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Presentation: Effective Performance Engineering at Twitter-Scale

InfoQ

Yao Yue recapitulates scaling a project at Twitter while summarizing some key lessons learned about effective performance engineering. By Yao Yue

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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. Auto Remediation generates recommendations by considering both performance (i.e., Multi-objective optimizations.

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Dynatrace and Red Hat expand enterprise observability to edge computing

Dynatrace

Successful deployments of cloud-native workloads at the edge help to reduce costs, boost performance, and improve customer experience. As organizations see an increasingly high number of compute locations, assessing health and finding root causes of emerging problems across heavily distributed workloads, at scale, has become a daunting task.

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Mitigating risk with AI observability: Dynatrace empowers organizations to embrace AI for all use cases

Dynatrace

From generating new code and boosting developer productivity to finding the root cause of performance issues with ease, the benefits of AI are numerous. Performance analytics Dynatrace hypermodal AI empowers development teams to dig deep into database statements and remediate issues quickly. The first risk is not adopting AI at all.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

While off-the-shelf models assist many organizations in initiating their journeys with generative AI (GenAI), scaling AI for enterprise use presents formidable challenges. This blog post explores how AI observability enables organizations to predict and control costs, performance, and data reliability.

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How Dynatrace empowers performance engineering teams to test at scale

Dynatrace

As organizations develop more applications and microservices, they are discovering they also need to run more performance tests in the same amount of time or less to meet service-level objectives (SLOs) that fulfill service-level agreements (SLAs). Current challenges with performance testing.

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Key Advantages of DBMS for Efficient Data Management

Scalegrid

Despite initial investment costs, DBMS presents long-term savings and improved efficiency through automated processes, efficient query optimizations, and scalability, contributing to enhanced decision-making and end-user productivity.