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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

Retrieval-augmented generation emerges as the standard architecture for LLM-based applications Given that LLMs can generate factually incorrect or nonsensical responses, retrieval-augmented generation (RAG) has emerged as an industry standard for building GenAI applications.

Cache 209
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How multicloud observability boosts cloud performance at Tractor Supply Co.

Dynatrace

Kiran Bollampally, site reliability and digital analytics lead for ecommerce at Tractor Supply Co., shifted most of its ecommerce and enterprise analytics workloads to Kubernetes-managed software containers running in Microsoft Azure. “We monitor all services that produce metrics in the top three clouds,” he said.

Cloud 176
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Redis® Monitoring Strategies for 2024

Scalegrid

With its widespread use in modern application architectures, understanding the ins and outs of Redis® monitoring is essential for any tech professional. Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring.

Strategy 130
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Sustainable IT: Optimize your hybrid-cloud carbon footprint

Dynatrace

Evaluating these on three levels—data center, host, and application architecture (plus code)—is helpful. Application architectures might not be conducive to rehosting. Implement appropriate caching layers (for example, read-only cache for static data). Is the solution to just move all workloads to the cloud?

Cloud 214
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Dynatrace supports SnapStart for Lambda as an AWS launch partner

Dynatrace

Lambda then takes a snapshot of the memory and disk state of the initialized execution environment, persists the encrypted snapshot, and caches it for low-latency access. Simplify error analytics. Understand and optimize your architecture. The latest Amazon Lambda innovation, Lambda SnapStart, has day one support from Dynatrace.

Lambda 229
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Observability vs. monitoring: What’s the difference?

Dynatrace

Organizations are depending more and more on distributed architectures to provide application services. Monitoring focuses on watching specific metrics. Observability is the ability to understand a system’s internal state by analyzing the data it generates, such as logs, metrics, and traces. Dynatrace news.

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Procella: unifying serving and analytical data at YouTube

The Morning Paper

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., ” For just the YouTube Analytics application, we’re looking at metrics like this, with a 99%-ile latency of 412ms: Embedded statistics use cases include the various counters such as views, likes, and subscriptions that are included in pages.