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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

This allows teams to sidestep much of the cost and time associated with managing hardware, platforms, and operating systems on-premises, while also gaining the flexibility to scale rapidly and efficiently. AWS Lambda functions are an example of how a serverless framework works: Developers write a function in a supported language or platform.

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Bringing the Magic of Amazon AI and Alexa to Apps on AWS.

All Things Distributed

Last week, I wrote a blog about helping the machine learning scientist community select the right deep learning framework from among many we support on AWS such as MxNet, TensorFlow, Caffe, etc. Developers can build, test, and deploy chatbots directly from the AWS Management Console. Amazon Lex.

AWS 165
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Get out-of-the-box visibility into your ARM platform (Early Adopter)

Dynatrace

The investment continues—we’re anticipating an upcoming release of the AWS Graviton2 processor , which has already been announced to be significantly more powerful than its predecessor. Other distributions like Debian and Fedora are available as well, in addition to other software like VMware, NGINX, Docker, and, of course, Java.

Java 134
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Full visibility into your serverless applications with AI-powered Azure Functions monitoring (GA)

Dynatrace

Dynatrace is thrilled to announce the General Availability of support for both the 2.x With Azure Functions, engineers don’t have to worry about provisioning and maintaining underlying hardware; they simply upload their code, and it’s up and running seconds later. So stay tuned! Azure Functions in a nutshell. What’s next.

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Document Model Support in DynamoDB: Flexibility, Availability, Performance, and Scale.Together at last

All Things Distributed

We designed DynamoDB to operate with at least 99.999% availability. We started with Amazon Dynamo, a simple key-value store that was built to be highly available and scalable to power various mission-critical applications in Amazon’s e-commerce platform. In 2012, we launched Amazon DynamoDB, the successor to Amazon Dynamo.

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Infinitely scalable machine learning with Amazon SageMaker

All Things Distributed

At AWS, we continue to strive to enable builders to build cutting-edge technologies faster in a secure, reliable, and scalable fashion. Now, thousands of customers are trying Amazon SageMaker and building ML models on top of their data lakes in AWS. Post-training model tuning and rich states. Acceleration and distribution.

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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes. Logs can include data about user inputs, system processes, and hardware states. In fact, the global log management market is expected to grow from 1.9 billion in 2020 to $4.1

Analytics 218