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[CLAIRE] Welcome to Talking Postgres, a monthly podcast for developers who love this database.

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I'm your host, Claire Giordano, and in this podcast, we explore the human side of Postgres

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databases in open source, which means we delve into why do people who work with Postgres do what

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they do and how did they get there? Thank you to the team at Microsoft for sponsoring this

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community conversation. Today's guest, and I'm so excited, this is episode 29, is Shireesh Thota.

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Shireesh is the CVP for all the Azure databases at Microsoft. He's responsible for leading

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engineering and product management for databases, including Azure Cosmos DB, Azure SQL DB,

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and Microsoft SQL Server, MySQL, and of course, my favorite, my absolute favorite, Postgres.

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Shireesh has been working on databases either as a developer or a product leader or engineering leader since 2006.

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And in addition to working at Microsoft, Shireesh spent the better part of a year in like the 2022-2023 timeframe as SVP of engineering at SingleStore,

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working on a database that used to be, some of you might remember it as MemSQL.

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Welcome Shireesh.

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[SHIREESH] Thank you, Claire.

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Really excited to be here today.

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[CLAIRE] I am too. We started talking about this months and months ago. So I'm glad that we're here.

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Today's topic is titled How I Got Started Leading Database Teams. But the I is not Claire,

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the I is Shireesh in this case. And I think before we get focused on the leadership part,

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right? How you got started leading database teams. I'm really curious how you got started in tech

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at all. Can we go in the Wayback Machine and talk about that?

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[SHIREESH] I'm happy to.

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So I've done my engineering in computer science.

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So I started right there.

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And then right after my computer science engineering,

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I did a brief internship at Oracle.

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So my database roots go all the way back to Oracle.

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And then it was just a quick few months.

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And then I started as a high availability engineer at Motorola.

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For those who don't know Motorola, this used to be a company and was acquired by Google.

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Motorola was a really big company that was basically into the embedded systems and it

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was trying to do wireless carrier software.

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So I started there, built a bunch of real-time operating systems code to do embedded packages

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for wireless carriers like Sprint, Verizon, etc.

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That was for one and a half years.

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Then I came to the United States to do my master's,

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again, in computer science.

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That was also...

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but it was mostly rooted in string algorithms,

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and I thought I was going to go into biotech.

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But I landed an internship at Microsoft,

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and then I spent almost 20 years at Microsoft ever since.

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[CLAIRE] Wow.

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And what about then the transition from being an engineer to being a manager?

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How did that come about?

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[SHIREESH] Yeah, you know, maybe I'll take a few minutes to talk about my journey at Microsoft,

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and then I'll touch upon your question, Claire, if that's okay.

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[CLAIRE] Okay.

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Absolutely.

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[SHIREESH] Yeah, so when I started at Microsoft,

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my first foray into Microsoft was basically being an intern in SQL Server.

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So I started working on Management Studio in SQL Server.

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It was very fascinating because what I was touching was impacting millions of developers,

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and it was touching so many important customers across the world.

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So it was super fascinating.

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I managed to build a tool that would compare two large databases.

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This was back in 2006.

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[CLAIRE] Okay.

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[SHIREESH] And then I loved the experience so much that I collapsed all my courses into one semester.

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I basically graduated in three semesters for my master's and came back and joined Microsoft

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full-time employee in the same team that I started.

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This was in SQL Server.

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So I spent around five years in SQL Server, contributed to major releases, 2008, 2008

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R2, then a bunch of releases.

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And then I was the developer number one, effectively, for Cosmos DB.

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So I was there right from day one.

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Spent a lot of time in Cosmos DB, built various pieces,

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query engine indexing, elasticity, lots of things.

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And then I took over the entirety of engineering for Cosmos DB.

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And then ever since, I've been a manager.

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So to then answer your question about my transition,

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I definitely did not wake up one morning thinking that it would be fun

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to do one-on-ones, performance reviews, budget management, et cetera.

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It definitely was not the case.

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[CLAIRE] T&E approvals, how about that?

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[SHIREESH] I became the manager in the old-fashioned way.

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My manager at that time tapped me on the shoulder and said,

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hey, I think you are good with people.

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We need to scale.

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We were just five engineers on Cosmos DB back in 2012.

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We started in '11, and for the first one, two years,

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for two years, I think we were just five people.

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Around that time, he said, "We need to scale, we're going to hire a bunch of people.

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I need you to help me."

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I said yes, without fully reading the spec.

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Then there's a big contrast between the life as a developer and life as a manager.

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As a developer, it's binary.

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You have bugs, you have architectures that you need to go build, you have to fix bugs,

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you have to really design things.

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Success was measurable in commits, PRs, and just the amount of usage that you're seeing, et cetera.

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When you become a manager, you have to really understand that the job role, of course, changes

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significantly. It is not just about really going and fixing things anymore, but it is really about

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unblocking, aligning, and amplifying. My role changed massively in terms of that transition

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to not just be the problem solver myself,

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but to really make space for others to shine and to enable them

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to first and foremost build a great team.

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And those things did not come easily, of course.

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It takes time.

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And one of the most important things to remember,

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and at least the mistake that I have done,

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was that early on as I was transitioning into being a manager,

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I managed like how I coded, right?

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And that doesn't work. People are not functions. They're different, of course. They're all human

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beings with different aspirations. So you really need to connect the vision that we have with their

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aspirations. It takes time. And then...

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[CLAIRE] Wait, can we pause on that for a second? [Yeah, yes, of course.]

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I managed like how I coded.

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Can you peel that onion and tell me more about what that means?

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[SHIREESH] Yeah. So when you're coding, you basically think of a lot of pieces in an objective way. You basically think that these are the input metrics,

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these are the output metrics. You want to basically achieve a few things in terms of being quick,

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being precise. You want to think about resiliency, security, and you're acting as though the pieces

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are all obviously objective functions and without any emotions attached to it. And so you don't want

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to treat your people in that way. And that is a common mistake when most of the engineers who

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become managers the first time. There's no documentation on the people. You have to go

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poke them, understand what they are trying to really achieve, what their aspirations are.

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Unlike APIs, when you're trying to use them, you have a lot of well-defined interfaces.

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You really know how to use them. When will they go right? When will they go wrong? How to use them,

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how not to use them, how to deploy them in the right places, to then go build the architecture.

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You have a lot of objective mechanisms around it.

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You're effectively doing the same kind of, you're solving a similar kind of a problem if you think about it.

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There is an architecture to organization as well.

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Who needs to play in what position?

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Who needs to do what you want to do so that everything comes together,

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just like how a bunch of functions,

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a bunch of classes come together to make a component.

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So in that sense, they are similar,

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except people don't have documentation.

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You have to really poke.

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You have to spend a good amount of time coaching,

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learning what they really want to do.

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So learning them and figuring out

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how we really come together as a team

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to then achieve our vision and mission

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is a different ballgame.

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So if you apply the same mentality and the same thinking that you do when you are coding and building things technically, and I've seen managers do this quite often.

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I myself have done this and I failed at it.

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Yeah, that is really what I meant to say.

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[CLAIRE] Okay, because sometimes I think about management as well, I don't know how old your kids are

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and you don't have to tell the world on the podcast but when you have teenagers a lot of times you

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you can't address an issue head-on, you kind of have to come at them sideways you know you have

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to understand like you said what are their motivations what are they trying to do and it's

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just different. Influencing people is hard.

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[SHIREESH] Absolutely.

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[CLAIRE] Hmm, you also started to talk about the organizational structure too, so there's managing people and all those

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challenges and then there's managing a larger organization and thinking about

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that hierarchy and that's probably, well that you probably didn't have to deal

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with that in your first management job, right?

