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Path to NoOps part 1: How modern AIOps brings NoOps within reach

Dynatrace

NoOps, or “no operations,” emerged as a concept alongside DevOps and the push to automate the CI/CD pipelines as early as 2010. For most teams, evolving their DevOps practices has been challenging enough. The need for developers and innovation is now even greater. Thus, the concept of NoOps takes DevOps a step further.

DevOps 225
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DynatraceGo! APAC 2021: Lessons in thick data and keeping pace with the market

Dynatrace

Because here is a group of people who thrive on discovering new things, transforming workplaces, and innovating in the true sense of the word, every single day. Breakout Sessions on Scaling DevOps and SRE, Simplifying Kubernetes, Accelerating Cloud Native Innovation, and Delivering Perfect Experiences with Full Stack Observability.

DevOps 246
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Seven benefits of AIOps to transform your business operations

Dynatrace

AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. AIOps aims to provide actionable insight for IT teams that helps inform DevOps, CloudOps, SecOps, and other operational efforts. Aggregation.

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What is AIOps? Everything you wanted to know

Dynatrace

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” But what is AIOps, exactly? And how can it support your organization? What is AIOps? Two approaches to AIOps.

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Mastering Hybrid Cloud Strategy

Scalegrid

This approach allows companies to combine the security and control of private clouds with public clouds’ scalability and innovation potential. A hybrid cloud strategy could be your answer. This article will explore hybrid cloud benefits and steps to craft a plan that aligns with your unique business challenges.

Strategy 130
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Software Testing Trends 2021 – What can we expect?

Testsigma

The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. From AI to ML, the shifting technology world is constantly innovating and making significant progress. Many changes are rendered through automated testing. from $12.6 bn in 2019 up to $28.8 bn in 2024.”

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Rethinking the 'production' of data

All Things Distributed

The founders had noticed that in many companies, product designers worked in a very detached manner from the rest of production. In this way, designers are part of an ecosystem in which the functionalities of simulations, data and people come together, enabling them to develop better products faster. Value creation through data.