Electric Vehicle Company Cuts Streaming Costs by 40% With AWS
When Advantages turn into Results
40% Reduction in Data Transmission Platform Costs
Migrating from Confluent Cloud to Amazon Kinesis reduced the costs of the event streaming service by approximately 40%
Enterprise-Scale Event Processing
It can process more than 130 million events per hour while maintaining a high level of reliability and performance
Modernization Based on Native AWS Technologies
It replaced third-party data transmission services with native AWS technologies, simplifying operations and enabling more agile scalability
Challenge
Modernizing a Mission-Critical Streaming Platform Without Disrupting Business Operations
- Manage a complex architecture consisting of 118 Kafka topics.
- Support high-volume workloads, processing streams of up to 130 million records per hour.
- Maintain data schema compatibility and preserve integrations with Databricks consumers.
- Ensure performance, scalability, data retention, and operational stability throughout the migration process.
- Complete the migration before the Confluent contract renewal to avoid additional licensing costs.
- Execute the transition without disrupting production services or business operations.
The Commitment
Migration to an AWS-Native Streaming Architecture
GFT, in partnership with AWS, designed and implemented a comprehensive migration from Confluent Cloud to a streaming architecture based on native AWS technologies, using Amazon Kinesis Data Streams and AWS Glue Schema Registry. The project encompassed assessment and planning, the design of the new platform, schema migration, and the execution of the transition, ensuring service continuity throughout the entire process.
The Benefit
A More Efficient, Scalable, and Future-Ready Data Platform
- The migration was successfully completed within three months, allowing the Confluent platform to be phased out before the contract renewal.
- Dependence on a third-party streaming platform was eliminated by adopting native AWS services.
- Operational efficiency was improved through tighter integration with the AWS ecosystem.
- Performance, stability, and scalability of business-critical workloads were maintained.
- A future-ready platform was established, capable of driving advanced analytics, data-driven innovation, and continued business growth.
- The project strengthened the strategic collaboration between the company, AWS, and GFT.
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