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Using Dynatrace to master the 5 pillars of the AWS Well-Architected Framework (Part 1)

Dynatrace

As organizations plan, migrate, transform, and operate their workloads on AWS, it’s vital that they follow a consistent approach to evaluating both the on-premises architecture and the upcoming design for cloud-based architecture. AWS 5-pillars. Dynatrace and AWS. through our AWS integrations and monitoring support.

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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

The phrase “serverless computing” appears contradictory at first, but for years now, successful companies have understood the benefit of using serverless technologies to streamline operations and reduce costs. Inefficiencies cost technology companies up to $100 billion per year. Dynatrace news. Pay Per Use.

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Best Practices in Cloud Security Monitoring

Scalegrid

By enhancing IAM (Identity Access Management), CASB (Cloud Access Security Broker), and SASE (Secure Access Service Edge) capabilities, these technologies bolster overall cloud security measures. For example, Blumira offers a third-party solution while AWS provides its own with CloudWatch.

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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes.

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Generative AI in the Enterprise

O'Reilly

Generative AI has been the biggest technology story of 2023. Executive Summary We’ve never seen a technology adopted as fast as generative AI—it’s hard to believe that ChatGPT is barely a year old. When 26% of a survey’s respondents have been working with a technology for under a year, that’s an important sign of momentum.

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Bringing the Magic of Amazon AI and Alexa to Apps on AWS.

All Things Distributed

We also have a great deal of machine learning technology that can benefit machine scientists and developers working outside Amazon. Last week, I wrote a blog about helping the machine learning scientist community select the right deep learning framework from among many we support on AWS such as MxNet, TensorFlow, Caffe, etc.

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