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Wenjing Liu

Member since 2019

Diamond League

17280 points
Develop Serverless Apps with Firebase Earned May 18, 2026 EDT
Arcade Voyage: Data Governance and Firebase Foundations Earned May 18, 2026 EDT
Build Infrastructure with Terraform on Google Cloud Earned May 15, 2026 EDT
Arcade Adventure: Modern App Deployment Earned May 14, 2026 EDT
Build a Website on Google Cloud Earned May 14, 2026 EDT
Deploy and Manage Applications on Google App Engine Earned May 14, 2026 EDT
Build a Data Mesh with Knowledge Catalog Earned May 13, 2026 EDT
The Basics of Google Cloud Compute Earned May 11, 2026 EDT
Arcade Base Camp May 2026 Earned May 11, 2026 EDT
Arcade Trail: Cloud Security and DevOps Foundations Earned May 10, 2026 EDT
Implement DevOps Workflows in Google Cloud Earned May 10, 2026 EDT
Develop Your Google Cloud Network Earned May 8, 2026 EDT
Work Meets Play: Expressive Efficiency Earned May 8, 2026 EDT
Use Machine Learning APIs on Google Cloud Earned May 8, 2026 EDT
Set Up a Google Cloud Network Earned May 8, 2026 EDT
Skill Up Summer Earned May 8, 2026 EDT
Manage Scalable Workloads in GKE Earned May 7, 2026 EDT
Google Kubernetes Engine Best Practices: Security Earned Apr 22, 2026 EDT
Manage Kubernetes in Google Cloud Earned Apr 21, 2026 EDT
Deploy Kubernetes Applications on Google Cloud Earned Apr 20, 2026 EDT
Architecting with Google Kubernetes Engine: Production Earned Apr 20, 2026 EDT
Architecting with Google Kubernetes Engine: Workloads Earned Apr 16, 2026 EDT
Getting Started with Google Kubernetes Engine Earned Apr 13, 2026 EDT
Google Cloud Fundamentals: Core Infrastructure Earned Apr 10, 2026 EDT
Deploy Multi-Agent Architectures Earned Apr 9, 2026 EDT
Accelerate Knowledge Exchange with Gemini Enterprise Earned Apr 8, 2026 EDT
Model Armor: Securing AI Deployments Earned Apr 8, 2026 EDT
Build AI Agents with Enterprise Databases Earned Apr 8, 2026 EDT
Unlock Insights with NotebookLM Earned Apr 8, 2026 EDT
Build intelligent agents with Agent Development Kit (ADK) Earned Apr 8, 2026 EDT
Deploy Multi-Agent Systems with Agent Development Kit (ADK) and Agent Engine Earned Apr 8, 2026 EDT
Introduction to Gemini Enterprise Earned Apr 7, 2026 EDT
Understand Google Cloud Agents Earned Apr 7, 2026 EDT
Build a Data Warehouse with BigQuery Earned Apr 5, 2026 EDT
BigQuery Fundamentals for Snowflake Professionals Earned Apr 5, 2026 EDT
BigQuery Fundamentals for Oracle Professionals Earned Apr 5, 2026 EDT
BigQuery Fundamentals for Teradata Professionals Earned Apr 5, 2026 EDT
BigQuery Fundamentals for Redshift Professionals Earned Apr 4, 2026 EDT
Cloud Architecture: Design, Implement, and Manage Earned Apr 2, 2026 EDT
Set Up an App Dev Environment on Google Cloud Earned Apr 1, 2026 EDT
Optimize Costs for Google Kubernetes Engine Earned Apr 1, 2026 EDT
Implement Cloud Security Fundamentals on Google Cloud Earned Mar 31, 2026 EDT
Build Google Cloud Infrastructure for AWS Professionals Earned Mar 30, 2026 EDT
Reliable Google Cloud Infrastructure: Design and Process Earned Mar 28, 2026 EDT
Logging and Monitoring in Google Cloud Earned Mar 22, 2026 EDT
Introduction to Vertex AI Studio Earned Mar 20, 2026 EDT
Google Cloud IAM and Networking for AWS Professionals Earned Mar 17, 2026 EDT

Complete the intermediate Develop Serverless Apps with Firebase skill badge course to demonstrate skills in the following: architecting and building serverless web applications with Firebase, utilizing Firestore for database management, automating deployment processes using Cloud Build, and integrating Google Assistant functionality into your applications.

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Working with data and applications requires the right balance of governance and agility. In this voyage, you’ll use Dataplex to organize, secure, and assess data quality while exploring concepts like data mesh. Alongside, you’ll get hands-on with Firebase—building serverless apps, working with Firestore, and managing data in real time—bringing together modern data management and application development.

