Chapter 1
Introduction to the Google Professional Cloud Architect Exam
Professional Cloud Architect Certification Exam objectives covered in this chapter include the following: Section 1: Designing and planning a cloud solution architecture The Google Cloud Professional Architect exam is not a body of knowledge exam. You can know Google Cloud product documentation 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. Rather, 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: The Google Cloud Professional Cloud Architect exam will test your architect skills, including the following: It is clear from the exam objectives that the full lifecycle of solution development is covered from inception and planning through monitoring and maintenance. 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 are 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: 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 may be satisfied by a combination of managed services, preemptible virtual machines, and the use of autoscalers. 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. 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. Preemptible VMs are low-cost instances that can run up to 24 hours before being preempted, or shut down. They are a good option for batch processing and other tasks that are easily recovered and restarted. Autoscaling enables engineers to deploy an adequate number of instances needed to meet the load on a system. When demand is high, instances are increased, and when demand is low, the number of instances is reduced. With autoscaling, organizations can stop purchasing infrastructure adequate to meet peak capacity and can instead adjust their infrastructure to meet the immediate need. 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 deployment 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 a large number of 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 microservices 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. There is no way to make a decision 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 important, you have to 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. The operational groups of a modern business depend on IT applications. A finance department needs access to accounting systems. A logistics analyst needs access to data about how well the fleet of delivery vehicles is performing. The sales team constantly queries and updates the customer management system. Different business units will have different business requirements around the availability of applications and services. A finance department may only need access to accounting systems during business hours. In that case, upgrades and other maintenance can happen during off-hours and would not require the accounting system to be available during that time. The customer management system, however, is typically used 24 hours a day, every day. The sales team expects the application to be available all the time. This means that support engineers need to find ways to update and patch the customer management system while minimizing downtime. Requirements about availability are formalized in service-level objectives (SLOs). SLOs can be defined in terms of availability, such as being available 99.9 percent of the time. A database system may have SLOs around durability or the ability to retrieve data. For example, the human resources department may have to store personnel data reliably for seven years, and the storage system must guarantee that there is a less than 1 in 10 billion chance of an object being lost. Interactive systems have performance-related SLOs. A web application SLO may require a page loading average response time of 2 seconds with a 95th percentile of 4 seconds. Logging and monitoring data is used to demonstrate compliance with SLOs. Stackdriver logging is used for collecting information about significant events, such as a disk running out of space. Monitoring services collect metrics from infrastructure, such as average CPU utilization during a particular period of time or the number of bytes written to a network in a defined time span. Developers can create reports and dashboards using logging details and metrics to monitor compliance with SLOs. These metrics are known as service-level indicators (SLIs). Incidents, in the context of IT services, are a disruption that causes a service to be degraded or unavailable. An incident can be caused by single factors, such as an incorrect configuration. Often, there is no single root cause of an incident. Instead, a series of failures and errors contributes to a service failure. For example, consider an engineer on call who receives a notification that customer data is not being processed correctly by an application. In this case, a database is failing to complete a transaction because a disk is out of space, which causes the application writing to the database to block while the application repeatedly retries the transaction in rapid succession. The application stops reading from a message queue, which causes messages to accumulate until the maximum size of the queue is reached, at which point the message queue starts to drop data. Once an incident begins, systems engineers and system administrators need information about the state of components and services. To reduce the time to recover, it is best to collect metrics and log events and then make them available to engineers at any time, especially during an incident response. The incident might have been avoided if database administrators created alerts on free disk space or if the application developer chose to handle retries using exponential backoff instead of simply retrying as fast as possible until it succeeds. Alerting on the size of the message queue could have notified the operations team of a potential problem in time to make adjustments before data was dropped. Many businesses are subject to government and industry regulations. Regulations range from protecting the privacy of customer data to ensuring the integrity of business transactions and financial reporting. Major regulations include the following: Complying with privacy regulations usually requires controls on who can access and change protected data. As an architect, you will have to develop schemes for controls that meet regulations. Fine-grained access controls may be used to control further who can update data. When granting access, follow security best practices, such as granting only the permissions needed to perform one’s job and separating high-risk duties across multiple roles. Business requirements define the context in which architects make