Transcript
Announcer: Hello, and welcome to Screaming in the Cloud with your host, Chief Cloud Economist at The Duckbill Group, Corey Quinn. This weekly show features conversations with people doing interesting work in the world of cloud, thoughtful commentary on the state of the technical world, and ridiculous titles for which Corey refuses to apologize. This is Screaming in the Cloud.

Corey: Welcome to Screaming in the Cloud. I’m Corey Quinn. I’m joined today by Steren Giannini, who is a senior product manager at Google Cloud, specifically on something called Google Cloud Run. Steren, thank you for joining me today.

Steren: Thanks for inviting me, Corey.

Corey: So, I want to start at the very beginning of, “Oh, a cloud service. What are we going to call it?” “Well, let’s put the word cloud in it.” “Okay, great. Now, it is cloud, so we have to give it a vague and unassuming name. What does it do?” “It runs things.” “Genius. Let’s break and go for work.” Now, it’s easy to imagine that you spent all of 30 seconds on a name, but it never works that way. How easy was it to get to Cloud Run as a name for the service?

Steren: [laugh]. Such a good question because originally it was not named Cloud Run at all. The original name was Google Serverless Engine. But a few people know that because they’ve been helping us since the beginning, but originally it was Google Serverless Engine. Nobody liked the name internally, and I think at one point, we wondered, “Hey, can we drop the engine structure and let’s just think about the name. And what does this thing do?” “It runs things.”

We already have Cloud Build. Well, wouldn’t it be great to have Cloud Run to pair with Cloud Build so that after you’ve built your containers, you can run them? And that’s how we ended up with this very simple Cloud Run, which today seems so obvious, but it took us a long time to get to that name, and we actually had a lot of renaming to do because we were about to ship with Google Serverless Engine.

Corey: That seems like a very interesting last-minute change because it’s not just a find and replace at that point, it’s—

Steren: No.

Corey: —“Well, okay, if we call it Cloud Run, which can also be a verb or a noun, depending, is that going to change the meaning of some sentences?” And just doing a find and replace without a proofread pass as well, well, that’s how you wind up with funny things on Twitter.

Steren: API endpoints needed to be changed, adding weeks of delays to the launch. That is why we—you know, [laugh] announced in 2018 and publicly launched in 2019.

Corey: I’ve been doing a fair bit of work in cloud for a while, and I wound up going down a very interesting path. So, the first native Google Cloud service—not things like WP Engine that ride on top of GCP—but my first native Google Cloud Service was done in service of this podcast, and it is built on Google Cloud Run. I don’t think I’ve told you part of this story yet, but it’s one of the reasons I reached out to invite you onto the show. Let me set the stage here with a little bit of backstory that might explain what the hell I’m talking about.

As listeners of this show are probably aware, we have sponsors whom we love and adore. In the early days of this show, they would say, “Great, we want to tell people about our product”—which is the point of a sponsorship—“And then send them to a URL.” “Great. What’s the URL?” And they would give me something that was three layers deep, then with a bunch of UTM tracking parameters at the end.

And it’s, “You do realize that no one is going to be sitting there typing all of that into a web browser?” At best, you’re going to get three words or so. So, I built myself a URL redirector, snark.cloud. I can wind up redirecting things in there anywhere it needs to go.

And for a long time, I did this on top of S3 and then put CloudFront in front of it. And this was all well and good until, you know, things happened in the fullness of time. And now holy crap, I have an operations team involved in things, and maybe I shouldn’t be the only person that knows how to work on all of these bits and bobs. So, it was time to come up with something that had a business user-friendly interface that had some level of security, so I don’t wind up automatically building out a spam redirect service for anything that wants to, and it needs to be something that’s easy to work with. So, I went on an exploration.

