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This is the second course of a four-course series for cloud architects and engineers with existing Azure knowledge. It aims to compare Google Cloud and Azure solutions and guide professionals on their use.

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This is the second course of a four-course series for cloud architects and engineers with existing Azure knowledge. It aims to compare Google Cloud and Azure solutions and guide professionals on their use.

This is the second course of a four-course series for cloud architects and engineers with existing Azure knowledge. It aims to compare Google Cloud and Azure solutions and guide professionals on their use. This course focuses on compute resources and load balancing in Google Cloud. The learner will apply the knowledge of using virtual machines and load balancers in Azure to explore the similarities and differences with configuring and managing compute resources and load balancers in Google Cloud. Learners will get hands-on practice building and managing Google Cloud resources.

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What's inside

Syllabus

Virtual Machines in Google Cloud
Load Balancing and Managed Instance Groups in Google Cloud

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for cloud architects and engineers with knowledge of Azure
Compares and contrasts Google Cloud and Azure solutions
In-depth focus on compute resources and load balancing in Google Cloud
Practical hands-on practice in building and managing Google Cloud resources
Taught by Google Cloud instructors

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Google Cloud Compute and Scalability for Azure Professionals with these activities:
Practice with Bash Scripting
Strengthen your Bash scripting skills to better navigate and manage resources in Google Cloud.
Browse courses on Bash Scripting
Show steps
  • Review Bash scripting basics and syntax.
  • Practice writing simple Bash scripts to automate tasks.
  • Utilize Bash scripting to interact with Google Cloud resources using the gcloud CLI.
Review computer networking fundamentals
Revisit essential networking principles to reinforce your understanding before starting the course.
Browse courses on TCP/IP
Show steps
  • Re-read course materials on networking fundamentals from previous coursework or study materials.
  • Complete practice questions on networking topics.
Review Networking Fundamentals
Strengthen your foundational understanding of networking to prepare for this Azure-focused course and to bridge gaps in knowledge between Azure and Google Cloud.
Show steps
  • Read the first three chapters of the book, focusing on the OSI model and network protocols.
  • Complete the practice exercises and review questions at the end of each chapter.
  • Summarize the key concepts in your own words and create a mind map of the OSI model.
Seven other activities
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Review Azure Compute and Load Balancing Concepts
Refresh your knowledge of Azure compute and load balancing concepts to build a stronger foundation for comparing and understanding Google Cloud solutions.
Browse courses on Azure Compute
Show steps
  • Review documentation and tutorials on Azure Virtual Machines and Load Balancing.
  • Complete hands-on exercises in the Azure portal to create and manage virtual machines and load balancers.
  • Identify the key differences and similarities between Azure compute and load balancing and Google Cloud compute and load balancing.
Configure virtual machines in Azure
Get practical experience configuring virtual machines in Azure to correlate with the upcoming lessons.
Browse courses on Virtual Machine
Show steps
  • Review documentation and tutorials on Azure Virtual Machine creation.
  • Set up an Azure account if you don't have one.
  • Create and configure virtual machines using the Azure portal.
  • Experiment with different virtual machine settings.
Explore Google Cloud Compute Engine and Load Balancing
Explore the Google Cloud Compute Engine and Load Balancing services through guided tutorials to gain hands-on experience and familiarity.
Show steps
  • Follow the Google Cloud tutorials on creating and managing virtual machines using Compute Engine.
  • Explore the documentation and create a load balancer using Google Cloud Load Balancing.
  • Configure and test the load balancer to distribute traffic across multiple virtual machines.
  • Experiment with different load balancing algorithms and monitor the performance of your load balancer.
Practice Creating and Managing Google Cloud Resources
Reinforce your understanding of Google Cloud by practicing the creation and management of various resources using the Google Cloud Console and gcloud CLI.
Browse courses on Google Cloud Platform
Show steps
  • Create and manage virtual machines, networks, and storage buckets in Google Cloud.
  • Use the gcloud CLI to perform resource management tasks from the command line.
  • Write scripts to automate resource provisioning and management.
Design a Cloud Solution Architecture
Apply your understanding of Google Cloud to design a cloud solution architecture for a real-world scenario, considering scalability, security, and cost-effectiveness.
Browse courses on Cloud Architecture
Show steps
  • Identify the requirements and constraints for the cloud solution.
  • Design the architecture, including the selection of services, resource allocation, and security measures.
  • Document the architecture in a clear and concise manner.
Contribute to Google Cloud Open Source Projects
Deepen your understanding of Google Cloud by contributing to open source projects in the Google Cloud ecosystem, enhancing your problem-solving and collaboration skills.
Browse courses on Open Source
Show steps
  • Identify a Google Cloud open source project that aligns with your interests.
  • Review the project documentation and codebase.
  • Find and fix bugs or suggest improvements.
  • Submit a pull request with your contributions.
Attend Google Cloud Community Events
Expand your network and stay updated on the latest Google Cloud trends and technologies by attending Google Cloud community events.
Show steps
  • Find and register for upcoming Google Cloud events in your area.
  • Attend the events and actively participate in discussions.
  • Connect with other Google Cloud enthusiasts and professionals.

