the industry, with business use cases ranging from customer service (including object detection from images and video streams, sentiment analysis) to […]