So, at first it showed that there were—like, I have an article out that I’ve spoken about before that there are, “17 Ways to Run Containers on AWS,” and then I wrote the sequel, “17 More Ways to Run Containers on AWS.” And I’m keeping a list, I’m almost to the third installation of that series, which is awful. So, great. There’s got to be some ways to build some URL redirect stuff with an interface that has an admin panel. And I spent three days on this trying a bunch of different things, and some were running on deprecated versions of Node that wouldn’t build properly and others were just such complex nonsense things that had got really bad. I was starting to consider something like just paying for Bitly or whatnot and making it someone else’s problem.

And then I stumbled upon something on GitHub that really was probably one of the formative things that changed my opinion of Google Cloud for the better. And within half an hour of discovering this thing, it was up and running. I did the entire thing, start to finish, from my iPad in a web browser, and it just worked. It was written by—let me make sure I get his name correct; you know, messing up someone’s name is a great way to say that we don’t care about them—Ahmet Balkan used to work at Google Cloud; now he’s over at Twitter. And he has something up on GitHub that is just absolutely phenomenal about this, called sheets-url-shortener.

And this is going to sound wild, but stick with me. The interface is simply a Google Sheet, where you have one column that has the shorthand slug—for example, run; if you go to snark.cloud/run, it will redirect to Google Cloud Run’s website. And the second column is where you want it to go. The end.

And whenever that gets updated, there’s of course some caching issues, which means it can take up to five seconds from finishing that before it will actually work across the entire internet. And as best I can tell, that is fundamentally magic. But what made it particularly useful and magic, from my perspective, was how easy it was to get up and running. There was none of this oh, but then you have to integrate it with Google Sheets and that’s a whole ‘nother team so there’s no way you’re going to be able to figure that out from our Docs. Go talk to them and then come back in the day.

They were the get started, click here to proceed. It just worked. And it really brought back some of the magic of cloud for me in a way that I hadn’t seen in quite a while. So, all which is to say, amazing service, I continue to use it for all of these sponsored links, and I am still waiting for you folks to bill me, but it fits comfortably in the free tier because it turns out that I don’t have hundreds of thousands of people typing it in every week.

Steren: I’m glad it went well. And you know, we measure tasks success for Cloud Run. And we do know that most new users are able to deploy their apps very quickly. And that was the case for you. Just so you know, we’ve put a lot of effort to make sure it was true, and I’ll be glad to tell you more about all that.

But for that particular service, yes, I suppose Ahmet—who I really enjoyed working with on Cloud Run, he was really helpful designing Cloud Run with us—has open-sourced this side project. And basically, you might even have clicked on a deploy to Cloud Run button on GitHub, right, to deploy it?

Corey: That is exactly what I did and it somehow just worked and—

Steren: Exactly.

Corey: And it knew, even logging into the Google Cloud Console because it understands who I am because I use Google Docs and things, I’m already logged in. None of this, “Oh, which one of these 85 credential sets is it going to be?” Like certain other clouds. It was, “Oh, wow. Wait, cloud can be easy and fun? When did that happen?”

Steren: So, what has happened when you click that deploy to Google Cloud button, basically, the GitHub repository was built into a container with Cloud Build and then was deployed to Cloud Run. And once on Cloud Run, well, hopefully, you have forgotten about it because that’s what we do, right? We—give us your code, in a container if you know containers if you don’t just—we support, you know, many popular languages, and we know how to build them, so don’t worry about that. And then we run it. And as you said, when there is low traffic or no traffic, it scales to zero.

When there is low traffic, you’re likely going to stay under the generous free tier. And if you have more traffic for, you know, Screaming in the Cloud suddenly becoming a high destination URL redirects, well, Cloud Run will scale the number of instances of this container to be able to handle the load. Cloud Run scales automatically and very well, but only—as always—charging you when you are processing some requests.

Corey: I had to fork and make a couple of changes myself after I wound up doing some testing. The first was to make the entire thing case insensitive, which is—you know, makes obvious sense. And the other was to change the permanent redirect to a temporary redirect because believe it or not, in the fullness of time, sometimes sponsors want to change the landing page in different ways for different campaigns and that’s fine by me. I just wanted to make sure people’s browser cache didn’t remember it into perpetuity. But it was easy enough to run—that was back in the early days of my exploring Go, which I’ve been doing this quarter—and in the couple of months this thing has been running it has been effectively flawless.

