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Bring Your Own Cloud (BYOC) vs. Dedicated Hosting at ScaleGrid

Scalegrid

A vast majority of the features are the same, outside of these advanced features available through the BYOC model: Virtual Private Clouds / Virtual Networks. Amazon Virtual Private Clouds (VPC) and Azure Virtual Networks (VNET) are private, isolated sections of the cloud infrastructure where you can launch resources.

Cloud 242
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Azure Well-Architected Framework: What it is and how to tame it with AI and automation

Dynatrace

Getting precise root cause analysis when dealing with several layers of virtualization in a containerized world. Using a data-driven approach to size Azure resources, Dynatrace OneAgent captures host metrics out-of-the-box to assess CPU, memory, and network utilization on a VM host. Missing caching layers.

Azure 193
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How to Assess MySQL Performance

HammerDB

Regardless of whether the computing platform to be evaluated is on-prem, containerized, virtualized, or in the cloud, it is crucial to consider several essential factors. Instead, focus on understanding what the workloads exercise to help us determine how to best use them to aid our performance assessment. 4.22 %usr 38.40 0.42 %sys 9.52

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A Decade of Dynamo: Powering the next wave of high-performance, internet-scale applications

All Things Distributed

VPC Endpoints give you the ability to control whether network traffic between your application and DynamoDB traverses the public Internet or stays within your virtual private cloud. Secure – DynamoDB provides fine-grained access control at the table, item, and attribute level, integrated with AWS Identity and Access Management.

Internet 128
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A persistent problem: managing pointers in NVM

The Morning Paper

The beauty of persistent memory is that we can use memory layouts for persistent data (with some considerations for volatile caches etc. Traditionally one of the major costs when moving data in and out of memory (be it to persistent media or over the network) is serialisation. in front of that memory , as we saw last week).