How to become Google Cloud Certified Associate Cloud Engineer(ACE) ?
Check out this Cert Prep guide
Fortunate, you all are for having so many resources to scale up, learn and earn your GCP certificate! Associate Cloud Engineer exam wasn’t launched yet at Google in 2017 and I had to bet on my hard-earned 200$ getting invested in GCP- Professional Cloud Architect (PCA) in Dec 2017. Results were not favoring me, and that single word “Fail” on my screen at the end of the exam made me determine “Never give up”!
I prepared well for a second attempt of GCP — PCA in May 2018 and cleared the same. Google launched Associate Cloud Engineer (ACE) in mid-2018, and I cleared the same too. Google ACE certification validity was expiring in 2 years. But, as I had attempted a Beta exam which is double the hours and double the questions, my validity remained for 2.5 years with some memorable Google Cloud Certified Swags too for Beta exam takers. I still cherish those mugs, jackets, and laptop covers from Google! 😊
Good news to ACE effective 1st Oct 2022, its’ validity is extended to 3 years! Check out more on this from my other blog.
Sharing my experience of being Google certified ACE twice with a recertification experience too in Sept 2020 to be updated & keep my credentials extended for 4 yrs!
I believe in cherishing the journey more than the destination (testing time). Here are my experiences that can benefit you. 😊
Certification Details
· Certification Name: Google Certified Associate Cloud Engineer
· Format: Multiple Select & Multiple Choice [ NO negative marking! Don’t let any questions unanswered]
· Exam Duration: 120 minutes [ 2hours exam]
· Number of Questions: 50[ Approx. 2 mins/question + some review time for questions which you’ve marked for review]
· Passing Score: GCP Certifications, doesn’t give a score! Pass or Fail is the only message after you submit the exam. No score, No breakdown of performance by topic later also unlike other certification providers like AWS/Azure etc. Yes, Google is unique! 😊
· Registration Fee: $125 (plus tax where applicable)
Certification Topics
I’ve provided necessary “Must refer topics” & study links that can benefit w.r.t that section and subsection. This is my preparation study guide per the Google exam study guide to explore GCP better and related question! Not a standard one; feel free to explore more and switch between sections if you feel comfortable with that particular section.
Section 1: Setting up a cloud solution environment
1.1 Setting up cloud projects and accounts.
Ø Creating projects
Ø Assigning users to predefined IAM roles within a project
Ø Managing users in Cloud Identity (manually and automated)
Ø Enabling APIs within projects
Ø Provisioning and setting up products in Google Cloud’s operations suite
- Difference between ProjectID and Project number. Which is mutable at the time of creation? Project quotas etc. https://cloud.google.com/resource-manager/docs/cloud-platform-resource-hierarchy
- Understand when to use Primitive/ Basic, Predefined, and Custom roles. https://cloud.google.com/iam/docs/understanding-roles
- https://cloud.google.com/identity [ Know different tiers and manual and automated ways of managing users
- Google Operations suite metrics scope — Stackdriver [Formerly referred]
Questions will refer both ways to test your acquaintance with Console and documentation. This supports both GCP + AWS projects with a Project connector. These links can be helpful in understanding it better
1.2 Managing billing configuration.
Ø Creating one or more billing accounts
Ø Linking projects to a billing account
Ø Establishing billing budgets and alerts
Ø Setting up billing exports to estimate daily/monthly charges
- All details related to billing especially Budget alerts, billing permissions for billing administrator etc. https://cloud.google.com/billing/docs
- Recommended watch, all 20+ Beyond your bill YouTube series on GCP billing. This details everything required for questions around this topic [ 20+ videos as on Jan 2023]
- Know different billing export sinks [ Google Cloud storage, BigQuery and their use case] GCS is more for sharing and lifecycle management and BQ is for analysis.
1.3 Installing and configuring the command line interface (CLI), specifically the Cloud SDK (e.g., setting the default project).
- Commands around gcloud, bq, gsutil for general purpose usage of GCP resources.
- Know when to use gcloud and kubectl. Understand these differences carefully!