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[SHIREESH] Not, yeah, not then.

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It definitely took a while for me to get to that point to then having organizations, manager of

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managers, and now where I have a really large organization. So that's the second level of

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transition. And I wouldn't think of that as really, it's not a promotion, really. It's almost like a

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transformation where you are really looking at things in a bigger lens and you have to zoom out.

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You really have to think about how to shape the environment and the bigger mission so that there

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is a scale aspect that can thrive in that environment. And that is truly the key piece.

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And often people don't think about up and down. They may either think about up, meaning trying to

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align well with the mission of the broader organization, and then forget about how to

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cascade it down. Sometimes people do the opposite, which is that they basically go focus quite a bit

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in terms of making sure that their organization thrives, but they fail at connecting to the

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broader mission that their company or their organization on top has. So you really need to

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play this game in three pieces. One is, of course, managing up and aligning well. The second is to

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make sure that your team is set up to achieve those functions that your broader organization has.

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There's also a third piece where you have to laterally manage your engagement with your other

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teams. Now, this is, in some sense, connected to the first piece, which is going up, but it is an

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equally important piece of the puzzle. And that takes a while in terms of really trying

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to figure out how do you go from, you know, a small boat to a medium sized ship to a really

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big ship.

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[CLAIRE] Yeah, and that managing, or networking, staying in touch, and in sync, and aligned with your peers

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which is what I think of when you talk about managing your engagement laterally, that's what

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you mean, right? [Exactly.] Other leaders of teams next to you. It's, I just feel like that's not documented

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well. Like a lot of people miss that in the beginning. And the thing is, I don't know why

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you think it's important to laterally manage other teams. So I should ask you that. But one of the

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things I've observed is that if you have a relationship with someone and maybe there's some

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trust or some background or some familiarity, then when there's a conflict, it's so much easier to

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resolve it versus if you haven't talked to them in nine months and you only see them in staff

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meetings and you don't really know each other then I think it's harder to resolve a conflict.

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[SHIREESH] It's a super important part, Claire, and I'm really glad you brought this up.

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This is really what I call a social capital.

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You really can't succeed in the tech without social capital.

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And it comes across in multiple ways.

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And one of the reasons why I encourage people to have a little bit of a face time,

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we are, of course, a hybrid company at Microsoft, and I really love that,

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but once in a while, sort of getting that social capital is important

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because it gets burnt really fast.

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And it is really important to understand people.

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It need not be just face-to-face, but even otherwise.

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Again, as I said, people, unlike APIs, are not documented strictly.

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So you really have to go and poke and have to figure that out.

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And that's the only way to unblock most of the tougher, harder situations.

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And they come up every day.

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[CLAIRE] How do you feel about, I know you talked about face time, right?

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And we are hybrid and I love that we're hybrid.

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I'm recording this from my home office today.

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I appreciate that about Microsoft tremendously,

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but how do you feel about the importance of like turning on video

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when you are having conversations with people

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and you're not in the same location?

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Is that something you do or does it not matter?

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Or do you have a philosophy on that?

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[SHIREESH] So personally, I do that in every meeting that I am in. I rarely go off camera. I believe that it benefits me a lot because I sort of really want to express my emotions and how I'm thinking more viscerally,

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and so people can see me and understand what's happening

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and the body language does play a bigger role.

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So I definitely do that and I know that a lot of my managers

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and the people that I collaborate with do that as well

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and I really respect that.

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Having said that, we live in a very hybrid, very diverse world

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and so I understand absolutely that there are cases

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and situations where you really can't.

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We have to manage a lot of things in our personal lives.

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I know many of my reports who have to drop their kids sometimes when they're taking calls,

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and it's not convenient.

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I totally get that.

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So I'm very supportive of those situations.

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Just broadly speaking, though, I would love to sort of do more often.

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You don't have to do it every case.

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We need to have that flexibility.

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But I encourage people to really go, come on video,

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because there's a lot that you would say without speaking a single word,

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and it can't show up, right?

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When you are living in a hybrid world, I think that's important.

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So I, especially when we are talking to customers, I really encourage my team members to go and do that.

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I do that myself.

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I know my manager does that.

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Yeah,

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so I'm in the, you know, try and keep the camera as much as possible on.

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I'm in that camp.

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[CLAIRE] I'm in that camp too, philosophically, but I'm not a morning person,

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and so for my 8:00, 8:30, even sometimes my 9:00 calls,

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I'm just not ready to be on camera.

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Anything after 10:00, my time, I'm on camera, no problem.

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But yeah, earlier in the morning, I just can't do it.

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So, but yeah, and then people are across time zones.

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So what's 10:00 for me might be 8:00 in the evening for somebody else.

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So that's always a complication.

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Okay, for anybody who's listening and maybe somebody who's a developer, has been a developer for years,

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but is trying to figure out their future career path and is wondering if management is a job that they would be good at or that would appeal to them.

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I'm curious if there are any other failures or surprises or big challenges that you had on that transition from being a developer to being a manager that are worth, I don't know, warning people about or sharing, sharing with people.

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[SHIREESH] Yeah, I think the number one thing, as I said,

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is that when you are transitioning from an IC to being a manager,

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You don't want to manage people like how you manage code.

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That's really a huge warning sign, I would say.

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The second thing I would say is that a lot of times,

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one of the best ICs on the team

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tends to become the manager for that team.

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And when that happens, they basically inadvertently,

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without any intent really,

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compete with the people that they're managing.

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And that's just a really big red flag.

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You're really not there to compete with them.

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You're no more trying to shine against the people.

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You're really enabling the people.

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You have to be secure enough to be a manager,

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to know that your win is rooted in their win.

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And that thinking and that emotional mindset is extremely important.

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And you have to think about it every day when you're a manager.

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You're really here to make sure that you enable them.

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You make space for other people to shine.

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And ultimately, the goal is for the team to win. And we are not playing a single person sport. We

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are absolutely not playing tennis. We are playing soccer. So that imagination, that thinking, needs

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to be there when you're a manager. I would also say and warn people that if you really don't enjoy

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meetings and trying to really go from topic to topic, then it can get a little harder.

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Because when you're a manager,

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you don't necessarily sit in front of the terminal often

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and you don't have,

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you're typically in back-to-back meetings

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with no compile button, right?

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There's no compilation.

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There's no build going on here.

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So you need to ensure that you're comfortable with that.

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You also need to ensure or be comfortable

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with the fact that your job

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is not being the smartest person in the room.

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It is about learning from others.

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It's making sure that you really are

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amplifying with your judgment. You're unblocking. You have to focus on the transitions and the

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changes. But building people as a manager and then focusing on the vision to amplify and to sort of

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culturally navigate the teams, those are the job functionalities. And you are trying to take on a

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leadership role, a manager role. And you have to be comfortable with these things. And it's totally

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okay for somebody to say that I'm not going to enjoy this. I'm better off being an IC.

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And there most of the corporate companies, Microsoft for sure,

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enables these things today. And that's a great news. You can definitely go quite far being an IC.

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So yeah, these are a few topics that I would say people need to remember.

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Now, naturally, there's a lot of nuances, but these are a few things that I see many of the new

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managers need to take some time to reflect on.

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[CLAIRE] Got it.

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Okay, so if we go back to the episode title,

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how I got started leading database teams,

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we've got the word database in there.

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And obviously, it looks like you've spent your entire career

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working on databases.

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You did not go into biotech,

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and so was there some aspect of databases or something that happened in that first Oracle internship or your first Microsoft internship?

