Rackspace increases customer retention on AWS using MontyCloud

Rackspace’s customers change their cloud environments constantly, adding resources, adjusting configurations, and shifting workloads in ways that can quietly introduce risk. For years, the hybrid cloud services provider captured a single snapshot of these changes across its base of more than 1,800 customers, documenting each environment once and building recommendations manually around that moment in time. Within a quarter or two, the customer’s environment had evolved well beyond what the report described, leaving Rackspace’s recommendations disconnected from what was actually running in the account.

That one-off approach limited what customers could see and what Rackspace could offer. On average, the company ran a few hundred assessments a year across its entire customer base, even while holding one of the highest AWS Partner tiers. “It wasn’t repeatable, it wasn’t scalable, and the customer couldn’t see the value,” says Matthew Normile, global partner leader for AWS at Rackspace. As a result, the gap between what the company documented and the customer’s actual environment grew wider with each passing quarter.

Rackspace’s engineering team built an internal tool and ran it alongside MontyCloud DAY2 for about 1 year. Comparing the results, the team found that MontyCloud’s solution captured far more detail per workload without months of added engineering time. Rather than maintain two parallel efforts, Rackspace expanded its use of MontyCloud and automated monthly customer assessments.

Rackspace organizes the assessments around the AWS Well-Architected Framework, which describes AWS best practices and strategies to use when designing and operating a cloud workload. The company also uses Landing Zone Accelerator on AWS to deploy a cloud foundation to support highly regulated workloads and complex compliance requirements. This way, the hybrid cloud and AI solutions provider can set up new customer accounts on the same security baseline. To read each customer’s assessment data, Rackspace built AI agents on Amazon Bedrock, which powers generative AI for more than 100,000 organizations worldwide. Using business language that doesn’t require deep AWS expertise, the agents draft a prioritized summary of what to fix first and why.

Rackspace built an internal chat tool that draws on this data. When an employee requests information about a specific customer account, the tool retrieves a response from current assessment data rather than outdated call records. From new hires to senior sellers, sales reps now enter customer conversations with the same technical detail at hand. That level of readiness helps Rackspace act as an adviser on a customer’s business outcomes rather than a reseller.

Using MontyCloud DAY2, Rackspace reengaged customers over 8 weeks and scanned more than 2,000 workloads. The company turned the results into net new professional services engagements in 59 percent of the scanned customers, and AWS offset some of the resulting project costs for customers. With access to assessment data, agents identified more than 300 AI-qualified leads directly from Rackspace’s existing resale base. “We measured a 20–25 percent increase in AWS consumption among the reengaged customers,” says Normile.

Rackspace can now run the full report cycle across workloads in about 45 minutes, instead of months or quarters. The shift from an annual review cycle to same-day answers gave the company’s sales and delivery teams a common, current view of customer accounts. “Using MontyCloud’s solution on AWS is a game changer, transforming what we can do for customers and how fast we can get there,” says Normile.

MontyCloud, an AWS Partner, offers a no-code platform for autonomous cloud operations.