DevOps and cloud computing are interdependent and closely related

The defining characteristics of software are soft. For example, compare a flip phone to a smartphone. If you wanted to change the color of a flip phone's button, since the button is a solid piece of plastic, this would require changes to its manufacturing process. It can take weeks or even months from idea generation to market implementation. However, smartphones use software to display their keys, and the scope of the change is just a line of code in the configuration file. This change takes only hours or even minutes from idea to market implementation.

So why do data centers need more software?

In recent years, almost every business is a software business, and enterprises using data centers may demand speed above all else. To them, velocity means agile software methods and rapid iteration, and the most efficient way to find the best ideas is to release as much software as possible. Doing so increases their chances of gaining more than their competitors, which translates into more revenue for the company.

This is why DevOps and cloud computing are important: give them the speed they crave.

Development work for developers

If an enterprise requires developers to create a ticket to launch a virtual machine that requires actual use of well-managed hardware in the data center, it must be made easy for customers (i.e. developers) to use it.

A developer's job typically revolves around a two-week development process, focusing on implementing a specific set of features or fixing bugs from a priority list. The list of items to be completed is maintained and organized by professionals, and each developer on the team encounters an issue and completes it before moving on to the next requirement.

There are more details on this deadline completion. It involves setting up an environment that is similar enough to production so that existing tasks are feasible, and then writing automated tests for new features. When these tests pass, the developer knows the work is complete. This approach is called "test-driven development". As environments are created and tests written, developers get the business of writing code that implements new functionality, often by breaking the problem into smaller parts, working on each and deploying the parts into the development environment.

Initially, all tests will fail. However, as more of these loops encoding individual snippets are completed, more tests pass; eventually they all pass, indicating that the work has been completed. The code is then checked into a source control system such as Git, where automation deploys the new code into the staging environment (possibly creating an entirely new staging environment) and executes not just the new functionality, but all Previous testing. . If all these tests pass, the code may be batched as part of a manual version. Or, other automation will deploy it to production immediately, depending on how the team operates.

A large number of loops to minimize waiting

The purpose of this looping process is to build a small piece of code into a complete feature, and any waiting time injected into the loop is detrimental to efficiency and developer morale. Suppose you are responsible for a new feature and try to create a development environment for the code, only to wait a full day while the ticket process configures a virtual machine for the environment. This results in a loss of productivity, which slows down the cycle.

Now imagine that a new environment can be created in minutes with a virtual machine, or in seconds with containers. This situation allows developers to get to the core of their work faster: writing code. By minimizing wait times, their efficiency and morale will increase. When they can't get minimal wait times from their own data centers, they turn to public cloud alternatives.

What DevOps success looks like

DevOps, then, is about designing the automation of these environments that developers need during the development and deployment cycle to minimize their wait time and allow them to get more iterations on top of their code. Given that these environments are in an ever-changing state, they are natural allies for cloud-based consumption, but if enterprises pressure developers on their preferences for public and private clouds, they will likely tell speed is more important than detail.

With this in mind, the successful implementation of DevOps enables cloud computing to immediately activate the resources needed to support the various environments involved in the development and deployment process. And integrating security, monitoring and other aspects of the environment that data center operators care about is critical, but not at the expense of speed. Without the ability to automate important aspects of managing virtual machines, developers will not have the option of external resources to provide management needs.

Summarize

Over the years, developers and operations staff have sometimes clashed, blaming each other. In years past, IT operations had a monopoly on hosting options for the software developers were building, but public cloud changed all that, ushering in an era of automated environment creation that became the new standard for developers. The data center business can still do the same by injecting the same DevOps operations into the development process automation, and getting the attention of those development teams that are closely related to the company's revenue is not only possible, but also a must.

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