ControlRooms operates at the intersection of industrial manufacturing and advanced analytics. Their mission is to help manufacturers in sectors like chemicals, fertilizers, and glass prevent costly downtime by identifying anomalies in data from thousands of sensors. The stakes are high—unplanned outages can mean millions in losses.
ControlRooms’ vision was to harness AI to monitor these data streams, flagging issues before they escalate.
Dysnix joined the journey at a pivotal moment. ControlRooms had a proof-of-concept for their anomaly detection platform, but the infrastructure was not yet ready for real-world, multi-tenant deployment. The company needed a robust cloud foundation and automated CI/CD pipelines to move from concept to scalable SaaS.
ControlRooms’ early prototype, built on Microsoft Azure, demonstrated the potential of their approach. But scaling to serve multiple enterprise customers—each with unique security, compliance, and integration needs—required a different level of technical maturity.
The project’s core challenge was architectural: ControlRooms needed a multi-tenant SaaS platform, capable of ingesting and analyzing high-velocity data streams from diverse sources, all while meeting the stringent requirements of large industrial clients. Many of these clients relied heavily on Microsoft technologies like Windows and Active Directory, and demanded enterprise-grade security and compliance from day one.
Dysnix managed to meet all these requirements and deliver the scalable solution in the shortest amount of time.
Dysnix’s first step was to design a high-level architecture that could support ControlRooms’ ambitions. The blueprint emphasized scalability, security, and compliance, with a clear path to production readiness.
The technical leadership from Dysnix—Daniel Yavorovych (CTO), Alexander Vorona, and Sergei Kolobov—worked closely with ControlRooms to define milestones and break them down into actionable tasks, managed via Atlassian Jira. As the project progressed, Sergei Kolobov led the Dysnix implementation team.
Dysnix embedded its team within ControlRooms’ organization, participating in daily syncs and using Slack and Zoom for seamless communication. This close collaboration helped maintain alignment and quickly address emerging challenges.
The Dysnix team selected the following key DevOps practices and tools for the solution:
The project unfolded in well-defined stages, from initial infrastructure setup to the rollout of AI-driven features. The most complex aspect was architecting a platform that could scale horizontally while maintaining strict isolation and security for each tenant.
Unexpected issues—such as evolving customer requirements or integration challenges with legacy systems—were addressed through agile processes and continuous feedback loops. Our team ensured scalability and reliability by leveraging Kubernetes’ native capabilities, robust monitoring, and automated failover strategies.
With Dysnix’s support, ControlRooms transformed their early-stage prototype into a production-ready, multi-tenant SaaS platform.
The new infrastructure enabled ControlRooms to onboard new enterprise customers, delivering AI-powered anomaly detection at scale and with the reliability demanded by industrial clients.
ControlRooms’ partnership with Dysnix demonstrates how early investment in DevOps and cloud architecture can accelerate the journey from proof-of-concept to scalable SaaS.
By combining deep expertise in AI, cloud, and DevOps, Dysnix helped ControlRooms realize their vision: a secure, scalable, and intelligent platform for industrial anomaly detection—ready to meet the demands of the world’s largest manufacturers.
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