AWS Open Source Blog
Open Source News Roundup: April 13, 2018
Open Source News from the AWS Summit San Francisco
The AWS Summit in San Francisco on April 4th saw a slew of announcements, including some in open source:
SAM Implementation is now open source!
“In 2016, we launched SAM and opened up the SAM specification on this Github repo to invite collaborators. We’ve loved your questions, proposals for new features, enhancements to examples, bug reports, and passionate discussions around developing serverless applications.
Today, we are incredibly excited to open source the underlying SAM implementation – the Python code that converts SAM templates to CloudFormation stacks. Now, in addition to proposing changes to the SAM Spec, you can contribute new features and enhancements to all of SAM! You’ll find the code under the samtranslator folder and the tests under the tests directory.” – GitHub, AWS What’s New, Slack Channel
Amazon SageMaker Now Supports Additional Instance Types, Local Mode, Open Sourced Containers, MXNet and Tensorflow Updates
“Today Amazon SageMaker has open sourced the MXNet and Tensorflow deep learning containers that power the MXNet and Tensorflow estimators in the SageMaker SDK. … These containers launch with support for Tensorflow 1.6.0 and MXNet 1.1.0 as well. Tensorflow has a number of new 1.6.0 features including support for CUDA 9.0, cuDNN 7, and AVX instructions which allows for significant speedups in many training applications. MXNet 1.1.0 adds a number of new features including a Text API mxnet.text with support for text processing, indexing, glossaries, and more. Two of the really cool pre-trained embeddings included are GloVe and fastText.” – Randall Hunt in the AWS News blog, AWS What’s New
Build smart chat apps with Amazon machine learning APIs and the PubNub ChatEngine
Adam Bavosa, Open Source Software Engineer at PubNub, explains “how to spin up the PubNub ChatEngine and add Amazon Translate and Amazon Polly for cross-lingual, speech-enabled chat apps that you can embed anywhere.” – AWS Machine Learning blog
And in other news…
Mapping Your Stack
At the Microservices & Cloud-Native Apps Meetup hosted at AWS’ office in Palo Alto in March, 2018, Adrian Cockcroft applied Simon Wardley’s mapping technique to explore and characterize application workloads and decisions about how to evolve the technology stack that supports them. Slides available on github.com/adrianco/slides.
Open Container Initiative Announces Distribution Specification Project
The Open Container Initiative (OCI), an open source community for creating open standards around containers, announced the launch of the Distribution Specification project to standardize container image distribution based on the specification for the Docker Registry HTTP API V2 protocol, which supports the pushing and pulling of container images. – Open Container Initiative announcement
Support for Spark 2.3.0 on Amazon EMR Release 5.13.0
You can now use Apache Spark 2.3.0, Apache HBase 1.4.2, and Presto 0.194 on Amazon EMR release 5.13.0. Spark 2.3.0 adds several new features and updates; more details on AWS What’s New.
New #Amazon SageMaker Notebooks
…showing you how to run TensorFlow and MXNet containers locally: tensorflow_distributed_mnist and mxnet_gluon_mnist – via @julsimon
AWS Lambda Supports Node.js v8.10
You can now develop your AWS Lambda functions using Node.js v8.10. In addition to the leveraging new features in Node.js v8.10 such as the new V8 6.0 engine, Lambda functions written in Node.js 8.10 can now use the async/await pattern to specify error or return values for the function execution. – AWS What’s New
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