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Streamlining Workflows with Feature Branches and Logical Stacks

Xebia

Efficient collaboration and streamlined deployment processes are crucial in modern development workflows, especially for teams working on complex projects. Feature branches and stack-based development approaches offer powerful ways to isolate changes, test effectively, and ensure seamless integration. The answer is quite simple!

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices. This allows teams to focus more on implementing improvements and optimizing AWS infrastructure.

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How Developer Observability is Transforming Dev Role

Hacker Earth Developers Blog

Alongside streamlined processes and collaborative efficiency, DevOps teams need real-time access to detailed, correlative, context-rich data and analytics. By understanding how observability in DevOps transforms development capabilities, you can maximize the effectiveness of your teams and your data. Let’s get into it.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

While organizations continue to discover the powerful applications of generative AI , adoption is often slowed down by team silos and bespoke workflows. As a result, building such a solution is often a significant undertaking for IT teams. Responsible AI components promote the safe and responsible development of AI across tenants.

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The Top 13 Sessions From 2018 Ops and Dev Conferences

OverOps

Liz Fong-Jones , Staff Developer Advocate at Google, explains how error budgets and Site Reliability Engineering practices can improve the reliability, maintainability, and feature velocity of products. Instead, it might be disregarding the very values and principles of true agile development. How Netflix Thinks of DevOps.

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How Cato Networks uses Amazon Bedrock to transform free text search into structured GraphQL queries

AWS Machine Learning - AI

With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, and quickly integrate and deploy them into your applications using AWS tools without having to manage the infrastructure. About the Authors Asaf Fried leads the Data Science team in Cato Research Labs at Cato Networks.

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The Good and the Bad of Apache Kafka Streaming Platform

Altexsoft

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. With these basic concepts in mind, we can proceed to the explanation of Kafka’s strengths and weaknesses. Scalability. Scalability is one of Kafka’s key selling points. Kafka advantages. Multiple producers and consumers.