I am studying for this Google Cloud Digital Leader Certification, as I understand, this is like AZ 900 but from Google.
Here is the exam breakdown, every topic they say they can charge on the exam: https://cloud.google.com/certification/guides/cloud-digital-leader
In this post I will explain all topics with my own words, try to provide links and etc, so this can become some quick guide on how to be prepared for each and every topic.
I will keep updating this post as long as I am studying for this exam.
About this certification exam
Length: 90 minutes
Registration fee: $99
Language: English, Japanese
Exam format: 50-60 multiple choice and multiple select questions
Certification Renewal / Recertification: Candidates must recertify in order to maintain their certification status. The Cloud Digital Leader certification is valid for three years from the date of certification. Recertification is accomplished by retaking the exam during the recertification eligibility time period and achieving a passing score. You may attempt recertification starting 60 days prior to your certification expiration date.
Cloud Digital Leader
Certification exam guide
A Cloud Digital Leader can articulate the capabilities of Google Cloud core products and services and how they benefit organizations. The Cloud Digital Leader can also describe common business use cases and how cloud solutions support an enterprise. The Cloud Digital Leader exam is job-role agnostic and does not require hands-on experience with Google Cloud.
The Cloud Digital Leader exam assesses your knowledge in these areas:
- Section 1: Digital transformation with Google Cloud (~10% of the exam)
- Section 2: Innovating with data and Google Cloud (~30% of the exam)
- Section 3: Infrastructure and application modernization (~30% of the exam)
- Section 4: Google Cloud security and operations (~30% of the exam)
Section 1: Introduction to digital transformation with Google Cloud (approximately 10% of the exam)
This is just 10% of the exam, so, no need to spend too much effort here, just knows the basics and move to the other sections where we actually get 30% relevance.
1.1 Explain why cloud technology is revolutionizing business
Well, cloud is like having unlimited infrastructure over the internet, in multiple regions, with unlimited computing and storage power. Also, cloud is about being scalable, flexible, adaptable, also easier to maintain, no need for upfront costs, pay as you go models, and reliability with all those regions, and dedicated hosts, etc.
● Define key terms such as cloud, cloud technology, data, and digital transformation
Cloud is having computing power and infra available on the internet.
Cloud technology, as my understanding, is what makes the cloud, like, cloud computing technology, cloud storage technology, cloud infra, etc.
Data is what users or external source provides and stores within the cloud.
Digital transformation is the process of using digital technologies to create new — or modify existing — business processes, culture, and customer experiences to meet changing business and market requirements. (source)
1.2 Explain why it is critical for businesses to adopt new technology
Adopting new tech is important for business so they can keep up with customers and clients demands and expectations. Also to be able to compete against the competition, to have technology edger over others, or to try to.
● Compare and contrast cloud technology and traditional or on-premises technology
We already know that cloud is elastic, scalable, reliable, flexible, etc. Whereas, in on-prem network we do can make our network also elastic, scalable, reliable, flexible, but it takes great cost, it’s usually not feasible. Therefore, with on-prem we usually have more customization, specially in the infrastructure part, but with cloud we don’t have much infra customization, as the cloud providers take care of it for us, but we have everything else, like power to use as much as computing power necessary, allocate and de-allocate resources at will, and only pay for what we use.
● Describe how customer expectations have changed because of cloud technology
Well, I think that now we are more used to always have systems with near 100% uptime, that never slows down because in the background the cloud is taking care of load by decreasing or increasing computing power, or storage, or ram, users are always expecting their apps/systems to behave like that, to have fail safes, to be also be able to recover from disaster, never loose data.
● Identify the business and technical considerations that organizations need to think about when adopting cloud technology, including: infrastructure; application and business platform modernization; the importance of data; security in the cloud
Very broad topic here, but I think they are talking about the shared responsibility model. See the images below.
They might also be talking about Total Cost of Ownership (TCO), and how CAPEX vs OPEX models works. In the cloud you are OPEX, meaning, it’s operational expenses, meaning you are paying for what you are using within the cloud. For CAPEX, you are using money upfront to acquire hardware and software, and to maintain it all, meaning to hire people, pay for power, location, etc.
