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What is software automation? Optimize the software lifecycle with intelligent automation

Dynatrace

In what follows, we define software automation as well as software analytics and outline their importance. What is software analytics? This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI. We also discuss the role of AI for IT operations (AIOps) and more.

Software 187
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Measuring the importance of data quality to causal AI success

Dynatrace

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. High-quality operational data in a central data lakehouse that is available for instant analytics is often teams’ preferred way to get consistent and accurate answers and insights. That’s where causal AI can help.

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Implementing service-level objectives to improve software quality

Dynatrace

As more organizations embrace microservices-based architecture to deliver goods and services digitally, maintaining customer satisfaction has become exponentially more challenging. Instead, they can ensure that services comport with the pre-established benchmarks. SLOs improve software quality. Define an application’s critical path.

Software 263
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. See more fault recovery experiments and insights in our full paper.

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Lerner?—?using RL agents for test case scheduling

The Netflix TechBlog

Netflix engineers run a series of tests and benchmarks to validate the device across multiple dimensions including compatibility of the device with the Netflix SDK, device performance, audio-video playback quality, license handling, encryption and security. Experiment with different neural network architectures.

Testing 163
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Web Performance Bookshelf

Rigor

Information Architecture. In her book, Lara Hogan helps you approach projects with page speed in mind, showing you how to test and benchmark which design choices are most critical. This book from 2002 is a brilliant must read: site architecture, security, reliability, and their impact on performance. Designing for Performance.

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Perform Las Vegas 2020: Reduce risk and iterate faster

Dynatrace

In the past, monolith architectures could only be implemented with big bang deployments which result in a slow pace of innovation and significant downtime. Using the Davis assistant for comparison and benchmarking. Creating dashboards highlighting business analytics of each deployment. From big bang to progressive deployments.