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Was there a trigger for why you stayed in this space?

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[SHIREESH] Yeah, so I was absolutely lucky to have gotten these opportunities to intern at some of the

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best places in terms of learning databases.

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When I was at SQL Server interning, and I obviously had the opportunity to talk to some of

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the stellar leaders who have made incredible contributions to SQL Server and to databases industry all up.

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What I've learned over the course of my time there, and obviously it kept building on me,

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was that databases are the microcosm of everything that's happening in computer science and just generally our technical industry.

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The reason why they're microcosm is because when you look at the stack for databases,

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you have to basically touch on every aspect of it.

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You have to start by looking into silicon.

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In fact, in our own databases organization,

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we look at what are all different possibilities

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to engage with hardware vendors,

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Intel, AMD, ARM vendors, etc.,

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to look at what we can do to make sure

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that our databases run really well on the silicon.

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So you start there, and then you go up

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and look into algorithms,

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query engines, query optimizations, system engineering.

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You have to figure out how do you work well with the operating system constructs.

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There's a lot of runtime aspects to it.

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Algorithms, of course.

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There's a lot of database theory that you touch on.

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And then on and on, networking, of course,

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because we are building a lot of distributed systems.

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And so there's quite a lot of scale-out aspects in there.

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And then you can go all the way up to full stack.

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You have to really go build great developer experiences with drivers.

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You have to make sure that the best drivers, best way of managing your databases, is available.

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So when you look at the entire stack of databases, they really touch on everything that's there

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in the technical industry, most everything.

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And now with AI, of course, there's a lot of infusion of AI in databases in lots of different

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ways.

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We are thinking about how to do vector indexing.

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We are thinking about how to bring the best way to semantically interpret query results.

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You do see a lot of that in Postgres and across other databases as well. But I was lucky enough

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to get that insight and feel like this is the place where it would be a complete experience,

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a really consummate sort of understanding of our tech. And so I stuck with it and I kept loving it

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more and more. Yeah.

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[CLAIRE] I think I mentioned this before that I was going to ask you this, and I don't know that you would

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remember, but when my kids were young, oftentimes you fill out these kind of templates that say,

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my favorite color is blue, and my favorite food is whatever it is, and my favorite thing to do

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is this. And there's usually a question, when I grow up, I want to be..., and I'm curious if you

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remember what your "when I grow up, I want to be" answer was?

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[SHIREESH] That's a great question. I do remember. I think when I was, very early on, I wanted to

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be a bus driver because I thought steering a giant vehicle with the honks, etc., it looked

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like absolute power. And obviously, every kid, you know, obviously, probably this was

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one of the popular choices being a kid, sitting in front of the front seat and pulling the horn.

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That was the dream, I guess.

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And then later on, as I probably grew up a little bit, I started loving math.

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And so I knew that I was going to be an engineer or I wanted to be an engineer.

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What kind of an engineer?

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I wasn't sure about that part.

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But yeah, that was really how we got started.

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But pretty early on, I loved math.

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And so I knew of some of the folks who became engineers in and around me.

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And that appealed to me quite a bit.

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I did not touch my first computer until I was in my seventh grade, high school, I think.

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So it came very late.

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I learned BASIC first, and then I choose computer science thinking that this is really the...

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I loved it, of course.

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Early on in high school, when I started playing with simple programs,

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it just gave me the absolute power that I was dreaming,

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that I couldn't get sitting in front of the front seat in the bus.

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But I could get that sitting in front of the computer.

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It just transforms you into a different world,

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and I really loved every bit of it.

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[CLAIRE] I mean, the metaphor of a bus driver almost works for your current job. [I guess, yes.]

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You're trying to make sure people get to where they're going,

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and there's all sorts of different kinds of people on the bus.

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I don't know. It sort of works.

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I don't know about the absolute power part of it,

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but you are steering a giant vehicle. [Thank you.]

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Okay. So, obviously, I know this but people listening might not know this, at Microsoft you

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are VP of engineering and product team responsible for all of our Azure database

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managed services, and some of the other database work that's going on as well,

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you know, Microsoft SQL Server is used on-prem, correct?

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[SHIREESH] Yes, yes.

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[CLAIRE] Okay, so it's not all and not only about Azure and cloud database services,

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but you have to work with lots of these different databases.

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Now, I have the luxury of getting to work with just one,

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which I think is pretty awesome for me.

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But I'm really curious what it's like to have that breadth

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and to span so many different technology stacks.

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[SHIREESH] I'm grateful. I enjoy it. I'm very excited about having this opportunity every day.

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The breadth is definitely pretty big, but the themes are similar. Now, every database is different.

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Ultimately, yes, many of the applications could go and be ported into one other database,

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from one database to the other database. But I am a firm believer that there's no one database

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that can answer all the questions, and it's the best fit for every problem that you got.

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Generally, it doesn't happen that way.

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So these databases are tuned and perfected in certain different ways.

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So if you look at, you know, some are,

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obviously there are bigger level differences in terms of relational and non-relational,

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and we do have a flagship non-relational database in Cosmos DB.

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Outside of that, everything else is a relational database.

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Amongst the relational databases, we have both, you know,

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on-prem databases as well as cloud versions, managed services in cloud.

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Most of our databases are managed databases.

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SQL [Server] is the only one that we offer on-prem.

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And it's a very classic, it's a extremely successful battle-tested database for several decades.

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So they're all very different.

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And Postgres, of course, it's one of the most important open source databases that we got here.

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And I love having the opportunity to work across.

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And they all shine in different ways.

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If you think about Cosmos DB, it's designed to offer you low latency at global scale

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with a superior elasticity, single-digit millisecond guarantees for reads and writes worldwide.

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And it has some of the most amazing distributed systems characteristics.

397
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If you look at SQL Server, it brings deep, deep, deep enterprise features

398
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and rock-solid security characteristics with amazing performance characteristics.

399
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It's been there for several decades, and it continues to grow,

400
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and we are investing deeply into SQL Server.

401
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And it's the same engine that powers both on-prem as well as in the cloud.

402
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Postgres is phenomenal.

403
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Now, I've come to appreciate and love Postgres quite a bit in the past few years.

404
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It is open source at its best.

405
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I joke with everyone that it's the Linux of databases,

406
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and it's amazing to have such a community who's very principled

407
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and forward-looking, marry the best of relational algebra,

408
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and then sort of really attract the vast majority

409
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of the developer ecosystem as well as the enterprise community.

410
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So it's really a Swiss knife, I would say,

411
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Swiss Army knife of databases.

412
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So, yeah, and then MySQL as well.

413
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There's still quite a lot of MySQL community out there

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in terms of really running the commercial databases, web apps.

415
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It's really a privilege for me to have the breadth and being involved in all these

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different databases.

417
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[CLAIRE] Yeah, but you've got to have to do some pretty dramatic context switching during the day.

418
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Although, maybe if you know, you're so familiar with all the different stacks and all the different people, maybe the context switching isn't hard.

419
00:29:32,690 --> 00:29:33,220
Is it hard?

420
00:29:35,419 --> 00:29:41,040
[SHIREESH] It's hard and easy, in cases where, you know, so obviously relational algebra is same no

421
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matter where you go.

422
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All the databases have the same kind of challenges in some sense.

423
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But they're optimized in different ways.

424
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So, yes, it's similar.

425
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So I know the stack, and I'm not really switching too much across the board.

426
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Non-relational database, Cosmos DB is a little different,

427
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but I know I've had the opportunity to build it from the day one.

428
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So I know Cosmos DB quite a bit, so that helps me.

