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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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Dynatrace log collection for ARM unlocks power-efficient architecture for your enterprise

Dynatrace

ARM architecture, based on a processor type optimized for cloud and hyperscale computing, has become the most prevalent on the planet, with billions of ARM devices currently in use. This is a crucial factor for all data centers, cloud or managed, where power consumption and cooling costs are reflected in the total cost of ownership.

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Optimizing your Kubernetes clusters without breaking the bank

Dynatrace

During a joint webinar , Henrik Rexed (Cloud Native Advocate, Dynatrace) joined us to talk about the Kubernetes challenges and how to leverage Dynatrace observability and Akamas AI-powered optimization to address them. Tuning thousands of parameters has become an impossible task to achieve via a manual and time-consuming approach.

Latency 192
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AWS re:Invent 2017: How Netflix Tunes EC2

Brendan Gregg

My last talk for 2017 was at AWS re:Invent, on "How Netflix Tunes EC2 Instances for Performance," an updated version of my [2014] talk. Our team looks after the BaseAMI, kernel tuning, OS performance tools and profilers, and self-service tools like Vector. html [Introducing Nitro]: [link]

Tuning 61
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AWS re:Invent 2017: How Netflix Tunes EC2

Brendan Gregg

My last talk for 2017 was at AWS re:Invent, on "How Netflix Tunes EC2 Instances for Performance," an updated version of my [2014] talk. Our team looks after the BaseAMI, kernel tuning, OS performance tools and profilers, and self-service tools like Vector. html [Introducing Nitro]: [link]

Tuning 52
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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes.

Analytics 198
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Automate complex metric-related use cases with the Metrics API version 2

Dynatrace

Besides all the metrics that originate from your hosts, Dynatrace also collects all the important key performance metrics for services and real-user monitored applications as well as cloud platform metrics from AWS, Azure, and Cloud Foundry. metrics/query?metricSelector=builtin:apps.other.apdex.osAndVersion:merge(App

Metrics 216