Essential features of DevOps technology in this cloud era

DevOps is the evolution of traditional application development and operations roles driven by the consumerization of all software and business demand for agility. DevOps meets the needs of today’s businesses to stay relevant by constantly innovating through software.

DevOps is as much about people and process as it is about tools, if not more. Without cultural and process changes, technology alone cannot enable DevOps success. DEVOPS, one of the first challenges is to figure out what the industry really thinks “DevOps” means. DEVOPS asked experts from across the industry to define what DevOps means to them. The purpose of this list is not to propose a one-sentence definition of DevOps to appeal to everyone. The goal is to show how many different ideas are connected to the concept of DevOps and, in the process, learn a little more about what DevOps is all about.

Several top DevOps experts made this abundantly clear as DEVOPS compiled this list. That said, a variety of technologies can be critical to supporting the people and processes that drive DevOps. DEVOPS asked experts from across the industry for their recommendation on a key technology needed for DevOps.

DevOps tools are designed to support those defining aspects of DevOps: collaboration, silo breaking, bringing Dev and Ops together, agile development, continuous delivery, and automation, to name a few.

The list covers performance management, monitoring, and analytics.

1. APPLICATION PERFORMANCE MANAGEMENT – There are clearly many tools vital to the advancement of DevOps, but Application Performance Management is the one that stands out today as it has become so entrenched as the primary vehicle by which professionals aggregate and share critical data.

2. MONITORING – While DevOps is most often associated with automation and continuous integration/delivery tools, I believe that the most important tool organizations need to adopt and properly use to make a transformation to DevOps is a monitoring system. You can’t improve what you can’t measure. Implementing key metrics across the enterprise to help recognize areas that most need improvement is the key to identifying bottlenecks that are preventing DevOps adoption.

3. END-USER EXPERIENCE MONITORING: The parts of DevOps that turn the tide and start exposing production data to developers are also increasingly being implemented, but the processes around them are not. For example, tools that allow exposure to real end-user experience in production should become more transparent to engineering departments rather than just operations. Furthermore, many of these tools also provide value to the business side, so a successful implementation in the user experience monitoring domain would further satisfy stakeholders.

4. SYNTHETIC MONITORING: DevOps implies that you need to communicate between Ops and Dev in a good way. Using application/API driven synthetic monitoring will always give you the yardstick to measure your success.

5. INFRASTRUCTURE MANAGEMENT – If you’re stranded on a desert island (but with a strong, reliable internet connection), you still need to make sure your infrastructure works and your users are happy with their experience. What is needed is a robust and extensible digital infrastructure management platform that can collect data from each layer of your stack, analyze what is normal, what is not, and visualize the impact of anomalous behavior. This will allow you to spot issues that may affect your operations before they actually affect your business.

6. INCIDENT MANAGEMENT: Organizations must understand that tools are only part of the answer. They must have the necessary people, processes, and tools to successfully implement a DevOps environment. There are a number of useful tools in the DevOps ecosystem. You want to think along the lines of productivity, repeatability, and security when considering the most appropriate tools to facilitate a DevOps mindset.

7. ANALYSIS: DevOps needs tools that go beyond continuous release and deployment. They need tools that provide continuous analytics to measure and analyze application activities against business goals. While the focus is often on continuous release and deployment, this is not always possible in some companies due to regulatory issues. However, there is a need for continuous monitoring, tracking and analysis. First, use monitoring to collect end-user experience data, as well as infrastructure and application data. Then trace and piece together the transactions to show a timeline of what happened. Finally, create shared metrics that allow analysis to be compared against technical and business goals.

8. MANAGER OF MANAGERS: The DevOps agile development model extends to its tools, and we have seen a large proliferation of tools introduced to improve some aspect of monitoring. While each tool solves a specific problem, the proliferation has inadvertently fostered silos of experience, domain-specific views, and massive volumes of data generated in various formats. As the number of applications and architecture complexity increases, the must-have tool for scaling production support is an analytics-based administrator manager. It has to ingest all this operational event data and apply machine learning to automate noise reduction and alert correlation. This gives DevOps teams earlier warning of developing issues, better collaboration, root cause visibility, and ultimately reduces the impact of production outages and incidents.