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The State of DevOps Automation assessment: How automated are you?

Dynatrace

In response to the scale and complexity of modern cloud-native technology, organizations are increasingly reliant on automation to properly manage their infrastructure and workflows. It addresses the extent to which an organization prioritizes automation efforts, including budgets, ROI models, standardized best practices, and more.

DevOps 191
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DevOps observability: A guide for DevOps and DevSecOps teams

Dynatrace

From site reliability engineering to service-level objectives and DevSecOps, these resources focus on how organizations are using these best practices to innovate at speed without sacrificing quality, reliability, or security. SRE applies software engineering principles to operations and infrastructure processes.

DevOps 203
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SRE vs DevOps: What you need to know

Dynatrace

The events of 2020 accelerated the trend of organizations shifting to cloud-native technologies in response to the dramatic increase in demand for online services. Cloud-native environments bring speed and agility to software development and operations (DevOps) practices. Adopting these practices is a culture shift.

DevOps 191
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Dynatrace Perform 2024 Guide: Deriving business value from AI data analysis

Dynatrace

Companies now recognize that technologies such as AI and cloud services have become mandatory to compete successfully. AI data analysis can help development teams release software faster and at higher quality. In what follows, we explore these key cloud observability trends in 2024.

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Up your quality and agility factor – using automation to build “performance-as-a-self-service”

Dynatrace

By 2023, over 500 million digital apps and services will be developed and deployed using cloud-native approaches. For software engineering teams, this demand means not only delivering new features faster but ensuring quality, performance, and scalability too. Industry apps explosion.

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Scaling Appsec at Netflix (Part 2)

The Netflix TechBlog

This approach has also allowed us to build strong relationships with central engineering teams at Netflix (Data Platform, Developer Tools, Cloud Infrastructure, IAM Product Engineering) that will continue to serve as central points of leverage for security in the long term. However, it has not been all sunshine and rainbows.

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Cloudy with a high chance of DBMS: a 10-year prediction for enterprise-grade ML

The Morning Paper

Enterprises in every industry are developing strategies for digitally transforming their businesses at every level. Many of the software engineering discipline and controls need to be brought over into an ML context. " Training in the cloud and the need for much better governance are both pretty uncontroversial directions.