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Tech Transforms podcast: Navigating complex cloud environments and improving efficiency

Dynatrace

Make sure to stay connected with our social media pages. UK Home Office: Metrics meets service The UK Home Office is the lead government department for many essential, large-scale programs. Tag us with #TechTransforms to be featured on our pages! It also helps reduce the agency’s carbon footprint.

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Rising Tide Rents and Robber Baron Rents

O'Reilly

Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.” Even social media started with the promise of information triage: for each person, a unique feed of updates from only the friends they had chosen to follow.

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OpenShift vs. Kubernetes: Understanding the differences

Dynatrace

IT teams can’t see into the internal state of Kubernetes containers , so they often collect a wide variety of telemetry data — such as logs, metrics, and distributed traces — to compensate for this lack of visibility. Like Kubernetes, it allocates resources efficiently and ensures high availability and fault tolerance.

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How digital experience monitoring helps deliver business observability

Dynatrace

Fast, consistent application delivery creates a positive user experience that can ultimately drive customer loyalty and improve business metrics like conversion rate and user retention. Expanding on the traditional observability pillars of metrics, logs, and traces, DEM collects user experience data to complete the end-to-end picture.

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How Dynatrace uses Dynatrace to combat the Log4j vulnerability (Log4Shell)

Dynatrace

As organizations started learning about Log4Shell from news feeds, blogs, and social media, the Dynatrace security team—and Dynatrace Application Security—kicked into action. On December 9, 2021, the first indicators of the Log4j vulnerability (Log4Shell) began to reverberate across the world.

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What is an A/B Test?

The Netflix TechBlog

We wait, and we then compare the values of a variety of metrics from Group A to those from Group B. Some metrics will be specific to the given hypothesis. We then compare metrics between the two groups. How do we most efficiently analyze the data? Here, Group B receives the Upside Down box art.

Testing 245
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To understand the risks posed by AI, follow the money

O'Reilly

The problems fostered by social media, search, and recommendation algorithms was never an engineering issue, but one of financial incentives (of profit growth) not aligning with algorithms’ safe, effective, and equitable deployment. User preferences were downgraded in algorithmic importance in favour of more profitable content.