Ran Pergamin
Employers on the program
- 2024–2026Amazon Web Services6 talks
Appearances by year
- AWS re:Invent
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| Nov 30, 2026 | AWS re:Invent 2026 | AWS re:Invent | lightning talk | Architecting video search at trillion scale with Amazon S3 Vectors as Amazon Web Services Storing and querying 1.5 trillion vectors demands rethinking traditional vector database architecture. | |
| Nov 30, 2026 | AWS re:Invent 2026 | AWS re:Invent | workshop | Build a fully managed data lake with Amazon S3 Tables as Amazon Web Services Data lakes have evolved from raw Parquet files with Hive-style partitioning to fully managed Apache Iceberg tables. In this hands-on workshop, you'll understand…Show lessData lakes have evolved from raw Parquet files with Hive-style partitioning to fully managed Apache Iceberg tables. In this hands-on workshop, you'll understand that evolution, then build a working analytics data lake with Amazon S3 Tables in under two hours. | |
| Nov 30, 2026 | AWS re:Invent 2026 | AWS re:Invent | chalk talk | From CSV to Iceberg: Understanding open data formats on Amazon S3 as Amazon Web Services Building a data lake on Amazon S3 and need to decide between Parquet, Hive, and Iceberg – or understand how your team already did? In this session we develop…Show lessBuilding a data lake on Amazon S3 and need to decide between Parquet, Hive, and Iceberg – or understand how your team already did? In this session we develop the mental model for storing structured data on Amazon S3 and trace how it evolved. | |
| Dec 1, 2025 | AWS re:Invent 2025 | AWS re:Invent | chalk talk | Building cost-effective data lakes with Apache Iceberg and Amazon S3 [REPEAT] as Amazon Web Services Optimize the cost-effectiveness of Apache Iceberg data lakes on Amazon S3 through expert-level implementation strategies for both self-managed Iceberg and S3…Show lessOptimize the cost-effectiveness of Apache Iceberg data lakes on Amazon S3 through expert-level implementation strategies for both self-managed Iceberg and S3 Tables deployments. | |
| Dec 1, 2025 | AWS re:Invent 2025 | AWS re:Invent | breakout | Inside S3: Lessons from exabyte-scale data lake modernization as Amazon Web Services Amazon S3 internally processes hundreds of petabytes daily across microservices, generating millions of logs. This session chronicles S3's journey from basic…Show lessAmazon S3 internally processes hundreds of petabytes daily across microservices, generating millions of logs. This session chronicles S3's journey from basic log analysis to a modern Apache Iceberg-based data lake. | Video |
| Dec 2, 2024 | AWS re:Invent 2024 | AWS re:Invent | workshop | Onboarding and optimizing AI/ML workloads with Amazon S3 & Amazon EKS [REPEAT] as AWS Join this workshop to learn about a solution to onboard and optimize distributed ML training workloads that use Amazon S3. Learn how to use the power of Amazon…Show lessJoin this workshop to learn about a solution to onboard and optimize distributed ML training workloads that use Amazon S3. Learn how to use the power of Amazon S3 as scalable storage for different types of ML training workloads, and harness the orchestration capabilities of Amazon EKS. |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Sumaja Kapa | 3 | 1 | 2026 |
| Aaron Chen | 3 | — | 2026 |
| Aaron Sempf | 3 | — | 2026 |
| Aarthi Raju | 3 | — | 2026 |
| Abbas Mooraj | 3 | — | 2026 |
| Abhijeet Jangam | 3 | — | 2026 |
| Abhishek Pandey | 3 | — | 2026 |
| Abhishek Sharma | 3 | — | 2026 |
| Abhishek Srivastav | 3 | — | 2026 |
| Abilashkumar P C | 3 | — | 2026 |
| Adam Hill | 3 | — | 2026 |
| Adam Richter | 3 | — | 2026 |
| Addy Upreti | 3 | — | 2026 |
| Aditi Garg | 3 | — | 2026 |
| Aditya Challa | 3 | — | 2026 |
Speakers with the same name are merged into one entry, so this page may combine more than one person. Affiliations are shown as each conference listed them.