429
00:30:08,260 --> 00:30:12,560
It is often the organizational architecture, the business challenges,

430
00:30:12,800 --> 00:30:14,360
how do we incorporate different pieces,

431
00:30:14,540 --> 00:30:17,440
how do we go to market with all these different offerings,

432
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and how do we enable customers, provide them the right choice.

433
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Those are the places where it gets tricky.

434
00:30:23,670 --> 00:30:25,540
So yeah, it becomes harder in those places.

435
00:30:26,290 --> 00:30:30,580
But we have a very good suite of database offerings

436
00:30:30,820 --> 00:30:32,420
where we enable the choice for the customer.

437
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So it's a win-win.

438
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[CLAIRE] Okay.

439
00:30:36,410 --> 00:30:43,780
So Affan Dar, who works for you and was a previous guest on this podcast, we'll try to include

440
00:30:43,780 --> 00:30:46,340
the link to his episode in the show notes,

441
00:30:47,080 --> 00:30:52,340
he wanted me to be sure to ask you, what is your favorite database and why?

442
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[SHIREESH] So I don't know if it's Affan, apparently the guest from the previous episode also wanted to

443
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be a bus driver. So I don't know if it was Affan, but I love Affan, so great question. And like

444
00:31:09,260 --> 00:31:15,320
any responsible parent, I would... I know the answer, but I wouldn't say it publicly, so...

445
00:31:17,840 --> 00:31:19,180
[CLAIRE] Wait, you're not allowed to have favorites,

446
00:31:19,340 --> 00:31:20,760
you love all your children equally,

447
00:31:21,060 --> 00:31:22,120
is that the deal?

448
00:31:21,120 --> 00:31:26,820
[SHIREESH] Yeah, absolutely. Yeah. You know, I have to keep it that way, unfortunately. But, you know,

449
00:31:26,880 --> 00:31:31,180
having said that, as I said, every one of these databases is just amazing.

450
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They have different strengths.

451
00:31:33,620 --> 00:31:37,600
We believe that there is a need to have this choice.

452
00:31:38,180 --> 00:31:39,920
You don't want to have 24 different databases,

453
00:31:40,340 --> 00:31:46,080
but there are a few databases in terms of how they're optimized.

454
00:31:47,960 --> 00:31:51,600
There are special cases where some databases are designed in a different way.

455
00:31:52,000 --> 00:31:56,340
Cosmos DB is built to have scale and high availability in its core DNA,

456
00:31:56,420 --> 00:32:02,420
right? And so it is going to be great when you want to have a distributed system challenges.

457
00:32:02,740 --> 00:32:09,120
SQL is designed to have that great hybrid characteristics both on premises as well as in

458
00:32:09,120 --> 00:32:15,500
the cloud. It is rooted in being a very strong general purpose database, there are a lot of

459
00:32:16,140 --> 00:32:24,499
SMP workloads, classic OLTP workloads, very security rich offerings in SQL, so if you're looking for

460
00:32:24,520 --> 00:32:25,840
that kind of a database for tier zeros,

461
00:32:26,180 --> 00:32:27,360
yes, SQL is a great choice.

462
00:32:27,460 --> 00:32:30,700
And Postgres, one of the greatest things about Postgres

463
00:32:30,760 --> 00:32:33,240
is that it's good across the spectrum,

464
00:32:33,500 --> 00:32:36,000
both on the developer front as well as on the enterprise front.

465
00:32:37,760 --> 00:32:39,380
And as you know, and as everybody knows,

466
00:32:39,780 --> 00:32:43,040
the ecosystem, the developer ecosystem,

467
00:32:44,280 --> 00:32:46,680
is rooted around Postgres significantly.

468
00:32:47,680 --> 00:32:50,240
As AI applications continue to mushroom,

469
00:32:50,780 --> 00:32:54,120
I think this is going to be one of the most amazing things for Postgres.

470
00:32:54,460 --> 00:32:57,880
So it's just designed for the AI era, in my opinion.

471
00:32:58,510 --> 00:33:01,560
And the amount of extensibility that Postgres brings,

472
00:33:01,860 --> 00:33:03,360
that's just going to be a huge advantage.

473
00:33:03,620 --> 00:33:05,780
So, yeah, I mean, I would say the same thing,

474
00:33:05,880 --> 00:33:08,280
that different databases are great at different things.

475
00:33:08,860 --> 00:33:10,400
I love all my children,

476
00:33:10,970 --> 00:33:13,020
and it's a privilege to have this opportunity.

477
00:33:13,880 --> 00:33:15,960
[CLAIRE] Okay, you know, Affan is going to give you a hard time.

478
00:33:16,740 --> 00:33:21,540
And you know that I really wanted you to say that Postgres is your favorite database.

479
00:33:19,679 --> 00:33:22,820
[SHIREESH] I will buy him ice cream.

480
00:33:25,300 --> 00:33:25,460
[CLAIRE] Okay.

481
00:33:26,180 --> 00:33:26,340
All right,

482
00:33:26,380 --> 00:33:31,040
so there's a really good question on the chat from Tristan Partin about,

483
00:33:32,020 --> 00:33:38,420
whether, what your perspective is on whether Postgres can learn things from other database

484
00:33:38,700 --> 00:33:39,860
projects you've been involved in.

485
00:33:40,700 --> 00:33:41,840
[SHIREESH] That's a really good question.

486
00:33:44,880 --> 00:33:49,520
So I think one of the most amazing things about Postgres

487
00:33:49,550 --> 00:33:50,780
is that it is extensible.

488
00:33:51,240 --> 00:33:55,240
It's super extensible and there's lots of contributions across the board.

489
00:33:55,300 --> 00:33:57,560
So naturally, that's just going to play to its strengths.

490
00:33:58,180 --> 00:34:03,240
I would also say that that sometimes becomes one of the challenges for Postgres.

491
00:34:04,720 --> 00:34:09,360
Just in terms of the pace at which you want to make big architectural choices and to get it done.

492
00:34:10,800 --> 00:34:14,659
And, you know, this is not a critique or any such thing against the way that the community works.

493
00:34:14,679 --> 00:34:15,360
I love it.

494
00:34:15,940 --> 00:34:16,560
Absolutely love it.

495
00:34:16,700 --> 00:34:17,440
Just zero doubts.

496
00:34:17,600 --> 00:34:19,700
There's no ifs and buts there.

497
00:34:20,659 --> 00:34:25,980
It is truly the strength, but if you want to really look into how to make some big architectural

498
00:34:26,280 --> 00:34:31,899
changes, that end-to-end thinking and how do we bring all pieces together really quickly,

499
00:34:32,580 --> 00:34:38,399
make bigger changes faster, is an area that's going to, it's a natural sort of like a balance

500
00:34:38,780 --> 00:34:40,780
problem that we need to get better at.

501
00:34:41,820 --> 00:34:43,179
I think this is going to be an evolution.

502
00:34:44,340 --> 00:34:49,659
Not a concern, but it is one of those things where I think as Postgres evolves and it's

503
00:34:49,679 --> 00:34:54,879
continuing to become one of the most sought after relational databases in the history

504
00:34:54,960 --> 00:35:00,260
of our tech, that is one area where it needs to learn how to get good at that, trying to

505
00:35:00,260 --> 00:35:01,960
take on bigger challenges.

506
00:35:00,500 --> 00:35:00,520
[CLAIRE] So

507
00:35:02,760 --> 00:35:04,360
I want to make sure I understood what you said.