Section 2: Innovating with data and Google Cloud (approximately 30% of the exam)
2.1 Describe the role of data in digital transformation and the importance of a data-driven culture
Those concepts are little abstract, but google and wikipedia can give us some general direction on this, so we can describe data-driven as:
The adjective data-driven means that progress in an activity is compelled by data, rather than by intuition or by personal experience.
Therefore, the role of data in the digital transformation is pivotal, since that with not data that would not be possible to achieve data-driven solutions or culture.
● Explain how cloud technology enables data to be applied in new ways
Cloud enable data to be applied in new ways because by using cloud you can access, ingest, store and analyze data like never before. With ETL cloud tech and cloud data store a new era of big data is at hand, and because of cloud auto-scale properties.
2.2 Identify common Google Cloud solutions for data management
Google has a great host of data solutions, such as: BigQuery, Cloud Spanner, Firestore, Firebase, Cloud Storage, Cloud SQL, etc, See here: https://cloud.google.com/products/databases
● Recognize examples of structured and unstructured data
Structured data is relational database, like excel tables, csv files.
Unstructured data is data like documents, images, videos, etc.
2.3. Identify common Google Cloud solutions for smart analytics
Google has resources like Vertex AI, Vision AI, Vision API, BigQuery ML, etc. See more here: https://cloud.google.com/products#section-3
● Articulate the business benefits of storing data in the cloud
It’s resilient, meaning the service will be almost always up and your data always there. I don’t mean your data will be hot and available, you can put in archive mode, but you can pick and choose how and where you will store your data, and that is great value for business.
● Apply appropriate business use cases for databases, data warehouses, and data lakes
Big, huge, topic here. Ahm… I think here it’s more like, when to use A or B database or which data warehouse solution to use, etc. Hard to give simple example like this, but here are some:
Lets say you have an architecture where you receive lots of stream data from all over and that you want to store that data to analyze, how can you do that? Well, for that you can use a pub/sub to gather your data, then use dataflow to store in cloud storage, then persist this on cloud BigTable and use BigQuery to read and analyze it.
● Explain the benefits of Google Cloud data products, including: Looker, BigQuery, Cloud Spanner, Cloud SQL, Cloud Storage
Looker: serverless way to analyze data on top of your data warehouse.
BigQuery: serverless, let’s you analyze lots of data using SQL. With built-in features like machine learning, geospatial analysis, and business intelligence.
Cloud Spanner: Fully managed relational database with unlimited scale, strong consistency, and up to 99.999% availability.
Cloud SQL: Fully managed relational database service for MySQL, PostgreSQL, and SQL Server with rich extension collections, configuration flags, and developer ecosystems.
Cloud Storage: is a managed service for storing unstructured data. Store any amount of data and retrieve it as often as you like.
2.4. Identify Google Cloud’s solutions for machine learning and AI
Here you can see them all: https://cloud.google.com/products#section-3. But I would focus on:
Vertex AI, Cloud AutoML, BigQueryML, Cloud Natural Language, Vision AI, Vision API
● Define artificial intelligence (AI) and machine learning (ML)
Artificial Intelligence (AI) is a branch of computer science that deals with the creation of intelligent machines that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.
The goal of AI research is to create systems that can perform tasks that normally require human intelligence, such as reasoning, learning, and perception.
Machine Learning (ML) is a subset of Artificial Intelligence (AI) that focuses on the development of algorithms that enable computers to learn and make predictions or decisions based on data, without being explicitly programmed to perform the task. In Machine Learning, algorithms analyze and learn from data, and then make a prediction or classification about new, unseen data.
● Outline the importance of data quality in ML prediction accuracy
Data quality is crucial to the accuracy of Machine Learning (ML) predictions because the quality of the data determines the quality of the model that is built.
In summary, high-quality data is a necessary foundation for accurate ML predictions. A model can only be as good as the data it is trained on, so it’s important to invest time and effort into data preparation and cleaning to ensure that the data used for ML is of high quality.
