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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

Traditional computing models rely on virtual or physical machines, where each instance includes a complete operating system, CPU cycles, and memory. VMware commercialized the idea of virtual machines, and cloud providers embraced the same concept with services like Amazon EC2, Google Compute, and Azure virtual machines.

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Site reliability engineering: 5 things you need to know

Dynatrace

As a discipline, SRE focuses on improving software system reliability across key categories including availability, performance, latency, efficiency, capacity, and incident response. ” According to Google, “SRE is what you get when you treat operations as a software problem.” Solving for SR.

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Mastering Hybrid Cloud Strategy

Scalegrid

The architecture usually integrates several private, public, and on-premises infrastructures. Key Components of Hybrid Cloud Infrastructure A hybrid cloud architecture usually merges a public Infrastructure-as-a-Service (IaaS) platform with private computing assets and incorporates tools to manage these combined environments.

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Site reliability engineering: 5 things to you need to know

Dynatrace

As a discipline, SRE focuses on improving software system reliability across key categories including availability, performance, latency, efficiency, capacity, and incident response. ” According to Google, “SRE is what you get when you treat operations as a software problem.” Solving for SR.

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Who will watch the watchers? Extended infrastructure observability for WSO2 API Manager

Dynatrace

Cloud-based application architectures commonly leverage microservices. In response to this trend, open source communities birthed new companies like WSO2 (of course, industry giants like Google, IBM, Software AG, and Tibco are also competing for a piece of the API management cake). High latency or lack of responses.

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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. Ford, et al., “TCP

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Artificial Intelligence in Cloud Computing

Scalegrid

AI algorithms embedded in cloud architecture automate repetitive processes, streamlining workloads and reducing the chance of human error. With a multi-cloud architecture, Scalegrid offers the flexibility and competitive edge necessary for AI applications in the rapidly evolving tech environment.