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Dynatrace Cost & Carbon Optimization certified for accuracy and transparency

Dynatrace

The explosion of AI models shines a new spotlight on the issue, with a recent study showing that using AI to generate an image takes as much energy as a full smartphone charge. The certification focuses on accuracy and transparency in calculating greenhouse gas (GHG) emissions for AWS, Azure, GCP, and on-premises host instances.

Energy 223
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What is a Distributed Storage System

Scalegrid

Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. Amazon S3 and Microsoft Azure Blob Storage leverage distributed storage solutions.

Storage 130
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Web Development Trends in 2023

KeyCDN

Chatbots and virtual assistants Chatbots and virtual assistants are becoming more common on websites and web applications as they provide an efficient and convenient way for users to interact with a business. These technologies can answer questions, provide customer support, or even complete transactions.

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Slower Memory Zeroing Through Parallelism

Randon ASCII

I’d been testing on a virtual machine in a data center that I had access to, purely because this machine has an internet connection that runs at over 2 Gbps. As somebody wise once said , spin locks waste energy and CPU power and should be avoided. Case closed. But I noticed something…. Server versions should be fine….

Cache 105
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Measuring Carbon is Not Enough?—?Unintended Consequences

Adrian Cockcroft

Let’s start by assuming that you have figured out a way to estimate the energy consumption and carbon footprint for a workload that is sensitive enough to register changes in the way you run the workload. The first thing to understand is that doing things consumes time and energy and has a carbon footprint of its own.

Energy 52
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Proposal for a Realtime Carbon Footprint Standard

Adrian Cockcroft

This proposal seeks to define a standard for real-time carbon and energy data as time-series data that would be accessed alongside and synchronized with the existing throughput, utilization and latency metrics that are provided for the components and applications in computing environments.

Energy 52