Google cloud

Google cloud

1. Big Data & ML Product

   • Google has developed a top layer of big data and ML products to abstract away a lot of the hard work of managing and scaling that infrastructure for you.

2. Security

   • The base layer that covers all of Google's applications

3. compute, storage, and networking

   • These allow you to process, store, and deliver business changing insights, data pipelines, and machine learning models.
   • ช่วยให้สามารถประมวลผล จัดเก็บข้อมูล
   • Storage
     • Storage bucket
   • Compute
     • Google's designed new types of hardware specifically for machine learning. The Tensor Processing Unit or TPU is an ASIC specifically optimized for ML. It has more memory and a faster processor for ML workloads than traditional CPUs or GPUs.
       • Ebay ก็ใช้ TPU
       • Google รวบรวมข้อมูลจาก sensor ทำ ML ช่วยลดการใช้ cooling energy 40% ทำให้ระบบโดยรวมมีประวิทธิภาพเพิ่มขึ้น 15%
     • Compute Engine
       • Demo: Creating a VM on Compute Engine
         • Compute engine -> VM instance -> ตั้งชื่อ -> เลือกเขตพื้นที่ (น่าจะควรเลือกที่อยู่ใกล้เรา) -> เลือก CPU
           • หลังจากสร้างไปที่ SSH ลง Git -> Git clone
       • Compute Engine which lets you run virtual machines on demand in the Cloud. It's Google Cloud's Infrastructure as a Service or IaaS solution. It provides maximum flexibility for people who prefer to manage server instances themselves.
       • Compute Engine is about individual machines running native code
       • App Engine
         • App Engine is GCP's fully managed Platform as a Service or PaaS framework. That means it's a way to run code in the Cloud without having to worry about infrastructure. You just focus on your code and let Google deal with all the provisioning and resource management.
     • GKE, Google Kubernetes Engine
       • GKE is about clusters of machines running containers. Containers have code packaged up with all its dependencies.
         • GKE enables you to run containerized applications in a Cloud environment that Google manages for you under your administrative control.
           • Since most use cases involve multiple programs that need to execute and communicate with each other, you need a way to orchestrate the containers running these separate programs.
             • Kubernetes is a way to orchestrate code that's running in containers.
     • Cloud Functions
       • Cloud Functions are used for code that's triggered by an event such as a new file hitting Cloud storage. The fastest way to lift and shift your data workloads is by provisioning a VM and running your code.
       • Cloud Functions is a completely serverless execution environment or Functions as a Service, FaaS. It executes your code in response to events whether those events occur once a day or many times a second