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Serverless and Edge Runtime

Apiumhub

This is the introductory post in a two-part series, exploring the world of Serverless and Edge Runtime. The main focus of this post will be Serverless, while the second one will focus on an alternative, newer approach in the form of Edge Computing. Scalability Of course, going serverless is not only for small projects.

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Modernizing on AWS: Strategies, Benefits, and Partnerships with Xebia

Xebia

This involves updating existing systems to take advantage of modern cloud-native architectures, technologies, and best practices, which always follow the six Pillars of AWS Well Architecture Framework: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.

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AoAD2 Practice: Evolutionary System Architecture

James Shore

To share your thoughts, join the AoAD2 open review mailing list. Evolutionary System Architecture. What about your system architecture? By system architecture, I mean all the components that make up your deployed system. When you do, you get evolutionary system architecture.

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Serverless Cloud – Why you should consider going serverless?

Trigent

serverless. Enter serverless computing. By adhering to some basic rules, services and applications can be deployed onto serverless systems. Of course, this is a significantly simplified explanation, and the systems are way more complicated. If things failed, it was NOT due to provisioning and capacity.

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The Cake is NOT a Lie: 5 Java Frameworks to Support Your Microservices Architecture

OverOps

Smaller code bases are easier to understand, and with clearly separated services the overall architecture is much “cleaner”. Higher frequency releases and increased collaboration between dev and ops is exciting, but it’s important to stay diligent. They promise to bring greater flexibility and easier scalability.

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4 paths to sustainable AI

CIO

Use more efficient processes and architectures Boris Gamazaychikov, senior manager of emissions reduction at SaaS provider Salesforce, recommends using specialized AI models to reduce the power needed to train them. “Is We see it as a recruiting and retention factor.” This results in a reduction of power consumption, he says.

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Anyscale adds $40M to bring its Ray-based distributed computing tech to the enterprise masses

TechCrunch

Jordan, said in an interview that the company is tapping into a moment spurred not just by the events of 2020 but by the bigger demand from companies — spurred by the growth of cloud computing, major digital transformation of their systems, and a need to go that extra mile to remain competitive. led by a16z.