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Reinventing our Dynatrace Core Values

Dynatrace

During this time, Rick and Bernd had also started to identify where they wanted to lead our people, aligned with their principles and tenets, and building on the values that have made us successful. This top-bottom and bottom-top approach gave us the right tools to redesign our values.

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5 DNS Troubleshooting Tips for Network Teams

DZone

Unfortunately, the reliability of DNS often causes us to take it for granted. It’s easy to write DNS off as a background service precisely because it performs so well. Yet this very “set it and forget it” strategy often creates blind spots for network teams by leaving performance and reliability issues undiagnosed.

Network 342
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How platform engineering and IDP observability can accelerate developer velocity

Dynatrace

As a result, teams can focus on writing code and building features rather than dealing with infrastructure nuances. “[An IDP] must be a product that developers want to use because it helps them get the job done,” Grabner said. They shouldn’t worry about the platform; they should just start writing code.”

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Tech Transforms podcast: The path forward for AI in the government

Dynatrace

federal government, agencies are leveraging AI tools for more than 700 use cases. During Episode 79 of the Tech Transforms podcast , Dr. Amy Hamilton joined us to discuss AI in the government. .” 1 Within the U.S. There are many ethical, societal, and workplace-related questions about this technology.

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3. Psyberg: Automated end to end catch up

The Netflix TechBlog

Write-Audit-Publish (WAP) Process This is the general pattern we use in our ETL pipelines. Write Apply the ETL business logic to the input data identified in Step 1 and write to an unpublished iceberg snapshot based on the Psyberg mode b. This also enables us to update the Psyberg layer without touching the workflows.

Tuning 244
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In Defence of DOM­Content­Loaded

CSS Wizardry

Honestly, I started writing this article, for no real reason and somewhat without context, in December 2022—over half a year ago! Not massively helpful, but an insight nonetheless, and at least shows us that the lab-based 12s is unlikely to be felt by anyone other than extreme outliers in the field. Or are they…?

Metrics 326
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2. Diving Deeper into Psyberg: Stateless vs Stateful Data Processing

The Netflix TechBlog

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.