● Describe Google Cloud’s differentiators with regard to AI and machine learning
Well, as I understand, the key differentiator is that Google try to make AI and ML easy to use and accessible, meaning, that even people without much training can benefit from Google AI and ML.
● Recognize the ways customers can use Google Cloud’s AI and ML solutions to create business value
I think that the main point is by Automation of business processes, where customers can use Google Cloud’s AI and ML solutions to automate repetitive and manual tasks, reducing errors and freeing up employees’ time for more strategic work.
Section 3: Infrastructure and application modernization (approximately 30% of the exam)
3.1 Learn what modernizing IT infrastructure with Google Cloud means
Modernizing IT infrastructure with Google Cloud means upgrading and transforming traditional IT systems and processes to take advantage of the scalability, security, and innovation offered by cloud computing.
● Explain why legacy infrastructure struggles to deliver modern services to customers
Legacy infra has a hard time upgrading their current workload, and even if they can upgrade it is usually expensive, and can’t scale well enough, because you will always have limited hardware resources.
● Explain the benefits of modernizing infrastructure with cloud technology
In comparison, cloud computing provides the scalability, flexibility, and innovation needed to deliver modern services to customers. By leveraging the power of the cloud, organizations can quickly and easily scale their IT resources, integrate new technologies, and keep pace with the latest innovations, all while reducing costs and improving security.
● Differentiate between hybrid and multicloud infrastructures
Hybrid is when you have Private Cloud + Public Cloud in your Organization.
Multicloud is when you have multiple, different, Public Clouds in your Organization.
● Differentiate between virtual machines, containers, and serverless computing within business use cases
VMs is IaaS, so you have control of the infra, you need to install and maintain your OS, etc.
Containers are usually PaaS, there you already have the OS installed, you just focus on developing, deploying and running your app.
Serverless Computing, you abstract everything, here you just need to provide code in form of functions. With serverless computing, customers only pay for the computing resources they actually use, rather than having to reserve and pay for a fixed amount of computing resources in advance.
In a serverless computing environment, the customer provides their application code in the form of functions, which are triggered by events, such as a user request or a change in data. The cloud provider then executes the code and manages the underlying infrastructure, including provisioning, scaling, and monitoring the resources needed to run the code.
● Identify the Google Cloud solutions that help businesses modernize their infrastructure
Google Cloud offers a range of solutions to help businesses modernize their infrastructure, including GCP, Kubernetes Engine, Cloud Functions, Google Cloud Anthos, and Google Cloud Virtual Machines.
This might help: https://cloud.google.com/products/#section-5
3.2 Understand modernizing applications with Google Cloud
● Describe the business drivers for modernizing applications
Business drivers for modernizing applications include increased efficiency, improved user experience, enhanced security, increased agility, better scalability, and improved collaboration. These drivers motivate organizations to invest in modernizing their applications to stay competitive and meet the changing needs of their customers and employees.
● Describe the benefits of using cloud-native applications
Cloud-native applications are designed to run on cloud computing infrastructure and take advantage of its scalability, reliability, and security features.
● Apply the appropriate change pattern to different business use cases
In general, applying the appropriate change pattern involves a process of analysis and evaluation, in which the specific requirements of each use case are considered, and the best method for making changes is selected based on those requirements.
● Explain the benefits of Google Kubernetes Engine, Anthos, and App Engine for application development
Google Kubernetes Engine (GKE): GKE is a fully managed Kubernetes service that makes it easy for organizations to run, manage, and scale containerized applications using Kubernetes.
Anthos is a hybrid and multi-cloud application platform that enables organizations to build, run, and manage applications on any cloud, including Google Cloud, on-premises, or other cloud providers.
Anthos provides a unified platform for managing applications, regardless of where they are deployed, which helps organizations to streamline their operations and increase their productivity.
App Engine is a fully managed platform for building and deploying web applications and mobile backends.
3.3 Understand the value of APIs
● Explain how application programming interfaces (APIs) can modernize legacy systems
APIs are a way for different systems to communicate with each other, making them more accessible and easier to use. They help businesses improve security, respond to changing needs, and integrate their systems with new data sources. APIs can modernize legacy systems and make them work better with new technology, resulting in a more efficient and effective business.