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Complete the intermediate Build Infrastructure with Terraform on Google Cloud skill badge to demonstrate skills in the following: Infrastructure as Code (IaC) principles using Terraform, provisioning and managing Google Cloud resources with Terraform configurations, effective state management (local and remote), and modularizing Terraform code for reusability and organization.

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Building and running applications on Google Cloud can take many forms—and this adventure brings them together. Get hands-on with App Engine, Cloud Run, Kubernetes Engine, and Compute Engine as you deploy applications, manage scaling, and explore modern architectures, including the shift from monolithic to microservices.

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Earn the introductory skill badge by completing the Build a Website on Google Cloud skill badge course. This course is based on the Get Cooking in Cloud series and covers`:`Deploying a website on Cloud RunHosting a web app on Compute EngineCreating, deploying, and scaling your website on Google Kubernetes EngineMigrating from a monolithic application to a microservices architecture using Cloud Build

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Earn a Skill Badge by completing the Deploy and Manage Applications on Google App Engine course, where you learn how to use App Engine with Python, Go, and PHP.

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Complete the introductory Build a Data Mesh with Knowledge Catalog skill badge to demonstrate skills in the following: building a data mesh with Knowledge Catalog to facilitate data security, governance, and discovery on Google Cloud. You practice and test your skills in tagging assets, assigning IAM roles, and assessing data quality in Knowledge Catalog.

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Earn a skill badge by completing the The Basics of Google Cloud Compute skill badge course, where you learn how to work with virtual machines (VMs), persistent disks, and web servers using Compute Engine.

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Welcome to Base Camp, where you’ll develop key Google Cloud skills (available in Spanish and Portuguese too!) and earn an exclusive credential that will open doors to the cloud for you. No prior experience is required!

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Securing applications and streamlining delivery go hand in hand in modern cloud environments. In this trail, you’ll work with tools like Cloud KMS, Identity-Aware Proxy, and service accounts to manage access and protect resources. You’ll also explore private Kubernetes clusters, artifact management, and build CI/CD pipelines with Cloud Build—bringing together the essentials of cloud security and DevOps in practice.

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Complete the intermediate Implement DevOps Workflows in Google Cloud skill badge to demonstrate skills in the following: creating git repositories with Cloud Source Repositories, launching, managing, and scaling deployments on Google Kubernetes Engine (GKE), and architecting CI/CD pipelines that automate container image builds and deployments to GKE.

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Earn a skill badge by completing the Develop your Google Cloud Network skill badge course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM roles and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches.

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As platforms grow, maintaining speed, reliability, and seamless user experiences becomes critical. Inspired by Bobble AI and its journey to support millions of real-time interactions, this challenge explores how cloud-native systems are designed for efficiency at scale. You’ll work with Docker and Kubernetes to run and orchestrate applications, while also using IAM, Cloud Storage, and Monitoring to manage access, data, and performance. The result: a clearer view of how the right mix of containers, automation, and observability keeps modern applications fast, resilient, and efficient.

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Earn the advanced skill badge by completing the Use Machine Learning APIs on Google Cloud course, where you learn the basic features for the following machine learning and AI technologies: Cloud Vision API, Cloud Translation API, and Cloud Natural Language API.

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Earn a skill badge by completing the Set Up a Google Cloud Network skill badge course, where you will learn how to perform basic networking tasks on Google Cloud Platform - create a custom network, add subnets firewall rules, then create VMs and test the latency when they communicate with each other.

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A season to build, experiment, and grow—one skill at a time. You’ll start with the fundamentals of networking, creating the foundation that connects everything together. From there, you’ll step into automation and application development using Cloud Scheduler, App Engine, and machine learning APIs. By the end, you’ll have a more confident, hands-on understanding of how modern applications are built, connected, and run on the cloud.

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Discover how to modernize, manage, and observe applications at scale using Google Kubernetes Engine Enterprise. This course uses lectures and hands-on labs to help you explore and deploy using Google Kubernetes Engine (GKE), GKE Fleets, Cloud Service Mesh, and Config Controller capabilities that will enable you to work with modern applications, even when they are split among multiple clusters hosted by multiple providers.

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Get Anthos Ready. This Google Kubernetes Engine-centric quest of best practice hands-on labs focuses on security at scale when deploying and managing production GKE environments -- specifically role-based access control, hardening, VPC networking, and binary authorization.

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Complete the intermediate Manage Kubernetes in Google Cloud skill badge course to demonstrate skills in the following: managing deployments with kubectl, monitoring and debugging applications on Google Kubernetes Engine (GKE), and continuous delivery techniques.

