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Lance Armah-Abraham

Member since 2020

Silver League

44983 points
Build Agents with Agent Development Kit (ADK) Earned мая 1, 2026 EDT
Plan Your Cloud Next Generation Firewall Needs Earned марта 2, 2026 EST
Introduction to Cloud Next Generation Firewall Earned февр. 25, 2026 EST
Evaluate Gen AI model and agent performance Earned окт. 9, 2025 EDT
Deploy a RAG application with vector search in Firestore Earned окт. 9, 2025 EDT
Edit images with Imagen Earned окт. 8, 2025 EDT
Empower Gen AI Apps with Tool Use Earned окт. 6, 2025 EDT
Build basic Conversational Agents with Playbooks and Flows Earned окт. 2, 2025 EDT
Extend virtual agents with webhooks, tools, and Messenger integration Earned окт. 2, 2025 EDT
Extend Conversational Agents Functionality with Webhooks and Tools Earned окт. 2, 2025 EDT
Vector Search and Embeddings Earned сент. 26, 2025 EDT
Create Embeddings, Vector Search, and RAG with BigQuery Earned сент. 25, 2025 EDT
Introduction to Data Engineering on Google Cloud Earned сент. 7, 2025 EDT
Optimize Costs for Google Kubernetes Engine Earned авг. 31, 2025 EDT
Cloud Architecture: Design, Implement, and Manage Earned авг. 30, 2025 EDT
Set Up a Google Cloud Network Earned авг. 30, 2025 EDT
Extend Gemini with controlled generation and Tool use Earned авг. 26, 2025 EDT
Engineer Effective Prompts for Generative Models Earned авг. 25, 2025 EDT
Explore Google's Gen AI Models Earned авг. 22, 2025 EDT
Deploy and Evaluate Model Garden Models Earned авг. 22, 2025 EDT
Monitor and Log with Google Cloud Observability Earned авг. 20, 2025 EDT
Develop Serverless Apps with Firebase Earned авг. 8, 2025 EDT
Deploy Kubernetes Applications on Google Cloud Earned авг. 8, 2025 EDT
Deploy Multi-Agent Systems with Gemini Enterprise Agent Platform Earned июля 27, 2025 EDT
Build intelligent agents with Agent Development Kit (ADK) Earned июля 27, 2025 EDT
Build Infrastructure with Terraform on Google Cloud Earned июля 14, 2025 EDT
Getting Started with Terraform for Google Cloud Earned июля 14, 2025 EDT
Scaling with Google Cloud Operations Earned июля 11, 2025 EDT
Exploring Data Transformation with Google Cloud Earned июля 9, 2025 EDT
Trust and Security with Google Cloud Earned июля 9, 2025 EDT
Digital Transformation with Google Cloud Earned июля 8, 2025 EDT
Modernize Infrastructure and Applications with Google Cloud Earned июля 7, 2025 EDT
Gen AI Apps: Transform Your Work Earned июня 11, 2025 EDT
Gen AI: Navigate the Landscape Earned июня 10, 2025 EDT
Gen AI: Unlock Foundational Concepts Earned июня 9, 2025 EDT
Gen AI: Beyond the Chatbot Earned мая 27, 2025 EDT
Architecting with Google Kubernetes Engine: Foundations Earned мая 20, 2025 EDT
Responsible AI: Applying AI Principles with Google Cloud Earned дек. 5, 2024 EST
[DEPRECATED]Introduction to Responsible AI Earned дек. 5, 2024 EST
[DEPRECATED] Generative AI Fundamentals Earned дек. 5, 2024 EST
Introduction to Large Language Models Earned мая 4, 2024 EDT
Introduction to Generative AI Earned мая 4, 2024 EDT
Develop Serverless Applications on Cloud Run Earned мая 13, 2021 EDT
Google Cloud Run Serverless Workshop Earned мая 13, 2021 EDT
Build a Secure Google Cloud Network Earned авг. 10, 2020 EDT
Set Up an App Dev Environment on Google Cloud Earned авг. 10, 2020 EDT
Implementing Cloud Load Balancing for Compute Engine Earned авг. 10, 2020 EDT
Develop Your Google Cloud Network Earned авг. 10, 2020 EDT
Google Kubernetes Engine Best Practices Earned июня 27, 2020 EDT
DEPRECATED Websites and Web Applications Earned июня 27, 2020 EDT
Google Developer Essentials Earned июня 10, 2020 EDT
Managing Cloud Infrastructure with Terraform Earned мая 28, 2020 EDT
Baseline: Deploy & Develop Earned мая 28, 2020 EDT
Automate Deployment and Manage Traffic on a Google Cloud Network Earned мая 12, 2020 EDT
Security & Identity Fundamentals Earned мая 12, 2020 EDT
DevOps Essentials Earned мая 5, 2020 EDT
Cloud Engineering Earned апр. 27, 2020 EDT
Baseline: Infrastructure Earned апр. 13, 2020 EDT
Google Cloud Essentials Earned апр. 7, 2020 EDT

