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Aaron Francis and Try Hard Studios에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Aaron Francis and Try Hard Studios 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Building an S3 Competitor with Tigris CEO Ovais Tariq

1:07:27
 
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Manage episode 518019257 series 3579868
Aaron Francis and Try Hard Studios에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Aaron Francis and Try Hard Studios 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Aaron talks with Ovais Tariq, co-founder and CEO of Tigris Data and former Uber engineer who helped scale one of the world’s largest distributed systems. They discuss Uber’s hyperscale infrastructure, what it takes to build an S3-compatible object store from scratch, and how distributed storage is evolving for the AI era.

Follow Ovais:
Twitter: https://twitter.com/ovaistariq
LinkedIn: https://www.linkedin.com/in/ovaistariq
Tigris: https://www.tigrisdata.com

Follow Aaron:
Twitter/X: https://twitter.com/aarondfrancis
Database School: https://databaseschool.com
Database School YouTube Channel: https://www.youtube.com/@UCT3XN4RtcFhmrWl8tf_o49g (Subscribe today)
LinkedIn: https://www.linkedin.com/in/aarondfrancis
Website: https://aaronfrancis.com - find articles, podcasts, courses, and more.

Chapters:
00:00 - Introduction and overview of the episode
01:35 - Ovais’s background and introduction to Tigris
03:00 - Building distributed databases and infrastructure at Uber
06:00 - Uber’s in-house philosophy and massive data scale
09:00 - Hardware, power density, and talking to chip manufacturers
12:00 - Learning curve of scaling hardware and data centers
14:00 - The Halloween outage and lessons from Cassandra
16:00 - Building data centers across the world for Uber
17:00 - Founding Tigris and the vision for global storage
18:45 - How Tigris differs from AWS S3
20:00 - The architecture of Tigris: caching, metadata, and replication
32:00 - Why Tigris uses FoundationDB and its reliability
36:00 - Managing global and regional metadata
38:00 - How Tigris dynamically moves and caches data
41:30 - Building their own data centers and backbone
43:45 - Specialized storage for AI workloads
46:00 - Small file optimization and real-world use cases
49:00 - Snapshots, forking, and agentic AI workflows
51:00 - How AI transformed Tigris’s customer base
54:00 - Partnership with Fly.io and the distributed cloud ecosystem
57:00 - Growth, customers, and focus on media and AI companies
59:00 - What’s next for Tigris: distributed file system plans
1:01:00 - Technical challenges and building trust in durability
1:03:00 - Call to action: try Tigris and upcoming snapshot feature
1:05:00 - Advice for engineers leaving big companies to start something new
1:06:30 - Where to find Ovais online and closing remarks

  continue reading

26 에피소드

Artwork
icon공유
 
Manage episode 518019257 series 3579868
Aaron Francis and Try Hard Studios에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Aaron Francis and Try Hard Studios 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Aaron talks with Ovais Tariq, co-founder and CEO of Tigris Data and former Uber engineer who helped scale one of the world’s largest distributed systems. They discuss Uber’s hyperscale infrastructure, what it takes to build an S3-compatible object store from scratch, and how distributed storage is evolving for the AI era.

Follow Ovais:
Twitter: https://twitter.com/ovaistariq
LinkedIn: https://www.linkedin.com/in/ovaistariq
Tigris: https://www.tigrisdata.com

Follow Aaron:
Twitter/X: https://twitter.com/aarondfrancis
Database School: https://databaseschool.com
Database School YouTube Channel: https://www.youtube.com/@UCT3XN4RtcFhmrWl8tf_o49g (Subscribe today)
LinkedIn: https://www.linkedin.com/in/aarondfrancis
Website: https://aaronfrancis.com - find articles, podcasts, courses, and more.

Chapters:
00:00 - Introduction and overview of the episode
01:35 - Ovais’s background and introduction to Tigris
03:00 - Building distributed databases and infrastructure at Uber
06:00 - Uber’s in-house philosophy and massive data scale
09:00 - Hardware, power density, and talking to chip manufacturers
12:00 - Learning curve of scaling hardware and data centers
14:00 - The Halloween outage and lessons from Cassandra
16:00 - Building data centers across the world for Uber
17:00 - Founding Tigris and the vision for global storage
18:45 - How Tigris differs from AWS S3
20:00 - The architecture of Tigris: caching, metadata, and replication
32:00 - Why Tigris uses FoundationDB and its reliability
36:00 - Managing global and regional metadata
38:00 - How Tigris dynamically moves and caches data
41:30 - Building their own data centers and backbone
43:45 - Specialized storage for AI workloads
46:00 - Small file optimization and real-world use cases
49:00 - Snapshots, forking, and agentic AI workflows
51:00 - How AI transformed Tigris’s customer base
54:00 - Partnership with Fly.io and the distributed cloud ecosystem
57:00 - Growth, customers, and focus on media and AI companies
59:00 - What’s next for Tigris: distributed file system plans
1:01:00 - Technical challenges and building trust in durability
1:03:00 - Call to action: try Tigris and upcoming snapshot feature
1:05:00 - Advice for engineers leaving big companies to start something new
1:06:30 - Where to find Ovais online and closing remarks

  continue reading

26 에피소드

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