508
00:35:04,780 --> 00:35:05,300
Did you basically,

509
00:35:05,980 --> 00:35:07,020
I'll try to paraphrase you,

510
00:35:07,360 --> 00:35:09,759
did you basically just say that the extensibility

511
00:35:09,780 --> 00:35:16,600
of Postgres, which is a big plus, you know, in many ways, also creates complexity that

512
00:35:16,800 --> 00:35:19,220
can make it hard to make big architectural changes?

513
00:35:20,140 --> 00:35:21,000
Is that what you said?

514
00:35:20,420 --> 00:35:20,580
[SHIREESH] Correct.

515
00:35:21,430 --> 00:35:27,640
Yeah, a few weeks ago, Marco Slot, from Snowflake now, wrote this blog about the complexity of

516
00:35:27,820 --> 00:35:28,240
extensibilities.

517
00:35:28,420 --> 00:35:34,820
And I was looking at it, and it really spoke to the challenges that I was thinking that Postgres has to deal with it.

518
00:35:34,940 --> 00:35:41,860
It's the same thing that is such a great thing about Postgres can also become a challenge.

519
00:35:42,940 --> 00:35:49,340
And that is the part that I think we need to navigate as a community in terms of how do we make sure that, you know,

520
00:35:49,340 --> 00:35:56,440
we continue to keep the good things but not let it create a huge amount of complexity.

521
00:35:58,540 --> 00:36:04,960
I would also add, in addition to that, just the challenge of building bigger changes.

522
00:36:05,740 --> 00:36:10,700
Obviously, the community has been debating about things such as moving to threads for connections.

523
00:36:11,520 --> 00:36:21,720
Those are the kind of changes that Postgres community has to figure out how do we really rally and make changes like that faster.

524
00:36:22,480 --> 00:36:27,620
Obviously, the AI era is going to create a significant amount of demand for Postgres.

525
00:36:28,120 --> 00:36:29,080
which is awesome.

526
00:36:30,140 --> 00:36:32,280
It is certainly really designed for the AI era.

527
00:36:33,210 --> 00:36:35,260
But these changes are going to be,

528
00:36:35,650 --> 00:36:37,060
these challenges need to be confronted.

529
00:36:38,920 --> 00:36:42,320
[CLAIRE] The Marco Slot post that you're talking about, [Yes.] was that based on the paper that just got

530
00:36:46,420 --> 00:36:52,720
published? I think Abigale Kim from UW–Madison was the lead author and Andy Pavlo was a co-author

531
00:36:52,940 --> 00:36:54,580
as well, and David Anderson, and Marco. And it was called something like Anarchy in the Database:

532
00:36:59,300 --> 00:37:04,240
A Survey and Evaluation of Database Management System Extensibility. Is it that?

533
00:37:05,280 --> 00:37:06,420
[SHIREESH] I think this is at the datacon.

534
00:37:07,240 --> 00:37:08,960
Is it at the datacon? [Oh.]

535
00:37:08,870 --> 00:37:09,660
The new...

536
00:37:09,660 --> 00:37:15,240
yeah, there was a conversation, that was a Bay Area datacon, I think.

537
00:37:15,420 --> 00:37:17,220
I'll find out the link and send it.

538
00:37:17,360 --> 00:37:21,780
It was basically talking about the do's and the don'ts of extensibilities and the challenges

539
00:37:21,890 --> 00:37:22,600
that come with it.

540
00:37:23,860 --> 00:37:26,240
[CLAIRE] Okay, I'll dig that one up and add it to the show notes then. Cool. Thank you.

541
00:37:25,120 --> 00:37:27,000
[SHIREESH] Yeah. But the paper that you're referring to is a good one too. It's

542
00:37:31,200 --> 00:37:40,640
a good one about the Anarchy in the Databases.

543
00:37:33,660 --> 00:37:36,500
[CLAIRE] Well, and also about extensibility and the challenges with them,

544
00:37:36,530 --> 00:37:38,800
so I just thought that was the connection.

545
00:37:40,820 --> 00:37:50,100
[SHIREESH] Right. I'm pretty sure there's a lot of cross references there. 

546
00:37:42,220 --> 00:37:46,820
[CLAIRE] Okay. Got it, yeah because he'd already worked on the paper by the time he put together that datacon talk.

547
00:37:47,000 --> 00:37:55,900
[That must have been the case. Yes.] Okay, all right, so we talked a little bit about your your work leading all

548
00:37:55,950 --> 00:38:02,620
these databases and obviously Microsoft SQL Server is on-prem, many of them are managed cloud

549
00:38:02,880 --> 00:38:08,540
services, you know, like the Azure Cosmos DB, Azure Database for PostgreSQL, etc.

550
00:38:09,720 --> 00:38:15,300
But one of the things that I really want everybody who listens to the show to know is that, at

551
00:38:15,600 --> 00:38:21,860
Microsoft, we have a team of people whose primary job is to contribute to the Postgres

552
00:38:21,990 --> 00:38:22,780
open source project.

553
00:38:23,700 --> 00:38:26,120
And some people don't realize that team exists.

554
00:38:26,750 --> 00:38:32,020
And so I always like to kind of shine a light on them because I think they're doing really

555
00:38:32,280 --> 00:38:32,840
important work.

556
00:38:33,220 --> 00:38:35,960
And I think it's important that Microsoft be,

557
00:38:36,540 --> 00:38:38,220
I mean, we have our managed service,

558
00:38:38,450 --> 00:38:40,960
but our managed service builds on top of Postgres open source.

559
00:38:41,580 --> 00:38:44,180
So it's kind of, to be a good citizen,

560
00:38:44,430 --> 00:38:45,820
I think we need to be contributing

561
00:38:46,120 --> 00:38:47,840
to the upstream open source project.

562
00:38:48,680 --> 00:38:50,360
And the good news is we are, which is cool.

563
00:38:50,880 --> 00:38:52,300
This is a very long question, I know.

564
00:38:53,820 --> 00:38:56,840
But I'm curious to hear from your perspective,

565
00:38:57,420 --> 00:38:59,620
like why do you fund this team?

566
00:38:59,740 --> 00:39:00,920
Why does this team exist?

567
00:39:01,300 --> 00:39:02,840
And why does this work matter?

568
00:39:04,200 --> 00:39:05,180
[SHIREESH] So, absolutely.

569
00:39:05,410 --> 00:39:07,420
You know, a lot of people are indeed surprised

570
00:39:07,590 --> 00:39:09,980
when they find out that Microsoft has a team of engineers

571
00:39:10,070 --> 00:39:12,980
to contribute directly to the Postgres open source project.

572
00:39:14,940 --> 00:39:17,220
I think increasingly people are learning

573
00:39:17,310 --> 00:39:19,040
and hopefully it's not a surprise anymore.

574
00:39:19,640 --> 00:39:26,060
It is not a side gig. These are folks who are core committers. They do the real deal. They're

575
00:39:26,280 --> 00:39:34,080
participating in community. They're writing code patches, extensions, and it's a full whole nine

576
00:39:34,240 --> 00:39:39,640
yards. Why do we do it? It's simple because Postgres matters. It's not just to us, but to the entire

577
00:39:39,800 --> 00:39:48,100
developer ecosystem. We have the vision of basically going to offer a world-class managed

578
00:39:48,120 --> 00:39:49,320
Postgres experience in Azure.

579
00:39:50,070 --> 00:39:51,760
And so we just can't be consumers.

580
00:39:52,030 --> 00:39:53,080
We have to be contributors

581
00:39:53,230 --> 00:39:54,880
when you have such a vision.

582
00:39:56,300 --> 00:39:58,280
And so we've created this dedicated team.

583
00:39:58,520 --> 00:40:02,360
They're not designed to basically assist us

584
00:40:02,410 --> 00:40:03,840
in just running our managed service.

