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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

This means you no longer have to provision, scale, and maintain servers to run your applications, databases, and storage systems. Lambda functions can be written in the language of your choice, and the service also supports container tools. AWS Step Functions: Step Functions focuses on orchestration. Data Store.

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

Adrian Cockcroft

The documentation is written for people that understand hardcore statistics with lots of greek symbols. I have enough math and stats background that I can muddle along and figure out how to use it, so I’m documenting that here without the greek. > system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5,

Lambda 98
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Top 9 web development trends to expect in 2022

Enprowess

So it is convenient for all to use irrespective of internet speed and it works offline using cached data. Here are some of the most popular toolsets used to design and document APIs: Swagger. IBM OpenWhisk, Microsoft Azure, AWS Lambda, and Google Cloud Functions are famous names that provide server-less services. API Blueprint.

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Optimizing CDN Management Using Terraform

IO River

When you codify infrastructure, you can integrate it with DevOps pipelines to automate various tasks like server provisioning, database scale, and security audits. The Terraform scripts you write not only serve as documentation but also as a disaster recovery plan. This level of granularity is not found in UI-managed systems.Â

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Optimizing CDN Management Using Terraform

IO River

When you codify infrastructure, you can integrate it with DevOps pipelines to automate various tasks like server provisioning, database scale, and security audits. The Terraform scripts you write not only serve as documentation but also as a disaster recovery plan. ‍If AutomationCode-based systems also shine in automation.

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A one size fits all database doesn't fit anyone

All Things Distributed

A common question that I get is why do we offer so many database products? To do this, they need to be able to use multiple databases and data models within the same application. Seldom can one database fit the needs of multiple distinct use cases. Seldom can one database fit the needs of multiple distinct use cases.

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