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Dynatrace launches automatic end-to-end observability via traces for AWS Lambda (Preview program)

Dynatrace

Now Dynatrace is pleased to announce another industry first: automatic, end-to-end observability for AWS Lambda functions in Node.js By leveraging the AWS Lambda Extensions API , Dynatrace brings the unique value of its Davis AI-engine for fully automatic root cause analysis to AWS Lambda. and Python via traces.

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Dynatrace supports SnapStart for Lambda as an AWS launch partner

Dynatrace

Dynatrace is proud to be an AWS launch partner in support of Amazon Lambda SnapStart. Today, application modernization efforts are centered on application programming interfaces and microservices that are sensitive to startup latency. What is Lambda? What is Lambda SnapStart? How does Dynatrace help?

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What is AWS Lambda?

Dynatrace

The 2014 launch of AWS Lambda marked a milestone in how organizations use cloud services to deliver their applications more efficiently, by running functions at the edge of the cloud without the cost and operational overhead of on-premises servers. What is AWS Lambda? Where does Lambda fit in the AWS ecosystem? Dynatrace news.

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Weighing a microservices approach means covering all architecture bases

Dynatrace

Then, they can split these services into functional application programming interfaces (APIs), rather than shipping applications as one large, collective unit. Microservice design patterns allow developers to use their preferred programming language or framework, which helps to prevent employee churn and the need for outsourced talent.

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Stuff The Internet Says On Scalability For August 17th, 2018

High Scalability

@coryodaniel : Rewrote an #AWS APIGateway & #lambda service that was costing us about $16000 / month in #elixir. it’s not Serverless anymore it’s running in a few containers on a kubernetes cluster. Its running in 3 nodes that cost us about $150 / month. myelixirstatus !#Serverless.No Serverless.No

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Cloudburst: stateful functions-as-a-service

The Morning Paper

Today’s paper choice is a fresh-from-the-arXivs take on serverless computing from the RISELab at Berkeley, addressing some of the limitations outlined in last year’s ‘ Berkeley view on serverless computing.’ Programming model. Cloudburst programs are written in Python. arXiv 2020.

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Expanding the Cloud: Amazon Machine Learning Service, the Amazon Elastic Filesystem and more

All Things Distributed

Amazon ML is highly scalable and can generate billions of predictions, and serve those predictions in real-time and at high throughput. When we designed Amazon EFS we decided to build along the AWS principles: Elastic, scalable, highly available, consistent performance, secure, and cost-effective. Amazon Lambda.

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