Case Study 2: Multicloud Automation & Observability – Scaling Cloud Operations Without Scaling Cost

Case Study 2: Multicloud Automation & Observability – Scaling Cloud Operations Without Scaling Cost
Photo by Jerry Zhang / Unsplash

As businesses scale, managing multi-cloud environments becomes a logistical and financial nightmare. Without automation, IT teams are forced to rely on manual provisioning, troubleshooting, and monitoring, leading to bottlenecks, wasted resources, and rising operational costs. A single misconfiguration or unnoticed outage can lead to performance degradation, security risks, and financial losses.

To stay competitive, companies need intelligent automation and observability tools that proactively identify issues, optimize infrastructure in real time, and reduce the burden on human teams. In this case study, we’ll dive into how we developed a series of enhancements to our 500 million ARR managed hosting platform by introducing AI-powered automation and robust observability, cutting provisioning times by 300%, driving an incremental increase of $10.3M in new ARR in the first year, and enhancing infrastructure reliability—all while reducing operational overhead.

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Challenge: Customers managing hybrid and multi-cloud environments faced high operational costs, frequent manual interventions, and a lack of unified visibility into performance metrics.

Strategy

  • Headed the product roadmap for a multi-cloud automation fabric, integrating multiple cloud platforms into a single digital front-end experience and powered by a highly automated and value focused backend.
  • Led a cross-functional team (product managers, architects, engineers) to build AI/ML-driven observability solutions that proactively identify potential system failures.

Impact

  • Deliver a modern 'Rackspace Cloud' experience to customers through our SDDC Managed Hosting Portfolio, the manage.rackspace UI, and the VM Management service stack.
  • Reduced provisioning times by 300%, accelerating onboarding and unlocking an estimated $10.3M in new ARR in the first year.
  • Increased customer satisfaction by streamlining infrastructure management tasks resulting in an average increase of NPS by 2 points.
  • Link to Rackspace Performance: The automation capabilities we drove helped Rackspace meet growing demand for managed cloud services. Rackspace reported double-digit growth in its Cloud & Apps segments in 2020–2021, as confirmed in their earnings calls. For instance, see the Rackspace Q4 2021 Earnings Call (Feb 22, 2022) (Transcript/Recording Here), where leadership highlighted how next-gen cloud solutions contributed to new customer wins.

Technical Overview

Objective: Automate multicloud observability and incident response with AI-driven insights, proactive remediation, and federated access controls to improve MTTR, operational efficiency, and security.

Infrastructure: Integrated Datadog, IaaC Solutions, and endpoint management tools into Rackspace’s central management fabric, providing real-time dashboards, automated remediation, and secure engineer access.

AI & Automation: Leveraged Python-based automation, AI-driven anomaly detection, and cloud-native orchestration to transition operations from reactive firefighting to proactive prevention.

Solution Breakdown

✅ Federated Access & Dashboards

  • Unified a powerful observability tool, the Rackspace Automation Fabric, and our digital UX portals to provide more robust customer experiences.
  • Federated authentication into key tools enabled seamless, role-based customer and engineer access.
  • Custom summary dashboards provided real-time insights into performance, security, and costs.

✅ AI-Driven Incident Detection & Remediation

  • Python-based automation triggered proactive remediation scripts based on Datadog alerts.
  • AI anomaly detection shifted operations to a proactive stance, reducing MTTR.
  • Integrated with infrastructure orchestration tools to self-heal workloads and optimize environments.

✅ IaaS-Based Automation & Billing Workflows

  • Tagging-based billing workflows ensured accurate cost allocation across multicloud deployments.
  • Automated agent installation and provisioning reduced manual errors and deployment times.
  • Event-driven infrastructure automation enforced consistency, compliance, and resource efficiency.

✅ Secure Endpoint Management

  • Implemented one-time access tools ensuring compliant, auditable Rackspace engineer access.
  • Zero-trust security policies enforced least-privilege access for sensitive workloads.