585
00:40:04,930 --> 00:40:06,500
This is designed, the team is designed,

586
00:40:06,600 --> 00:40:08,020
to significantly improve,

587
00:40:09,900 --> 00:40:13,880
just push the whole core idea of Postgres forward

588
00:40:14,480 --> 00:40:17,360
independent of what it means to Microsoft alone.

589
00:40:17,760 --> 00:40:23,200
This is purely to help the project and to make sure that the whole community benefits from it.

590
00:40:23,760 --> 00:40:27,080
And every vendor gets benefited and we collaborate with every other vendor as well.

591
00:40:27,540 --> 00:40:37,120
Whoever wants to participate in the community, we are trying to make sure that we offer the best that we have to push this awesome project.

592
00:40:38,140 --> 00:40:41,260
And when you run a cloud service at scale like Azure Database for PostgreSQL,

593
00:40:42,040 --> 00:40:48,260
you do, of course, inevitably hit edge cases, performance tuning scenarios, and features

594
00:40:48,420 --> 00:40:49,200
that need to push the limit.

595
00:40:50,380 --> 00:40:58,160
Our goal is to not just duct tape around them, but we want to give it back, make changes and

596
00:40:58,160 --> 00:40:58,920
give it back upstream.

597
00:41:00,080 --> 00:41:06,620
I think that that's the only sustainable way to improve the core of Postgres, which then

598
00:41:06,860 --> 00:41:08,700
benefits us and everyone else.

599
00:41:09,860 --> 00:41:11,900
That's kind of the mind shift here.

600
00:41:13,760 --> 00:41:15,520
If you think about Microsoft in general,

601
00:41:16,440 --> 00:41:20,140
it's true that we did not operate in this way always.

602
00:41:21,120 --> 00:41:24,520
But today, thanks to our new operating structure,

603
00:41:24,850 --> 00:41:26,140
our cultural transformation, et cetera,

604
00:41:26,250 --> 00:41:28,320
we are one of the biggest contributors to open source,

605
00:41:28,540 --> 00:41:31,000
just broadly speaking, not just Postgres.

606
00:41:31,980 --> 00:41:35,140
But this Postgres team, it's a reflection of that transformation

607
00:41:35,390 --> 00:41:37,900
and is perhaps a really good project,

608
00:41:38,220 --> 00:41:45,140
a really good example, and demonstrates the new Microsoft, I would say. And, you know, again,

609
00:41:45,540 --> 00:41:51,320
this is really what makes Microsoft great. We adapt and we are here to play our part in the

610
00:41:51,390 --> 00:41:57,260
open source community in the right way. And we love the Postgres community. So this team is designed

611
00:41:58,140 --> 00:42:04,380
specifically to really push that vision forward. And that's it. That's really it. It's simple.

612
00:42:08,020 --> 00:42:14,180
[CLAIRE] One of the statements that I sometimes make is that if we want, we at Microsoft want, Postgres

613
00:42:14,320 --> 00:42:21,220
to continue to be technically relevant and commercially relevant in the future, then it

614
00:42:21,420 --> 00:42:25,380
means we need to do our part to contribute to the open source project.

615
00:42:26,340 --> 00:42:31,260
And then, you know when, I talk to a lot of people about this because I find it interesting,

616
00:42:31,280 --> 00:42:34,480
and it also is tangentially related to my job, right?

617
00:42:35,960 --> 00:42:38,840
And some people will be like, well, but if Microsoft walked away,

618
00:42:39,080 --> 00:42:43,240
everybody else would still be contributing and it wouldn't, it would be okay, right?

619
00:42:43,740 --> 00:42:44,940
Like, I get that question.

620
00:42:45,060 --> 00:42:47,580
And maybe it's from people who like to play devil's advocate

621
00:42:47,900 --> 00:42:51,360
or just people who like to debate, you know, or be provocative.

622
00:42:53,300 --> 00:42:59,140
And I don't think anybody can just assume that a successful project today

623
00:42:59,480 --> 00:43:01,040
will be successful in five years.

624
00:43:01,160 --> 00:43:03,720
I think you have to keep putting in the work.

625
00:43:04,760 --> 00:43:09,080
And there is a lot of work involved in every single new release of Postgres,

626
00:43:09,320 --> 00:43:13,240
and all those quarterly patch releases, and a ton of work behind the scenes as well,

627
00:43:13,660 --> 00:43:16,420
beyond the code itself, right, to make the project run.

628
00:43:18,840 --> 00:43:21,040
So I'm really glad we're doing this, I guess.

629
00:43:23,020 --> 00:43:25,840
[SHIREESH] I completely agree. You really said it well. Absolutely.

630
00:43:27,520 --> 00:43:30,300
[CLAIRE] Okay, so let's pivot for a second.

631
00:43:30,400 --> 00:43:34,100
I imagine that you meet with lots of customers.

632
00:43:35,640 --> 00:43:42,660
And for developers who work on Postgres, are there any insights, things that you hear from

633
00:43:43,020 --> 00:43:48,720
customers all the time in the context of Postgres, for example, or even databases more generally?

634
00:43:49,180 --> 00:43:53,020
Are there things that you think developers should keep in mind?

635
00:43:54,840 --> 00:43:56,920
[SHIREESH] So, it's a great question.

636
00:43:57,060 --> 00:44:05,900
And developers and customers just across the board, they all have, they have a lot of clarity in terms of what they want from databases.

637
00:44:06,340 --> 00:44:15,080
So I always tell my team and I strongly believe that databases are really the stars that basically enable applications to shine.

638
00:44:15,620 --> 00:44:22,160
We are very happy to sort of like stay out of the limelight, but enable the applications to shine, and the app developers to really win.

639
00:44:22,920 --> 00:44:27,100
Ultimate goal for databases is to make sure that the developers can forget about databases.

640
00:44:27,550 --> 00:44:29,240
They need not really even think about them.

641
00:44:29,460 --> 00:44:31,080
Of course, that's an extreme statement.

642
00:44:31,550 --> 00:44:38,060
But my point is that the database app developers should be able to get what they need in their frameworks, tool chains.

643
00:44:39,000 --> 00:44:41,420
And then databases are always up.

644
00:44:41,880 --> 00:44:42,900
They're always available.

645
00:44:43,370 --> 00:44:46,880
And they're giving the performance guarantees in the way that the app needs.

646
00:44:47,700 --> 00:44:50,940
Making sure that there's cost efficiency as well.

647
00:44:51,880 --> 00:44:57,660
There are all these different tensions that you need to get. Performance, availability, cost governance.

648
00:44:57,830 --> 00:45:03,680
You think of these three as like the tensions that go against each other in some sense, but that is the trick.

649
00:45:03,850 --> 00:45:10,360
And so when you really talk to the customers, it depends on the flavor of the application that they are dealing with.

650
00:45:10,800 --> 00:45:14,720
There are a lot of mission-critical applications who are not as cost-sensitive,

651
00:45:14,790 --> 00:45:20,180
but they are certainly, they want to make sure that they can run the Postgres database, or any database in this case.

652
00:45:20,920 --> 00:45:23,140
They don't want surprises during upgrades.

653
00:45:23,440 --> 00:45:25,400
They want to have fewer knobs.

654
00:45:25,550 --> 00:45:27,060
They want to have better observability.

655
00:45:28,240 --> 00:45:31,660
And critically, the uptime is pretty high,

656
00:45:32,260 --> 00:45:34,780
and they can trust that their workloads won't break

657
00:45:35,540 --> 00:45:37,480
when we are scaling or when we are really doing

658
00:45:37,570 --> 00:45:39,940
any maintenance work, et cetera, on Postgres.