● Describe how APIs can create new business value
APIs allow businesses to securely share their data and services with others, opening up new opportunities for growth and innovation. By making their services available to others, businesses can reach new customers, create new revenue streams, improve their own services, and drive innovation. APIs can help businesses create new business value by leveraging the creativity and expertise of others.
● Explain the benefits of Apigee
Google Cloud Apigee is a tool that helps businesses create and manage their APIs in a simple and secure way. Using Apigee, businesses can increase their productivity by quickly creating and deploying APIs, improve security by protecting sensitive data, ensure reliability by monitoring API performance, handle more traffic by automatically scaling, make the process easier for developers, and respond quickly to changing business needs by deploying new APIs. In short, Apigee helps businesses efficiently and effectively create and manage their APIs.
Section 4: Understanding Google Cloud security and operations (approximately 30% of the exam)
4.1 Describe financial governance in the cloud and Google Cloud’s recommended best practices for effective cloud cost management
● Explain how adopting cloud technology affects the total cost of ownership (TCO)
Adopting cloud technology can affect the total cost of ownership (TCO) by reducing costs in several ways. The most significant cost savings come from reducing capital expenses as organizations no longer have to purchase, maintain, and upgrade expensive hardware and software.
Another factor is that cloud providers offer a pay-as-you-go model, where customers only pay for the resources they use, instead of having to make large upfront investments. This helps organizations reduce risk, as they are only paying for what they need, and can also help them manage cash flow more effectively.
Additionally, operating expenses are reduced as cloud providers manage the infrastructure, reducing the need for internal IT staff.
Cloud technology can also increase agility, allowing organizations to quickly respond to changing business needs without incurring additional costs. Furthermore, the ability to scale resources up or down as needed can help optimize costs, avoiding overprovisioning or underutilization of resources.
● Identify the cost management strategy needed in a given business scenario
Cost management can depend on several factors. For Google Cloud you can leverage the use of Sustained use discounts, or committed use discounts, or the use of resources that can scale to zero, etc.
4.2 Describe a cloud security approach and Google Cloud security benefits
● Define fundamental cloud security terms, including privacy, availability, security, and control
In the context of cloud technology, privacy is a key concern and organizations must ensure that their cloud provider implements adequate measures to protect sensitive information.
In the context of cloud technology, high availability is a critical requirement to ensure the seamless functioning of applications and services.
In the context of cloud technology, security is a top priority and organizations must ensure that their cloud provider implements robust security measures to keep their data and applications safe.
In the context of cloud technology, control is a key concern for organizations who must ensure that they have the necessary visibility and management capabilities to secure their data and applications in the cloud.
● Explain what is meant by a shared responsibility model
The shared responsibility model in Google Cloud refers to the division of security responsibilities between the customer and Google. According to this model, Google is responsible for securing the infrastructure and services provided by the cloud platform, while the customer is responsible for securing the applications and data that run on that infrastructure.
● Describe the security benefits of using Google Cloud
Google Cloud offers security benefits such as secure infrastructure, data protection, and compliance with industry standards. These features help ensure the safety and privacy of your data and applications.
For the exam, it is important to focus on the following services, Cloud Data Loss Prevention and Security Command Center.
● Identify today’s top cybersecurity challenges and threats to data privacy
● Demonstrate how organizations can control and manage access to cloud resources
Organizations can control and manage access to cloud resources through a combination of techniques, such as identity and access management (IAM), network security, and encryption.
4.3 Explain how IT operations need to adapt to thrive in the cloud
When moving to the cloud, IT operations need to change the way they work to fully leverage the benefits of the cloud. This often involves adopting new processes and tools, such as automation and orchestration, to manage and scale resources dynamically.
● Differentiate service availability requirements in the cloud versus in on-premises environments
In a cloud environment, the service availability refers to the ability of the users to access and use the services provided by the cloud provider without interruption. In comparison, in an on-premises environment, the service availability refers to the ability of the users to access and use the services provided by the local IT infrastructure without interruption.
