In today’s competitive IT landscape, automation and optimization of critical workloads are essential for enterprises aiming to maintain an edge. This success story highlights the collaboration between Microsoft Azure and SUSE Quality Engineering (QE) Department in automating testing for SAP workloads on Azure—an initiative that not only enhanced customer satisfaction but also paved the way for future opportunities.

Background: The need for reliable automated quality testing of operating system changes

SAP workloads form the backbone of mission-critical operations for many enterprises, and migrating these workloads to platforms like Azure requires a commitment to performance, reliability, and security. SAP customers managing their infrastructure on SUSE Linux Enterprise Server (SLES) on Azure face specific challenges: They need to ensure their operating systems remain updated and secure while avoiding disruptions.

To meet these demands, Microsoft and SUSE recognized the importance of automated quality engineering processes. By validating and optimizing SAP workloads on Azure, they could guarantee a seamless, consistent user experience for customers. Key areas of focus included automated testing for new releases, functionality validation, and regression prevention.

The challenge: Achieving consistent reliability

Migrating mission-critical workloads like SAP to Azure presents complex demands for performance and uptime. For SUSE QE and Microsoft, the goal was to introduce automated processes that would make deployment seamless and reliable. They identified a need to:

• Ensure all building blocks of the SAP workloads on Azure were thoroughly tested.
• Integrate testing for both major and minor releases.
• Validate functional correctness and perform comprehensive regression testing.

The collaboration: A joint mission for automated testing

SUSE QE and Microsoft Azure’s SAP Engineering team joined forces to address these needs by implementing an end-to-end automated testing solution. SUSE’s openQA, coupled with Azure’s SAP Deployment Automation Framework (SDAF), became the backbone of this project.

Key steps

• Strategic discussions: Stakeholders from both teams discussed the project’s goals, anticipated benefits, and potential obstacles.
• Task force creation: Engineers, architects, and project managers formed a dedicated team to oversee the automation of testing.
• Identifying gaps: Microsoft and SUSE worked together to identify components, were not commonly covered by testing and experienced issues in the past.
  • SAP tools (sapcontrol) – focus on functions, used in high availability configurations
  • cloud-init-netconfig
  • Azure Fence agent – cover both MSI and SPN configuration
• Implementation scenarios: Microsoft provided important end-to-end scenarios for automated testing of SAP workloads on Azure.
• Define the architectural components of the test automation framework and agree on integration points.
  • SDAF – automate the deployment of end-to-end SAP on Azure scenarios, integrated with openQA.
  • SUSE OpenQA – execute the defined tests, including injecting failures in the scenarios and verify all components perform as expected

Technical implementation and development in action

Over several months, experts from both teams collaborated weekly to refine the automation processes, develop testing pipelines, and address technical challenges. By establishing continuous communication, they ensured timely progress on deployment, integration, and testing.

The collaboration led to the creation of optimized deployment templates, new testing pipelines and enhanced SDAF functions.

• Integration of newly designed tests into SUSE’s openQA workflow.
• Creation of templates for best practices in SAP workload deployment on Azure.

Results: Enhanced testing automation, reliability and customer satisfaction

The automated processes developed through this collaboration had significant results:

• Early new SUSE OS pre-validation and end-to-end testing: leads to faster support for SAP on Azure on the new SUSE OS.
• Early detection of regressions: Early testing during development cycles to catch potential bugs.
• Enhanced automation: Automated testing significantly reduced the time required to validate SAP workloads on Azure, improving reliability.
• Improved delivery: Early detection of regressions ensured smoother Day-One operations.
• Customer satisfaction: SAP customers experienced higher satisfaction due to reliable, seamless migration and management of their workloads on Azure.

SUSE QE contributed to this success by delivering comprehensive test scenarios, including:

• Fence Agent Testing: Automated testing for Azure’s Pacemaker cluster options.
• Azure Resource Agents: Validations for services like Azure Load Balancer and Azure Metadata Service.
• SAP Tools and Cloud-Init: Automated testing for essential tools and initialization services, ensuring complete coverage.
• Implementing test scenarios for end-to-end SAP on Azure deployments in high availability configurations.

Future opportunities: Building on success

The positive outcomes of this collaboration open doors for exciting future advancements, including:

• Extended automation: Expanding automation processes to cover more workloads and scenarios, enhancing efficiency further.
• AI and machine learning: Leveraging Azure’s AI capabilities to proactively predict and address potential issues.
• Broader industry adoption: Promoting this solution across industries to help more organizations benefit from automated SAP workload quality engineering on Azure.
• Day-Two-Operation: Developing additional solutions for continuous maintenance and improvement of SAP workloads on Azure.

Conclusion: A benchmark for future innovation

The partnership between Microsoft Azure SAP Engineering and SUSE’s Quality Engineering Department exemplifies the impact of collaboration in driving innovation and customer success. By automating SAP workload quality engineering processes, they delivered a solution that meets modern enterprise demands for reliability and efficiency. This project serves as a benchmark for future initiatives, setting the stage for ongoing advancements in the cloud computing landscape.