design decisions. On the Google Cloud Professional Architect exam, you must understand business requirements and how they constrain technical options and specify characteristics required in a technical solution. Brick and Mortar A term to describe businesses with physical presence, especially retail stores. Capital Expenditure (Capex) Funds spent to acquire assets, such as computer equipment, vehicles, and land. Capital expenditures are used to purchase assets that will have a useful life of at least a few years. The other major type of expenditure is operational expenditures. Compliance Implementing controls and practices to meet the requirements of regulations. Digital Transformation Major changes in businesses as they adopt information technologies to develop new products, improve customer service, optimize operations, and make other major improvements enabled by technology. Brick-and-mortar retailers using mobile technologies to promote products and engage with customers is an example of digital transformation. Governance Procedures and practices used to ensure that policies and principles of organizational operations are followed. Governance is the responsibility of directors and executives within an organization. Key Performance Indicator (KPI) A measure that provides information about how well a business or organization is achieving an important or key objective. For example, an online gaming company may have KPIs related to the number of new players acquired per week, total number of player hours, and operational costs per player. Line of Business The parts of a business that deliver a particular class of products and services. For example, a bank may have consumer banking and business banking lines, while an equipment manufacturer may have industrial as well as agricultural lines of business. Different lines of business within a company will have some business and technical requirements in common as well as their own distinct needs. Operational Expenditures (Opex) An expense paid for from the operating budget, not the capital budget. Operating Budget A budget allocating funds to meet the costs of labor, supplies, and other expenses related to performing the day-to-day operations of a business. Contrast this to capital expenditure budgets, which are used for longer-term investments. Service-Level Agreement (SLA) An agreement between a provider of a service and a customer using the service. SLAs define responsibilities for delivering a service and consequences when responsibilities are not met. Service-Level Indicator (SLI) A metric that reflects how well a service-level objective is being met. Examples include latency, throughput, and error rate. Service-Level Objective (SLO) An agreed-upon target for a measurable attribute of a service that is specified in a service-level agreement. Technical requirements specify features of a system that relate to functional and nonfunctional performance. Functional features include providing ACID transactions in a database, which guarantees that transactions are atomic, consistent, isolated, and durable; ensuring at least once delivery in a messaging system; and encrypting data at rest. Nonfunctional features are the general features of a system, including scalability, reliability, and maintainability. The exam will require you to understand functional requirements related to computing, storage, and networking. The following are some examples of the kinds of issues you will be asked about on the exam. Google Cloud has a variety of computing services, including Compute Engine, App Engine, and Kubernetes Engine. As an architect, you should be able to determine when each of these platforms is the best option for a use case. For example, if there is a technical requirement to use a virtual machine running a particular hardened version of Linux, then Compute Engine is the best option. Sometimes, though, the choice is not so obvious. If you want to run containers in the Google Cloud Platform (GCP), you could choose either App Engine Flexible or Kubernetes Engine for a managed service. If you already have application code running in App Engine and you intend to run a small number of containers, then App Engine Flexible is a good option. If you plan to deploy and manage a large number of containers and want to use a service mesh like Istio to secure and monitor microservices, Kubernetes Engine is a better option. There are even more options when it comes to storage. There are a number of factors to consider when choosing a storage option, including how the data is structured, how it will be accessed and updated, and for how long it will be stored. Let’s look at how you might decide which data storage service to use given a set of requirements. Structured data fits well with both relational and NoSQL databases. If SQL is required, then your choices are Cloud SQL, Spanner, BigQuery, or running a relational database yourself in Compute Engine. If you require a global, strongly consistent transactional data store, then Spanner is the best choice, while Cloud SQL is a good choice for regional-scale databases. If the application using the database requires a flexible schema, then you should consider NoSQL options. Cloud Datastore is a good option when a document store is needed, while Bigtable is well suited for ingesting large volumes of data at low latency. Of course, you could run a NoSQL database in Compute Engine. If a service needs to ingest time-series data at low latency and one of the business requirements is to maximize the use of managed services, then Bigtable should be used. If there is no requirement to use managed services, you might consider deploying Cassandra to a cluster in Compute Engine. This would be a better choice, for example, if you are planning a lift-and-shift migration to the cloud and are currently running Cassandra in an on-premises data center. When long-term archival storage is required, then Cloud Storage is probably the best option. Since Cloud Storage has four types of storage, you will have to consider access patterns and reliability requirements. If the data is frequently accessed, then regional or multiregional class storage is appropriate. If high availability of access to the data is a concern or if data will be accessed from different areas of the world, you should consider multiregional storage. If data will be infrequently accessed, then Nearline or Coldline storage is a good choice. Nearline storage is designed for data that won’t be accessed more than once a month. Coldline storage is well suited for data that will be accessed not more than once a year. Networking topics