It’s set it; it’s forget it. The only challenges I had with it are it was a little opaque getting a custom domain set up that—which is still in beta, to be clear—and I’ve heard some horror stories of people saying it got wedged. In my case, no, I deployed it and I started refreshing it and suddenly, it start throwing an SSL error. And it’s like, “Oh, that’s not good, but I’m going to break my own lifestyle here and be patient for ten minutes.” And sure enough, it cleared itself and everything started working. And that was the last time I had to think about any of this. And it just worked.

Steren: So first, Cloud Run is HTTPS only. Why? Because it’s 2020, right? It’s 2022, but—

Corey: [laugh].

Steren: —it’s launched in 2020. And so basically, we have made a decision that let’s just not accept HTTP traffic; it’s only HTTPS. As a consequence, we need to provision a cert for your custom domain. That is something that can take some time. And as you said, we keep it in beta or in preview because we are not yet satisfied with the experience or even the performance of Cloud Run custom domains, so we are actively working on fixing that with a different approach. So, expect some changes, hopefully, this year.

Corey: I will say it does take a few seconds when people go to a snark.cloud URL for it to finish resolving, and it feels on some level like it’s almost like a cold start problem. But subsequent visits, the same thing also feel a little on the slow and pokey side. And I don’t know if that’s just me being wildly impatient, if there’s an optimization opportunity, or if that’s just inherent to the platform that is not under current significant load.

Steren: So, it depends. If the Cloud Run service has scaled down to zero, well of course, your service will need to be started. But what we do know, if it’s a small Go binary, like something that you mentioned, it should really take less than, let’s say, 500 milliseconds to go from zero to one of your container instance. Latency can also be due to the way the code is running. If it occurred is fetching things from Google Sheets at every startup, that is something that could add to the startup latency.

So, I would need to take a look, but in general, we are not spinning up a virtual machine anytime we need to scale horizontally. Like, our infrastructure is a multi-tenant, rapidly scalable infrastructure that can materialize a container in literally 300 milliseconds. The rest of the latency comes from what does the container do at startup time?

Corey: Yeah, I just ran a quick test of putting time in front of a curl command. It looks like it took 4.83 seconds. So, enough to be perceptive. But again, for just a quick redirect, it’s generally not the end of the world and there’s probably something I’m doing that is interesting and odd. Again, I did not invite you on the show to file a—

Steren: [laugh].

Corey: Bug report. Let’s be very clear here.

Steren: Seems on the very high end of startup latencies. I mean, I would definitely expect under the second. We should deep-dive into the code to take a look. And by the way, building stuff on top of spreadsheets. I’ve done that a ton in my previous lives as a CTO of a startup because well, that’s the best administration interface, right? You just have a CRUD UI—

Corey: [unintelligible 00:12:29] world and all business users understand it. If people in Microsoft decided they were going to change Microsoft Excel interface, even a bit, they would revert the change before noon of the same day after an army of business users grabbed pitchforks and torches and marched on their headquarters. It’s one of those things that is how the world runs; it is the world’s most common IDE. And it’s great, but I still think of databases through the lens of thinking about it as a spreadsheet as my default approach to things. I also think of databases as DNS, but that’s neither here nor there.

Steren: You know, if you have maybe 100 redirects, that’s totally fine. And by the way, the beauty of Cloud Run in a spreadsheet, as you mentioned is that Cloud Run services run with a certain identity. And this identity, you can grant it permissions. And in that case, what I would recommend if you haven’t done so yet, is to give an identity to your Cloud Run service that has the permission to read that particular spreadsheet. And how you do that you invite the email of the service account as a reader of your spreadsheet, and that’s probably what you did.

Corey: The click button to the workflow on Google Cloud automatically did that—

Steren: Oh, wow.

Corey: —and taught me how to do it. “Here’s the thing that look at. The end.” It was a flawless user-onboarding experience.

