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AWS observability: AWS monitoring best practices for resiliency

Dynatrace

Like general observability , AWS observability is the capacity to measure the current state of your AWS environment based on the data it generates, including its logs, metrics, and traces. AWS Lambda. AWS Lambda makes it easy to design, run, and maintain application systems without having to provision or manage infrastructure.

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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

AWS Lambda functions are an example of how a serverless framework works: Developers write a function in a supported language or platform. AWS Lambda allows developers to use NodeJS or Python while you can control nearly every detail of a REST API. Pay Per Use. With a pay-per-use model, resources never go to waste.

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AWS and Dynatrace automation hit the jackpot at Perform Las Vegas

Dynatrace

In the past, setting up all the hosts, clusters, and demo applications was a manual process that was very time consuming and error-prone. All the infrastructure to run the applications used for the sessions were created using CloudFormation and Lambda. Dynatrace AWS monitoring with CloudWatch metrics and metadata. Automation.

AWS 169
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What is Google Cloud Functions?

Dynatrace

In a time when modern microservices are easier to deploy, GCF, like its counterparts AWS Lambda and Microsoft Azure Functions , gives development teams an agility boost for delivering value to their customers quickly with low overhead costs. Join us for the on-demand Power Demo: Google Cloud Observability for Ops, Apps and Biz Teams.

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

Dynatrace

This release is just the latest addition to advanced observability for cloud-native technologies offered by the Dynatrace Software Intelligence Platform, which provides the fastest and easiest approach to end-to-end monitoring and tracing of web applications on serverless technologies like Azure Functions, Azure App Service, or AWS Lambda.

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

Adrian Cockcroft

For this demo on an old MacBook (2.7 This seems reasonable overhead for a real time algorithm that could be applied to histogram data as part of a metric collection pipeline. > > system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5, > system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5,

Lambda 98
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Full visibility into your serverless applications with AI-powered Azure Functions monitoring (GA)

Dynatrace

This release is just the latest addition to advanced observability for cloud-native technologies offered by the Dynatrace Software Intelligence Platform, which provides the fastest and easiest approach to end-to-end monitoring and tracing of web applications on serverless technologies like Azure Functions, Azure App Service, or AWS Lambda.