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Tekton is a powerful yet flexible Kubernetes-native open-source framework for creating continuous integration and delivery (CI/CD) systems. It lets you build, test, and deploy across multiple cloud providers or on-premises systems by abstracting away the underlying implementation details.
Gradle plugin to build and deploy Google App Engine applications
Google Cloud Tools for PowerShell lets you script, automate, and manage your Windows workloads running on Cloud Platform. Using PowerShell’s powerful scripting environment, customize your cloud workflows using the Windows tools you're already familiar with.
Service mesh is a powerful abstraction that's become increasingly popular to deliver microservices and modern applications. In a service mesh, the service mesh data plane, with service proxies like Envoy, moves the traffic around and the service mesh control plane provides policy, configuration, and intelligence to these service proxies. Traffic Director is GCP's fully managed traffic control plane for service mesh. With Traffic Director, easily deploy global load balancing across clusters and VM instances in multiple regions, offload health checking from service proxies, and configure sophisticated traffic control policies.
Scalable, cloud-native firewall service Fully distributed, cloud-native, firewall service delivers granular control, including micro-segmentation without network re-architecting.
Cloud Datastore is a highly scalable NoSQL database for your applications. Cloud Datastore automatically handles sharding and replication, providing you with a highly available and durable database that scales automatically to handle your applications' load.
Workflows Combine Google Cloud services and APIs to build reliable applications, process automation, and data and machine learning pipelines. New customers get $300 in free credits to spend on Workflows. All customers get 5,000 steps and 2,000 external API calls per month, not charged against your credits.
Want your website and apps to instantly translate texts into more than one hundred languages? Translation API uses Google’s pre-trained neural machine translation to deliver fast, dynamic results. Within Translation API, you can now even choose to use custom model translations, streamlining your workflow within the same client library.
The Google Vertex AI SDK is a comprehensive suite of tools designed to facilitate the development, deployment, and management of machine learning (ML) models on Google Cloud's Vertex AI platform. It offers a unified environment that streamlines the entire ML lifecycle, enabling data scientists and developers to efficiently build, train, and scale ML models and generative AI applications. Key Features and Functionality: - Unified Platform: Integrates tools for data preparation, model training, evaluation, deployment, and monitoring within a single API and user interface, simplifying the ML workflow. - Model Training Options: Supports both AutoML for code-free model training and custom training for full control over ML frameworks and hyperparameter tuning. - Model Garden: Provides access to a curated catalog of over 200 enterprise-ready models, including Google's foundation models like Gemini, Imagen, and Veo, as well as third-party and open-source models. - MLOps Tools: Includes Vertex AI Pipelines for workflow orchestration, Feature Store for managing ML features, Model Registry for versioning models, and Model Monitoring for detecting training-serving skew and inference drift. - Agent Builder and Agent Engine: Offers tools for building, deploying, and governing AI agents, supporting development with the Agent Development Kit (ADK) and providing infrastructure for deploying and scaling agents. Primary Value and User Solutions: The Vertex AI SDK addresses the complexities of ML model development by offering a cohesive and scalable platform that reduces the need for extensive code, thereby accelerating the transition from experimentation to production. By consolidating various ML tools and services, it enhances collaboration among data scientists and developers, improves operational efficiency, and facilitates the deployment of robust AI solutions. This comprehensive approach empowers organizations to harness the full potential of machine learning and artificial intelligence in their applications.
Google Reviews
Ravi P.
Fast, Accurate Translations with Easy Google Cloud Integration
Erick L.
Project Engineer at AI InternationalEasy to Use, Clean Interface
Sayan M.
Smart Tool-Call Editing That Delivers
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