One major difference is that in a cloud environment, the cloud provider is responsible for ensuring the availability of the services, while in an on-premises environment, the responsibility falls on the local IT team. Another difference is that cloud providers typically offer higher levels of service availability and reliability, often with Service Level Agreements (SLAs) that guarantee certain levels of uptime. In an on-premises environment, achieving high levels of service availability can be more challenging and requires more investment in hardware, software, and staffing.
● Describe the operational challenges that DevOps solves
DevOps is a set of practices that combines software development and IT operations to optimize the delivery of software products. It aims to improve the collaboration, communication, and automation of software development processes.
● Apply the goals of site reliability engineering (SRE) to different business use cases
Site reliability engineering (SRE) is a software engineering practice that aims to ensure the reliability, availability, and performance of a software system by combining the principles of software development and systems operations. The goals of SRE can be applied to different business use cases in order to improve the overall reliability and performance of their systems.
4.4 Identify Google Cloud solutions for cloud resource monitoring and application performance management
Google Cloud offers several solutions for cloud resource monitoring and application performance management. Some of them include:
- Stackdriver: a comprehensive solution for monitoring, logging, and diagnosing the performance of cloud-powered applications.
- Cloud Monitoring: a cloud-native monitoring solution that provides insights into the performance and health of cloud resources.
- Cloud Trace: a distributed tracing system that provides visibility into the performance of microservices-based applications.
- Cloud Profiler: a performance profiling tool that helps identify performance bottlenecks and optimize the performance of applications running on Google Cloud.
- Cloud Debugger: a cloud-based debugging tool that enables developers to quickly find and fix performance issues in production applications.
● Explain the potential impact of unexpected or prolonged downtime
Unexpected or prolonged downtime can have a significant impact on a business. It can cause disruptions to operations, leading to loss of revenue and customers. Downtime can also harm the reputation of a company and impact customer trust in the brand. Additionally, prolonged downtime can cause long-term damage to a company’s bottom line, as the costs associated with resolving the issue and restoring operations can be high. Moreover, it can result in missed opportunities, such as new business or increased market share. In an increasingly competitive landscape, having reliable and available systems is critical to business success, making the potential impact of unexpected or prolonged downtime a significant concern for organizations of all sizes.
● Define monitoring, logging, and observability within the context of cloud operations
Monitoring refers to the process of tracking the performance, availability, and resource utilization of an IT system. It is used to detect and diagnose issues in the system, and to ensure that the system is functioning correctly.
Logging involves collecting, storing, and analyzing log data generated by an IT system. Log data can be used to diagnose problems, track system activity, and support security and compliance requirements.
Observability refers to the ability to understand the behavior of a complex system by analyzing the data it generates. It enables IT operations teams to monitor the performance of their systems, detect and diagnose problems, and understand the root cause of issues. By improving observability, IT operations teams can ensure the reliability and performance of their systems, even as they scale and evolve.
● Identify the Google Cloud resource monitoring and maintenance tools.
Google Cloud offers several tools for monitoring and maintenance of cloud resources, including:
- Stackdriver: a comprehensive monitoring, logging, and diagnostics platform
- Cloud Monitoring: provides visibility into the performance and health of your cloud resources and applications
- Cloud Logging: provides real-time logs and insights into your applications and infrastructure
- Cloud Trace: helps you understand the performance and behavior of your cloud-based applications
- Cloud Profiler: provides performance profiling data for your applications running in the cloud
- Cloud Debugger: helps you diagnose and debug your cloud-based applications in production.
Cloud Digital Leader Sample Questions
The Cloud Digital Leader sample questions will familiarize you with the format of exam questions and example content that may be covered on the exam. These questions are for the latest version of the exam that launched January 26, 2022.
The sample questions do not represent the range of topics or level of difficulty of questions presented on the exam. Performance on the sample questions should not be used to predict your Cloud Digital Leader exam result.
Sample Questions Answered and Reviewed
Here are some questions I find worth sharing with you.
