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CG - DIAZ SANTOS JONATHAN

Member since 2024

Diamond League

100646 points
Manage Scalable Workloads in GKE Earned Mar 28, 2026 EDT
Integrating Applications with Gemini 1.0 Pro on Google Cloud Earned Feb 13, 2026 EST
Developing Applications with Cloud Run Functions on Google Cloud Earned Feb 8, 2026 EST
Troubleshooting with AI Using Cloud Assist Investigations Earned Feb 2, 2026 EST
Streamline App Development with Gemini Code Assist Earned Jan 18, 2026 EST
Select a Google Cloud Database for Your Applications Earned Jan 17, 2026 EST
Accelerate App Development with Gemini CLI Earned Jan 14, 2026 EST
Developing Applications with Cloud Run on Google Cloud: Fundamentals Earned Jan 11, 2026 EST
Developing Containerized Applications on Google Cloud Earned Jan 11, 2026 EST
Develop and Secure APIs with Apigee X Earned Jan 9, 2026 EST
Service Orchestration and Choreography on Google Cloud Earned Jan 7, 2026 EST
Developing Applications with Google Cloud: Foundations Earned Dec 30, 2025 EST
Develop Serverless Applications on Cloud Run Earned Dec 1, 2025 EST
Secure Software Delivery Earned Dec 1, 2025 EST
Mitigate Threats and Vulnerabilities with Security Command Center Earned Dec 1, 2025 EST
Managing Cloud Infrastructure with Terraform Earned Nov 30, 2025 EST
Google Kubernetes Engine Best Practices: Security Earned Nov 26, 2025 EST
Elastic Google Cloud Infrastructure: Scaling and Automation Earned Nov 23, 2025 EST
Create ML Models with BigQuery ML Earned Nov 15, 2025 EST
Detect, Respond, and Recover from Cloud Cybersecurity Attacks Earned Nov 2, 2025 EST
Put It All Together: Prepare for a Cloud Security Analyst Job Earned Oct 24, 2025 EDT
Cloud Security Risks: Identify and Protect Against Threats Earned Sep 24, 2025 EDT
Introduction to Security Principles in Cloud Computing Earned Sep 23, 2025 EDT
Strategies for Cloud Security Risk Management Earned Sep 21, 2025 EDT
Getting Started with Google Kubernetes Engine Earned Sep 15, 2025 EDT
Essential Google Cloud Infrastructure: Core Services Earned Aug 20, 2025 EDT
Kubernetes in Google Cloud Earned Aug 17, 2025 EDT
Essential Google Cloud Infrastructure: Foundation Earned Aug 10, 2025 EDT
Optimize Costs for Google Kubernetes Engine Earned Aug 7, 2025 EDT
Architecting with Google Kubernetes Engine: Production Earned Jun 6, 2025 EDT
Architecting with Google Kubernetes Engine: Workloads Earned Apr 20, 2025 EDT
Architecting with Google Kubernetes Engine: Foundations Earned Apr 3, 2025 EDT
[DEPRECATED] The Skills Challenge at Next 2025 Earned Mar 14, 2025 EDT
Develop Your Google Cloud Network Earned Mar 3, 2025 EST
Responsible AI: Applying AI Principles with Google Cloud Earned Feb 21, 2025 EST
Prompt Design in Vertex AI Earned Feb 21, 2025 EST
Introduction to Responsible AI Earned Feb 18, 2025 EST
Introduction to Large Language Models Earned Feb 18, 2025 EST
Introduction to Generative AI Earned Feb 17, 2025 EST
Preparing for Your Associate Cloud Engineer Journey Earned Feb 13, 2025 EST
Build a Website on Google Cloud Earned Jan 21, 2025 EST
Set Up a Google Cloud Network Earned Jan 16, 2025 EST
Deploy Kubernetes Applications on Google Cloud Earned Jan 16, 2025 EST
Get Started with Pub/Sub Earned Jan 15, 2025 EST
Create and Manage Cloud SQL for PostgreSQL Instances Earned Jan 15, 2025 EST
App Engine: 3 Ways Earned Jan 12, 2025 EST
Manage Kubernetes in Google Cloud Earned Jan 10, 2025 EST
Build Infrastructure with Terraform on Google Cloud Earned Jan 4, 2025 EST
Monitor and Log with Google Cloud Observability Earned Jan 2, 2025 EST
Using DevSecOps in your Google Cloud Environment Earned Dec 31, 2024 EST
Observability in Google Cloud Earned Dec 27, 2024 EST
DEPRECATED Cloud Operations and Service Mesh with Anthos Earned Dec 21, 2024 EST
Logging and Monitoring in Google Cloud Earned Dec 19, 2024 EST
Getting Started with Terraform for Google Cloud Earned Dec 14, 2024 EST
Reliable Google Cloud Infrastructure: Design and Process Earned Dec 13, 2024 EST
Implement DevOps Workflows in Google Cloud Earned Dec 10, 2024 EST
Introduction to Data Analytics on Google Cloud Earned Aug 6, 2024 EDT
Developing a Google SRE Culture Earned Feb 21, 2024 EST
Prepare Data for ML APIs on Google Cloud Earned Feb 19, 2024 EST
Set Up an App Dev Environment on Google Cloud Earned Feb 18, 2024 EST
Build a Secure Google Cloud Network Earned Feb 18, 2024 EST
Google Cloud Computing Foundations: Networking & Security in Google Cloud Earned Feb 17, 2024 EST
Implementing Cloud Load Balancing for Compute Engine Earned Feb 17, 2024 EST
Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Earned Feb 15, 2024 EST
Google Cloud Computing Foundations: Infrastructure in Google Cloud Earned Feb 11, 2024 EST
Google Cloud Fundamentals: Core Infrastructure Earned Feb 7, 2024 EST
Google Cloud Computing Foundations: Cloud Computing Fundamentals Earned Feb 5, 2024 EST

