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Need for Speed: Cubic’s Journey with Tasktop Viz and Flow Metrics

Tasktop

It’s why the company has racked up so many industry firsts across transportation, defense and beyond. The first geodetic SECOR satellite surveying system to offer coast-to-coast measurement of the country. And first to invent the “Top Gun” Air Combat Training System back in the early ‘70s. .

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Observations on the Importance of Cloud-based Analytics

All Things Distributed

In the past analytics within an organization was the pinnacle of old style IT: a centralized data warehouse running on specialized hardware. With the new BI system the company is able to run analytics across 140 stories per day, in real time, and increase their agility for completing analytics tasks from months to days.

Analytics 135
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AI for everyone - How companies can benefit from the advance of machine learning

All Things Distributed

The management consultants at McKinsey expect that the global market for AI-based services, software and hardware will grow annually by 15-25% and reach a volume of around USD 130 billion in 2025. If you can predict demand, you can plan more efficiently. In B2B and B2C businesses, it is critical that goods are available quickly.

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What is container as a service? How CaaS compares to PaaS, IaaS, and FaaS

Dynatrace

The containerization craze has continued for enterprises, with benefits such as portability, efficiency, and scalability. These containers are software packages that include all the relevant dependencies needed to run software on any system. In FaaS environments, providers manage all the hardware. million in 2020. CaaS vs. FaaS.

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Kubernetes vs Docker: What’s the difference?

Dynatrace

Think of containers as the packaging for microservices that separate the content from its environment – the underlying operating system and infrastructure. Just like shipping containers revolutionized the transportation industry, Docker containers disrupted software. In production, containers are easy to replicate. Networking.

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Snap: a microkernel approach to host networking

The Morning Paper

It’s been clear for a while that software designed explicitly for the data center environment will increasingly want/need to make different design trade-offs to e.g. general-purpose systems software that you might install on your own machines. The desire for CPU efficiency and lower latencies is easy to understand. Enter Google!

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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 MPI runtime library. in ways that are seldom transparent.