Couchbase announced a broad range of enhancements to its Database-as-a-Service Couchbase Capella™.
After my last two blogs about how Application Lifecycle Management (ALM) and DevOps have progressed and discussing the greatest challenges facing DevOps adoption, it's now time to look ahead and spend some time preparing for the future. What trends will have the biggest impact on the software industry and DevOps in particular this year and beyond? How can enterprises set themselves up to succeed with so many rapid changes occurring in development and delivery?
Start with Analyst Insights on Accomplishments, Challenges & Opportunities in DevOps - Part 1
Start with Analyst Insights on Accomplishments, Challenges & Opportunities in DevOps - Part 2
Industry analysts Stephen Hendrick (AD Research), Clive Longbottom (Quocirca), Altaz Valani (InfoTech) and Edwin Yuen (ESG) all shared insights with CollabNet in a recent Q&A. The analysts were asked, "What technologies/innovations will emerge in 2017 that will have the biggest impact on the DevOps industry?"
Integration is Key
The responses vary a bit, but three of the analysts mention the need for integration. We now have a large number of DevOps point tools in enterprise environments, each generating data, that must be rationalized in order to be useful for decision making. Not only do tools and data need to be integrated, but teams and processes as well. All of these moving parts need to be visible to managers in one unified place.
Edwin Yuen explains: "I think the area for greatest innovation is for more integration between the various functions and tools in DevOps. We've seen great innovation in specific areas, such as collaboration, communication, or automation, but how do we more tightly integrate those functions together and also manage them?"
Yuen also notes the coming opportunity to evolve more traditional development methods. He adds, "I continue to see potential for innovations on integrating and migrating traditional development models and processes into Agile and DevOps."
Altaz Valani again raises the issue of leveraging data throughout the Software Development Lifecycle (SDLC), he sees a new category rising — "Assistive Lifecycle Management" — to tackle the data integration challenge.
"We now have the data throughout the SDLC. The next step is assistive lifecycle management using this historic data to navigate risks in the software delivery pipeline. This will have implications to resourcing, capacity management, and release management," said Valani.
Keep an Eye on Containers
Clive Longbottom, brings our attention to a different area and says what's coming is "Containers 2.0." He explains, "Current container technology is pretty weak. There are large security issues in sharing so much of the underlying resources in the way that Docker does."
What does this have to do with DevOps? As you know, DevOps approaches span the entire delivery pipeline. As for containers, organizations use them to package and deploy monolithic and microservices-based applications. In regards to microservices, leveraging the packaging and deploying of applications so they are portable across cloud providers and providing a loosely coupled, single-function component model is what organizations want to achieve with both technologies.
In general, organizations are hoping that by applying DevOps tools and processes they can see lower failure rates of new releases, shortened lead time between fixes and faster mean time to recovery. But, unless you can measure your processes and tooling, you will never know how much the intersection between using microservices and containers to support a DevOps environment is adding value.
Longbottom continues, "Expect 2017 to see some pretty fundamental changes in container technology — and therefore how DevOps will have to deal with them across a broad, heterogeneous cloud environment."
Stephen Hendrick also mentions the way that containerization and serverless computing are revolutionizing how we think about development and deployment. He says, "These technologies will challenge software quality assurance from an integration standpoint."
Highlighting integration as key, he continues, "This will require a more comprehensive approach to integration testing and completeness and consistence checking of the policy that drives the decision on actions."
Don't Forget About IoT and How Software is Eating the World
It might be remiss to have a discussion about future technology without mentioning IoT and the changes in our world due to technology. Altaz reminds us that tools must keep up with the increasing amount of software now being used by a wider range of industries. He says, "Increased emphasis on IoT will require significant maturity in distributed application testing. Tools need to mature in order to accommodate this demand."
As software is embedded into more and more areas of our every-day lives, the demand for these testing capabilities will increase.
It will be exciting to see how these expert insights on innovation and new technology play out as the year progresses. I am particularly looking forward to seeing more mature tools as integration technologies advance, new innovations and best practices for containers, more comprehensive integration testing, and assistive lifecycle management as next steps for the SDLC.
Thank you to the analysts for sharing their thoughts on innovation in 2017 and for participating in this three-part Q&A series!
Eric Robertson is VP DevOps Product Engineering & Management at CollabNet.
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Red Hat announced new capabilities for Red Hat OpenShift AI.
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Red Hat announced Red Hat Developer Hub, an enterprise-grade, unified and open portal designed to streamline the development process through a supported and opinionated framework.