Question here is, what is maturity level to Google Cloud? What is this “transformational one” maturity level?
To be able to answer this question we must know about Google Cloud Adoption Framework (GCAF), it is a guide from Google to help customers with cloud adoption. You can check it in completeness here (it’s a pdf).
There are many topics on GCAF, but for this particular question what we need to understand is this:
GCAF Phases (source)
Google Cloud Adoption Framework also suggests that a businesses readiness for success in the cloud is determined by current business practices in each of these four themes. For each theme, those practices will fall into one of the following phases:
Tactical (short term goals): Individual workloads are in place, but no coherent plan encompassing all of them with a strategy for building out to the future. The focus is on reducing the cost of discrete systems and on getting to the cloud with minimal disruption. The wins are quick, but there is no provision for scale.
Strategic (mid term goals): A broader vision governs individual workloads, which are designed and developed with an eye to future needs and scale. You have begun to embrace change, and the people and processes portion of the equation are now involved. IT teams are both efficient and effective, increasing the value of harnessing the cloud for your business operations.
Transformational (long term goals): With cloud operations functioning smoothly, you’ve turned your attention to integrating the data and insights garnered from working now in the cloud. Existing data is transparently shared. New data is collected and analyzed. The predictive and prescriptive analytics of machine learning applied. Your people and processes are being transformed, which further supports the technological changes. IT is no longer a cost center, but has become instead a partner to the business.
I didn’t really know what was SLO, so here it is Google Cloud definition for SLO with an example: “Latency can exceed 300 ms in only 5 percent of the requests over a rolling 30-day period”. But yeah, lowering SLO (I was trying to think SLO same as SLA) wouldn’t make any good. So this couldn’t be the correct answer.
Move to hybrid also not, because the question says “has completed migrated to the cloud”, why go back to on-prem? Makes no sense, so no.
Modernize their apps, this is the correct one, kind of simple and objective, but way too vague, so I thought, but well, it is what it is.
Manually provision, yeah, this is counter intuitive, we are moving towards the age of fully automatic stuff, so I guess I guessed wrong here.
If you noticed, like I am noticing now, this is that kind of question where you remove all that you know that is wrong and go with the one that can be the answer, even if the correct answer is as vague as it is.
Developers want cloud providers to take full control of their apps performance, what, how? Makes no sense.
IT managers want to stop making gradual changes. Well, honestly I thought this could be the answer, but maybe IT managers aren’t the ones doing changes, so I left this one.
IT managers want cloud providers to make infra changes for them. I should kept my thought on IT managers don’t run changes, and left this one, but I didn’t, that’s why I failed.
Developers want to test ideas and experiment with more ease. In the end this is really the one that makes more sense, as in the cloud you can scale in and out, up and down, and also deploy resources quickly and easily.
I was like, ok, they have the hardware, they have their cloud, so now use API to integrate that hardware to your cloud, or public cloud. But nope, so API here is actually being used to connect the hardware to their customer service app, whatever it is. The answer reflects my line of thought, but I still picked the wrong answer.
Again, same thing here. No sensitive data goes to the public cloud, apparently. But I was more thinking about push notifications, so dashboards and charts wasn’t really looking like a correct answer to me, that’s why I got it wrong.
Those questions are so tricky and vague. Ok, you can establish a partnership between sectors, but how does that guarantees that you will lower you cloud costs? Google might have some paper on this, once/if I found it, this will be updated.
That’s a good one. I was really like between A and C. I probably already saw that question/answer on some Azure scenario.
