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Shasidhar Eranti

Speaker

Shasidhar Eranti

2

talks

Manager, Field Engineering Databricks

Shasidhar is part of Specialist Solutions Architects team at Databricks. He is an expert in designing and building batch and streaming applications at scale using Apache Spark. At Databricks he works directly with customers to build. deploy and manage end-to-end spark pipelines in production, also help guide towards Spark best practices. Shashidhar started his Spark journey back in 2014 in Bangalore, later he worked as an independent consultant for couple of years and joined Databricks in 2018.

Bio from: Databricks DATA + AI Summit 2023

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Talks & appearances

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Schiphol Group’s Transformation to Unity Catalog

Discover how Europe’s third-busiest airport, Schiphol Group, is elevating its data operations by transitioning from a standard Databricks setup to the advanced capabilities of Unity Catalog. In this session, we will share the motivations, obstacles and strategic decisions behind executing a seamless migration in a large-scale environment — one that spans hundreds of workspaces and demands continuous availability. Gain insights into planning and governance, learn how to safeguard data integrity and maintain operational flow, and understand the process of integrating Unity Catalog’s enhanced security and governance features. Attendees will leave with practical lessons from our hands-on experience, proven methods for similar migrations, and a clear perspective on the benefits this transition offers for complex, rapidly evolving organizations.

Disaster Recovery Strategies for Structured Streams

In recent years, many businesses have adopted real-time streaming applications to enable faster decision making, quicker predictions, and improved customer experiences. Few of these applications are driving critical business use cases like financial fraud detection, loan application processing, personalized offers, etc. These business critical applications need robust disaster recovery strategies to recover from the catastrophic events to reduce the lost uptime. However, most organizations find it hard to set up disaster recovery for streaming applications as it involves continuous data flow. Streaming state and temporal behavior of data brings add complexities to the DR strategy. A reliable disaster recovery strategy includes backup, failover and failback approaches for the streaming application. Unlike the batch applications, these steps include many moving elements and need a very sophisticated approach to ensure that the services are failing over the DR region and meet the set RTO and RPO requirements.

In this session, we will cover following topics with a FINSERV use case demo: - Backup strategy: backup of delta tables, message bus services and checkpoint including offsets - Failover strategy: failover strategy to disable services in the primary region and start the services in the secondary region with minimum data loss - Failback strategy: failback strategy to restart the services in the primary region once all the services are restored - Common challenges and best practices for backup

Talk by: Shasidhar Eranti and Sachin Balgonda Patil

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