DevOps is a business model that combines cultural philosophies, tools, and practices that boost the organization’s capacity to deliver services and products at a very quick rate. A business that’s able to use the DevOps model can evolve and improve their products much more quickly than other businesses that use traditional software development and infrastructure management processes. Because of this enhanced speed for creating and improving products, a DevOps business can compete more effectively by creating high customer satisfaction.
Part of DevOps is about getting peoples from all disciplines to work effectively together. Usually, this means merging development and operations teams into a single cohesive unit so that the same people are working at all.
How did such a concept develop? Let’s take a closer look at IT’s role in business to understand how DevOps came to be.
The Arrival of the PC
Before the coming of the personal computer, the role of IT in business basically to improve operational efficiency. IT played a supporting role by reducing the cost of executing processes or by making processes go faster. This was the general situation in the 1960s and 1970s.
The personal computer arrived during the 1980s, and it became apparent that there were times when the software can’t be bought off the shelf to produce custom results for a business. This meant that businesses were tasking their IT people to build customized applications.
That started the cooperative efforts between people who want the custom applications (the “business side”) and the IT folks who built those applications. But there were clear delineations between the IT department and the business side of things. There arose a project-centric approach for IT, with the express goal of delivering a well-defined set of requirements on budget and on time.
The business side of the company also learned some IT tricks on their own, with office packages (word processors and spreadsheets) offering macros and embedded programming capabilities. The business side was then able to execute IT-like solutions on their own, without bothering the IT department.
Technology-Driven Differentiation in the 1990s
Still, there was at least some sort of collaboration between the business side and IT, and it enabled some people to realize that their technology can boost their company’s standing in the market. IT wasn’t just able to deliver existing products in more efficient ways. IT can actually come up with things that are completely new.
This meant a shift in focus. Previously it was about reducing the cost of delivering an IT project. But now it was all about creating profits from new technology. The rise of the dotcom economy saw the continuation of this trend called technology-driven differentiation, with the adoption of agile software development in the 2000s.
Though the dot-com economy eventually crashed, many noted the advantages of using the collaborative and product-focused approach that so many dotcoms adopted. It became apparent to many people that cycle time was the crucial key that businesses needed to focus on.
The Importance of the Cycle Key
Before all these, businesses typically concentrated on reliability and throughput. The businesses wanted a reliable process that transformed their business requirements into actual working software. They also wanted to deliver as many features as they could within a certain development capacity. Some companies than actually tried to improve their reliability and throughput even by sacrificing cycle time.
But some companies saw it differently. They realized that it was better for a business to make it a much shorter time to turn a new business idea into running software.
Obviously, these people couldn’t just sacrifice reliability and throughput just to shorten the cycle time, and so they searched for an approach that took all 3 factors into account. That meant there was an absolute need for close collaboration between the business side and the IT side.
That was what agile software development offered. It promoted collaboration with lots of short feedback cycles. Companies started releasing incomplete but usable versions of their software and then received customer feedback. The feedback-directed the next developmental stages, as the developers boosted the reliability of their software while also putting in the features that the users were looking for. This streamlined the process since they weren’t wasting time and effort on incorporating features that people didn’t like.
Improving on the Agile Software Development Approach
Even before the 2010s arrived, it became pretty apparent to quite a few people that the agile development approach still wasn’t enough. The people in the business side of things were often unable to describe precisely the system requirements they needed for the IT group to make. For the IT folks, they still struggled to keep the path to production short and without obstacles.
The first solution for these problems was using small cross-functional teams that kept the focus on particular aspects of the overall product. While this worked well enough for small startups, for larger enterprises it was more challenging to transition to this product-focused approach. It was hard to replace entrenched specialized teams for front-ends, back-ends, and databases with such cross-functional teams that brought together the development and operations people.
Thus we come to the DevOps movement, which was a grassroots movement that came up with techniques to make this joint effort possible. These techniques were able to help organizations use customer feedback to put in functional features in days and not in weeks or months. It dramatically shortens cycle time and thus boosted a company’s position in the market.
Here are some practices that are essential components of DevOps:
Continuous Integration (CI)
This means the developers need to regularly merge their code changes into a central repository. Then they can automate the build process and run their tests. The aims include find and addressing the bugs more quickly, improving the quality of the software, and reducing the time between new software updates.
Continuous Delivery (CD)
This is the practice which expands upon continuous integration. The code changes are all automatically built, and then tested and prepared for the production release. With continuous delivery, after the build stage, all the code changes are then sent to the testing and production environment. This means the IT folks have a product that’s always ready for deployment after passing a standardized test process.
In this approach, building a single application is regarded as building a set of small services instead. You have each service running its own process to achieve its single purpose. You can use an HTTP-based application programming interface (API) so that each service can communicate with the other services.
Infrastructure as Code
You provision and manage the infrastructure by using code and software development techniques. These can include continuous integration and version control. Because the API is in the cloud, your developers and system administrators are able to interact with infrastructure programmatically and at scale. They won’t have to set up and configure their resources manually. They can instead use code-based tools to interface with the infrastructure.
Basically, your engineers can treat the infrastructure in much the same way they treat application code. The infrastructure and servers are regarded as code, which means they can be deployed very quickly using standardized patterns. They can be updated with the latest patches and versions, or they can be duplicated in standardized and repeatable ways.
Policy as Code
Since you have your infrastructure and its configuration codified with the cloud, your organization can now monitor and enforce compliance dynamically and at scale. It’s easier to monitor changes over resources and to make sure that security measures are enforced properly. The non-compliant resources can be automatically flagged, and it may even be possible to automatically bring them back to compliance.
Monitoring Metrics and Logs
Your company can monitor logs and metrics to find out how the application and infrastructure performance affects the experience of the end users of your products. Your applications and infrastructure can generate data and logs that you can capture, categorize, and then analyze. You need to create automatic alerts or perform data analysis in real time to check on your services.
You should get new information regarding the root causes of unexpected changes and problems. With active monitoring, your services are able to remain available at all times.
Increased Communication and Collaboration
This is one of the most important cultural aspects of DevOps. You can enable collaboration by physically combining the workflows and responsibilities of development and operations. You can also use chat applications, wikis, and tracking systems for issues and projects to help encourage both groups to share information and to communicate with each other. This can speed up the communication process, and all parts of your organization can share the same goals and work together on the same projects.
Just as industrial automation in the 20th century changed manufacturing, so can DevOps change how companies can build and deliver software. Collaboration between the development and operations of people is the key when technology is the business.
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