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Petabyte-scale data migration made simple: AppsFlyer’s best practice journey with Amazon EMR Serverless

  • AppsFlyer successfully migrated their data infrastructure from self-managed Hadoop clusters to Amazon EMR Serverless, reducing costs and operational complexity.
  • EMR Serverless dynamically scales resources in real-time, providing agility and high availability for AppsFlyer's massive data operations.
  • AppsFlyer's architecture includes Apache Spark, Kafka, Iceberg, and Airflow, handling 100 PB of data daily across various open source technologies.
  • The migration enhanced scalability, cost-efficiency, and operational simplicity, freeing up engineering teams for innovation.
  • AppsFlyer utilized infrastructure templates, Airflow integration, and solutions for permissions management to streamline the migration.
  • Custom Spark plugins and seamless cross-account permissions management were key in ensuring a successful migration to EMR Serverless.
  • AppsFlyer leveraged Spline for lineage tracking and Datadog for centralized logging, enhancing visibility and compliance.
  • Monitoring and observability played a crucial role in ensuring stability and efficiency for AppsFlyer's operations on EMR Serverless.
  • The transition to EMR Serverless empowered AppsFlyer teams to operate autonomously, focus on innovation, and achieve significant cost savings.
  • The approach taken by AppsFlyer can serve as a model for organizations looking to migrate to EMR Serverless for improved data processing capabilities.

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