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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.

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SRE Best Practices for Java Applications

DZone

Site reliability engineering (SRE) plays a vital role in ensuring Java applications' high availability, performance, and scalability. This discipline merges software engineering and operations, aiming to create a robust infrastructure that supports seamless user experiences.

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Scaling Is Not Just About Products – It’s About Teams, Too

DZone

We are well aware of what is meant by system scalability. System scalability is about maintaining the SLA of the system as the user base continues to grow and as the user activity continues to rise. However, to build highly successful products, this is not the only type of scalability that we should worry about. Introduction.

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What is platform engineering?

Dynatrace

With growing multicloud complexity and the need for organization-wide scalability, self-service and automation capabilities have become increasingly essential for developer productivity. In response to this shift, platform engineering is growing in popularity. The result is a cloud-native approach to software delivery.

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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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SRE vs DevOps: What you need to know

Dynatrace

Cloud-native environments bring speed and agility to software development and operations (DevOps) practices. DevOps is focused on optimizing software development and delivery, and SRE is focused on operations processes. DevOps is best thought of as a practical approach to speeding up new software development and delivery.

DevOps 268
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Computational Causal Inference at Netflix

The Netflix TechBlog

These methods can provide rich information for decision making, such as in experimentation platforms (“XP”) or in algorithmic policy engines. We want to amplify the effectiveness of our researchers by providing them software that can estimate causal effects models efficiently, and can integrate causal effects into large engineering systems.