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How Airties achieved scalability and cost-efficiency by moving from Kafka to Amazon Kinesis Data Streams
- Airties, a wireless networking company, transitioned from Kafka to Amazon Kinesis Data Streams to enhance scalability and cost-efficiency.
- Airties focuses on AI-driven solutions for home connectivity, offering proactive customer care and network optimization through Airties Home.
- By leveraging AWS managed services, Airties improved Wi-Fi experiences, reduced help desk calls, and cut operational costs.
- The migration to Kinesis Data Streams allowed for serverless operations, automatic scaling, and cost reduction.
- Challenges with the previous Kafka-based architecture included operational overhead, scaling complexities, and cluster capacity issues.
- Kinesis Data Streams brought auto-scaling capabilities, stream isolation, dynamic shard management, and Application Auto Scaling for Airties.
- Airties implemented a decoupled architecture for historical data access, utilizing Kinesis Data Streams, Amazon S3, and Amazon DynamoDB.
- The new architecture provided scalability, performance, reliability, operational efficiency, and cost optimization benefits for Airties.
- The transition resulted in a 33% reduction in infrastructure costs, enhanced system reliability, and reduced environmental impact.
- The move to Kinesis Data Streams showcases Airties' commitment to operational excellence, sustainability, and efficient operations on AWS.
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