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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It is clear that distributed in-stream data processing has something to do with query processing in distributed relational databases. Basics of Distributed Query Processing.

Big Data 154
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Kubernetes in the wild report 2023

Dynatrace

The strongest Kubernetes growth areas are security, databases, and CI/CD technologies. Strongest Kubernetes growth areas are security, databases, and CI/CD technologies. Of the organizations in the Kubernetes survey, 71% run databases and caches in Kubernetes, representing a +48% year-over-year increase. Java, Go, and Node.js

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No need to compromise visibility in public clouds with the new Azure services supported by Dynatrace

Dynatrace

In addition to providing visibility for core Azure services like virtual machines, load balancers, databases, and application services, we’re happy to announce support for the following 10 new Azure services, with many more to come soon: Virtual Machines (classic ones). Effortlessly optimize Azure database performance.

Azure 147
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A guide to Autonomous Performance Optimization

Dynatrace

Stefano started his presentation by showing how much cost and performance optimization is possible when knowing how to properly configure your application runtimes, databases, or cloud environments: Correct configuration of JVM parameters can save up to 75% resource utilization while delivering same or better performance!

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RSA Guide 2023: Cloud application security remains core challenge for organizations

Dynatrace

This includes collecting metrics, logs, and traces from all applications and infrastructure components. Meanwhile, traditional databases have demonstrated limitations in increasingly complex and distributed cloud-native environments. Only 27% of those CIOs say their teams fully adhere to a DevOps culture.

Cloud 185
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What is IT operations analytics? Extract more data insights from more sources

Dynatrace

Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information. Here are the six steps of a typical ITOA process : Define the data infrastructure strategy. Choose a repository to collect data and define where to store data.

Analytics 186
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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 184