Discover how to modernize, manage, and observe applications at scale using Google Kubernetes Engine. 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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This short course on integrating applications with Gemini 1.0 Pro models on Google Cloud helps you discover the Gemini API and its generative AI models. The course teaches you how to access the Gemini 1.0 Pro and Gemini 1.0 Pro Vision models from code. It lets you test the capabilities of the models with text, image, and video prompts from an app.

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In this course, you learn about Cloud Run functions, Google's serverless, fully-managed functions as a service (FaaS) product that lets you implement single-purpose function code that reponds to HTTP requests and events from your cloud infrastructure.

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Cloud Assist Investigations is an AI-enabled tool for iterative troubleshooting in Google Cloud environments, and aims to help users troubleshoot common issues to find the root cause of problems that may occur when using Google Cloud services. This course equips DevOps, SRE, and platform engineers with the skills to effectively use Cloud Assist Investigations for streamlined troubleshooting of Google Cloud services. The training focuses on foundational knowledge of Cloud Assist Investigations, with the intent to reduce troubleshooting time and enhance overall operational efficiency for users of Google Cloud.

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Designed for developers of all levels, this course introduces you to the core features and functionalities of Gemini Code Assist, an AI-powered app development collaborator for Google Cloud. From intelligent code suggestions and auto-completion to real-time error detection and refactoring assistance, you'll discover how Gemini Code Assist can significantly enhance your productivity and code quality, and save valuable time to focus on more productive and enjoyable tasks.

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In this course, you learn to analyze and choose the right database for your needs, to effectively develop applications on Google Cloud. You explore relational and NoSQL databases, dive into Cloud SQL, AlloyDB, and Spanner, and learn how to align database strengths with your application requirements, including those of generative AI. Gain hands-on experience configuring Vector Search and migrating applications to the cloud.

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This course is designed for app developers and DevOps engineers who want to work smarter by using Gemini CLI, a generative AI agent made for the terminal and powered by Gemini. This course discusses Gemini CLI installation and configuration, and introduces use cases and security best practices. It explains commands, tools, MCP servers, and extensions. With a hands-on exercise, you'll install and configure Gemini CLI and use it to analyze code and build and modify an app.

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This course introduces the Cloud Run serverless platform for running applications. In this course, you learn about the fundamentals of Cloud Run, its resource model and the container lifecycle. You learn about service identities, how to control access to services, and how to develop and test your application locally before deploying it to Cloud Run. The course also teaches you how to integrate with other services on Google Cloud so you can build full-featured applications.

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In this course, you learn about containers and how to build, and package container images. The content in this course includes best practices for creating and securing containers, and provides an introduction to Cloud Run and Google Kubernetes Engine for application developers.