that require an architect tend to fall into two categories: structuring virtual private clouds and supporting hybrid cloud computing. Virtual private clouds (VPCs) isolate a Google Cloud Platform customer’s resources. Architects should know how to configure VPCs to meet requirements about who can access specific resources, the kinds of traffic allowed in or out of the network, and communications between VPCs. To develop solutions to these high-level requirements, architects need to understand basic networking components such as the following: Many companies and organizations adopting cloud computing also have their own data centers. Architects need to understand options for networking between on-premises data centers and the Google Cloud Platform network. Options include using a virtual private network, dedicated interconnect, and partner interconnects. Virtual private networks are a good choice when bandwidth demands are not high and data is allowed to traverse the public Internet. Partner interconnects provide a minimum of 50 Mbps bandwidth, and data is transmitted through the partner’s network, not the public Internet. Dedicated interconnects are used when bandwidth requirements are 10 Gbps or greater. Nonfunctional requirements often follow from business requirements. They include the following: Availability is a measure of the time that services are functioning correctly and accessible to users. Availability requirements are typically stated in terms of percent of time a service should be up and running, such as 99.99 percent. Fully supported Google Cloud services have SLAs for availability so that you can use them to help guide your architectural decisions. Note, alpha and beta products typically do not have SLAs. Reliability is a closely related concept to availability. Reliability is a measure of the probability that a service will continue to function under some load for a period of time. The level of reliability that a service can achieve is highly dependent on the availability of systems upon which it depends. Scalability is the ability of a service to adapt its infrastructure to the load on the system. When load decreases, some resources may be shut down. When load increases, resources can be added. Autoscalers and instance groups are often used to ensure scalability when using Compute Engine. One of the advantages of services like Cloud Storage and App Engine is that scalability is managed by GCP, which reduces the operational overhead on DevOps teams. Durability is used to measure the likelihood that a stored object will be retrievable in the future. Cloud Storage has 99.999999999 percent (eleven 9s) durability guarantees, which means it is extremely unlikely that you will lose an object stored in Cloud Storage. Because of the math, as the number of objects increases, the likelihood that one of them is lost will increase. The Google Cloud Professional Cloud Architect exam tests your ability to understand both business requirements and technical requirements, which is reasonable since those skills are required to function as a cloud architect. The Google Cloud Professional Cloud Architect Certification exam uses three case studies as the basis for some questions on the exam. Become familiar with the case studies before the exam in order to save time while taking the test. Each case study includes a company overview, solution concept, technical requirements, business requirements, and an executive statement. As you read each case study, be sure that you understand the driving business considerations and the solution concept. These provide constraints on the possible solutions. When existing infrastructure is described, think of what GCP services could be used as a replacement if needed. For example, Cloud SQL can be used to replace an on-premise MySQL server, Cloud Dataproc can replace self-managed Spark and Hadoop clusters, and Cloud Pub/Sub can be used instead of RabbitMQ. Read for the technical implications of the business statements—they may not be stated explicitly. For example, in the Dress4Win case study, the statement “Improve business agility and speed of innovation through rapid provisioning of new resources” could mean that you should plan to use infrastructure-as-code deployments and enable autoscaling when possible. There is also the statement: “Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle,” which describes an opportunity to use autoscaling to optimize resource usage. Both examples show business statements that imply additional requirements that the architect needs to identify without being told that there is a requirement explicitly stated. The three case studies are available online here: Dress4Win https://cloud.google.com/certification/guides/cloud-architect/ casestudy-dress4win-rev2 Mountkirk Games https://cloud.google.com/certification/guides/cloud-architect/ casestudy-mountkirkgames-rev2 TerramEarth https://cloud.google.com/certification/guides/cloud-architect/ casestudy-terramearth-rev2 The Google Cloud Professional Architect exam covers several broad areas, including the following: These areas require business as well as technical skills. For example, since architects regularly work with nontechnical colleagues, it is important for architects to understand issues such as reducing operational expenses, accelerating the pace of development, maintaining and reporting on service-level agreements, and assisting with regulatory compliance. In the realm of technical knowledge, architects are expected to understand functional requirements around computing, storage, and networking as well as nonfunctional characteristics of services, such as availability and scalability. The exam includes three case studies, and some exam questions reference the case studies. Questions about the case studies may be business or technical questions. Assume every word matters in case studies and exam questions. Some technical requirements are stated explicitly, but some are implied in business statements. Review the business requirements as carefully as the technical requirements in each case study. Similarly, when reading an exam question, pay attention to all of the statements. What may look like extraneous background information at first may turn out to be information that you need in order to choose between two options. Study and analyze case studies before taking the exam. Become familiar with the case studies before the exam to save time while taking the text. You don’t need to memorize the case studies, as you’ll have access to them during the test. Watch for numbers that indicate the scale of the problem. If you need to