Highlights on Google Cloud Resources
Here are some notes I took my own while studying for this certification:
- Charged only when being used
- Use for scenarios where you want to eliminate cost of Windows licensing; you need something as fully managed as possible
- Can be written in many languages; PHP, Java, etc
- Automatically spins up or down (scale to zero)
- Use when you want to create an APP that will only be used during business hours
- Is able to perform event-driven services, build serverless backend, process real-time data
- Container Orchestration platform
- Scalable an flexible configuration
- Complete control over orchestration, such as network, storage, observability
- Supports stateful APP use case
- Open source solution
- Use for lift and shift your on-prem WMWare based APP to the cloud
- Scalable data integration
- Use to clean, prepare, transfer and transform data
- Has a web UI
- CDAP open-source pipeline development
- Can be used as visualization tool for ETL
- Organization is the root node of Google Cloud hierarchy of resources
- Apply policies on root node when you need those policies to replicate on all levels (folders, projects, resources, billing accounts, etc)
- Use to run specialized workloads, meaning, use when there isn’t a proper resource to do it already in the cloud
- Integrate with GCP with minimal latency
- Google recommends the creation of one central cloud Billing Account for the whole Organization
- To merge all projects under a single Billing Account move all projects to the root organization
Managed Instance Group for Compute Engine
- Uses instance template to create identical instances
- Allows operational on multiple identical VWs
Folders and Projects
- Create a folder per department is the standard for multiple departments and allow better organization
- Create a project per workload allows each workload to follow specific governance and compliance policies
- Projects are the base, basis, level organizing unit in GCP (resources are foundation level)
- Projects are required to use service-level resources
- All service-level resources are parented by Projects
- Least privilege
- Resource policy for access and permissions
- Networking: firewall rules
- Use when resources in a resource group need access to something, like BigQuery
- Create a Service Account for each functionality-security equivalent resource
- Monitor, analyze, alert logging data and events from both clouds (AWS and CGP)
Transfer Appliance Service
- Use when you want to quickly transfer 50TB of data from on-prem to GCP
- Use when you want to make sure that internal company data should only be accessible from cooperating devices when being accessed within the corporate offices
- Used for mobile gaming
- Cloud hosted, NoSQL database
- Keeps your data in-sync in real time across devices
- Scalable, low-maintenance, and serveless document database
- Use when your organization has a LDAP server and want to allow their users to access GCP resources
- Sync users and groups from AD/LDAP with GCP
- Use for handling ingestion from many clients simultaneously
- Gather events from many clients simultaneously
Business Payments Profile
- Use this if you are paying in name of your company
- Use if you want to give a person the ability to download all possible invoices for year-end tax purposes
- Use for Apache Spark solutions, also for Presto, Apache Flink, etc
- Manage APPS by running containers and other workloads across on-premises and multi-public clouds
Preemptible Virtual Machine (PVM)
- Cheap, short-lived compute instances
- Use for batch and fault-tolerant workloads
- PVM lasts up to 24 hours
- PVM is the cheapest computation solution
Container Optimized OS
- Is and OS image for your compute engine VM that is optimized for running Docker containers
- Use to reduce boot time from VM to a minimal
- Enables Customer Aware Support
- Enables Account Manager
Storage Transfer Service
- Use to transfer from AWS S3 to GCP cloud store online
- Allows to quickly import data online into cloud storage
- Allows repeating schedule for transferring data
- Use to transfer data within cloud storage from one bucket to another
Cost Table Report
- Cost detail per invoice per month
- Gives a tabular view of your monthly costs for a given invoice
Cloud Big Table
- Use to receive large amount of traffic
- Reads has very low latency
- Fully managed, scalable NoSQL datbase service
- Ideal to store very large amounts of data in a key-value store
- Use for large NoSQL analytical workloads
- Can handle stream with spikes to ingest data
- Handles large volume of data from sensors, IOT, stream, etc
- Can work with stream data at a rate of 6000 clicks per minute up to 8500 clicker per second
- File share system that can be mounted effectively on several compute engine instances for media workloadsa
- Use NFS
- Use for managing APIs and establish security policies
- APIGEE is a platform to develop and manage APIs
- Dev tool that works as IDE
- Write, debug and deploy
