GEMA – Central process control with Camunda
GEMA orchestrates more than 580 cross-team processes with millions of records centrally using Camunda. cimt developed the process control and supported the migration to Google Cloud.
Otto Group GDPR deletion requests
Otto Group
Customer
About the Otto Group
Industry: Retail and wholesale
Headquarters: Germany
Your contact
Rouven HomannMember of the Board, cimt Group
Consulting focus
- Google Cloud Platform (GCP)
- Java
- GKE
- Pub/Sub
- IaC (Infrastructure as Code)
- CI/CD
Quantifiable benefits
- Increased robustness
- Increased scalability
- Reduced operating costs
About the Otto Group
Founded in Germany in 1949, the Otto Group is a globally active retail and services group with around 41,000 employees in 30 major corporate groups, operating mainly in the economic regions of Germany, Europe and the USA. Its business activities cover the segments of platforms, brand concepts, retailers, services and financial services.
The project: GDPR deletion requests in BI
The existing software solution for capturing and processing information in order to fully implement the right to erasure under Art. 17 GDPR in BI , was to be replaced. In line with the BI department’s cloud strategy, cimt rebuilt the application for the Google Cloud Platform (GCP) and optimised it for maintainability, security and efficiency.
The challenge
The previous tool, a hard-to-maintain Lua script running in a third-party analytics database, was inadequate for this task and not cloud-ready. In addition, the tool was unable to query Google BigQuery, one of the company’s central data stores, which made integration even more difficult. Maintaining the old process was also very labour-intensive. The BI department therefore needed a new, future-proof solution for capturing and processing deletion requests under Art. 17 GDPR.
The solution approach
cimt implemented a containerised Java service that provides an interface to various data sources such as Google BigQuery and stores the collected data in Cloud SQL. The container platform chosen was Google Kubernetes Engine. The previously self-managed ActiveMQ was replaced by Cloud Pub/Sub.
The result
The robust and scalable infrastructure reduced manual intervention and significantly improved operational efficiency. It also created a sustainable foundation for the company to manage the capture and processing of deletion requests in BI more efficiently and to continue ensuring GDPR compliance.
Using Cloud Build and Artifact Registry to build and store container images contributed significantly to the robustness of the solution. In addition, considerable cost savings were achieved in BigQuery by optimising queries and aggregated data.
References
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