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Protecting critical infrastructure and services: Ensure efficient, accurate information delivery this election year

Dynatrace

These components include schools; transportation; energy; water; and communications such as the accuracy, timeliness, and transparency of election reporting. Every hardware, software, cloud infrastructure component, container, open source tool, and microservice generates records of every activity within modern environments.

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Kubernetes in the wild report 2023

Dynatrace

On-premises data centers invest in higher capacity servers since they provide more flexibility in the long run, while the procurement price of hardware is only one of many cost factors. That trend will likely continue as Kubernetes security awareness further rises and a new class of security solutions becomes available.

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Kubernetes vs Docker: What’s the difference?

Dynatrace

Just like shipping containers revolutionized the transportation industry, Docker containers disrupted software. Initially developed by Google, it’s now available in many distributions and widely supported by all public cloud vendors. The time and effort saved with testing and deployment are a game-changer for DevOps.

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Towards a Reliable Device Management Platform

The Netflix TechBlog

Complementing the hardware is the software on the RAE and in the cloud, and bridging the software on both ends is a bi-directional control plane. For example, when running tests, the state of the device will change from “available for testing” to “in test.” In this blog post, we will focus on the latter feature set.

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Snap: a microkernel approach to host networking

The Morning Paper

I’m jumping ahead a bit here, but the component of Snap which provides the transport and communications stack is called Pony Express. Rather than reimplement TCP/IP or refactor an existing transport, we started Pony Express from scratch to innovate on more efficient interfaces, architecture, and protocol. Enter Google! Emphasis mine).

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Why I hate MPI (from a performance analysis perspective)

John McCalpin

According to Dr. Bandwidth, performance analysis has two recurring themes: How fast should this code (or “simple” variations on this code) run on this hardware? The user environment defines the mapping of MPI ranks to hardware resources (cores, sockets, nodes). The source code to the library may not be available.

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RPCValet: NI-driven tail-aware balancing of µs-scale RPCs

The Morning Paper

While this core is stalled on the TLB miss(es), it is best to dispatch RPCs to other available cores on the server. It’s designed for “ emerging architectures featuring fully integrated NIs and hardware-terminated transport protocols.” In theory, how fast could we go? Consider a 16-core server handling 16 requests.

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