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Building an Optimized Data Pipeline on Azure Using Spark, Data Factory, Databricks, and Synapse Analytics

DZone

Data processing in the cloud has become increasingly popular due to its scalability, flexibility, and cost-effectiveness. This article will explore how these technologies can be used together to create an optimized data pipeline for data processing in the cloud.

Azure 246
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Bandwidth-friendly Query Profiling for Azure SQL Database

SQL Performance

SQL Server has always provided the ability to capture actual queries in an easily-consumable rowset format – first with legacy SQL Server Profiler, later via Extended Events, and now with a combination of those two concepts in Azure SQL Database. Unfortunately, my excitement was short lived for a couple of reasons.

Azure 96
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues. The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources.

Cache 201
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The right person at the right time makes all the difference: Best practices for ownership information

Dynatrace

Secondly, knowing who is responsible is essential but not sufficient, especially if you want to automate your triage process. As teams and their structure and metadata are often maintained in a dedicated database, such as Microsoft Entra ID (formerly Azure Active Directory) or ServiceNow.

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Kubernetes in the wild report 2023

Dynatrace

As Kubernetes adoption increases and it continues to advance technologically, Kubernetes has emerged as the “operating system” of the cloud. Kubernetes is emerging as the “operating system” of the cloud. The strongest Kubernetes growth areas are security, databases, and CI/CD technologies. Kubernetes moved to the cloud in 2022.

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Artificial Intelligence in Cloud Computing

Scalegrid

Key Takeaways AI integration in cloud computing increases operational efficiency by automating processes, optimizing resource allocation, and improving scalability, leading to cost savings and allowing IT teams to concentrate on strategic initiatives. Discover how AI is reshaping the cloud and what this means for the future of technology.

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Designing Instagram

High Scalability

The streaming data store makes the system extensible to support other use-cases (e.g. System Components. The system will comprise of several micro-services each performing a separate task. The system will comprise of several micro-services each performing a separate task. Component Design. Posting on Instagram.

Design 334