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Essential Features of Devops Technology in This Cloud Era
DevOps is an evolution of traditional application development and operations roles driven by the consumerization of all software and the business demand for agility. DevOps helps today’s business needs to stay relevant through constant software innovation.
DevOps is about people and processes as much as tools. Without cultural and process changes, technology alone cannot ensure DevOps success. DEVOPS, one of the first challenges is to find out what the industry really thinks "DevOps" means. DEVOPS asked experts from across the industry to define what DevOps means to them. This list is not intended to be a one-sentence definition of DevOps that applies to everyone. The goal is to show you how many diverse ideas are related to the concept of DevOps, and in the process learn a little more about what DevOps is.
Several top experts in the DevOps arena made this very clear before DEVOPS compiled this list. That being said, different technologies can be critical in supporting the people and processes that drive DevOps. DEVOPS asked experts from across the industry for their recommendations on the core technology required for DevOps.
DevOps tools are designed to support these ultimate aspects of DevOps: collaboration, breaking down silos, unifying Dev and Ops, agile development, continuous delivery, and automation, to name a few.
The list includes performance management, monitoring and analytics.
1. Application Performance Management: There are obviously many tools for advancing DevOps, but application performance management is one that stands out today because it is so deeply embedded as the primary means by which practitioners collect and share critical data.
2. Monitoring: While DevOps is most often associated with automation and continuous delivery/integration tools, I believe the single most important tool that organizations need to properly adopt and use to transform to DevOps is a monitoring system. You can’t improve what you can’t measure. Implementing key metrics across the business to help identify areas most in need of improvement is key to identifying the gaps holding back DevOps adoption.
3. End User Experience Monitoring: The pieces of DevOps that are turning the tables and starting to expose production data to developers are also becoming more and more common, but the processes around them are not. For example, tools that enable the manufacturing end-user experience to become more transparent to engineering departments, not just operations. Moreover, many of these tools value the business side as well, so a successful deployment in the user experience monitoring domain will satisfy even more stakeholders.
4. Synthetic monitoring: DevOps implies that you need good communication between Ops and Dev. Using application/API-centric synthetic monitoring will always give you a yardstick to measure your success.
5. Infrastructure Management: If you’re stranded on a desert island (but with a strong and reliable internet connection), you still need to make sure your infrastructure is working and your customers are happy with their experience. You need a robust and scalable digital infrastructure management platform that can collect data from all layers of your stack, analyze what’s normal and what’s not, and visualize the impact of anomalous behavior. This will allow you to catch issues that could affect your operations before they really affect your business.
6. Incident Management: Organizations must understand that tools are only one part of the answer. They must have the people, processes, and tools in place to successfully implement a DevOps environment. There are a number of useful tools in the DevOps ecosystem. You’ll want to think along the lines of productivity, repeatability, and security when considering the tools best suited to facilitate a DevOps mindset.
7. Analytics: DevOps requires tools that go beyond continuous release and deployment. They need tools that provide continuous analytics to measure and analyze application activities against business goals. Although the focus is often on continuous release and deployment, this is not always possible at some firms due to regulatory concerns. However, there is a need for continuous monitoring, tracking and analytics. First, use monitoring to collect end-user experience as well as infrastructure and application data. Then track and merge transactions to show what happened. Finally, create common metrics that enable analysis to be compared against both technical and business goals.
8. Manager of Managers: DevOps’ agile development model extends to its tools, and we’ve seen a huge proliferation of tools implemented to improve some aspect of monitoring. While each tool solves a specific problem, the proliferation has inadvertently contributed to silos of expertise, domain-specific views, and the generation of massive amounts of data in different formats. As the number of applications and architectural complexity increases, an analytics-driven manager of managers is an essential tool for scaling production support. It should take data from all these operational events and use machine learning to automate noise reduction and alert correlation. This gives DevOps teams early warning of emerging issues, better collaboration, root cause visibility – ultimately reducing the impact of production disruptions and incidents.
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