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

Dynatrace

As organizations adopt microservices architecture with cloud-native technologies such as Microsoft Azure , many quickly notice an increase in operational complexity. To guide organizations through their cloud migrations, Microsoft developed the Azure Well-Architected Framework. What is the Azure Well-Architected Framework?

Azure 178
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What is a Distributed Storage System

Scalegrid

This process effectively duplicates essential parts of information to safeguard against potential loss. By breaking up large datasets into more manageable pieces, each segment can be assigned to various network nodes for storage and management purposes.

Storage 130
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Designing Instagram

High Scalability

There are two major processes which gets executed when a user posts a photo on Instagram. Firstly, the synchronous process which is responsible for uploading image content on file storage, persisting the media metadata in graph data-storage, returning the confirmation message to the user and triggering the process to update the user activity.

Design 334
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Implementing AWS well-architected pillars with automated workflows

Dynatrace

And how can you verify this performance consistently across a multicloud environment that also uses Microsoft Azure and Google Cloud Platform frameworks? This process enables you to continuously evaluate software against predefined quality criteria and service level objectives (SLOs) in pre-production environments.

AWS 236
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Azure Virtual Machines for SQL Server Usage

SQL Performance

One initial, easy step to moving your SQL Server on-premises workloads to the cloud is using Azure VMs to run your SQL Server workloads in an infrastructure as a service (IaaS) scenario. One important choice you will still have to make is what type and size of Azure virtual machine you want to use for your existing SQL Server workload.

Azure 72
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Extending relational query processing with ML inference

The Morning Paper

Extending relational query processing with ML inference , Karanasos, CIDR’10. The vision is that data scientists use their favourite ML framework to construct a model, which together with any data pre-processing steps and library dependencies forms a model pipeline. " Query execution. ." " Query execution.

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The Amazing Evolution of In-Memory Computing

ScaleOut Software

From Distributed Caches to Real-Time Digital Twins. Emerging in the early 2000s, the first such platforms provided distributed caching on clustered servers with straightforward APIs for storing and retrieving in-memory objects.