How Kubernetes allows developers to deploy without worrying about DevOps

Source – siliconangle.com As an active distributor of the Kubernetes container orchestration management system, Canonical Ltd is giving developers a way to step up their game. The company is taking away the developer operations component to the developer job so they are free to focus on other important aspects of development that they have more expertise in, according to Stephan Fabel (pictured), director of product management at Canonical. “… We’ve been very active in this space fairly early on and have been an active distributor of Kubernetes and a

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The Next Generation of DevOps: ML Ops

Source – insidebigdata.com In this special guest feature, Debashis Saha, Vice President of Platform Engineering at Intuit, discusses how DevOps methodologies can be applied to machine learning, in what he calls “ML Ops.” With ML Ops, he believes it can provide an end-to-end automation of the process, creating transparency and delivering efficiency and productivity for everyoenbody involved to deliver value rapidly. As VP of Platform Engineering for Intuit, Debashis leads the engineering teams responsible for the platform, developer and application services that

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DevOps and Machine Learning are highly demanded jobs this year

Source – techworm.net DevOps and machine learning professionals to control technology opportunities this year Stack Overflow, a popular developer community and jobs site, published their eight Annual Developer Survey results this year, which saw over 100,000 developers around the world take the 30-minute survey. The survey conducted by Stack Overflow reveals that DevOps and machine learning engineers earn highest salaries in the tech sector, averaging between $70,000 and $90,000 a year worldwide. However, salaries for these two ranges between $110,000 annually for DevOps

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Seven steps to move a DevOps team into the ML and AI world

Source – techtarget.com Nobody questions the potential for machine learning and artificial intelligence to revolutionize DevOps productivity and business efficiency as a whole, really. An invisible hand, however, keeps organizations from seeing ML and AI to their full potential. There are seven basic rules to implement ML and AI in real-life DevOps situations. Done right, ML/AI and DevOps can turn enterprises into digital attackers that release higher-quality software faster and at lower cost. To release on time and within budget, there

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How AI will influence the world of cloud-based collaboration and conferencing

Source – cloudcomputing-news.net Those who attended Cloud Expo Europe earlier this week took their opportunity to assess the next level of cloud services, ranging from blockchain, to artificial intelligence (AI) and machine learning. The cloud underpins these technologies and enables them to flourish, while as this publication has previously reported, the M&A cycle has been lit up by it. But what are some of the practical applications for cloud-enabled AI? Lifesize, a cloud-based conferencing hardware and software provider, is exploring how

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Emerging Data Center Trends: From DevOps To DataOps

Source – forbes.com If asked to list the top trends that are shaping the enterprise data center today, most technologists and tech investors would likely agree on a core set. The list would include technologies like such as cloud computing, containers and virtualization, microservices, machine learning and data science, flash memory, edge computing, NVMe and GPUs. These technologies are all important for organizations pushing digital transformation. The harder question: What’s coming next? Which emerging technologies or paradigm shifts are poised to

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How technology changes the rules for doing agile

Source – enterprisersproject.com More companies are trying agile and DevOps for a clear reason: Businesses want more speed and more experiments – which lead to innovations and competitive advantage. DevOps helps you gain that speed. But doing DevOps in a small group or startup and doing it at scale are two very different things. Any of us who’ve worked in a cross-functional group of 10 people, come up with a great solution to a problem, and then tried to apply the

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IT ops pros predict routes to DevOps efficiency in 2018

Source – techtarget.com IT operations is a fast-moving river of change. It might bend or fork as it travels, you might go over a Waterfall, but it never doubles back. Expert IT professionals and analysts –– many of whom write tips on the tools and technologies you use every day — lay out their predictions for where IT operations is heading in 2018. Everyone expects a heavier emphasis on DevOps efficiency through smarter adoption and evolved tools and practices. Another broad

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How to work through the four complicated DevOps stages

Source – techtarget.com For thousands of years, we have been devising ways to cross bodies of water. Historically, our attempts were crude — makeshift rafts and rickety, ferrylike vessels. So, we started building bridges, albeit basic ones. Ferries and bridges still need upkeep as weather and increasing traffic require intelligent decision-making and technology to optimize transit. Let’s apply this to DevOps. Like bridging two shorelines together, DevOps involves efficiently linking an organization’s business idea to its market. For an organization to

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5 reasons DevOps will be a big deal in the year ahead

Source – infosurhoy.com The typical enterprise has become a nonstop software and data factory, operating 24×7. Technology has to be there at all times. DevOps has been a hot topic and pursuit for a few years now. During this time, many enterprises have been attempting to put this way of working — in which development output is aligned with ongoing business requirements — in place in one form or another. But 2018 promises to be the year when it all really

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