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Earn a skill badge by completing the Develop and Secure APIs with Apigee X skill badge course, where you learn how to modernize your APIs, use service accounts and Google Authentication to securely access backend services from Apigee API proxies, productize APIs using API products and developer portals, secure APIs using features like API keys, OAuth, private variables and fault handling, integrate Apigee with Google Cloud services like Pub/Sub and Cloud Logging, and call Google Cloud APIs like the Natural Language API and the Geocoding API.

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This course introduces you to event-based applications and teaches you how to use service orchestration and choreography to coordinate microservices. Using lectures and hands-on labs, you learn how to use Workflows, Eventarc, Cloud Tasks, and Cloud Scheduler to build microservices applications on Google Cloud.

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In this course, you learn the fundamentals of application development on Google Cloud. You learn best practices for cloud applications, and how to select compute and data options to match your application use cases. You're introduced to generative AI and how it's used to help build applications. You learn about authentication and authorization, application deployment, continuous integration and delivery, and monitoring and performance tuning for your applications running in Google Cloud. Using lectures and hands-on labs, you learn how to get started building and running applications on Google Cloud.

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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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Complete the intermediate Secure Software Delivery skill badge to demonstrate your proficiency in proactively integrating security into the software development lifecycle (SDLC) with DevSecOps principles. You'll learn how to utilize Google Kubernetes Engine (GKE) and Cloud Run for secure container image deployment, implement automated vulnerability scanning to proactively identify risks, and streamline application development with Artifact Registry while maintaining a focus on security. Additionally, you'll gain skills in integrating Cloud Build for robust development processes and implementing Admission Control Policies for fine-grained control over your environment.

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Complete the intermediate Mitigate Threats and Vulnerabilities with Security Command Center skill badge course to demonstrate skills in the following: preventing and managing environment threats, identifying and mitigating application vulnerabilities, and responding to security anomalies.

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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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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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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including securely interconnecting networks, load balancing, autoscaling, infrastructure automation and managed services.

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Complete the intermediate Create ML Models with BigQuery ML skill badge to demonstrate skills in creating and evaluating machine learning models with BigQuery ML to make data predictions.

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This is the fourth of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll focus on developing capabilities in logging, security, and alert monitoring, along with techniques for mitigating attacks. You'll gain valuable knowledge in customizing threat feeds, managing incidents, handling crisis communications, conducting root cause analysis, and mastering incident response and post-event communications. Using Google Cloud tools, you'll learn to identify indicators of compromise and prepare for business continuity and disaster recovery. Alongside these technical skills, you'll continue updating your resume and practicing interview techniques.

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This is the fifth of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll combine and apply key concepts such as cloud security principles, risk management, identifying vulnerabilities, incident management, and crisis communications in an interactive capstone project. Additionally, you'll finalize your resume updates and put to practice all the new interview techniques you've learned, preparing you to confidently apply for and interview for jobs in the field.

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This is the third of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore the principles of identity management and access control within a cloud environment, covering key elements like AAA (Authentication, Authorization, and Auditing), credential handling, and certificate management. You'll also explore essential topics in threat and vulnerability management, cloud-native principles, and data protection measures. Upon completing this course, you will have acquired the skills and knowledge necessary to secure cloud-based resources and safeguard sensitive organizational information. Additionally, you'll continue to engage with career resources and hone your interview techniques, preparing you for the next step in your professional journey.

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This is the first of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore the essentials of cybersecurity, including the security lifecycle, digital transformation, and key cloud computing concepts. You’ll identify common tools used by entry-level cloud security analysts to automate tasks.

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This is the second of five courses in the Google Cloud Cybersecurity Certificate. In this course, you’ll explore widely-used cloud risk management frameworks, exploring security domains, compliance lifecycles, and industry standards such as HIPAA, NIST CSF, and SOC. You'll develop skills in risk identification, implementation of security controls, compliance evaluation, and data protection management. Additionally, you'll gain hands-on experience with Google Cloud and multi-cloud tools specific to risk and compliance. This course also incorporates job application and interview preparation techniques, offering a comprehensive foundation to understand and effectively navigate the complex landscape of cloud risk management.

