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

Dynatrace

Additionally, ITOA gathers and processes information from applications, services, networks, operating systems, and cloud infrastructure hardware logs in real time. Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information.

Analytics 197
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What is a Distributed Storage System

Scalegrid

This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
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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. In addition, we survey the current and emerging technologies and provide a few implementation tips. The article is based on a research project developed at Grid Dynamics Labs.

Big Data 154
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What is ITOps? Why IT operations is more crucial than ever in a multicloud world

Dynatrace

As more organizations adopt cloud-native technologies, traditional approaches to IT operations have been evolving. Complex cloud computing environments are increasingly replacing traditional data centers. In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. So, what is ITOps?

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Kubernetes in the wild report 2023

Dynatrace

While Kubernetes is still a relatively young technology, a large majority of global enterprises use it to run business-critical applications in production. Findings provide insights into Kubernetes practitioners’ infrastructure preferences and how they use advanced Kubernetes platform technologies. Java, Go, and Node.js

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Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices

The Morning Paper

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., When a QoS violation is predicted to occur and a culprit microservice located, Seer uses a lower level tracing infrastructure with hardware monitoring primitives to identify the reason behind the QoS violation.

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Structural Evolutions in Data

O'Reilly

” That came to mind when a friend raised a point about emerging technology’s fractal nature. Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” Millions of tests, across as many parameters as will fit on the hardware.