transmit more than 10 Gbps, then you should consider a Cloud Interconnect solution over a VPN solution, which works up to about 3 Gbps. Understand what is needed in the near term and what may be needed in the future. For example, in the TerramEarth case study, 200,000 vehicles are equipped with cellular communications equipment that can collect data daily. What would change about your design if all 20 million vehicles in production reported their data daily? This requirement is not stated, and not even implied, but it is the kind of planning for the future that architects are expected to do. Understand how to plan a migration. Migrations are high-risk operations. Data can be lost, and services may be unavailable. Know how to plan to run new and old systems in parallel so that you can compare results. Be able to identify lower-risk migration steps so that they can be scheduled first. Plan for incremental migrations. Know agile software development practices. You won’t have to write code for this exam, but you will need to understand continuous integration/continuous deployment and maintaining development, test, staging, and production environments. Understand what is meant by an infrastructure-as-code service and how that helps accelerate development and deployment. Keep in mind that solutions may involve non-Google services or applications. Google has many services, but sometimes the best solution involves a third-party solution. For example, Jenkins and Spinnaker are widely used tools to support continuous integration and deployment. Google Cloud has a code repository, but many developers use GitHub. Sometimes businesses are locked into existing solutions, such as a third-party database. The business may want to migrate to another database solution, but the cost may be too high for the foreseeable future. You have been tasked with interviewing line-of-business owners about their needs for a new cloud application. Which of the following do you expect to find? You have been asked by stakeholders to suggest ways to reduce operational expenses as part of a cloud migration project. Which of the following would you recommend? Some executives are questioning your recommendation to employ continuous integration/continuous deployment (CI/CD). What reasons would you give to justify your recommendation? The finance director has asked your advice about complying with a document retention regulation. What kind of service-level objective (SLO) would you recommend to ensure that the finance director will be able to retrieve sensitive documents for at least the next seven years? When a document is needed, the finance director will have up to seven days to retrieve it. The total storage required will be approximately 100 GB. You are facilitating a meeting of business and technical managers to solicit requirements for a cloud migration project. The term incident comes up several times. Some of the business managers are unfamiliar with this term in the context of IT. How would you describe an incident? You have been asked to consult on a cloud migration project that includes moving private medical information to a storage system in the cloud. The project is for a company in the United States. What regulation would you suggest that the team review during the requirements-gathering stages? You are in the early stages of gathering business and technical requirements. You have noticed several references about needing up-to-date and consistent information regarding product inventory. Inventory is managed on a global scale, and the warehouses storing inventory are located in North America, Africa, Europe, and India. Which managed database solution in Google Cloud would you include in your set of options for an inventory database? A developer at Mountkirk Games is interested in how architects decide which database to use. The developer describes a use case that requires a document store. The developer would rather not manage database servers or have to run backups. What managed service would you suggest the developer consider? Members of your company’s legal team are concerned about using a public cloud service because other companies, organizations, and individuals will be running their systems in the same cloud. You assure them that your company’s resources will be isolated and not network-accessible to others because of what networking resource in Google Cloud? What two business drivers are behind Dress4Win’s interest in moving to the cloud? Dress4Win is considering replacing its self-managed MySQL database with a managed service. Which Google Cloud service would you recommend that they consider? Which of the following requirements from a customer makes you think the application should run in Compute Engine and not App Engine? Consider the TerramEarth case study. What aspect of that case study prompts you to consider potentially significant changes to requirements in the future? Mountkirk Games wants to store player game data in a time-series database. Which Google Cloud managed database would you recommend? The game analytics platform for Mountkirk Games requires analysts to be able to query up to 10 TB of data. What is the best managed database solution for this requirement?
This Study Guide is designed to help you acquire the technical knowledge and analytical skills that you will need to pass the Google Cloud Professional Architect certification exam. This exam is designed to evaluate your skills for assessing business requirements, identifying technical requirements, and mapping those requirements to solutions using Google Cloud products, as well as monitoring and maintaining those solutions. This breadth of topics alone is enough to make this a challenging exam. Add to that the need for “soft” skills, such as working with colleagues in order to understand their business requirements, and you have an exam that is difficult to pass.
Exam Objectives
Analyzing Business Requirements
Reducing Operational Expenses
Accelerating the Pace of Development
Reporting on Service-Level Objectives
Reducing Time to Recover from an Incident
Improving Compliance with Industry Regulations
Business Terms to Know
Analyzing Technical Requirements
Functional Requirements
Understanding Compute Requirements
Understanding Storage Requirements
Understanding Network Requirements
Nonfunctional Requirements
Exam Case Studies
Exam case studies are reprinted with permission from Google LLC. They are subject to change as are the exams themselves. Please visit the Google website to check for the latest Google Cloud Professional Architect exam case studies.Summary
Exam Essentials
Review Questions