Dokumentasi batch
Batch adalah layanan terkelola sepenuhnya yang memungkinkan Anda menjadwalkan, memasukkan dalam antrean, dan menjalankan tugas pemrosesan batch pada resource Google Cloud yang disediakan secara otomatis. Pelajari lebih lanjut.
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Introduction to Google Batch
Batch jobs typically require complicated setup, ongoing management, and high costs. Introducing Google Batch from Google Cloud, a fully managed job scheduler to help you run thousands of batch jobs with a single command. Watch along and learn how to
Batch Scheduler for HPC
Today you will see an Google Batch Scheduler for an HPC application
Google Mainframe Modernization - Refactor for Batch
For more information, please visit Google Cloud Mainframe Modernization → https://goo.gle/3SGO7Qy Google Cloud Mainframe Refactor for batch allows customers to modernize mainframe batch applications, written in COBOL and JCL, to Google Cloud, and
Dynamic Workload Scheduler for AI workloads
Discover how Dynamic Workload Scheduler (DWS) simplifies hardware acquisition for AI workloads on Google Cloud. This video explains DWS modes (Calendar and Flex Start) and their integration with products like Compute Engine, Kubernetes Engine, Vertex
Why GKE is perfect for running batch workloads
Kubernetes is the top container orchestration platform for batch workloads like data processing, machine learning, and scientific simulations. In this video, Mofi Rahman, Cloud Advocate at Google, discusses why Google Kubernetes Engine (GKE) is the
Cloud Run: what's new
Cloud Run is Google Cloud's serverless runtime. It’s the simplest way to deploy a website or web API or perform streaming and batch data processing. In this session, we’ll cover what's new for two major areas of Cloud Run: Enterprise architectures
What's new in Kubernetes: Run batch and high performance computing in GKE
Learn best practices on how to run batch and high-performance computing workloads on Google Kubernetes Engine (GKE) and how PGS used these to replace their 260,000-core Cray supercomputers. Hear about the latest feature launches in the data
Advancing Serverless Data Processing in Cloud Dataflow (Cloud Next '18)
Our Cloud Dataflow was the first product to pioneer serverless computing for batch and streaming big data workloads. How can we further reduce operational overhead that gets in the way of focusing on the application logic? Learn how Google has
Large scale and batch computing on Google Compute Engine (Google Cloud Next '17)
In this video, you'll learn how to think about and architect batch processing systems on Google Compute Engine (GCE). Michael Basilyan and Eric Brewer cover reference architectures applicable to business, engineering, and scientific applications as
Cloud OnAir: Advancing Serverless Data Processing in Cloud Dataflow
Google's Cloud Dataflow was the first product to pioneer serverless computing for both batch and streaming big data workloads. We asked ourselves, how can we further reduce operational overhead that gets in the way of focusing on the application
How To Build Real-Time #MachineLearning Solutions Faster: Tecton Feature Platform and #GoogleCloud
Tecton makes it easy to build and manage batch and real-time #datapipelines that power your #machinelearning models on Google Cloud. Accelerate the iteration and deployment cycle of production #ML models with Tecton’s feature platform on #Google
Introducción a Dataflow (Hablemos en Cloud)
Dataflow es la solucion gestionada de Apache Beam de Google. Nos permite transformar y cargar datos a Google Cloud usando el mismo código para streaming y batch. Recursos → https://goo.gle/30TOaMH Hablemos en Cloud → https://goo.gle/2I4UIPU
Write ~Backwards~ For Better Performance!
Writing backwards makes it easier to batch requests for better performance when writing a doc programmatically with the Google Docs API. Start at the end and finish with the title, no more tracking indexes, happy batching! Google Docs API →
Run impact-less ad hoc queries and data exports on Cloud Spanner
Learn how you can run ad hoc batch queries or export terabytes of data on demand from your Cloud Spanner database without impacting your business-critical applications. This session will go over how world renowned Deutsche Bank partnered with Google
What is Dataflow Prime?