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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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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, systems and applications services. This course also covers deploying practical solutions including customer-supplied encryption keys, security and access management, quotas and billing, and resource monitoring.

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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this course, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications.

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This accelerated on-demand course introduces participants to the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Compute Engine. Through a combination of video lectures, demos, and hands-on labs, participants explore and deploy solution elements, including infrastructure components such as networks, virtual machines and applications services. You will learn how to use the Google Cloud through the console and Cloud Shell. You'll also learn about the role of a cloud architect, approaches to infrastructure design, and virtual networking configuration with Virtual Private Cloud (VPC), Projects, Networks, Subnetworks, IP addresses, Routes, and Firewall rules.

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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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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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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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This Course is utilized to certify completion of The Skills Challenge at Next 2025.

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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 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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Complete the introductory Prompt Design in Vertex AI skill badge to demonstrate skills in the following: prompt engineering, image analysis, and multimodal generative techniques, within Vertex AI. Discover how to craft effective prompts, guide generative AI output, and apply Gemini models to real-world marketing scenarios.

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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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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.

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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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This course helps you structure your preparation for the Associate Cloud Engineer exam. You will learn about the Google Cloud domains covered by the exam and how to create a study plan to improve your domain knowledge.

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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 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 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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Earn a skill badge by completing the Get Started with Pub/Sub skill badge course, where you learn how to use Pub/Sub through the Cloud console, how Cloud Scheduler jobs can save you effort, and when Pub/Sub Lite can save you money on high-volume event ingestion.

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Complete the introductory Create and Manage Cloud SQL for PostgreSQL Instances skill badge to demonstrate skills in the following: migrating, configuring, and managing Cloud SQL for PostgreSQL instances and databases.

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Earn a skill badge by completing the App Engine`:` 3 ways course, where you learn how to use App Engine with Python, Go, and PHP.

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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 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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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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In this course, you will learn the basic skills to implement secure and efficient DevSecOps practices on Google Cloud. You'll learn how to secure your development pipeline with Google Cloud services like Artifact Registry, Cloud Build, Cloud Deploy, and Binary Authorization. This enables you to build, test, and deploy containerized applications with security controls throughout the CI/CD pipeline.

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Welcome to Observability in Google Cloud, the second part of a two-part course series. It is suggested that you complete part 1, Logging and Monitoring in Google Cloud, prior to taking this course. This course is all about application performance management tools, including Error Reporting, Cloud Trace, and Cloud Profiler.

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Course two of the Architecting Hybrid Cloud with Anthos series prepares students to operate and observe Anthos environments. Through presentations and hands-on labs, participants explore adjusting existing clusters, setting up advanced traffic routing policies, securing communication across workloads, and observing clusters in Anthos. This course is a continuation of course one, Multi-Cluster, Multi-Cloud with Anthos, and assumes direct experience with the topics covered in that course.

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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 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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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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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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In this beginner-level course, you will learn about the Data Analytics workflow on Google Cloud and the tools you can use to explore, analyze, and visualize data and share your findings with stakeholders. Using a case study along with hands-on labs, lectures, and quizzes/demos, the course will demonstrate how to go from raw datasets to clean data to impactful visualizations and dashboards. Whether you already work with data and want to learn how to be successful on Google Cloud, or you’re looking to progress in your career, this course will help you get started. Almost anyone who performs or uses data analysis in their work can benefit from this course.

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In many IT organizations, incentives are not aligned between developers, who strive for agility, and operators, who focus on stability. Site reliability engineering, or SRE, is how Google aligns incentives between development and operations and does mission-critical production support. Adoption of SRE cultural and technical practices can help improve collaboration between the business and IT. This course introduces key practices of Google SRE and the important role IT and business leaders play in the success of SRE organizational adoption.

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Complete the introductory Prepare Data for ML APIs on Google Cloud skill badge to demonstrate skills in the following: cleaning data with Dataprep by Trifacta, running data pipelines in Dataflow, creating clusters and running Apache Spark jobs in Dataproc, and calling ML APIs including the Cloud Natural Language API, Google Cloud Speech-to-Text API, and Video Intelligence API.

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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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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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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This third course covers cloud automation and management tools and building secure networks.

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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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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud

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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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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This first course provides an overview of cloud computing, ways to use Google Cloud, and different compute options.

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