One of the most amazing dynamics within the DevOps enterprise community is seeing business leaders co-presenting success stories with their technology leadership counterparts. For example, Ken Kennedy (executive vice president and president for Technology and Product at CSG) and Kimberly Johnson (chief operating officer at Fannie Mae) described the achievements of their technology leadership counterparts and why it was important to them. I expect this trend to continue, especially given how COVID-19 has accelerated the rate of digital disruption. I believe this bodes well for all of technology. With the rise of hybrid (remote/in-office) product teams, upskilling and online training initiatives will expand.
Artificial intelligence has taken the tech world to a new level of automation. Today, almost every specialization demands the intervention of machine learning to develop AI technologies that help businesses do more with less time and resources. Still, some organizations question whether leading with AI is a good investment. For DevOps, the answer is a resounding yes. AI can enhance DevOps practices to accelerate the pace of software releases, helping businesses achieve continuous delivery. This enables programmers to release software about 10 times faster and allows programs to be reviewed before they are released.
If you are involved in software development, you probably know what DevOps is. Its methods are becoming more popular in developers' circles, so no wonder why the majority of huge companies are implementing it in their workflows. So it shouldn't surprise you that DevOps experts and developers say they've improved the quality and speed of their software deployments, 55% report improved collaboration, and 38% say they've improved code quality. What's more, Puppet Labs reports a reduction in defects and crashes. At the same time, over of surveyed companies found the DevOps approach "very difficult." They all called security the bottleneck in this strategy. In response to these concerns, SecDevOps was born.
Wind River today revealed a waterfall of new features available designed to automate and accelerate DevSecOps and other "pipelines" across the lifecycle of intelligent systems. The latest release of their platform is focused on transformational automation technologies, including a customizable automation engine, digital feedback loop, enhanced security, and analytics with machine learning capabilities. The announcement also included industry-proven technologies from ecosystem partners to the Wind River Studio Marketplace, which makes solutions available that are developed and delivered on the Wind River Studio "cloud-native platform for the development, deployment, operations, and servicing of mission-critical intelligent systems from devices to cloud." The company claims the platform "enables dramatic improvements in productivity, agility, and time-to-market, with seamless technology integration that includes far edge cloud compute, data analytics, security, 5G, and AI/ML." "The next generation of cloud-connected intelligent systems require the right software infrastructure to securely capture and process real-time machine data with digital feedback from a multitude of embedded systems, enabling advanced automated and autonomous scenarios," said Kevin Dallas, president, and CEO, Wind River.
DevOps is a combination of practices that aims to enhance development processes by improving the collaboration between operations and development departments. Aim of DevOps is to provide continuous delivery with high software quality and shorten the systems development life cycle. Experts say that DevOps future trends are going to be popular and its popularity is going to reach its peak in 2020. Traditional Ops are 41% more time-consuming overall and spend an average of 7.2 hours weekly on communication while also traditional Ops spends 21% more time putting out fires. But DevOps spends 33% more time on infrastructure improvements and spends 60% less time handling support cases.