Client background & business context

  • Client profile: leading consumer electronics retailer in Europe 
  • Project: SAP BW migration to Google Cloud Platform 


For this client, a collaboration was ongoing on other SAP-related projects. With years of SAP-related experience, we managed to deliver to our client a stable and performance SAP Systems in Cloud. 

Besides the time limitations, for this project, we had to surpass and find solutions to some important challenges such as: 

  • Ensure a smooth migration path: migrate the BW on HANA Solution to Google Cloud Platform with a complete architectural redesign, from concept to the Cloud go-live 
  • Properly respond to system size and complexity: during the project we had to migrate over 22 HANA servers and 8 ABAP/Java servers, with a total of 28 TB RAM HANA Database and 1 TB RAM ABAP/Java, of a total of 2596 vCPUs. 
  • Ensure a minimal system downtime during and after the migration: for each system, we had an accepted downtime of the systems of 1 day/system. Also, we had to create different scripts to automatically stop and then start the systems during night-time and weekends, thus optimising costs and reducing to a minimum the possible losses resulted from downtime. 
  • Time to market: ensure that the migration is undergone in a short period of time. 

Our approach

Our client was using two operating systems (AIX and Linux) with different databases (HANA and Oracle) on premise. After a thorough analysis, we suggested a migration to the Google Cloud Platform, which allowed the systems to operate with only one operating system (Linux) and one database system (HANA). 

Due to the complexity of the project we approached this migration in five different steps: 

Project assessment

  • Duration: 1 month 
  • On this phase we made an on-premise SAP landscape analysis, drafting the preliminary sizing. Then we created the Target Architecture providing all the details of the future state of the architecture being developed. As part of this phase, we have undergone the GCP Infrastructure discovery and assessment.

Preparation of the migration plan 

  • Duration: 2 months 
  • As part of this phase, we established the target sizing, the target technical architecture, and the technical migration plan. Also, during this period, we made a High Availability/Disaster Recovery proposal that also considered different cost models.

Migration to Cloud 

  • Duration: 1 month 
  • Only after preparing and securing clear scenarios and high availability, we started to set-up the Cloud Infrastructure. We ensured the data replication to the Cloud and the take-over in Cloud. Then, our developers made the HANA upgrade and the go-live in GCP.

Handover procedures 

  • Duration: 1 month 
  • As a standard in all our approaches, we want to empower our clients with all the information necessary to have ownership over a platform. We delivered all the needed documentation, together with the setup procedures, a disaster recovery simulation, and technical monitoring in the Cloud.

Continuous monitoring and improvement 

  • Duration: 1 month 
  • In this phase, we ensured all the daily operations and script-based automation needed for resource optimisation and infrastructure administration. 


  • Google Cloud Platform
  • SUSE


For this Google Cloud Migration project, our specialists created a new architecture, which covered the optimisation as drafted in the challenges, and guaranteed 99.75% availability in case of disaster. 

The network was configured to make the transition to the Cloud almost invisible to the end-users and to minimise all possible losses that might’ve resulted from eventual downtime. 

We managed to reduce the system complexity of the BW Landscape by redesigning the technical architecture and optimising the system processes. This allowed the platform to operate with less technical resources in terms of both hardware and software 

With the help of the Cloud capabilities, all the time needed for scaling up or out, creating new systems, or system decommissioning decreased with approx. 60%. 

Also, we designed the target architecture and the migration process to reduce the functional testing of the systems to approx. 2 days, leading to a decrease in costs and in implementation time. 

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