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A Closer Look at DevOps – Breaking down organizational silos for greater efficiency and reduced time to market

The trend of DevOps has really picked up speed. Today, we’ll answer the question “what is DevOps?” and take a look at how businesses are using DevOps methodology stay ahead of the competition.

What is DevOps?

DevOps is a combination of the terms development and operations. DevOps is an extension of the agile development philosophy to promote faster and more efficient development and deployment of software.

Many businesses are adopting this approach because it helps them stay competitive by bringing new product features (or bug fixes) to market much faster. DevOps methodology advocates for automation and monitoring across steps in the process of software production – from integration, QA testing, deployment to production and infrastructure management. The result is shorter development cycles, more dependable software releases and increased deployment frequency.


What is DevOps? IBM Distinguished Engineer and Solutions Architect Sanjeev Sharma delivers a basic, comprehensive overview of DevOps methodology

Agile, DevOps & Continuous Delivery

Agile software development follows a philosophy combining the ideas of collaboration, adaptive planning and continual improvement to rapidly respond to feedback and evolving requirements. Seeing success using the Agile approach, organizations wanted to release the software faster and more frequently, giving birth to continuous delivery and the DevOps culture.

DevOps and continuous delivery are often used interchangeably because of their shared goal to speed up software deployment, but there is a subtle difference between the two. Continuous delivery is focused on automating software delivery processes. DevOps takes this one step further to also break down organizational silos for greater collaboration between the many functional areas that have a hand in this process.

DevOps and the Mainframe

Many business-critical applications rely on mainframes. If you want to efficiently deploy and maintain those applications, you need to make mainframes part of your DevOps workflow.

In our recent interview with Trevor Eddolls, he asserted that DevOps offers the greatest opportunity for organizations to get the most of our their mainframe investment. “For organizations that haven’t looked at DevOps and Agile computing, or are unaware of the fact that RESTful protocols work with IMS and CICS, this kind of modernization will bring them the greatest advantages in terms of growth and improved service.”

Organizations that do DevOps most effectively understand that, while technologies like Docker are one important component, an DevOps-optimized workflow involves all parts of an organization’s infrastructure.

Related: DevOpsify Your Mainframe: Continuous Improvement on Big Iron

Breaking down the mainframe silo

If you have a mainframe, there’s a good chance that your mainframe is one of the biggest silos inside your organization. That’s because, by default, mainframe data is very disconnected from the rest of your infrastructure. It exists in formats that are difficult to convert and use with modern analytics tools. It takes a long time to offload and is expensive to store for long periods

Fortunately, things don’t have to be this way. You can also de-silo your mainframe data by bridging the gap between your mainframe and the rest of your infrastructure.

See how applying DevOps principles can help you unlock the value of mainframe data – read Mainframe Challenge: Unlocking the Value of Legacy Data

Read our eBook -- Mainframe Challenge: Unlocking the Value of Legacy Data

How DevOps has changed mainframe careers

The DevOps revolution is meaningfully changing the job descriptions for the mainframe experts they hire. The idea that constant collaboration should be a central feature of IT workflows, and that team members should be prepared to coordinate with one another as much as possible, is now deeply embedded in the way most businesses organize their approach to software delivery.

Mainframe programmers are now required to branch out from roles strictly programming roles to also participate in administrative tasks. It also means that programmers and system administrators who specialize in mainframes need to collaborate more closely with the rest of the IT organization.

This greater collaboration requires a working understanding of other systems – as well as a preparedness to integrate information and resources quickly between mainframes and other types of environments. (In other words, you can’t pitch yourself as solely a mainframe engineer anymore.)

Big Data and DevOps: The Case for Bringing Them Together

DevOps… and Big Data?

You’ll notice that the description of DevOps and continuous delivery didn’t mention data. And it’s true that, by most conventional definitions, it is not closely linked to Big Data. But new ideas have recently emerged to bring them together.

Integrating Big Data into DevOps

If the goal of DevOps is to make software production and delivery more efficient, then including data specialists within the continuous delivery process can be a big win for organizations working to embrace DevOps. By integrating Big Data, organizations can achieve more effective software update planning, lower error rates, closer alignment between development and production environments and more accurate feedback from production.

Applying these principles to data management

DevOps focuses on software production, and at first glance might not seem to offer much to people working with data. But data specialists have much to learn from the movement.

But upon closer inspection, we notice that the data management process is similar to software production in that both involve multiple teams. A group to set up data storage, another to run the database and a third to work on analytics, plus a security team to keep the data safe and enforce compliance policies.

Traditionally, these different teams have not always collaborated closely. The folks who set up MySQL databases usually don’t know much about using Hadoop, for example. By embracing the core ideas of DevOps, however, organizations can achieve DataOps to make these different teams collaborate more effectively.

Check out these related articles:

Has your organization adopted DevOps methodologies that integrates your mainframe? Have you applied these principles to your data management strategy? See how Syncsort Integrate products can help you break down the silos.

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