First, it's just PostgreSQL, but operationalized in a way that @googlecloud does so well. It's 100% compatible PostgreSQL 14.
Performance is silly great. 4x faster than standard PostgreSQL for traditional workloads, and 2x faster than AWS Aurora. And you can use it for analytical queries, where it's 100x faster than standard PostgreSQL.
Other things I like? 99.99% SLA, automatic failover and recovery, automatic backups, and integration with Vertex AI to pull predictions into SQL queries. Oh, and pricing that easy. Pay only for the storage you use, and you don't get saddled with IO charges.
Let's take a look at provisioning a cluster. First, you're asked whether you want an HA cluster, or an HA cluster with read pools.
After picking a cluster type, I was asked to pick a region and private network.
Next I get the only infrastructure question I need to answer. I chose a machine type, which I can change later.
Then I added a read pool with a couple of nodes. Again, this is easy to resize after the fact.
It took a few minutes to provision everything. I was taken to a view that showed some metrics and such.
Once it was done, I could resize instances, view metrics, and more. And for an instance I created yesterday, I can see a couple of automatic backups we took.
AlloyDB is a feat of engineering, and a terrific database option in @googlecloud.
You might treat AI Studio as a sandbox before jumping into code. Makes sense.
There's a button to get the code related to the prompt you just created. And you can get back a few options including Python, JavaScript, Go, and even cURL.
We announced Duet AI in @googlecloud at Google IO and are working hard on a product that makes the cloud experience better for you. We’ve also been kinda quiet about our progress. Let’s change that.
I got permission (at least I think I did) to show off my favorite things. A 🧵:
As a reminder, Duet AI in @googlecloud makes it easier for you to use the cloud and build cloud-ready applications.
We’ve shared intro videos, but it’s time to show you the real products in Preview that will GA later this year.
@googlecloud 1️⃣ I really like the IDE-based code assistance. I can use this on my local IDE such as VSCode, IntelliJ, or, within @googlelcoud Workstations.
The first thing I like is code gen. I can generate entire Java classes, or @googlecloud friendly code.
It's been fun to watch @googlecloud Anthos find it's fit both for customers primarily in Google Cloud, and also those earlier in their journey.
So what's new with this Kubernetes + management plane product that makes it a good choice for anyone running containers? Quick 🧵 ...
First, I like seeing a new dashboard experience! This the view is at the "fleet" level. Regardless of where your clusters are—Google Cloud, other clouds, on-prem, edge—you get an all-up view of health and policy compliance. Awesome.
We've also added an Anthos UX (and an easier Terraform experience) for your on-premises clusters. Provision on-prem clusters from the cloud!
Ok, the #googlecloudnext announcements are coming out, and let's explore one in particular.
Cloud Workstations are in public preview! This isn't your parent's virtual desktop. It's a fast, flexible dev environment with security in mind. Let's explore together in a 🧵 ...
Browser-based IDEs are a thing now. It's how Googlers do a lot of their engineering work. It's ready for primetime.
To start with @googlecloud Cloud Workstations, you create a cluster. It manages lifecycle and networking things. I can put these around the world, close to devs.
Once I have a cluster, I create a Workstation configuration. You can imagine your Platform team or Ops team setting up some default configurations.
You're not going to watch every talk at #GoogleCloudNext. I know it. You know it. Not a big deal, I won't either.
But there are a handful you might want to bookmark to learn what's new, or what the other clouds will be talking about in a year or two. A 🧵 of your best bets ...
One of the fastest ways to deploy an app? Push to @googlecloud Run by running this command against your source code: "gcloud run deploy ."
But do that for prod deployments? Unlikely. We just added Cloud Run support to Cloud Deploy, and I wanted to try it out. A 🧵 …
For reference, Cloud Deploy is our continuous deployment service that supports staged rollouts to GKE, and now Cloud Run (in preview). It relies on declarative configurations to define deployment pipelines and targets.