Best DevOps

DataOps: The New DevOps of Analytics

Source- insidebigdata.com According to Gartner’s report, Innovation Insight for DataOps, 27 December 2018, “DataOps is a collaborative data management practice focused on improving the communication, integration, and automation of data flows across an organization.” A relatively new approach, DataOps represents a change in culture that focuses on improving collaboration and accelerating service delivery by adopting lean or iterative practices. Unlike its close cousin DevOps, which focuses on operations and development teams, DataOps is geared towards the data developers, data analysts or data

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4 steps to ensure virtual machine security in cloud computing

Source- searchsecurity.techtarget.com Security is a problem. Network security is an even bigger problem because of the complex factors that define risks and the profound negative effects that can occur if you fail. Virtual network security is the worst problem of all because it combines issues generated by traditional hosting and application security with those from network security, and then adds the challenges of virtual resources and services. It’s no wonder we’re only now starting to recognize the problems of cloud-virtual networking. And we’re

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The New AI Overseer Role in DevOps

Source- devops.com Robot overlords are the stuff of science fiction fantasy. Today, with more teams implementing artificial intelligence (AI), DevOps teams need a hard, continuous look at reality. An AI overseer watching apps at work could make the difference between sadness and euphoria in your efforts. We’re seeing AI misses more and more often. Facebook recently admitted its algorithms failed to stop uploads of a particularly heinous live-streamed video. Autonomous vehicles have struck cars and people. Jaywalkers in China have been

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2019 is the year that Agile and DevOps go large

Source- computing.co.uk ‘At scale’ or ‘large-scale’ Agile and DevOps development – sometimes separately but often in the same breath – was a topic that has been cropping up more frequently in the enterprise-IT world. The ‘scale’ message is topical because it chimes with how software development increasingly involves the entire enterprise. For instance, IoT products cover hardware and software engineering, while video game development encompasses coders and artists with various specialities. This broader application of Agile is also affected by having to

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What DevOps Can Teach Us About Cybersecurity

Source- securityboulevard.com DevOps and cybersecurity are both top priorities for many enterprises, as well as areas that have experienced considerable innovation recently. And even though these are two very different sides of IT, there are lessons to be learned between the two. Both areas are in the midst of major transitions. For application development, the shift is from slow, monolithic releases too fast and responsive development cycles. For cybersecurity, the shift is from the old perimeter block/allow enforcement model to more

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Can IT admins benefit from a DevOps environment?

Source- searchdatacenter.techtarget.com If DevOps is implemented poorly, it increases the pressure on admins to deal with uncontrolled code rollouts in the operational environment, which can drain hardware resources and increase troubleshooting time. However, a good DevOps environment with all the right checks and balances in place reduces the number of mind-numbing tasks that admins face, and it provides more time for interesting, value-add tasks that help the business. DevOps also gives admins oversight of developers. Powerful DevOps tools place all the correct filters

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With great speed comes great responsibility: software testing now a continuous race

Source- zdnet.com Continuous integration and continuous delivery is giving us software updates every day in many cases. A recent survey of 500 IT executives finds 58% of enterprises deploy a new build daily, and 26% at least hourly. That’s why Agile and DevOps are so important. With great speed comes great responsibility. A constant stream of software needs constant quality assurance. To make sure things are functioning as they should, organizations are turning to continuous testing. That’s the takeaway from the survey,

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How CI/CD Can Fast-Track Next-Gen Media Rollouts.

Source- searchitoperations.techtarget.com Online video consumption has been increasing tremendously with rapid change in consumer expectations to have seamless viewing experience across various digital devices. To capture this growing demand, it is critical for digital service providers (DSPs) to deliver fast-track rollout of next-gen media services. Moreover, to counter the growing influence of over-the-top content providers (OTTs), DSPs must deliver media services that are high quality, right the first time and consistent, along with creating competitive advantage through speed to market. However,

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Defining DevOps success: the 5 stages of DevOps evolution.

Source- networksasia.net DevOps is changing the way organizations look at application and infrastructure solutions today. By reducing redundancies and automating mundane processes, organizations are able to reap the benefits of adopting DevOps practices to increase agility, create a more collaborative work environment and enable IT to respond to business requirements faster With the Asia Pacific DevOps market expected to grow at a CAGR of 20.2% between 2017 and 2023, and more organizations recognizing the opportunity to adopt DevOps, mapping out the

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Cloud to help emerging markets diminish tech, cost barriers.

Source- rcrwireless.com The cloud is a powerful transformational agent for emerging markets, but only when dovetailed with other emerging and evolving digital technologies to deliver complete solutions.  The International Data Corporation or IDC’s top 10 predictions for IT, 2019, says that by 2022, 40% of organizations’ cloud developments will execute artificial intelligence (AI) algorithms. IDC forecasts that by 2022, any endpoint device on a cloud-enabled network will be performing AI-driven inferencing and relying on machine learning algorithms to continually ‘learn’ which

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