Learn about how you can use Agent Development Kit (ADK) to build complex, production-ready AI agents. This course covers ADK’s open-source framework, moving from simple prompt engineering to a code-first, structured software development approach suitable for enterprise-grade, multi-agent systems. Explore other content in the Gemini Agent Ready (GEAR) program.

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Identify critical assets and their compliance requirements.

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This training course introduces Cloud NGFW. Topics include how Cloud NGFW provides centralized firewall management, centralized firewall visibility, advanced threat protection, and firewall insights.

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Complete the Evaluate Gen AI model and agent performance skill badge to demonstrate your ability to use the Gen AI evaluation service. You will evaluate models to select the best model for a given task, compare models against each other and evaluate the performance of agents. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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This lab tests your ability to develop a real-world Generative AI Q&A solution using a RAG framework. You will use Firestore as a vector database and deploy a Flask app as a user interface to query a food safety knowledge base.

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Complete the Edit images with Imagen skill badge to demonstrate your skills with Imagen's mask modes and editing modes to edit images according to certain prompts. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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An LLM-based application can process language in a way that resembles thought. But if you want to extend its capabilities to take actions by running other functions you have coded, you will need to use function calling. This can also be referred to as tool use. Additionally, you can give a model the ability to search Google or search a data store of documents to ground its responses. In other words, to base its answers on that information. In this course, you’ll explore these concepts.

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Complete the Build basic Conversational Agents with Playbooks and Flows skill badge to demonstrate your proficiency in building virtual agents using traditional NLU and generative-based features. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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Complete the Extend agent functionality with Webhooks, Tools, and Integrations skill badge to demonstrate your ability to let conversational agents take actions. You will create a flow that calls a webhook and a playbook with a tool and combine them into a hybrid agent. You'll also prepare custom payload for rich content experiences in the Conversational Messenger. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!

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Connect conversational agents to external systems and APIs to expand what agents can do, designing an end-to-end system that is resilient, fault-tolerant and secure.

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Explore AI-powered search technologies, tools, and applications in this course. Learn semantic search utilizing vector embeddings, hybrid search combining semantic and keyword approaches, and retrieval-augmented generation (RAG) minimizing AI hallucinations as a grounded AI agent. Gain practical experience with Vertex AI Vector Search to build your intelligent search engine. Explore other content in the Gemini Agent Ready (GEAR) program.

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This course explores a Retrieval Augmented Generation (RAG) solution in BigQuery to mitigate AI hallucinations. It introduces a RAG workflow that encompasses creating embeddings, searching a vector space, and generating improved answers. The course explains the conceptual reasons behind these steps and their practical implementation with BigQuery. By the end of the course, learners will be able to build a RAG pipeline using BigQuery and generative AI models like Gemini and embedding models to address their own AI hallucination use cases.

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In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.

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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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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 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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Complete the Extend Gemini with controlled generation and Tool use skill badge to demonstrate your proficiency in connecting models to external tools and APIs. This allows models to augment their knowledge, extend their capabilities and interact with external systems to take actions such as sending an email. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the assessment challenge lab, to receive a skill badge that you can share with your network. When you complete this course, you can earn the badge displayed here and claim it on Credly! Boost your cloud career by showing the world the skills you have developed!"

