“Netuitive offers an adaptive monitoring solution for cloud infrastructure, applications, and services, powered by a patented self-learning correlation engine,” says Brian Spindler, VP of Engineering, Netuitive. The engine uses multivariate regression analysis to calculate correlation coefficients between metrics based on time-series data collected, leveraging the significance of certain relationships between metrics variables across the data.
The Netuitive technology establishes a baseline of what metrics and their relationships have been historically. Netuitive policies enable development and operations teams to see anomalies that present with significance above the historical baseline and related to AWS EC2, Linux OS, MySQL, and other systems and technologies.
“We have launched a SaaS version of our product wherein we now deliver code to production on a weekly basis,” says Spindler. This increase in deployment speed is thanks to the company’s new DevOps processes. Here is the first part of Netuitive’s two-part story.
Before Moving to a DevOps Shop
Before moving to a DevOps software development approach including continuous delivery, Netuitive used a Scrum framework together with Jenkins and Ant products and scripts the company developed in-house to develop Netuitive software and the patented self-learning correlation engine within. “We recognized the value of automation early on—using simple shell scripts and our own Web API we were able to orchestrate quite a lot,” says Spindler.
Still, these methods presented challenges. The extensive planning process, including conjuring up development time estimates that Scrum requires for Sprints were challenging. In addition to and despite all that planning, numerous interrupts occurred surrounding testing and deployment issues that stemmed from software complexity and integration management. “These interrupts slowed us down and impacted our burn rate,” says Spindler. (The burn rate calculates the speed of the business spend above and beyond income.)
Mountains of bug fixes were also a concern. With an exorbitant amount of time spent fixing bugs that would only present themselves in rare edge cases, Netuitive was putting too much effort into builds while getting too little in improvement or new features out of the process. “While we sought a solution for feedback loop issues, it became clear that this would require a more agile approach. We looked to DevOps for inspiration, which led us to migrate from Scrum to Kanban,” says Spindler. Kanban is an illustrative process for managing targeted production goals, including what to develop when and how far to extend that development.
As enterprises adopting DevOps often mention, the cultural change necessary to move to DevOps approaches was the most challenging. In particular, getting everyone on board with automated testing as a proof of software validity was tricky. Internal teams such as QA and developers had to transform their existing relationship. “For years, these groups were adversaries; now I am asking them to be allies. This required the developers to take on the responsibility of writing tests while QA validates and ensures the tests are sufficiently broad,” says Spindler.
Goals, Results, & Hazards: Method to Madness?
Netuitive had specific outcomes in mind from switching to a more complete DevOps shop. Quality and productivity improvements were high on the list. In fact, the two would have to be mutually inclusive and close knit to ensure both. To accomplish this, Netuitive deploys on a weekly basis, using the full Atlassian suite for collaborations and issue tracking along with a combination of Bamboo, Gradle, and Salt Stack to automate the configuration, manage the infrastructure, and manage deployment operations. This orchestration helps quality and productivity to dance in harmony.
The results are more than aesthetically pleasing. “We are increasing the velocity of deployments through continuous process improvements,” says Spindler. By deconstructing the Netuitive product and dividing it up into independent service modules and components, the company can move overall progress along more quickly by improving each individual component separately and simultaneously, making faster progress gradually than they would by waiting to finalize a single, complete product update.
Netuitive experienced three fully distinct bumps in the road or ‘hazards’ on the way to morphing itself into a DevOps shop. “There were issues related to automating testing, changing the organizational workflows to accommodate automation, and deconstructing the product into granular enough services that we could deploy independently,” says Spindler. These were all related to the desire to automate the product production as a whole. Netuitive works continually to refine the necessary balance between layering on additional tests across those granular services to raise the bar on quality and excising some of those testing layers in order to increase deployment velocity.
Tune next time when DevOps.com reproduces the relative chronological Netuitive DevOps development process from release to release along with differentiations, benefits, and the payoffs that the company did not expect.