Steren: Very nicely done. But indeed, you know, there is this built-in security which is the principle of minimal permission, like each of your Cloud Run service should basically only be able to read and write to the backing resources that they should. And by default, we give you a service account which has a lot of permissions, but our recommendation is to narrow those permissions to basically only look at the cloud storage buckets that the service is supposed to look at. And the same for a spreadsheet.

Corey: Yes, on some level, I feel like I’m going to write an analysis of my own security approach. It would be titled, “My God, It's Full Of Stars” as I look at the IAM policies of everything that I’ve configured. The idea of least privilege is great. What I like about this approach is that it made it easy to do it so I don’t have to worry about it. At one point, I want to go back and wind up instrumenting it a bit further, just so I can wind up getting aggregate numbers of all right, how many times if someone visited this particular link? It’ll be good to know.

And I don’t know… if I have to change permissions to do that yet, but that’s okay. It’s the best kind of problem: future Corey. So, we’ll deal with that when the time comes. But across the board, this has just been a phenomenal experience and it’s clear that when you were building Google Cloud Run, you understood the assignment. Because I was looking for people saying negative things about it and by and large, all of its seem to come from a perspective of, “Well, this isn’t going to be the most cost-effective or best way to run something that is hyperscale, globe-spanning.”

It’s yes, that’s the thing that Kubernetes was originally built to run and for some godforsaken reason people run their blog on it instead now. Okay. For something that is small, scales to zero, and has long periods where no one is visiting it, great, this is a terrific answer and there’s absolutely nothing wrong with that. It’s clear that you understood who you were aiming at, and the migration strategy to something that is a bit more, I want to say robust, but let’s be clear what I mean when I’m saying that if you want something that’s a little bit more impressive on your SRE resume as you’re trying a multi-year project to get hired by Google or pretend you got hired by Google, yeah, you can migrate to something else in a relatively straightforward way. But that this is up, running, and works without having to think about it, and that is no small thing.

Steren: So, there are two things to say here. The first is yes, indeed, we know we have high developer satisfaction. You know, we measure this—in Google Cloud, you might have seen those small satisfaction surveys popping up sometimes on the user interface, and you know, we are above 90% satisfaction score. We hire third parties to help us understand how usable and what satisfaction score would users get out of Cloud Run, and we are constantly getting very, very good results, in absolute but also compared to the competition.

Now, the other thing that you said is that, you know, Cloud Run is for small things, and here while it is definitely something that allows you to be productive, something that strives for simplicity, but it also scales a lot. And contrary to other systems, you do not have any pre-provisioning to make. So, we have done demos where we go from zero to 10,000 container instances in ten seconds because of the infrastructure on which Cloud Run runs, which is fully managed and multi-tenant, we can offer you this scale on demand. And many of our biggest customers have actually not switched to something like Kubernetes after starting with Cloud Run because they value the low maintenance, the no infrastructure management that Cloud Run brings them.

So, we have like Ikea, ecobee… for example ecobee, you know, the smart thermostats are using Cloud Run to ingest events from the thermostat. I think Ikea is using Cloud Run more and more for more of their websites. You know, those companies scale, right? This is not, like, scale to zero hobby project. This is actually production e-commerce and connected smart objects production systems that have made the choice of being on a fully-managed platform in order to reduce their operational overhead.

[midroll 00:17:54]

Corey: Let me be clear. When I say scale—I think we might be talking past each other on a small point here. When I say scale, I’m talking less about oh tens or hundreds of thousands of containers running concurrently. I’m talking in a more complicated way of, okay, now we have a whole bunch of different microservices talking to one another and affinity as far as location to each other for data transfer reasons. And as you start beginning to service discovery style areas of things, where we build a really complicated applications because we hired engineers and failed to properly supervise them, and that type of convoluted complex architecture.

