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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. The new Amazon capability enables customers to improve the startup latency of their functions from several seconds to as low as sub-second (up to 10 times faster) at P99 (the 99th latency percentile). Understand and optimize your architecture.

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Dynatrace supports the newly released AWS Lambda Response Streaming

Dynatrace

Dynatrace is a launch partner in support of AWS Lambda Response Streaming , a new capability enabling customers to improve the efficiency and performance of their Lambda functions. This enhancement allows AWS users to stream response payloads back to clients. To learn more about the AWS Lambda features, visit the Lamba features page.

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Implementing AWS well-architected pillars with automated workflows

Dynatrace

If you use AWS cloud services to build and run your applications, you may be familiar with the AWS Well-Architected framework. These workflows also utilize DavisĀ® , the Dynatrace causal AI engine, and all your observability and security data across all platforms, in context, at scale, and in real-time.

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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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Supercomputing Predictions: Custom CPUs, CXL3.0, and Petalith Architectures

Adrian Cockcroft

Hereā€™s some predictions Iā€™m making: Jack Dongarraā€™s efforts to highlight the low efficiency of the HPCG benchmark as an issue will influence the next generation of supercomputer architectures to optimize for sparse matrix computations. Next generation architectures will use CXL3.0 Next generation architectures will use CXL3.0

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So many bad takes?ā€”?What is there to learn from the Prime Video microservices to monolith story

Adrian Cockcroft

Then they tried to scale it to cope with high traffic and discovered that some of the state transitions in their step functions were too frequent, and they had some overly chatty calls between AWS lambda functions and S3. A real-time user experience analytics engine for live video, that looked at all users rather than a subsample.

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Optimizing your Kubernetes clusters without breaking the bank

Dynatrace

The Akamas vision is that only an autonomous optimization approach powered by AI can effectively enable performance engineers, SREs, and architects to identify the best configurations that ensure maximum service performance and resilience, at the lowest possible cost and at business speed. below 500ms) and error rates (e.g. lower than 2%.).

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