Introduction One challenge with any distributed system, including Workflows, is ensuring that requests sent from one service to another are processed exactly once, when needed; for example, when placing a customer order in a shipping queue, withdrawing funds from a bank account, or processing a payment. In this blog post, we’ll provide an example of a website invoking Workflows, and Workflows in turn invoking a Cloud Function. We’ll show how to make sure both Workflows and the Cloud Function logic only runs once. We’ll also talk about how to invoke Workflows exactly once when using HTTP callba ..read more

In the realm of modern application design, developers have a range of choices available to them for crafting architectures that are not only simple, but also scalable, performant and resilient. Container platforms like Kubernetes (k8s) offer users the ability to seamlessly adjust node and pod specifications, so that services can scale. This scalability does not come at the expense of elasticity, and also ensures consistent performance for service consumers. So it’s no surprise that Kubernetes has become the de facto standard for building distributed and resilient systems in medium-to-large or ..read more

The intricate hierarchical data structures in data warehouses and lakes sourced from diverse origins can make data modeling a protracted and error-prone process. To quickly adapt and create data models that meet evolving business requirements without having to rework them excessively, you need data models that are flexible, modular and adaptable enough to accommodate many requirements. This requires advanced technologies, proficient personnel, and robust methodologies. The advancements in generative AI offer numerous opportunities to address these challenges. Multimodal large language models ..read more

Ensuring application and service teams have the resources they need is crucial for platform administrators. Fleet team management features in Google Kubernetes Engine (GKE) make this easier, allowing each team to function as a separate “tenant” within a fleet. In conjunction with Config Sync, a GitOps service in GKE, platform administrators can streamline resource management for their teams across the fleet. Specifically, with Config Sync team scopes, platform admins can define fleet-wide and team-specific cluster configurations such as resource quotas and network policies, allowing each appl ..read more

Sullivan County, New York, is home to the Catskills Mountains. It’s a great place to live, play, and raise a family, and we have a robust group of visitors and tourists. We are also a fairly small county. Being on the cutting edge of technology isn’t typically something people associate with local governments, and I’m proud of Sullivan County for consistently innovating. Traditionally, in offices like ours, our teams are routinely answering rote questions about operating hours or document filing processes. These calls take up hours of their day they’d like to spend helping solve more complex ..read more

Introduction Machine learning (ML) models thrive on massive datasets, and fast data loading is key for cost-effective ML training. We recently launched a PyTorch Dataset abstraction, the Dataflux Dataset, for accelerating data loading from Google’s Cloud Storage. Dataflux provides up to 3.5x faster training times compared to fsspec, with small files.  Today’s launch builds upon Google’s commitment to open standards that spans over two decades of OSS contributions like TensorFlow, JAX, TFX, MLIR, KubeFlow, and Kubernetes, as well as sponsorship for critical OSS data science initiatives lik ..read more

We’re excited to announce the release of a quickstart solution and reference architecture for retrieval augmented generation (RAG) applications, designed to accelerate your journey to production. In this post, you’ll learn how to quickly deploy a complete RAG application on Google Kubernetes Engine (GKE), and Cloud SQL for PostgreSQL and pgvector, using Ray, LangChain, and Hugging Face. What is RAG? RAG can improve the outputs of foundation modes, such as large language models (LLMs), for a specific application. Rather than relying purely on knowledge developed during training, AI apps equipp ..read more

In today’s digital age, endpoints are a business requirement for collaborating with coworkers, engaging with customers, and building great products. However, with a rise in cyber attacks, increased scrutiny on cost, and pressure to innovate, IT departments require a new kind of endpoint that improves user experience, simplifies management, increases security and reduces costs—which are some of the key traits of what we refer to as the modern endpoint. We commissioned Forrester Consulting to survey 652 IT professionals to explore the meaning of a modern endpoint to IT departments, which Forr ..read more

Written by: Ofir Rozmann, Asli Koksal, Adrian Hernandez, Sarah Bock, Jonathan Leathery   APT42, an Iranian state-sponsored cyber espionage actor, is using enhanced social engineering schemes to gain access to victim networks, including cloud environments. The actor is targeting Western and Middle Eastern NGOs, media organizations, academia, legal services and activists. Mandiant assesses APT42 operates on behalf of the Islamic Revolutionary Guard Corps Intelligence Organization (IRGC-IO). APT42 was observed posing as journalists and event organizers to build trust with their victims th ..read more

For the fifth consecutive year, Gartner® has named Google as a Leader in the Magic Quadrant™ for Cloud AI Developer Services (CAIDS). We believe this is a testament to our history of offering innovative AI products and delivering continuous improvement for our customers. Download the complimentary 2024 Gartner Magic Quadrant™ for Cloud AI Developer Services report. Google has two decades of experience building and running advanced AI workloads at scale. We funneled this experience into Vertex AI, which launched nearly four years ago with the goal of providing the best AI/ML platform for ac ..read more