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Learn a variety of strategies and techniques to engineer effective prompts for generative models

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Learn how to leverage Gemini multimodal capabilities to process and generate text, images, and audio and to integrate Gemini through APIs to perform tasks such as content creation and summarization.

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In this skill bagde, you will demonstrate your ability to use and compare models available in the Vertex AI Model Garden. You'll deploy a model to a Vertex AI Endpoint, query other models via their API, and use Vertex AI's Gen AI evaluation service to measure the performance of multiple models.

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Complete the introductory Monitor and Log with Google Cloud Observability skill badge course to demonstrate skills in the following: monitoring virtual machines in Compute Engine, utilizing Cloud Monitoring for multi-project oversight, extending monitoring and logging capabilities to Cloud Functions, creating and sending custom application metrics, and configuring Cloud Monitoring alerts based on custom metrics.

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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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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 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 Agent Runtime on Gemini Enterprise Agent Platform to run as a managed agentic flow, with infrastructure decisions and resource scaling handled by Agent Runtime. 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 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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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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This course provides an introduction to using Terraform for Google Cloud. It enables learners to describe how Terraform can be used to implement infrastructure as code and to apply some of its key features and functionalities to create and manage Google Cloud infrastructure. Learners will get hands-on practice building and managing Google Cloud resources using Terraform.

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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. This course explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Cloud technology is a powerful asset, and when paired with data, it becomes a catalyst for innovation and enhanced customer experiences. Exploring Data Transformation with Google Cloud examines how organizations can leverage the cloud to make their data more accessible, actionable, and valuable. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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As organizations move their data and applications to the cloud, they must address a rapidly evolving landscape of security challenges. This course explores the foundations of cloud security, the value of Google Cloud’s secure-by-design infrastructure, and the defense-in-depth strategy, while highlighting how AI-driven operations and compliance tools help organizations meet strict global regulatory requirements. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Digital transformation is a critical journey for modern organizations, and establishing a strong baseline in cloud computing is the first step toward driving meaningful innovation. Digital Transformation with Google Cloud introduces the core technologies and strategic frameworks that help organizations modernize their operations. This course explores fundamental cloud concepts, global network infrastructure, and the shared responsibility model to help leaders navigate their path to the cloud with confidence. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Many traditional enterprises use legacy systems and apps that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems and investing in new products and services. This course explores these challenges and offers solutions to overcome them by using cloud technology. As part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google’s gen AI applications, such as Google Workspace with Gemini and Gemini Notebook. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.

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Gen AI: Navigate the Landscape is the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.

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Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google Cloud strategies to address the limitations of foundation models and the key challenges for responsible and secure AI development and deployment.

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Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the power of gen AI. The course also guides you through important considerations you should make when developing a successful gen AI strategy for your organization.

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In this course, "Architecting with Google Kubernetes Engine: Foundations," you get a review of the layout and principles of Google Cloud, followed by an introduction to creating and managing software containers and an introduction to the architecture of Kubernetes. 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: Workloads course.

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As the use of enterprise Artificial Intelligence and Machine Learning continues to grow, so too does the importance of building it responsibly. A challenge for many is that talking about responsible AI can be easier than putting it into practice. If you’re interested in learning how to operationalize responsible AI in your organization, this course is for you. In this course, you will learn how Google Cloud does this today, together with best practices and lessons learned, to serve as a framework for you to build your own responsible AI approach.

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This is an introductory-level microlearning course aimed at explaining what responsible AI is, why it's important, and how Google implements responsible AI in their products. It also introduces Google's 3 AI principles.

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Earn a skill badge by passing the final quiz, you'll demonstrate your understanding of foundational concepts in generative AI. A skill badge is a digital badge issued by Google Cloud in recognition of your knowledge of Google Cloud products and services. Share your skill badge by making your profile public and adding it to your social media profile.

