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How Red Hat and Dynatrace intelligently automate your production environment

Dynatrace

Problem remediation is too time-consuming According to the DevOps Automation Pulse Survey 2023 , on average, a software engineer takes nine hours to remediate a problem within a production application. Context-rich tickets can be created in systems like Jira or ServiceNow for traceability and compliance.

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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data.

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Extend the AI and automation core of Dynatrace with host extensions to resolve infrastructure problems

Dynatrace

GPU-based machine learning system crashes, and you don’t know why? All the data bound to hosts is analyzed by the Davis AI causation engine and made available on custom dashboards and events pages. One of our software engineers, Tomasz Gajger, has been involved in a research project related to GPU performance analysis.

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Unlock the Power of DevSecOps with Newly Released Kubernetes Experience for Platform Engineering

Dynatrace

Platform engineering is on the rise. According to leading analyst firm Gartner, “80% of software engineering organizations will establish platform teams as internal providers of reusable services, components, and tools for application delivery…” by 2026. Automation, automation, automation.

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Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Netflix TechBlog

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and Efficiency By: Di Lin , Girish Lingappa , Jitender Aswani Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question?—?“Can

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Software engineering for machine learning: a case study

The Morning Paper

Software engineering for machine learning: a case study Amershi et al., More specifically, we’ll be looking at the results of an internal study with over 500 participants designed to figure out how product development and software engineering is changing at Microsoft with the rise of AI and ML. ICSE’19.

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Site reliability done right: 5 SRE best practices that deliver on business objectives

Dynatrace

Keeping pace with modern digital transformation requires ensuring that applications are responsive, resilient, and always available amid increased complexity. Site reliability engineering (SRE) has recently become a critical discipline in recent years as the world has shifted in favor of web-based interactions.