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What is ITOps? Why IT operations is more crucial than ever in a multicloud world

Dynatrace

Besides the traditional system hardware, storage, routers, and software, ITOps also includes virtual components of the network and cloud infrastructure. Although modern cloud systems simplify tasks, such as deploying apps and provisioning new hardware and servers, hybrid cloud and multicloud environments are often complex.

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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
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Understanding operational 5G: a first measurement study on its coverage, performance and energy consumption

The Morning Paper

We are standing on the eve of the 5G era… 5G, as a monumental shift in cellular communication technology, holds tremendous potential for spurring innovations across many vertical industries, with its promised multi-Gbps speed, sub-10 ms low latency, and massive connectivity. Throughput and latency. energy consumption).

Energy 130
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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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A case for managed and model-less inference serving

The Morning Paper

As we saw with the SOAP paper last time out, even with a fixed model variant and hardware there are a lot of different ways to map a training workload over the available hardware. The following figure highlights how just one of these variables, batch size, impacts throughput and latency on ResNet50.

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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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Kubernetes for Big Data Workloads

Abhishek Tiwari

faster access to external storage and data locality (I/O, bandwidth). For instance, scatter/gather pattern can be used to implement a MapReduce like batch processing architecture on top of Kubernetes. Storage provisioning. But Kubernetes storage is evolving quite quickly. optimised container networking and security.