What's the Future of DevOps?
What's the Future of DevOps?
Industry executives' visions for the future of DevOps are wide-ranging, with ubiquity and security being popular responses.
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To gather insights on the state of DevOps, we spoke with 22 executives at 19 companies implementing DevOps for themselves and helping clients to implement a DevOps methodology. We asked, "What’s the future of DevOps from your perspective, where do the greatest opportunities lie?" Here's what they told us:
- The next wave of activity will be its application to where most customers are today in legacy enterprises. How to do DevOps in the datacenter to accelerate software and application development.
- A lot to be done and there are opportunities with the cloud. Traditional problems like needing a developer because a lot of infrastructure has gone away – we don’t have to build it, or manage it, ourselves. Democratizes small teams to build scalable systems with fewer people and less expertise.
- Our greatest opportunities lie in automation. We are constantly striving for 100 percent automation in testing and deployments to our Dev, Staging and Production environments. With continuous deployments, we are constantly improving the process.
- Simplification around a core set of values. Simplification of toolchains so that it’s more turnkey. A lot of silos and tools will be integrated – CI, CD, integrated testing, unit testing, feature testing – more of a “God Box.” Ultimately simpler implementation.
- Further decomposition with microservices and serverless. Managing fleets of things. There will be new tools to analyze large fleets of code and microservices.
- Standardization and consolidation. Able to standardize interfaces of sub-libraries with regards to CPUs and performance bottlenecks.
- DevOps will be fully adopted along with the strategy, tools, processes, and culture needed to create value for the consumer, which in turn will create value for the company and their shareholders.
- The most exciting is AI/ML in different fields and tools. As tools start to adopt AI, they will find patterns in logs and event monitoring to identify outliers to prevent and solve problems. Work more toward prevention.
- Self-healing. More tests in place the less the team has to worry. Autoscaling. Close off issues before they occur by being proactive.
Here’s who we talked to:
- Gil Sever, CEO, Applitools
- Mike Tria, Head of Infrastructure, Atlassian
- John Trembley, CMO and Scott Harvey, V.P. Engineering, Atmosera
- Aruna Ravichandran, VP DevOps Products and Solutions Marketing, CA Technologies
- Flint Brenton, CEO, Collabnet
- Tom Hearn, Data Center Architect, Datalink
- Shehan Akmeemana, CTO, Data Dynamics
- Robert Reeves, Co-founder and CTO, Datical
- Anders Wallgren, CTO, Electric Cloud
- Job van der Voort, Vice President of Product, GitLab
- Ben Slater, Chief Product Officer, Instaclustr
- Ilya Pupko, Chief Architect, Jitterbit
- Tom Joyce, CEO, Pensa
- Stephanos Bacon, Chief of Product, Portfolio Strategy for Application Platforms, Red Hat
- Michael Mazyar, CTO, Samanage
- Eric Wahl, IT Director and John Joseph, Vice President of Marketing, Scribe Software
- Manish Gupta, CEO and Founder, ShiftLeft
- Martin Loewinger, Director of SaaS Operations and Jonathan Parrilla, DevOps Engineer, SmartBear
- Chris McFadden, V.P. Engineering and Operations, SparkPost
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