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Complete the intermediate Deploy Kubernetes Applications on Google Cloud skill badge course to demonstrate skills in the following: Configuring and building Docker container images.Creating and managing Google Kubernetes Engine (GKE) clusters.Utilizing kubectl for efficient cluster management.Deploying Kubernetes applications with robust continuous delivery (CD) practices.

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In this course, you'll learn about Kubernetes and Google Kubernetes Engine (GKE) security; logging and monitoring; and using Google Cloud managed storage and database services from within GKE. This is the second course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Reliable Google Cloud Infrastructure: Design and Process course or the Hybrid Cloud Infrastructure Foundations with Anthos course.

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In "Architecting with Google Kubernetes Engine- Workloads", you'll embark on a comprehensive journey into cloud-native application development. Throughout the learning experience, you'll explore Kubernetes operations, deployment management, GKE networking, and persistent storage. This is the first course of the Architecting with Google Kubernetes Engine series. After completing this course, enroll in the Architecting with Google Kubernetes Engine- Production course.

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Welcome to the Getting Started with Google Kubernetes Engine course. If you're interested in Kubernetes, a software layer that sits between your applications and your hardware infrastructure, then you’re in the right place! Google Kubernetes Engine brings you Kubernetes as a managed service on Google Cloud. The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, as it’s commonly referred to, and how to get applications containerized and running in Google Cloud. The course starts with a basic introduction to Google Cloud, and is then followed by an overview of containers and Kubernetes, Kubernetes architecture, and Kubernetes operations.

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Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

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Complete the advanced Deploy Multi-Agent Architectures skill badge to demonstrate skills in the following: building multi-agent systems with ADK, connecting agents with the Agent-to-Agent (A2A) protocol, integrating external tools using the Model Context Protocol (MCP), and deploying a complete multi-agent solution to Agent Engine.

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Unite Google’s expertise in search and AI with Gemini Enterprise, a powerful tool designed to help employees find specific information from document storage, email, chats, ticketing systems, and other data sources, all from a single search bar. The Gemini Enterprise assistant can also help brainstorm, research, outline documents, and take actions like inviting coworkers to a calendar event to accelerate knowledge work and collaboration of all kinds. (Please note Gemini Enterprise was previously named Google Agentspace, there may be references to the previous product name in this course.)

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This course reviews the essential security features of Model Armor and equips you to work with the service. You’ll learn about the security risks associated with LLMs and how Model Armor protects your AI applications.

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Build AI agents that can leverage enterprise databases using the MCP Toolbox for Databases. You will define secure database interaction tools, and implement intelligent querying capabilities (leveraging vector embeddings, structured queries).

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In this course, you will learn how to centralize diverse sources like PDFs, web pages, and even audio files into a single, intelligent workspace. You will learn to chat with your documents to find specific information, generate instant summaries, and verify answers with AI-powered citations.

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This structured course is for developers interested in building intelligent agents using the Agent Development Kit (ADK). It combines hands-on experience, core concepts, and practical application, to provide a comprehensive guide to using ADK. You can also join our community of Google Cloud experts and peers to ask questions, collaborate on answers, and connect with the Googlers making the products you use every day.

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In this course, you’ll learn to use the Google Agent Development Kit to build complex, multi-agent systems. You will build agents equipped with tools, and connect them with parent-child relationships and flows to define how they interact. You’ll run your agents locally and deploy them to Vertex AI Agent Engine to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Engine. Please note these labs are based off a pre-released version of this product. There may be some lag on these labs as we provide maintenance updates.

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This course introduces Gemini Enteprise, a powerful platform that brings together AI agents, enterprise search, NotebookLM, and intelligent data access to solve organizational challenges. Through real-world examples and hands-on exploration, learners will be able to connect Gemini Enterprise capabilities to real business needs, describe its architecture, and explain how it handles data access and privacy across roles.

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This course provides a comprehensive overview of Google Cloud's agent platforms, including Vertex AI Agent Builder, Gemini Enterprise, Conversational Agents, and the Agent Development Kit. Learners will understand the unique capabilities of each offering, distinguish between the optimal solution for specific use cases, and gain foundational knowledge in creating search and chat applications.

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Complete the intermediate Build a Data Warehouse with BigQuery skill badge course to demonstrate skills in the following: joining data to create new tables, troubleshooting joins, appending data with unions, creating date-partitioned tables, and working with JSON, arrays, and structs in BigQuery.

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This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Snowflake and want to begin working in BigQuery. Through interactive lecture content and hands-on labs, you learn how to provision resources, create and share data assets, ingest data, and optimize query performance in BigQuery. Drawing upon your knowledge of Snowflake, you also learn about similarities and differences between Snowflake and BigQuery to help you get started with data warehouses in BigQuery. After this course, you can continue your BigQuery journey by completing the skill badge quest titled Build and Optimize Data Warehouses with BigQuery.