What is Dataflow? → https://goo.gle/3RnUEwN Dataflow Product Page → https://goo.gle/3T2FL3Y Dataflow Documentation → https://goo.gle/3evJh7W We’re excited to announce Dataflow Prime, the next generation of Dataflow: Google Cloud’s truly unified batch
Unify batch and stream data for real-time intelligence at Google scale
Enterprises know speed is the world’s utmost advantage, and today’s datasphere is opening a new fast lane for smart businesses. Fueled by the digitization of commerce and society, real-time and streaming data will grow 5X by 2024. Leaders must
How to process stream data on Apache Beam
Windows and Triggers notebook → https://goo.gle/3lqXItT Google Cloud Dataflow → https://goo.gle/3sKT7XJ Beam College → https://goo.gle/39CvbyJ How do you handle processing streaming data with Apache Beam? In this episode of Getting Started with
What is Apache Beam?
Google Cloud Dataflow → https://goo.gle/3Nb1nsp Beam College → https://goo.gle/3NdzHDm Apache Beam is a flexible and open source tool that unifies batch and streaming parallel data processing, in the programming language of your choice. Welcome to
What's next in Kubernetes
In the beginning, Kubernetes aimed to provide users around the world with the tools to run their applications at scale. Google and the Kubernetes community created a shared vision for a platform with the flexibility to grow and shift, serving the
Introducing Google Cloud Workflows
Learn more about Google Cloud Workflows → http://goo.gle/3qlo0hJ As more services are integrated into your solutions, it can become hard to develop, debug, and visualize. Fortunately, Google Cloud Workflows is a fully managed service that allows you
The power of serverless Cloud Run
Google Cloud serverless products have been used to map the planet, track objects in space, reliably deliver breaking news, accelerate science and disease research, and much more. So how can we move serverless forward? Batch data transformations,
Arm on Google Cloud: T2A VMs
Read the blog → https://goo.gle/3IR4BQi Arm-based chips are already ubiquitous in mobile devices, and have proven themselves for supercomputing workloads. And now Arm has arrived at Google Cloud! We’re now announcing our first VM family based on the
Lessons Learned Scaling Machine Learning at Go-Jek on Google Cloud (Cloud Next '18)
Go-Jek, Indonesia’s first billion-dollar startup, has seen an incredible amount of growth in both users and data over the past two years. Many of the ride-hailing company's services are backed by machine learning models hosted on Google Cloud
Unlock biology & medicine potential with AlphaFold on Google Cloud
The next answers to the mysteries of life and discovery of disease treatments have never felt more attainable with these no-cost solutions to run AlphaFold on Vertex AI. Stephanie uncovers how AlphaFold has revolutionized the scientific community and
Cold Disaster recovery on Google Cloud for on-premise applications
Learn how to set up a cold disaster recovery pattern for applications that are primarily deployed on-premise. Whether you’re running batch processing workloads, an ecommerce site, or video streaming solutions, there are solutions for everyone
Cloud Speech API Demo
The Cloud Speech API (https://cloud.google.com/speech) transcribes audio in over 80 languages, and supports both batch and streaming formats. This demo shows how to make a curl request to the API. Code for the bash script in the demo can be found
Serverless data processing with Google Cloud Dataflow (Google Cloud Next '17)
In this video, you'll learn how data transformation services, dynamic work rebalancing, batch and streaming autoscaling and automatic input sharding make Cloud Dataflow auto-awesome. Missed the conference? Watch all the talks here:
Deploy Your Next Application to Google Kubernetes Engine (Cloud Next '19)
Deploying your application on Google Kubernetes Engine sets you up for success. Whether you’re starting small with a single VM or deploying a large existing app, you can take advantage of a comprehensive set of workload primitives to run whatever you
Grid Computing With Dataflow: UBS Tries Option Pricing as an Example Use Case (Cloud Next '18)
In this session Neil Boston, Head of Investment Bank Technology for UBS, and Reza Ardeshir Rokni, Google Solution Architect, will explore the use of Dataflow as a Grid. Using real market data, Dataflow will be used to price foreign exchange options,
Cloud Run Jobs #Shorts
Are you still writing nightly batch jobs? These tend to be long and linear while running on a single server. In this Short, Martin discusses Cloud Run jobs, which can spin up many containerized workers in the cloud! Watch along and hear why Batch