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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. Dependency agent Installation – Maps connections between servers and processes. Available as an agent installer). How does Dynatrace fit in?

Azure 137
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

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. Observing AI models Running AI models at scale can be resource-intensive.

Cache 204
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How multicloud observability boosts cloud performance at Tractor Supply Co.

Dynatrace

shifted most of its ecommerce and enterprise analytics workloads to Kubernetes-managed software containers running in Microsoft Azure. Further, Tractor Supply’s transition to Kubernetes introduced many new processes—particularly regarding security. “At one point, we saw a process that was causing a lot of CPU contention.

Cloud 171
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Kubernetes in the wild report 2023

Dynatrace

Most Kubernetes clusters in the cloud (73%) are built on top of managed distributions from the hyperscalers like AWS Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE). Cloud-hosted Kubernetes clusters are on par to overtake on-premises deployments in 2023.

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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 246
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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.