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Microservices Sucks — Amazon Goes Back to Basics

DevOps.com

In this week’s #TheLongView: Amazon Prime Video has ditched its use of microservices-cum-serverless, reverting to a traditional, monolithic architecture. It vastly improved the workload’s cost and scalability. The post Microservices Sucks — Amazon Goes Back to Basics appeared first on DevOps.com.

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Evaluating a Microservice Architecture

Tandem

Microservice architecture has been a hot topic in the realm of software development for a while now. It’s often portrayed as a revolutionary method for constructing software systems that are scalable, adaptable, and efficient. However, like any technology, it has its strengths and weaknesses.

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14 in-demand cloud roles companies are hiring for

CIO

Those bumps in spending include added demand for cloud and cloud-adjacent workers who can help maintain and continuously improve and expand enterprise cloud networks. According to the Foundry report, 78% of organizations say that, in response to cloud investments made by the organization, they have added new roles.

Cloud 304
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Serverless NiFi Flows with DataFlow Functions: The Next Step in the DataFlow Service Evolution

Cloudera

With DFF, users now have the choice of deploying NiFi flows not only as long-running auto scaling Kubernetes clusters but also as functions on cloud providers’ serverless compute services including AWS Lambda, Azure Functions, and Google Cloud Functions. New use cases: event-driven, batch, and microservices.

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How to avoid converting “Distributed monolith” microservices into “Serverless monoliths”

The Agile Monkey

From Microservices to Serverless: How to avoid converting “Distributed monolith” microservices into “Serverless monoliths” Learning from the past: converting a monolith into… a worse monolith When microservices became mainstream, a lot of companies started to migrate their monolithic systems to a distributed microservice architecture.

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4 remedies to avoid cloud app migration headaches

CIO

Although cloud service providers emphasize the use of open platforms and data access protocols, which in theory are easy to use, network limitations and security to access these services are often overlooked,” he says. When deciding which cloud-native services to use, sometimes organizations have no choice. Security is a good example.

Cloud 300
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AWS at NVIDIA GTC 2024: Accelerate innovation with generative AI on AWS

AWS Machine Learning - AI

The company is combining this expertise with the highly scalable, reliable, and secure AWS Cloud infrastructure to help customers run advanced graphics, machine learning, and generative AI workloads at an accelerated pace. NVIDIA is known for its cutting-edge accelerators and full-stack solutions that contribute to advancements in AI.