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Breaking data silos: Liquid Reply’s journey to custom API observability with OpenTelemetry and Dynatrace

Dynatrace

Modern IT organizations are generating more data from more tools and technologies than ever. Data is proliferating in separate silos from containers and Kubernetes to open source APIs and software to serverless compute services, such as AWS and Azure. For this comprehensive monitoring in context, they had adopted Dynatrace.

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No need to compromise visibility in public clouds with the new Azure services supported by Dynatrace

Dynatrace

As adoption rates for Microsoft Azure continue to skyrocket, Dynatrace is developing a deeper integration with the platform to provide even more value to organizations that run their businesses on Azure or use it as a part of their multi-cloud strategy. Azure Batch. Azure DB for MariaDB. Azure DB for MySQL.

Azure 147
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Driving your FinOps strategy with observability best practices

Dynatrace

Following FinOps practices, engineering, finance, and business teams take responsibility for their cloud usage, making data-driven spending decisions in a scalable and sustainable manner. Empowering teams to manage their FinOps practices, however, requires teams to have access to reliable multicloud monitoring and analysis data.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

This blog post explores how AI observability enables organizations to predict and control costs, performance, and data reliability. It also shows how data observability relates to business outcomes as organizations embrace generative AI. GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues.

Cache 204
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Dynatrace extends automatic and intelligent observability to cloud and Kubernetes logs for smarter automation at scale

Dynatrace

Leveraging cloud-native technologies like Kubernetes or Red Hat OpenShift in multicloud ecosystems across Amazon Web Services (AWS) , Microsoft Azure, and Google Cloud Platform (GCP) for faster digital transformation introduces a whole host of challenges. Collecting data requires massive and ongoing configuration efforts.

Cloud 259
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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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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? These workflows also utilize Davis® , the Dynatrace causal AI engine, and all your observability and security data across all platforms, in context, at scale, and in real-time.

AWS 246