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Sustainability: Thoughts from a software engineer

Dynatrace

Scale to zero Scaling systems to match current demand prevents underutilized machines from consuming significant energy while idling. While building production systems that can scale to zero and reliably restart can be challenging, it’s often simpler in test stages and build pipelines, making this a great place to start.

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The Next Major Shift in Enterprise Software Engineering: From Platforms to “Platformless”

DZone

The evolution of enterprise software engineering has been marked by a series of "less" shifts — from client-server to web and mobile ("client-less"), data center to cloud ("data-center-less"), and app server to serverless.

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Low-Maintenance Backend Architectures for Scalable Applications

DZone

After years of working in the intricate world of software engineering, I learned that the most beautiful solutions are often those unseen: backends that hum along, scaling with grace and requiring very little attention. Developers could understand and manage the entire systems intricacies.

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Our First Netflix Data Engineering Summit

The Netflix TechBlog

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community! Learn more about how batch and streaming data pipelines are built at Netflix.

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Showcasing engineering excellence at Dynatrace

Dynatrace

Whilst our traditional Dynatrace website predominantly showcases Dynatrace content and product information for visitors, the idea behind the creation of our new Engineering website – engineering.dynatrace.com – was to set up a space to feature the results of our research and innovation efforts and aims to be a site made by engineers for engineers.

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Key Elements of Site Reliability Engineering (SRE)

DZone

Site Reliability Engineering (SRE) is a systematic and data-driven approach to improving the reliability, scalability, and efficiency of systems. It combines principles of software engineering, operations, and quality assurance to ensure that systems meet performance goals and business objectives.

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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. Recovery time of the latency p90.