in detail, memorize most of what you read in this guide, and view multiple online courses, but that will not guarantee that you pass the exam. You will be required to exercise judgment. You will have to understand how business requirements constrain your options for choosing a technical solution. You will be asked the kinds of questions a business sponsor might ask about implementing their project.
This chapter will review the following:
Exam objectives
Scope of the exam
Case studies written by Google and used as the basis for some exam questions
Additional resources to help in your exam preparation
Exam Objectives
The Google Cloud Professional Cloud Architect exam will test your architect skills, including the following:
Planning cloud solutions
Managing and provisioning cloud solutions
Securing systems and processes
Analyzing and optimizing technical and business processes
Managing implementations
Ensuring solution and operations reliability
It is clear from the exam objectives that the test covers the full lifecycle of solution development from inception and planning through monitoring and maintenance.
Analyzing Business Requirements
An architect starts the planning phase by collecting information, starting with business requirements. You might be tempted to start with technical details about the current solution. You might want to ask technical questions so that you can start eliminating options. You may even think that you've solved this kind of problem before and you just have to pick the right architecture pattern. Resist those inclinations if you have them. All architecture design decisions must be made in the context of business requirements.
Business requirements define the operational landscape in which you will develop a solution. Example business requirements are as follows:
The need to reduce capital expenditures
Accelerating the pace of software development
Reporting on service-level objectives
Reducing time to recover from an incident
Improving compliance with industry regulations
Business requirements may be about costs, customer experience, or operational improvements. A common trait of business requirements is that they are rarely satisfied by a single technical decision.
Reducing Operational Expenses
Reducing operational expenses may be satisfied by using managed services instead of operating services yourself, accepting different services commitments such as preemptible virtual machines and Pub/Sub Lite, and using services that automatically scale to load.
Managed services reduce the workload on systems administrators and DevOps engineers because they eliminate some of the work required when managing your own implementation of a platform. Note that while managed services can reduce costs, that is not always the case; if cost is a key driver for selecting a managed service, it is important to verify that managed services will actually cost less. A database administrator, for example, would not have to spend time performing backups or patching operating systems if they used Cloud SQL instead of running a database on Compute Engine instances or in their own data center. BigQuery is a widely used data warehouse and analytics managed service that can significantly reduce the cost of data warehousing by eliminating many database administrator tasks, such as managing storage infrastructure.
Some services have the option of trading some availability, scalability, or reliability features for lower costs. Preemptible VMs, for example, are low-cost instances that can be shut down at any time but can run up to 24 hours before they will be preempted, that is, shut down and no longer available to you. They are a good option for batch processing and other tasks that are easily recovered and restarted. Pub/Sub Lite can be an order of magnitude less expensive than Pub/Sub but comes with lower availability and durability. Pub/Sub Lite is recommended only when the cost savings justify additional operational work to reserve and manage resource capacity.
Autoscaling enables engineers to deploy an adequate number of resources needed to meet the load on a system. In a Compute Engine Managed Instance Group, additional virtual machines are added to the group when demand is high; when demand is low, the number of instances is reduced. With autoscaling, organizations can stop pre-purchasing infrastructure to meet peak capacity and can instead scale their infrastructure to meet the immediate need. With Cloud Run, when a service is not receiving any traffic, the revision of that service is scaled to zero and no costs are incurred.
Accelerating the Pace of Development
Successful businesses are constantly innovating. Agile software development practices are designed to support rapid development, testing, deployment, and feedback.
A business that wants to accelerate the pace of development may turn to managed services to reduce the operational workload on their operations teams. Managed services also allow engineers to implement services, such as image processing and natural language processing, which they could not do on their own if they did not have domain expertise on the team.
Continuous integration and continuous delivery are additional practices within software development. The idea is that it's best to integrate small amounts of new code frequently so that it can be tested and deployed rather than trying to release many changes at one time. Small releases are easier to review and debug. They also allow developers to get feedback from colleagues and customers about features, performance, and other factors.
As an architect, you may have to work with monolithic applications that are difficult to update in small increments. In that case, there may be an implied business requirement to consider decomposing the monolithic application into a microservice architecture. If there is an interest in migrating to a microservice architecture, then you will need to decide if you should migrate the existing application into the cloud as is, known as lift and shift, or you should begin transforming the application during the cloud migration. Alternatively, you could also rebuild on the cloud using cloud-native design without migrating, which is known as rip and replace.
There is no way to decide about this without considering business requirements. If the business needs to move to the cloud as fast as possible to avoid a large capital expenditure on new equipment or to avoid committing to a long-term lease in a co-location data center or if the organization wants to minimize change during the migration, then lift and shift is the better choice. Most importantly, you must assess if the application can run in the cloud with minimal modification. Otherwise, you cannot perform a lift-and-shift migration.
If the monolithic application is dependent on deprecated components and written in a language that is no longer supported in your company, then rewriting the application or using a third-party application is a reasonable choice.