That’s where it feels like Cloud Run increasingly, as you move in that direction, starts to look a little bit less like the tool of choice. Which is fine, I want to be clear on that point. The sense that I’ve gotten of it is a great way to get started, it’s a great way to continue running a thing you don’t have to think about because you have a day job that isn’t infrastructure management. And it is clear to—as your needs change—to either remain with the service or pivot to a very close service without a whole lot of retooling, which is key. There’s not much of a lock-in story to this, which I love.

Steren: That was one of the key principles when we started to design Cloud Run was, you know, we realized the industry had agreed that the container image was the standard for the deployment artifact of software. And so, we just made the early choice of focusing on deploying containers. Of course, we are helping users build those containers, you know, we have things called build packs, we can continuously deploy from GitHub, but at the end of the day, the thing that gets auto-scaled on Cloud Run is a container. And that enables portability.

As you said. You can literally run the same container, nothing proprietary in it, I want to be clear. Like, you’re just listening on a port for some incoming requests. Those requests can be HTTP requests, events, you know, we have products that can push events to Cloud Run like Eventarc or Pub/Sub. And this same container, you can run it on your local machine, you can run it on Kubernetes, you can run it on another cloud. You’re not locked in, in terms of API of the compute.

We even went even above and beyond by having the Cloud Run API looks like a Kubernetes API. I think that was an extra effort that we made. I’m not sure people care that much, but if you look at the Cloud Run API, it is actually exactly looking like Kubernetes, Even if there is no Kubernetes at all under the hood; we just made it for portability. Because we wanted to address this concern of serverless which was lock-in. Like, when you use a Function as a Service product, you are worried that the architecture that you are going to develop around this product is going to be only working in this particular cloud provider, and you’re not in control of the language, the version that this provider has decided to offer you, you’re not in control of more of the complexity that can come as you want to scan this code, as you want to move this code between staging and production or test this code.

So, containers are really helping with that. So, I think we made the right choice of this new artifact that to build Cloud Run around the container artifact. And you know, at the time when we launched, it was a little bit controversial because back in the day, you know, 2018, 2019, serverless really meant Functions as a Service. So, when we launched, we little bit redefined serverless. And we basically said serverless containers. Which at the time were two worlds that in the same sentence were incompatible. Like, many people, including internally, had concerns around—

Corey: Oh, the serverless versus container war was a big thing for a while. Everyone was on a different side of that divide. It’s… containers are effectively increasingly—and I know, I’ll get email for this, and I don’t even slightly care, they’re a packaging format—

Steren: Exactly.

Corey: —where it solves the problem of how do I build this thing to deploy on Debian instances? And Ubuntu instances, and other instances, God forbid, Windows somewhere, you throw a container over the wall. The end. Its DevOps is about breaking down the walls between Dev and Ops. That’s why containers are here to make them silos that don’t have to talk to each other.

Steren: A container image is a glorified zip file. Literally. You have a set of layers with files in them, and basically, we decided to adopt that artifact standard, but not the perceived complexity that existed at the time around containers. And so, we basically merged containers with serverless to make something as easy to use as a Function as a Service product but with the power of bringing your own container. And today, we are seeing—you mentioned, what kind of architecture would you use Cloud Run for?

So, I would say now there are three big buckets. The obvious one is anything that is a website or an API, serving public internet traffic, like your URL redirect service, right? This is, you have an API, takes a request and returns a response. It can be a REST API, GraphQL API. We recently added support for WebSockets, which is pretty unique for a service offering to support natively WebSockets.

So, what I mean natively is, my client can open a socket connection—a bi-directional socket connection—with a given instance, for up to one hour. This is pretty unique for something that is as fully managed as Cloud Run.

Corey: Right. As we’re recording this, we are just coming off of Google I/O, and there were a number of announcements around Cloud Run that were touching it because of, you know, strange marketing issues. I only found out that Google I/O was a thing and featured cloud stuff via Twitter at the time it was happening. What did you folks release around Cloud Run?

