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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. For AWS Lambda, the largest contributor to startup latency is the time spent initializing an execution environment, which includes loading function code and initializing dependencies. What is Lambda? What is Lambda SnapStart?

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Dynatrace Support for AWS Lambda Functions Powered by x86 and AWS Graviton2

Dynatrace

Dynatrace is proud to partner with AWS to support AWS Lambda functions powered by x86-based processors and Graviton2 Arm-based processors announced earlier this year. According to the official AWS announcement, Graviton2-based Lambda functions offer up to 34% better price-performance improvement. Dynatrace Data explorer.

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AWS serverless services: Exploring your options

Dynatrace

Amazon compute solutions are designed to streamline resource provisioning and container management with two services: AWS Lambda : Lambda provides serverless compute infrastructure that lets you run code in response to predetermined events or conditions and automatically manage all compute resources required for these processes.

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Hashnode Creates Scalable Feed Architecture on AWS with Step Functions, EventBridge and Redis

InfoQ

The company used serverless services on AWS, including Lambda, Step Functions, EventBridge, and Redis Cache. The solution leverages Step Functions' distributed maps feature that enables high-concurrency processing. Hashnode created a scalable event-driven architecture (EDA) for composing feed data for thousands of users.

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Percentiles don’t work: Analyzing the distribution of response times for web services

Adrian Cockcroft

> system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5, > system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5, > system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5, The normal fitted peaks are then subtracted out of the data.

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Cloudburst: stateful functions-as-a-service

The Morning Paper

Last week we looked at a function shipping solution to the problem; Cloudburst uses the more common data shipping to bring data to caches next to function runtimes (though you could also make a case that the scheduling algorithm placing function execution in locations where the data is cached a flavour of function-shipping too).

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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. Fault-tolerance.

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