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This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps. Explore other content in the Gemini Agent Ready (GEAR) program.

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This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.

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Complete the intermediate Develop Serverless Applications on Cloud Run skill badge course to demonstrate skills in the following: integrating Cloud Run with Cloud Storage for data management, architecting resilient asynchronous systems using Cloud Run and Pub/Sub, constructing REST API gateways powered by Cloud Run, and building and deploying services on Cloud Run.

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Twelve years ago Lily started the Pet Theory chain of veterinary clinics, and has been expanding rapidly. Now, Pet Theory is experiencing some growing pains: their appointment scheduling system is not able to handle the increased load, customers aren't receiving lab results reliably through email and text, and veteranerians are spending more time with insurance companies than with their patients. Lily wants to build a cloud-based system that scales better than the legacy solution and doesn't require lots of ongoing maintenance. The team has decided to go with serverless technology. For the labs in the Google Cloud Run Serverless Quest, you will read through a fictitious business scenario in each lab and assist the characters in implementing a serverless solution. Looking for a hands on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, enroll in and finish the additional challenge lab at the end of this quest to receive an exclusive Google…

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Earn a skill badge by completing the Build a Secure Google Cloud Network skill badge course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud.

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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 introductory Implementing Cloud Load Balancing for Compute Engine skill badge to demonstrate skills in the following: creating and deploying virtual machines in Compute Engine and configuring network and application load balancers.

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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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Get Anthos Ready. Demand for Google Kubernetes Engine is growing, and customers are looking to Google and its partners to provide in-depth technical knowledge. This first Google Kubernetes Engine-centric Quest of best practices hands-on labs will get you started containerizing to modernize in place , and then managing your deployed apps and services -- with monitoring, tracing, and logging.

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When it comes to hosting websites and web applications, you want a framework that’s robust, fast, and secure. By choosing the Google Cloud Platform, you will have all of those needs covered. In this fundamental-level quest, you will get hands-on practice with GCPs key infrastructure and computing services for the web. From deploying your first web app, to integrating Cloud SQL with Ruby on Rails, to mapping the NYC subway system on App Engine, you will learn all the skills needed to harness GCPs web hosting power.

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This introductory-level quest shows application developers how the Google Cloud ecosystem could help them build secure, scalable, and intelligent cloud native applications. You learn how to develop and scale applications without setting up infrastructure, run data analytics, gain insights from data, and develop with pre-trained ML APIs to leverage machine learning even if you are not a Machine Learning expert. You will also experience seamless integration between various Google services and APIs to create intelligent apps.

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In this Quest, the experienced user of Google Cloud will learn how to describe and launch cloud resources with Terraform, an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. In these nine hands-on labs, you will work with example templates and understand how to launch a range of configurations, from simple servers, through full load-balanced applications.

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In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.

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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This course will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Automate Deployment and Manage Traffic on a Google Cloud Network will give you the practical experience needed so you can start building robust networks right away.

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Security is an uncompromising feature of Google Cloud services, and Google Cloud has developed specific tools for ensuring safety and identity across your projects. In this fundamental-level quest, you will get hands-on practice with Google Cloud’s Identity and Access Management (IAM) service, which is the go-to for managing user and virtual machine accounts. You will get experience with network security by provisioning VPCs and VPNs, and learn what tools are available for security threat and data loss protections.

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Obtain a competitive advantage through DevOps. DevOps is an organizational and cultural movement that aims to increase software delivery velocity, improve service reliability, and build shared ownership among software stakeholders. In this course you will learn how to use Google Cloud to improve the speed, stability, availability, and security of your software delivery capability. DevOps Research and Assessment has joined Google Cloud. How does your team measure up? Take this five question multiple-choice quiz and find out!

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this course is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Monitoring and Cloud Functions. You will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.

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In this introductory-level course, you get hands-on practice with the Google Cloud’s fundamental tools and services. Optional videos are provided to provide more context and review for the concepts covered in the labs. Google Cloud Essentials is a recommendeded first course for the Google Cloud learner - you can come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features.

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