Steren: Good question, actually. Part of the Google I/O Developer keynote, I pitched a story around how Cloud Run helps developers, and the I/O team liked the story, so we decided to include that story as part of the live developer keynote. So, on stage, we announced Cloud Run jobs. So now, I talked to you about Cloud Run services, which can be used to expose an API, but also to do, like, private microservice-to-microservice communication—because cloud services don’t have to be public—and in that case, we support GRPC and, you know, a very strong security mechanism where only Service A can invoke Service B, for example, but Cloud Run jobs are about non-request-driven containers. So, today—I mean, before Google I/O a few days ago, the only requirement that we imposed on your container image was that it started to listen for requests, or events, or GRPC—

Corey: Web requests—

Steren: Exactly—

Corey: It speaks [unintelligible 00:24:35] you want as long as it’s HTTP. Yes.

Steren: That was the only requirement we asked you to have on your container image. And now we’ve changed that. Now, if you have a container that basically starts and executes to completion, you can deploy it on a Cloud Run job. So, you will use Cloud Run jobs for, like, daily batch jobs. And you have the same infrastructure, so on-demand, you can go from zero to, I think for now, the maximum is a hundred tasks in parallel, for—of course, you can run many tasks in sequence, but in parallel, you can go from zero to a hundred, right away to run your daily batch job, daily admin job, data processing.

But this is more in the batch mode than in streaming mode. If you would like to use a more, like, streaming data processing, than a Cloud Run service would still be the best fit because you can literally push events to it, and it will auto-scale to handle any number of events that it receives.

Corey: Do you find that the majority of customers are using Cloud Run for one-off jobs that barely will get more than a single container, like my thing, or do you find that they’re doing massively parallel jobs? Where’s the lion’s share of developer and customer interest?

Steren: It’s both actually. We have both individual developers, small startups—which really value the scale to zero and pay per use model of Cloud Run. Your URL redirect service probably is staying below the free tier, and there are many, many, many users in your case. But at the same time, we have big, big, big customers who value the on-demand scalability of Cloud Run. And for these customers, of course, they will probably very likely not scale to zero, but they value the fact that—you know, we have a media company who uses Cloud Run for TV streaming, and when there is a soccer game somewhere in the world, they have a big spike of usage of requests coming in to their Cloud Run service, and here they can trust the rapid scaling of Cloud Run so they don’t have to pre-provision things in advance to be able to serve that sudden traffic spike.

But for those customers, Cloud Run is priced in a way so that if you know that you’re going to consume a lot of Cloud Run CPU and memory, you can purchase Committed Use Discounts, which will lower your bill overall because you know you are going to spend one dollar per hour on Cloud Run, well purchase a Committed Use Discount because you will only spend 83 cents instead of one dollar. And also, Cloud Run and comes with two pricing model, one which is the default, which is the request-based pricing model, which is basically you only have CPU allocated to your container instances if you are processing at least one request. But as a consequence of that, you are not paying outside of the processing of those requests. Those containers might stay up for you, one, ready to receive new requests, but you’re not paying for them. And so, that is—you know, your URL redirect service is probably in that mode where yes when you haven’t used it for a while, it will scale down to zero, but if you send one request to it, it will serve that request and then it will stay up for a while until it decides to scale down. But you the user only pays when you are processing these specific requests, a little bit like a Function as a Service product.

Corey: Scales to zero is one of the fundamental tenets of serverless that I think that companies calling something serverless, but it always charges you per hour anyway. Yeah, that doesn’t work. Storage, let’s be clear, is a separate matter entirely. I’m talking about compute. Even if your workflow doesn’t scale down to zero ever as a workload, that’s fine, but if the workload does, you don’t get to keep charging me for it.

Steren: Exactly. And so, in that other mode where you decide to always have CPU allocated to your Cloud Run container instances, then you pay for the entire lifecycle of this container instances. You still benefit from the auto-scaling of Cloud Run, but you will pay for the lifecycle and in that case, the price points are lower because you pay for a longer period of time. But that’s more the price model that those bigger customers will take because at their scale, they basically always receive requests, so they already to pay always, basically.