659
00:45:40,080 --> 00:45:42,560
So these are a few things that they care a lot more

660
00:45:43,200 --> 00:45:44,400
than features, right?

661
00:45:44,620 --> 00:45:47,919
So you really have to remember that it is one of those

662
00:45:48,180 --> 00:45:52,880
ironic things when we may be chasing quite a lot of features, but customers are thinking about

663
00:45:53,440 --> 00:46:00,980
foundational pieces, resiliency, security, foremost than anything else. So those are really

664
00:46:00,990 --> 00:46:08,600
some of the things that I run into whenever I talk to customers. And Postgres, I hear when I

665
00:46:08,610 --> 00:46:13,879
talk to Postgres customers that they love Postgres, but they wish that they didn't have to be a

666
00:46:13,900 --> 00:46:20,920
Postgres expert to use it well. And that's the challenge, and the opportunity, right? So if you

667
00:46:20,920 --> 00:46:27,120
can make Postgres powerful by design, and simple by default, then you unlock a whole new generation

668
00:46:27,200 --> 00:46:34,620
of developers who can bear with it, not fearing it, and then take it to enterprise scale. We are

669
00:46:35,160 --> 00:46:40,979
certainly seeing the uprise of Postgres going from the mid-market to sort of enterprises and then

670
00:46:41,000 --> 00:46:46,980
slowly making it into tier zero kind of applications. And along this curve, we're going to have to

671
00:46:47,580 --> 00:46:53,540
deal with these kinds of tensions. And that is kind of really the trick here, the customers.

672
00:46:54,940 --> 00:47:00,860
And it's also interesting when you move from on-premises to cloud, because it takes away a lot

673
00:47:00,860 --> 00:47:07,019
of their pain. But you need to do it in a way that it doesn't look like a black box. They need

674
00:47:07,040 --> 00:47:11,780
to have observability, they need to make sure that there is predictability without having to break

675
00:47:11,820 --> 00:47:17,500
their bank. So that empathy for the operator, the developer, the workload architect, that is what

676
00:47:17,540 --> 00:47:21,800
they are seeking. And it comes up loud and clear whenever I talk to these customers.

677
00:47:23,660 --> 00:47:28,540
Yeah, so I think I probably covered quite a lot of ground here, but these are a few things that

678
00:47:28,740 --> 00:47:31,300
come to my mind when I think about talking to customers.

679
00:47:32,140 --> 00:47:34,300
[CLAIRE] You did cover a lot of ground and I love your answer.

680
00:47:34,640 --> 00:47:37,660
And there's like five different directions I could pivot from.

681
00:47:39,030 --> 00:47:42,920
The one thing, and this is just kind of random, but I want to point out that you use the phrase

682
00:47:43,120 --> 00:47:45,180
"it depends." [Right.]

683
00:47:45,140 --> 00:47:50,700
because when you were talking about those mission critical customers, right,

684
00:47:52,120 --> 00:47:57,980
and the fact that some people care more about cost governance and other people care more about

685
00:47:58,300 --> 00:48:05,640
availability for example, and anyway, I just think it's, amusing is the wrong word to

686
00:48:05,920 --> 00:48:11,120
describe the fact that the phrase "it depends" shows up so much in conversations about databases,

687
00:48:12,000 --> 00:48:17,220
and trade-offs... [It's a very good point.]

688
00:48:13,760 --> 00:48:21,820
[SHIREESH] It's a very good point because that's, any complex system, anything

689
00:48:22,020 --> 00:48:29,779
that basically deals with various aspects of state, it has to behave this way and it

690
00:48:29,800 --> 00:48:35,180
It has to be, it depends, because unfortunately, there's no one architecture, one answer, one

691
00:48:35,230 --> 00:48:39,280
set of choices that is universally applicable for all applications.

692
00:48:39,630 --> 00:48:42,860
And hence, it depends.

693
00:48:43,560 --> 00:48:49,620
[CLAIRE] And maybe that's part of why, you know, at Microsoft, you're responsible for several

694
00:48:49,930 --> 00:48:51,280
different databases, right?

695
00:48:51,540 --> 00:48:56,280
Because, in fact, as much as we, those of us who work with Postgres, there's this

696
00:48:56,330 --> 00:49:01,320
phrase called "just use Postgres" that suggests that you can use Postgres for pretty much any

697
00:49:01,660 --> 00:49:01,960
situation.

698
00:49:02,430 --> 00:49:08,880
But in fact, right, there is room for in the world for multiple different databases. [100%.]

699
00:49:08,580 --> 00:49:10,040
And we're not the only ones.

700
00:49:08,900 --> 00:49:11,820
[SHIREESH] 100%.

701
00:49:12,090 --> 00:49:14,340
But the one great thing about Postgres, though,

702
00:49:14,760 --> 00:49:18,100
which I definitely acknowledge and love to give the credit where it's due,

703
00:49:18,600 --> 00:49:21,960
is, again, going back to the extensibility aspect of it

704
00:49:22,060 --> 00:49:29,700
and really the flavor of the communities coming together,

705
00:49:27,340 --> 00:49:32,380
adding so many pieces without having to really make it as a matrix of things.

706
00:49:32,640 --> 00:49:34,960
Most of the database architectures are generally matrix

707
00:49:34,980 --> 00:49:39,760
where you touch something, it kind of connects into something else.

708
00:49:40,740 --> 00:49:44,120
And that sort of is a challenge because you really can't scale that way.

709
00:49:45,100 --> 00:49:50,100
But Postgres has mechanisms where you could create your own sort of chain of extensibilities

710
00:49:50,270 --> 00:49:52,220
without having to connect to every other piece,

711
00:49:52,930 --> 00:49:53,760
and that's quite powerful.

712
00:49:55,440 --> 00:50:01,860
[CLAIRE] So, there is a, well I was going to say a question, but it's really more of a comment,

713
00:50:02,090 --> 00:50:05,640
on the chat about the new VS Code extension for Postgres.

714
00:50:06,140 --> 00:50:09,120
So first of all, I'm thrilled that somebody brought it up.

715
00:50:09,240 --> 00:50:10,400
And this is not a plant.

716
00:50:11,920 --> 00:50:13,760
Tristan Partin is the one who brought it up,

717
00:50:14,260 --> 00:50:19,400
and he specifically said that he would love to see the new Postgres VS Code extension be

718
00:50:19,580 --> 00:50:20,200
open sourced.

719
00:50:21,160 --> 00:50:21,660
And so I'm curious if you have any thoughts on that.

720
00:50:23,880 --> 00:50:31,040
[SHIREESH] Yeah, so firstly, I really love the fact that the VS Code extension is one of those things that kind of took off really well.

721
00:50:32,440 --> 00:50:36,000
We put in a lot of effort here, so kudos to the team who worked on this.

722
00:50:36,460 --> 00:50:40,680
It came out really well, and I'm really thrilled that it helps not just Microsoft developers,

723
00:50:40,870 --> 00:50:47,080
but all the developers, anyone who wants to use Postgres, because VS Code is kind of really the dominant IDE.

724
00:50:47,370 --> 00:50:53,600
So this extension should really be very helpful for all the app developers, anyone who is a Postgres developer.

725
00:50:54,260 --> 00:50:55,480
So thrilled to hear that.

726
00:50:56,220 --> 00:50:59,240
And then on the interest about really open sourcing this,

727
00:50:59,460 --> 00:51:01,200
I know the team is evaluating it.

