Now that IBM has completed the acquisition of HashiCorp the focus will now shift toward integrating the various DevOps tools, frameworks and platforms the combined companies provide to securely automate the development and deployment of software.
Meghan Liese, vice president of product marketing for HashiCorp, said the goal now is to make it simpler for DevOps teams to use tools such as Terraform to provision IT infrastructure alongside frameworks such as Ansible for Red Hat and FinOps tools from Apptio to manage IT operations. IBM acquired Apptio in 2023.
Collectively, that foundation will make it simpler for DevOps and platform engineering teams to keep a system-of-record as changes are dynamically made to IT environments that are being managed as code, she noted.
As part of that effort, the managed cloud services provided by HashiCorp will reduce the overall number of misconfigurations that have historically occurred when application developers programmatically provision IT infrastructure, Liese added.
HashiCorp, of course, as a unit of IBM will also be able to take greater advantage of investments in artificial intelligence (AI) that have been previously made. It’s not clear to what degree AI will automate the provisioning and management of IT infrastructure, but it’s already apparent that many workflows will soon be re-engineered using, for example, AI agents to more reliably provision IT infrastructure and optimize consumption of resources.
Less clear is to what degree DevOps teams might soon rationalize the number of tools and platforms currently used to build and deploy software as more DevOps workflows become automated.
Regardless of approach, DevOps teams would be well-advised to identify now which tasks are likely to become more automated as AI technologies become more pervasively employed. Undoubtedly, some organizations will use those capabilities to reduce the overall size of their IT teams, while others will seize an opportunity to build and deploy more applications at higher levels of scale. One way or the other, higher levels of automation should substantially reduce the amount of toil currently experienced by most DevOps teams. Despite a deep commitment among DevOps practitioners to ruthlessly automating as many processes as possible, there are still plenty of manual bottlenecks in workflows that truth be told many of the engineers performing would rather see eliminated so long as their overall role continues to evolve.
Of course, it remains to be seen in the age of AI just how much software can be built, deployed, secured and maintained by any one organization but the one thing that is likely to increase is complexity. The more applications deployed, the greater the number of dependencies between software components there will be. In larger organizations, the amount of software deployed is already well beyond the ability of IT teams to manually track and manage.
The challenge and the opportunity now is to leverage advances being made in automation to make it simpler for organizations of any size to build, deploy and consume as much software as they could possibly need without necessarily always needing to hire a small army of software engineers to support it.