- Works with IntelliJ, VS Code or your browser
- Works with Cloudshell
- Abstracts infra management by automatically scaling up and down depending on traffic
- Only charges for resource used
- Can build data processing APPs that transform lightweight data, as it arrives, and stores it as structured data
- Grants temporary access to a google storage resource
- Fully managed platform for web and mobile APP development
- Is serverless and can scale to zero
- Is an alternative to Cloud Run when to focus on building and deploying APPs in a high optimized framework
- Can help identify products of interest within images and visually search product catalogs
- Offers powerful pre-trained ML models
- Detect objects and faces, reads printed and handwritten text
- Find products of interest within images
- Visually search product catalogs
- Detect and classify multiple objects, including location, based on image
- Helps categorization of products using images
- Can train, host and use ML models to make predictions at scale
- Is an integrated suite of products that combines AI platform functions with pre-trained, AutoML and custom tooling
- Hosts tensorflow models
Data Loss Prevention
- Protect Sensitive data as you move to the cloud
- Allows to classify sensitive data in structured and unstructured workloads
- Use to ensure that PII (personally identifiable information) are de-identified via masking to keep information safe
Cloud Shell and CLoud SDK
- Administer GCP resources using Google Cloud CLI commands
App Engine Flexible
- Allows devs to focus on writing code
- Scale to zero, while also balacing load
- Based used when APPs runs on Docker
- For APPs that receive constant traffic, experience regular traffic fluctuations
APP Engine Standard
- Ideal for APPs that experience sudden and extreme spikes of traffic which requires immediate scaling
- Can scale up in seconds to handle large spikes in demand
Google Cloud VPN
- Cloud network solution to establish a secure connection to a VPN (virtual private cloud)
- Connect peer network to VPC using IPSec VPN connection
- Use if you need to establish a secure connection to a company VPC
- Is cost effective
- Use if low-latency is not a requirement
- Use if high availability is not a requirement
- Store PII information in table format in the cloud
- Ideal for ERP, CRM, E-commerce
Cloud Spanner (SQL like)
- Use to avoid scaling issue with mobile games
- Use SQL-like database
- Unlimited scale, strong consistency and 99.999% uptime for multi-region
- Never needs to pause for patching, backups, etc
- Analyze BigQuery data using Machine Learning
- Creates and run ML models in BigQuery
- Uses standard SQL queries
- Can host tensorflow models
- Use if you need to store container image within Google Cloud and support multi-region or regional repositories
- Enables you to store artifacts and build dependencies
- Integrate with Cloud Build and others CI/CD systems
- Provides a single location for storing and managing your packages and Docker container images
- Use to perform a break down by region of your GCP costs
- Cost breakdown by region
Committed Use Discounts
- Use if your workloads are, and will continue, constant for a long time
- This is the cheapest option for 1-3 years of commitement
Migrate to Compute Engine
- Use if you want to migrate to GCP your on-prem VM Machines (not VM Apps)
Cloud Identity (IDaaS)
- Manage devices remotely using the company on-prem AD server
- Use Cloud Identity to federate IDs from different providers with Google
- Can serve as CDN (content delivery network)
- Use if a specific object in your APP has to be shared across numerous VM instances and zones
- Archive storage class; lowest cost
- Archive storage class; good for archiving data if you plan accessing less than once a year
- Archive storage class; minimum 365-day storage duration
- Storage Admin; grant this permission if users needs to access and manage cloud storage buckets and files
- Storage Admin; can be applied to an individual bucket
- Coldline storage; very low-cost for storing infrequently accessed data
- Coldline storage; 90 day minimum data duration
- Automation in building, testing and deploying
- Creates pipelines to automate deployments
- Deploy to multiple clouds
- Is protected by GCP Security
- Do not reveal IP address
- Allows you to provisioning your APP instances without public IP address while allowing them to access the internet
https://docs.google.com/document/d/10yMTxjhAAriZUTLcnyCeS4zBWXX_8DkAGYYYALQe0VE/edit?usp=sharing – Google Cloud Digital Leader Exam Prep Guide
https://medium.com/@walkrinthecloud/how-to-prepare-for-the-google-cloud-digital-leader-certification-exam-6bf1dcf017d7 – How to Prepare For The Google Cloud Digital Leader Certification Exam
https://www.exampro.co/gcp-cdl – Free and paid material, also questions, lots of questions
After topic 2 I got tired of writing everything and started using ChatGPT to write for me. Meaning, Topics 3 and 4 are generated using ChaGPT.