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Kubernetes in the wild report 2023

Dynatrace

The report also reveals the leading programming languages practitioners use for application workloads. The strongest Kubernetes growth areas are security, databases, and CI/CD technologies. are the top 3 programming languages for Kubernetes application workloads. Kubernetes is emerging as the “operating system” of the cloud.

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DBaaS Pros & Cons

Scalegrid

In today’s rapidly evolving digital landscape, the way we manage databases is undergoing a transformative shift. The rise of Database-as-a-Service (DBaaS) is not just a trend but a strategic response to the growing complexities of data management. However, using a database as a service is not without its set of challenges.

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Understanding What Kubernetes Is Used For: The Key to Cloud-Native Efficiency

Percona

If you have any experience working with database software, you have undoubtedly heard the term Kubernetes a lot. Your workloads, encapsulated in containers, can be deployed freely across different clouds or your own hardware. You may already be using it daily and find it makes running applications in the cloud much more manageable.

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Generative AI in the Enterprise

O'Reilly

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. Many AI adopters are still in the early stages.

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What Is Hyperautomation?

O'Reilly

We’ll see it in healthcare. Selenium , the first tool for automated browser testing (2004), could be programmed to find fields on a web page, click on them or insert text, click “submit,” scrape the resulting web page, and collect results. We’ll see it in the processing of the thousands of documents businesses handle every day.

Games 116
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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Application developers often deploy IMDGs as a distributed cache that sits between an application and its database; the IMDG offloads ephemeral data from the database. Offloading the database boosts performance, reduces bottlenecks, and lowers costs. That’s where performance problems can begin.

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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Application developers often deploy IMDGs as a distributed cache that sits between an application and its database; the IMDG offloads ephemeral data from the database. Offloading the database boosts performance, reduces bottlenecks, and lowers costs. That’s where performance problems can begin.