728
00:51:01,280 --> 00:51:02,080
They're looking into it.

729
00:51:02,200 --> 00:51:04,980
Our intent is to make sure that the community really contributes here,

730
00:51:05,160 --> 00:51:05,720
loves it, et cetera.

731
00:51:06,020 --> 00:51:08,760
So we certainly are thinking in that direction.

732
00:51:10,380 --> 00:51:13,700
Affan and Charles, who run the engineering and the product,

733
00:51:13,820 --> 00:51:14,800
they are thinking through it.

734
00:51:14,880 --> 00:51:20,080
So you'll hear a lot more about it in the coming few weeks and months about this.

735
00:51:20,200 --> 00:51:23,520
So I don't have a specific answer to give right now.

736
00:51:23,940 --> 00:51:26,220
But we are certainly thinking in that direction.

737
00:51:27,720 --> 00:51:33,080
[CLAIRE] The other comment on the chat that I really like is that VS Code needed a good, or a great,

738
00:51:33,400 --> 00:51:34,160
Postgres extension.

739
00:51:35,200 --> 00:51:36,980
And I couldn't agree more.

740
00:51:37,340 --> 00:51:39,580
It felt like a neglected space.

741
00:51:39,810 --> 00:51:42,100
And so I'm really excited about this thing too.

742
00:51:43,120 --> 00:51:47,360
[SHIREESH] I totally, totally agree and love the comments for sure.

743
00:51:47,510 --> 00:51:51,300
And really, yeah, it's heartwarming to see the adoption.

744
00:51:52,160 --> 00:51:57,400
[CLAIRE] Yeah, and for anyone who's listening, just to point out, this VS Code extension is not

745
00:51:57,860 --> 00:51:59,100
limited to Azure.

746
00:51:59,600 --> 00:52:00,720
It is about everything.

747
00:52:01,140 --> 00:52:08,740
It can be used with Postgres open source, it can be used on-prem, it's useful for all

748
00:52:09,140 --> 00:52:10,160
instances of Postgres.

749
00:52:10,490 --> 00:52:15,960
I think even any cloud, is that correct?

750
00:52:15,960 --> 00:52:16,160
[SHIREESH] Correct.

751
00:52:16,400 --> 00:52:17,420
Yeah, and absolutely.

752
00:52:18,380 --> 00:52:19,840
And we will keep it that way for sure.

753
00:52:20,200 --> 00:52:23,000
And we certainly really don't want it to be limited at all.

754
00:52:23,240 --> 00:52:26,720
We want all developers across the board

755
00:52:27,570 --> 00:52:28,500
to enjoy the benefits.

756
00:52:27,660 --> 00:52:29,100
[CLAIRE] And Docker locally, I'm told. [That too.]

757
00:52:30,110 --> 00:52:31,220
Okay,

758
00:52:32,340 --> 00:52:34,260
so I have a random question for you.

759
00:52:35,080 --> 00:52:40,320
Once upon a time, one of our Postgres committers, David Rowley, was on the show, and we learned

760
00:52:40,340 --> 00:52:44,860
about how he got started as a developer and in Postgres and it had to do with a forklift

761
00:52:44,960 --> 00:52:45,740
and a cheese factory.

762
00:52:46,370 --> 00:52:46,800
And then people started coming to the show and saying, you know, I worked for a cheese

763
00:52:50,820 --> 00:52:54,640
company, or I did an internship that relates to Postgres and cheese.

764
00:52:55,090 --> 00:52:57,560
And so we started getting all these random cheese stories.

765
00:52:58,160 --> 00:53:02,060
I'm curious, does cheese have anything to do with your database journey?

766
00:53:05,280 --> 00:53:09,540
[SHIREESH] No, I don't... I mean, I have to go back and think about it, but I don't think there's any database

767
00:53:09,740 --> 00:53:17,080
and cheese story. I love the metaphor for change from the Who Moved My Cheese book,

768
00:53:18,390 --> 00:53:22,420
and I guess I could connect it back to databases because that kind of changed my life.

769
00:53:23,640 --> 00:53:27,620
So there is a little bit of Who Moved My Cheese story in my journey of databases,

770
00:53:27,790 --> 00:53:32,100
but not really directly, I would say. I'm a cheddar guy.

771
00:53:32,120 --> 00:53:37,880
[CLAIRE] I just had to ask. People get on my case when I don't ask. It's like an expectation now at the end of each

772
00:53:38,110 --> 00:53:39,680
episode. All right, I want to thank you so much, Shireesh, for joining us today.

773
00:53:44,400 --> 00:53:49,900
I've really enjoyed learning more about your background, all the way from when you were six

774
00:53:50,020 --> 00:53:56,700
years old and you wanted to be a bus driver, to the work that you do today. And also just

775
00:53:57,280 --> 00:54:02,840
thank you for supporting the Postgres open source community work that my team gets to do.

776
00:54:03,380 --> 00:54:15,720
I feel privileged to be able to do things like this podcast, or create POSETTE, or support all the Postgres community conferences with sponsorships and, you know, sending people there as speakers.

777
00:54:16,060 --> 00:54:21,420
There's a lot of stuff we do that wouldn't happen if you weren't so committed to the open source project. So thank you.

778
00:54:22,240 --> 00:54:23,120
[SHIREESH] So, firstly, Claire, thank you so very much.

779
00:54:26,160 --> 00:54:29,240
And I want to thank each and everyone who's listening to this.

780
00:54:29,580 --> 00:54:31,120
I really appreciate your time,

781
00:54:31,580 --> 00:54:34,220
obviously love it, and thank you so very much.

782
00:54:35,520 --> 00:54:39,060
Just, again, I would repeat what I said about Postgres.

783
00:54:39,260 --> 00:54:42,280
It's one of those amazing, amazing databases, amazing community.

784
00:54:43,720 --> 00:54:47,400
We really love this community, and we are 100% committed to making sure

785
00:54:48,160 --> 00:54:53,660
that there is a great, agnostic, community for the sake,

786
00:54:54,400 --> 00:54:57,180
provisioning what we can, offering what we can,

787
00:54:57,880 --> 00:55:00,100
working closely with all the vendors,

788
00:55:00,720 --> 00:55:04,160
and that's the intent here to really take Postgres

789
00:55:04,240 --> 00:55:06,260
and make sure that it realizes its full potential.

790
00:55:07,320 --> 00:55:11,000
So I'm thrilled to be a part of this journey, in a small way.

791
00:55:12,560 --> 00:55:13,060
[CLAIRE] Well thank you.

792
00:55:13,660 --> 00:55:15,660
Thank you to Shireesh Thota for joining us.

793
00:55:16,020 --> 00:55:20,820
And if you liked today's episode and you want to hear more of these Talking Postgres episodes,

794
00:55:21,480 --> 00:55:25,860
you should subscribe on Apple, or Spotify, or YouTube, or wherever you get your

795
00:55:26,140 --> 00:55:27,880
podcasts. And please tell your friends.

796
00:55:28,480 --> 00:55:31,860
And if you leave a review, that helps even more people discover the show.

797
00:55:32,660 --> 00:55:36,440
You can always get to past episodes and get links to subscribe on the different

798
00:55:36,720 --> 00:55:41,720
platforms at TalkingPostgres.com, and transcripts are included on the episode

799
00:55:41,960 --> 00:55:44,060
pages on TalkingPostgres.com too.

800
00:55:44,680 --> 00:55:48,660
And a big thank you to everybody who joined the live recording and participated

801
00:55:49,240 --> 00:55:50,720
in the live text chat on Discord.

802
00:55:51,940 --> 00:56:44,780
Thank you.