Corey: I really want to thank you for taking the time to chat with me. Before you go, one last question that we’ll be using as a teaser for the next episode that we record together. It seems like this is a full-time job being the product manager on Cloud Run, but no Google, contrary to popular opinion, does in fact, still support 20% projects. What’s yours?

Steren: So, I’ve been looking to work on Cloud Run since it was a prototype, and you know, for a long time, we’ve been iterating privately on Cloud Run, launching it, seeing it grow, seeing it adopted, it’s great. It’s my full-time job. But on Fridays, I still find the time to have a 20% project, which also had quite a bit of impact. And I work on some sustainability efforts for Google Cloud. And notably, we’ve released two things last year.

The first one is that we are sharing some carbon characteristics of Google Cloud regions. So, if you have seen those small leaves in the Cloud Console next to the regions that are emitting the less carbon, that’s something that I helped bring to life. And the second one, which is something quite big, is we are helping customers report and reduce their gross carbon emissions of their Google Cloud usage by providing an out of the box reporting tool called Google Cloud Carbon Footprint. So, that’s something that I was able to bootstrap with a team a little bit on the side of my Cloud Run project, but I was very glad to see it launched by our CEO at the last Cloud Next Conference. And now it is a fully-funded project, so we are very glad that we are able to help our customers better meet their sustainability goals themselves.

Corey: And we will be talking about it significantly on the next episode. We’re giving a teaser, not telling the whole story.

Steren: [laugh].

Corey: I really want to thank you for being as generous with your time as you are. If people want to learn more, where can they find you?

Steren: Well, if they want to learn more about Cloud Run, we talked about how simple was that name. It was obviously not simple to find this simple name, but the domain is https://cloud.run.

Corey: We will also accept snark.cloud/run, I will take credit for that service, too.

Steren: [laugh]. Exactly.

Corey: There we are.

Steren: And then, people can find me on Twitter at @steren, S-T-E-R-E-N. I’ll be happy—I’m always happy to help developers get started or answer questions about Cloud Run. And, yeah, thank you for having me. As I said, you successfully deployed something in just a few minutes to Cloud Run. I would encourage the audience to—

Corey: In spite of myself. I know, I’m as surprised as anyone.

Steren: [laugh].

Corey: The only snag I really hit was the fact that I was riding shotgun when we picked up my daughter from school and went through a dead zone. It’s like, why is this thing not loading in the Google Cloud Console? Yeah, fix the cell network in my area, please.

Steren: I’m impressed that you did all of that from an iPad. But yeah, to the audience give Cloud Run the try. You can really get started connecting your GitHub repository or deploy your favorite container image. And we’ve worked very hard to ensure that usability was here, and we know we have pretty strong usability scores. Because that was a lot of work to simplicity, and product excellence and developer experience is a lot of work to get right, and we are very proud of what we’ve achieved with Cloud Run and proud to see that the developer community has been very supportive and likes this product.

Corey: I’m a big fan of what you’ve built. And well, of course, it links to all of that in the show notes. I just want to thank you again for being so generous with your time. And thanks again for building something that I think in many ways showcases the best of what Google Cloud has to offer.

Steren: Thanks for the invite.

Corey: We’ll talk again soon. Steren Giannini is a senior product manager at Google Cloud, on Cloud Run. I’m Cloud Economist Corey Quinn and this is Screaming in the Cloud. If you’ve enjoyed this podcast, please leave a five-star review on your podcast platform of choice, whereas if you’ve hated this podcast, please leave a five-star review on your podcast platform of choice. If it’s on YouTube, put the thumbs up and the subscribe buttons as well, but in the event that you hated it also include an angry comment explaining why your 20% project is being a shithead on the internet.

Corey: If your AWS bill keeps rising and your blood pressure is doing the same, then you need The Duckbill Group. We help companies fix their AWS bill by making it smaller and less horrifying. The Duckbill Group works for you, not AWS. We tailor recommendations to your business and we get to the point. Visit duckbillgroup.com to get started.

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