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Why you need Dynatrace on Azure Workloads

Dynatrace

Hopefully, this blog will explain ‘why,’ and how Microsoft’s Azure Monitor is complementary to that of Dynatrace. Do I need more than Azure Monitor? Azure Monitor features. A typical Azure Monitor deployment, and the views associated with each business goal. Available as an agent installer). How does Dynatrace fit in?

Azure 137
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Kubernetes in the wild report 2023

Dynatrace

Findings provide insights into Kubernetes practitioners’ infrastructure preferences and how they use advanced Kubernetes platform technologies. Kubernetes infrastructure models differ between cloud and on-premises. Kubernetes infrastructure models differ between cloud and on-premises. Kubernetes moved to the cloud in 2022.

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Building an elastic query engine on disaggregated storage

The Morning Paper

Building an elastic query engine on disaggregated storage , Vuppalapati, NSDI’20. This paper presents Snowflake design and implementation along with a discussion on how recent changes in cloud infrastructure (emerging hardware, fine-grained billing, etc.) But the ephemeral storage service for intermediate data is not based on S3.

Storage 112
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Designing Instagram

High Scalability

FUN FACT : In this talk , Rodrigo Schmidt, director of engineering at Instagram talks about the different challenges they have faced in scaling the data infrastructure at Instagram. After that, the post gets added to the feed of all the followers in the columnar data storage. System Components. Fetching User Feed. Streaming Data Model.

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? Storing frequently accessed data in faster storage, usually in-memory caching, improves data retrieval speed and overall system performance. Beyond

AWS 246
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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
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The Amazing Evolution of In-Memory Computing

ScaleOut Software

From Distributed Caches to Real-Time Digital Twins. The pace of these changes has made it challenging for server-based infrastructures to manage fast-growing populations of users and data sources while maintaining fast response times.