Cloud Migration and Automation for Cost Optimization in a Global Tech Company

The client is a global provider of managed cloud services with nearly 10,000 employees in offices worldwide. They offer personalized white-glove cloud hosting solutions to help their customers simplify infrastructure management and reduce the strain on IT resources. The client has over 40 data centers around the world, managing hundreds of thousands of customers' virtual machines. Every few minutes, they receive data from each piece of equipment, such as servers, routers, switches, etc., which is essential for generating Monthly Service Reviews (MSRs) - equipment performance reports that are sent to clients every month.

The client, a global provider of managed cloud services, was facing challenges in generating monthly service reports for their clients. The process was not cost-effective due to the extensive manual work involved and the use of a paid third-party tool. The root cause of this issue was the lack of a centralized and unified approach to handle the vast amounts of data received from their equipment. The company’s data was managed on-premises, leading to significant costs and scalability issues. The scattered IT resources also caused problems with data accessibility, leading to inefficient data governance, storage, and organization. This inefficiency was particularly problematic when generating Monthly Service Reviews (MSRs) - equipment performance reports sent to clients every month.

N-iX, a software development company, helped the client by migrating their MS SQL Server infrastructure to Google Cloud Platform (GCP) and automating the process of generating service reports. Over 70 operational data sources, 4 data warehouses, and 1 data lake were migrated and consolidated to Google Cloud. This migration led to the decommissioning of over 20 servers, resulting in significant savings for the client. N-iX also ensured high data quality in the warehouse by locating and eliminating anomalies. The client's data from over 40 data centers worldwide was standardized and unified. The new solution used Google Cloud Dataflow to transfer data from Kafka to BigQuery. The ELT (Extract-Load-Transform) method was used instead of the standard ETL (Extract-Transform-Load) approach, enabling the creation of comprehensible reporting tables with information about the performance of each server instance. The generation of MSRs was also streamlined by consolidating information to BigQuery as a single location and automating the manipulation of raw data into MSRs.

• The migration to GCP and the automation of the service report generation process brought about significant operational improvements for the client. The unified data warehouse built on GCP elevated data management across the business. The new solutions created on GCP and the maintained data quality of the migrated data warehouse allowed the client to optimize operations, automate manual processes, and cut costs. The client was able to replace the third-party tool with their own solution, making the process more efficient and cost-effective. The standardization and unification of data from different vendors on their servers (Cisco, IBM, etc.) also improved the comprehensibility of the reporting tables.

• Migration from MS SQL Server to GCP and decommissioning over 20 servers resulted in significant cost savings.

• Centralizing and unifying all data in Google Cloud streamlined data collection, management, and accessibility.

• Automating the MSR generation process saved nearly 17,000 working hours per year and eliminated the need for an expensive third-party tool.