Multi-language libraries and samples for GenAI in Vertex AI

You might think that you need to know Python to be able to use GenAI with VertexAI. While Python is the dominant language in GenAI (and Vertex AI is no exception in that regard), you can actually use GenAI in Vertex AI from other languages such as Java, C#, Node.js, Go, and more. Let’s take a look at the details. Vertex AI SDK for Python The official SDK for Vertex AI is Vertex AI SDK for Python and as expected, it’s in Python. Read More →

Introducing a new Eventarc destination - internal HTTP endpoint in a VPC network

Introduction Eventarc helps users build event-driven architectures without having to implement, customize, or maintain the underlying infrastructure. Eventarc has added support (in public preview) for delivering events to internal HTTP endpoints in a Virtual Private Cloud (VPC) network. Customers, especially large enterprises, often run compute (typically GKE or GCE) on VPC-private IPs, often behind internal load balancers. This launch will enable these services to consume Eventarc events. Internal HTTP endpoints can be an internal IP address or fully qualified DNS name (FQDN) for any HTTP endpoint in the VPC network. Read More →

Buffer workflow executions with a Cloud Tasks queue

Introduction In my previous post, I talked about how you can use a parent workflow to execute child workflows in parallel for faster overall processing time and easier detection of errors. Another useful pattern is to use a Cloud Tasks queue to create Workflows executions and that’s the topic of this post. When your application experiences a sudden surge of traffic, it’s natural to want to handle the increased load by creating a high number of concurrent workflow executions. Read More →

Workflows executing other parallel workflows: A practical guide

Introduction There are numerous scenarios where you might want to execute tasks in parallel. One common use case involves dividing data into batches, processing each batch in parallel, and combining the results in the end. This approach not only enhances the speed of the overall processing but it also allows for easier error detection in smaller tasks. On the other hand, setting up parallel tasks, monitoring them, handling errors in each task, and combining the results in the end is not trivial. Read More →

Generative AI Learning Path Notes – Part 2

If you’re looking to upskill in Generative AI, there’s a Generative AI Learning Path in Google Cloud Skills Boost. It currently consists of 10 courses and provides a good foundation on the theory behind Generative AI. As I went through these courses myself, I took notes, as I learn best when I write things down. In part 1 of the blog series, I shared my notes for courses 1 to 6. Read More →

Generative AI Learning Path Notes – Part 1

If you’re looking to upskill in Generative AI (GenAI), there’s a Generative AI Learning Path in Google Cloud Skills Boost. It currently consists of 10 courses and provides a good foundation on the theory behind Generative AI and what tools and services Google provides in GenAI. The best part is that it’s completely free! As I went through these courses myself, I took notes, as I learn best when I write things down. Read More →

New Batch connector for Workflows

Workflows just released a new connector for Batch that greatly simplifies how to create and run Batch jobs from Workflows. Let’s take a look how you can use the new Batch connector of Workflows. Recap: Batch and Workflows Batch is a fully managed service to schedule, queue, and execute batch jobs on Google’s infrastructure. These batch jobs run on Compute Engine VM instances but they are managed by Batch service, so you don’t have to provision and manage VM instances yourself. Read More →

Buffer HTTP requests with Cloud Tasks

Cloud Tasks is a fully-managed service that manages the execution, dispatch, and asynchronous delivery of a large number of tasks to App Engine or any arbitrary HTTP endpoint. You can also use a Cloud Tasks queue to buffer requests between services for more robust intra-service communication. Cloud Tasks introduces two new features, the new queue-level routing configuration and BufferTask API. Together, they enable creating HTTP tasks and adding to a queue without needing the tasks client library. Read More →

Workflows gets an updated JSON Schema

If you use Workflows, you’ve been crafting your Workflows definitions in YAML (or JSON). You’re probably painfully aware of the limited support you get in your IDE with syntax validation or auto-completion with these YAML definitions. This was due to Workflow’s schema being out of date, as I covered in my previous post last year. I’m happy to report that our team recently updated the Workflows schema with the latest syntax. Read More →

Extending Cloud Code with custom templates

Cloud Code is a set of IDE plugins for popular IDEs that make it easier to create, deploy and integrate applications with Google Cloud. Cloud Code provides an excellent extension mechanism through custom templates. In this post, I show you how you can create and use your own custom templates to add some features beyond those supported natively in Cloud Code, such as .NET functions, event triggered functions and more. As a recap, in my Introducing Cloud Functions support in Cloud Code post, I pointed out some limitations of the current Cloud Functions support in Cloud Code: Read More →