What makes some teams capable of generating and sustaining high-velocity, unparalleled, relentless improvement and innovation?

We will talk about fundamental principles by which such acceleration occurs, give examples of those principles in practice, and give participants an opportunity to test how those principles can be applied and translated to their own work, this will be quick workshop.

Automation is driving a radical shift in the delivery, infrastructure agility will improve predictability and achieve to reduce operational cost, enhance service levels, nowhere is this more apparent than in IT infrastructure management, where companies across industries are adopting various automation solutions

Autonomic computing is a self-managing computing model named after, and patterned on, the human body's autonomic nervous system. An autonomic computing system would control the functioning of computer applications and systems without input from the user, in the same way that the autonomic nervous system regulates body systems without conscious input from the individual. The goal of autonomic computing is to create systems that run themselves, capable of high-level functioning while keeping the system's complexity invisible to the user.

Large-scale systems, such as mega data centers, computer clouds, cyber-physical systems, Internet of Things, are becoming increasingly complex and burdensome for people to manage.

The goal of autonomic computing is to create self-regulating, self-healing computer systems. If you’ve ever had to troubleshoot your own computer problems, you can imagine what time and energy could be saved if the computer could troubleshoot itself.

DevOps alone is not going to help for better software delivery. DevOps with some analytics will give you smarter & intelligent software delivery pipeline.

The simple truth is that, as currently configured, data-centric companies will struggle to cross the divide between what is currently considered effective data and a modality where analytics is an inherent part of the fundamental fabric of business operations that benefits from continuous improvement. Today data is all too often a process where new insights and models get developed as a one-time effort or deployed to production on an ad hoc basis, and require regular babysitting for monitoring and updating.

I strongly believe DevOps with Analytics (Cognitive Services) would give tremendous outcomes in the IT operations perspective. Every organization is struggling to maintain the data noise. Data noise is nothing but a data overload and human’s inability to interpret.

Automation is driving a radical shift in the delivery, infrastructure agility will improve predictability and achieve to reduce operational cost, enhance service levels, nowhere is this more apparent than in IT infrastructure management, where companies across industries are adopting various automation solutions

Autonomic computing is a self-managing computing model named after, and patterned on, the human body's autonomic nervous system. An autonomic computing system would control the functioning of computer applications and systems without input from the user, in the same way that the autonomic nervous system regulates body systems without conscious input from the individual. The goal of autonomic computing is to create systems that run themselves, capable of high-level functioning while keeping the system's complexity invisible to the user.

Large-scale systems, such as mega data centers, computer clouds, cyber-physical systems, Internet of Things, are becoming increasingly complex and burdensome for people to manage.

The goal of autonomic computing is to create self-regulating, self-healing computer systems. If you’ve ever had to troubleshoot your own computer problems, you can imagine what time and energy could be saved if the computer could troubleshoot itself.

What makes some teams capable of generating and sustaining high-velocity, unparalleled, relentless improvement and innovation?

We will talk about fundamental principles by which such acceleration occurs, give examples of those principles in practice, and give participants an opportunity to test how those principles can be applied and translated to their own work.

DevOps has become buzzword that means different things to different people. Instead of trying to define DevOps, we are going to describe the foundational concepts that different people associate with DevOps.

IT organizations are adopting DevOps practices to enable more frequent software releases to production, both to accelerate time to market and improve the overall customer experience. But adopting DevOps practices requires a cultural shift in terms of the people, processes and technologies involved in development, testing and operations. Many organizations encounter significant challenges when embracing DevOps.