What is the recommended architecture for powerful and efficient TFX pipelines?
The recommended architecture for powerful and efficient TFX pipelines involves a well-thought-out design that leverages the capabilities of TensorFlow Extended (TFX) to effectively manage and automate the end-to-end machine learning workflow. TFX provides a robust framework for building scalable and production-ready ML pipelines, allowing data scientists and engineers to focus on developing and deploying models
How does GKE handle workload deployment and what tools can be used for packaging and deployment?
Google Kubernetes Engine (GKE) is a managed environment for deploying, managing, and scaling containerized applications using Kubernetes on Google Cloud Platform (GCP). GKE handles workload deployment by providing a robust and scalable infrastructure that simplifies the process of packaging and deploying applications. To deploy workloads on GKE, there are several tools and techniques that can
- Published in Cloud Computing, EITC/CL/GCP Google Cloud Platform, GCP basic concepts, Google Kubernetes Engine GKE, Examination review
How does Cloud Code support the creation and deployment of Kubernetes applications?
Cloud Code is a powerful set of tools provided by Google Cloud Platform (GCP) that greatly simplifies the creation and deployment of Kubernetes applications. By integrating seamlessly with popular Integrated Development Environments (IDEs) such as Visual Studio Code and IntelliJ IDEA, Cloud Code offers developers a streamlined workflow for building, testing, and deploying their applications
- Published in Cloud Computing, EITC/CL/GCP Google Cloud Platform, GCP overview, GCP code and build tools, Examination review