Career center

Learners who complete Google Cloud Compute and Scalability for Azure Professionals will develop knowledge and skills that may be useful to these careers:
Cloud Architect
Cloud Architects design, build, and manage cloud computing systems. They work with clients to understand their business needs and then design and implement cloud solutions that meet those needs. Cloud Architects must have a deep understanding of cloud computing technologies and how they can be used to solve business problems. They must also be able to communicate effectively with both technical and non-technical stakeholders.
Cloud Engineer
Cloud Engineers build and manage cloud computing systems. They work with Cloud Architects to design and implement cloud solutions and then manage those solutions on a day-to-day basis. Cloud Engineers must have a deep understanding of cloud computing technologies and how they can be used to solve business problems. They must also be able to work independently and as part of a team.
Site Reliability Engineer
Site Reliability Engineers (SREs) are responsible for the reliability of cloud computing systems. They work to ensure that systems are up and running and that they are performing at their best. SREs must have a deep understanding of cloud computing technologies and how they can be used to build reliable systems. They must also be able to work independently and as part of a team.
DevOps Engineer
DevOps Engineers work to bridge the gap between development and operations teams. They use their knowledge of both development and operations to help teams deliver software faster and more efficiently. DevOps Engineers must have a deep understanding of both development and operations processes and tools. They must also be able to work effectively with both developers and operations staff.
Cloud Security Engineer
Cloud Security Engineers design, build, and manage cloud security systems. They work with clients to understand their security needs and then design and implement security solutions that meet those needs. Cloud Security Engineers must have a deep understanding of cloud security principles and technologies. They must also be able to work independently and as part of a team.
Cloud Security Analyst
Cloud Security Analysts monitor and analyze cloud security systems for threats. They work with Cloud Security Engineers to identify and mitigate security risks. Cloud Security Analysts must have a deep understanding of cloud security principles and technologies. They must also be able to work independently and as part of a team.
Cloud Storage Engineer
Cloud Storage Engineers design, build, and manage cloud storage systems. They work with clients to understand their storage needs and then design and implement storage solutions that meet those needs. Cloud Storage Engineers must have a deep understanding of cloud storage principles and technologies. They must also be able to work independently and as part of a team.
Cloud Network Engineer
Cloud Network Engineers design, build, and manage cloud networking systems. They work with clients to understand their networking needs and then design and implement networking solutions that meet those needs. Cloud Network Engineers must have a deep understanding of cloud networking principles and technologies. They must also be able to work independently and as part of a team.
Cloud Database Engineer
Cloud Database Engineers design, build, and manage cloud database systems. They work with clients to understand their database needs and then design and implement database solutions that meet those needs. Cloud Database Engineers must have a deep understanding of cloud database principles and technologies. They must also be able to work independently and as part of a team.
Cloud Architect Associate
Cloud Architect Associates work under the supervision of Cloud Architects to design, build, and manage cloud computing systems. They must have a deep understanding of cloud computing technologies and how they can be used to solve business problems. Cloud Architect Associates may also be responsible for managing cloud computing projects.
Data Scientist
Data Scientists use data to solve business problems. They work with clients to understand their business needs and then use data to develop solutions that meet those needs. Data Scientists must have a deep understanding of data science principles and technologies. They must also be able to work independently and as part of a team.
Cloud DevOps Engineer
Cloud DevOps Engineers work to bridge the gap between development and operations teams in the cloud. They use their knowledge of both development and operations to help teams deliver software faster and more efficiently. Cloud DevOps Engineers must have a deep understanding of both development and operations processes and tools. They must also be able to work independently and as part of a team.
Machine Learning Engineer
Machine Learning Engineers design, build, and manage machine learning models. They work with clients to understand their business needs and then design and implement machine learning solutions that meet those needs. Machine Learning Engineers must have a deep understanding of machine learning principles and technologies. They must also be able to work independently and as part of a team.
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with clients to understand their business needs and then design and implement software solutions that meet those needs. Software Engineers must have a deep understanding of software development principles and technologies. They must also be able to work independently and as part of a team.
Data Engineer
Data Engineers design, build, and manage data pipelines. They work with clients to understand their data needs and then design and implement data solutions that meet those needs. Data Engineers must have a deep understanding of data engineering principles and technologies. They must also be able to work independently and as part of a team.

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Google Cloud Compute and Scalability for Azure Professionals.
Provides a deep dive into the design and implementation of data-intensive applications. It covers topics such as data modeling, data storage, and data processing.
Provides a comprehensive overview of computer networks. It covers topics such as network architecture, protocols, and security.
Provides a concise and easy-to-understand overview of operating systems. It covers topics such as process management, memory management, and file systems.
Provides a comprehensive guide to software development. It covers topics such as requirements analysis, design, and testing.
Provides a classic overview of the challenges of software development.
Provides a practical guide to thinking and learning like a pragmatist.
Provides a comprehensive overview of systems thinking. It covers topics such as feedback loops, system boundaries, and leverage points.
Provides a practical guide to building a successful startup. It covers topics such as customer development, lean manufacturing, and agile development.

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