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This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Oracle and want to begin working in BigQuery. Through interactive lecture content and hands-on labs, you learn how to provision resources, create and share data assets, ingest data, and optimize query performance in BigQuery. Drawing upon your knowledge of Oracle, you also learn about similarities and differences between Oracle and BigQuery to help you get started with data warehouses in BigQuery.

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This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Teradata and want to begin working in BigQuery. Through interactive lecture content and hands-on labs, you learn how to provision resources, create and share data assets, ingest data, and optimize query performance in BigQuery. Drawing upon your knowledge of Teradata, you also learn about similarities and differences between Teradata and BigQuery to help you get started with data warehouses in BigQuery.

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This course covers BigQuery fundamentals for professionals who are familiar with SQL-based cloud data warehouses in Redshift and want to begin working in BigQuery. Through interactive lecture content and hands-on labs, you learn how to provision resources, create and share data assets, ingest data, and optimize query performance in BigQuery. Drawing upon your knowledge of Redshift, you also learn about similarities and differences between Redshift and BigQuery to help you get started with data warehouses in BigQuery. After this course, you can continue your BigQuery journey by completing the skill badge quest titled Build and Optimize Data Warehouses with BigQuery.

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Earn a skill badge by completing the Cloud Architecture: Design, Implement, and Manage to demonstrate skills in the following: deploy a publicly accessible website using Apache web servers, configure a Compute Engine VM using startup scripts, configure secure RDP using a Windows Bastion host and firewall rules, build and deploy a Docker image to a Kubernetes cluster and then update it, and create a CloudSQL instance and import a MySQL database. This skill badge is a great resource for understanding topics that will appear in the Google Cloud Certified Professional Cloud Architect certification exam.

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Earn a skill badge by completing the Set Up an App Dev Environment on Google Cloud skill badge course, where you learn how to build and connect storage-centric cloud infrastructure using the basic capabilities of the following technologies: Cloud Storage, Identity and Access Management, Cloud Functions, and Pub/Sub.

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Complete the intermediate Optimize Costs for Google Kubernetes Engine skill badge course to demonstrate skills in the following: creating and managing multi-tenant clusters, monitoring resource usage by namespace, configuring cluster and pod autoscaling for efficiency, setting up load balancing for optimal resource distribution, and implementing liveness and readiness probes to ensure application health and cost-effectiveness.

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Complete the intermediate Implement Cloud Security Fundamentals on Google Cloud skill badge course to demonstrate skills in the following: creating and assigning roles with Identity and Access Management (IAM); creating and managing service accounts; enabling private connectivity across virtual private cloud (VPC) networks; restricting application access using Identity-Aware Proxy; managing keys and encrypted data using Cloud Key Management Service (KMS); and creating a private Kubernetes cluster.

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Earn a skill badge by completing the Build Google Cloud Infrastructure for AWS Professionals course, where you learn how to configure IAM permission, orchestrate workloads using Kubernetes, host a web application using compute engine, and configure load balancing.

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This course equips students to build highly reliable and efficient solutions on Google Cloud using proven design patterns. It is a continuation of the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine courses and assumes hands-on experience with the technologies covered in either of those courses. Through a combination of presentations, design activities, and hands-on labs, participants learn to define and balance business and technical requirements to design Google Cloud deployments that are highly reliable, highly available, secure, and cost-effective.

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Welcome to the two-part course on Logging, Monitoring, and Observability in Google Cloud. The core operations tools in Google Cloud break down into two major categories. The operations-focused components and the application performance management tools. This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring. After taking this course, it is suggested that you complete part 2, Observability in Google Cloud, to learn about the available application performance management tools.

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This course introduces Vertex AI Studio, a tool to interact with generative AI models, prototype business ideas, and launch them into production. Through an immersive use case, engaging lessons, and a hands-on lab, you’ll explore the prompt-to-product lifecycle and learn how to leverage Vertex AI Studio for Gemini multimodal applications, prompt design, prompt engineering, and model tuning. The aim is to enable you to unlock the potential of gen AI in your projects with Vertex AI Studio.

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This is the first course of a four-course series for cloud architects and engineers with existing AWS knowledge, and it compares Google Cloud and AWS solutions and guides professionals on their use. This course focuses on Identity and Access Management (IAM) and networking in Google Cloud. The learners apply the knowledge of access management and networking in AWS to explore the similarities and differences with access management and networking in Google Cloud. Learners get hands-on practice building and managing Google Cloud resources.

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