- Usage of bq dry run option. Explore other options around bq
- Usage of gsutil with signedurl, expiration date, delete options , copy , sync operations etc
Tips : For gcloud , focus more on : init, config, auth, container, compute, sql , app , iam etc.
https://cloud.google.com/sdk/gcloud/reference
Section 2: Planning and configuring a cloud solution
This module is all about choice decisions according to Google Recommended Practices. Majority is regarding Compute, Networking, Storage and DB services. I’ve done enough exploration & learning on this topic and sharing all resources that can help you choose right services not just in your project but also in exam too!
2.1 Planning and estimating GCP product use using the Pricing Calculator
Explore all major services estimation using Pricing calculator. Especially explore which services supports GPU usage, BigQuery with on demand pricing and Flat rate pricing. Know what a slot is! https://cloud.google.com/products/calculator
2.2 Planning and configuring compute resources.
Ø Selecting appropriate compute choices for a given workload (e.g., Compute Engine, Google Kubernetes Engine, App Engine, Cloud Run, Cloud Functions)
Ø Using preemptible VMs and custom machine types as appropriate
Explore and look at the key parameters! What is supported in a compute service and what is not compatible! These videos and help docs can help you master this!
· https://cloud.google.com/hosting-options
· Where should I run my stuff? Choosing to compute options
· Choosing the right to compute option in GCP: a decision tree
· Top 3 ways to run your containers on Google Cloud
· GCP Sketch notes — Where should I run my stuff?
· Preemptible machines/Spot VMsare a boon to cost-saving options. Understand its use case, notification time before instances get revoked, and what are the on-host maintenance type available when Preemptible instances are ON.
· Explore Custom Machine types limits. It is very important to answer scenario-based questions, especially when cited with boundary cases.
2.3 Planning and configuring data storage options.
Ø Product choice (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Bigtable)
Ø Choosing storage options (e.g., Standard, Nearline, Coldline, Archive)
All you need to know about services in storage and database is here!
Storage options with their use case
Databases options with their use cases
Storage classes on Google Cloud storage bucket. Know the minimum # of days, retrieval costs, etc., to set the Lifecycle policies
Choose the right DB, Storage option video
Data lifecycle — Solutions that gives a holistic view of all Storage and database products. Must read!!
2.4 Planning and configuring network resources.
Ø Differentiating load balancing options
Ø Identifying resource locations in a network for availability
Ø Configuring Cloud DNS
· First thing to know is Hybrid connectivity options: Use case and speed limit for all options and watchwords!
o Interconnect — up to 100GBps [ Partner and Dedicated limits too]
o VPC Peering[ To save network cost, cutting egress cost ] Remember, Peering isn’t transitive.
o VPN [ Secure tunnel upto 3Gbps]
https://cloud.google.com/load-balancing/images/choose-lb.svg
Section 3: Deploying and implementing a cloud solution
3.1 Deploying and implementing Compute Engine resources.
Ø Launching a compute instance using Cloud Console and Cloud SDK (gcloud) (e.g., assign disks, availability policy, SSH keys)
Ø Creating an autoscaled managed instance group using an instance template
Ø Generating/uploading a custom SSH key for instances
Ø Configuring a VM for Stackdriver monitoring and logging
Ø Assessing compute quotas and requesting increases
Ø Installing the Stackdriver Agent for monitoring and logging
· Understand different custom machine types, explore beyond standard configurations like Availability policy, networking, managing disks, snapshots with persistent disk volumes, SSH keys, the difference between managed and unmanaged instance groups etc. Be familiar with using gcloud commands too. https://cloud.google.com/compute
· Quotas are only hard limits. If there is a project need, a soft limit increase ticket can be raised with the Google Cloud support team.
· Importance of installing agents on VM — Monitoring & logging.
3.2 Deploying and implementing Google Kubernetes Engine resources.
· Deploying a Google Kubernetes Engine cluster
· Deploying a container application to Google Kubernetes Engine using pods
· Configuring Google Kubernetes Engine application monitoring and logging
Explore key features like Pod and Cluster autoscaling, Autopilot mode etc. https://cloud.google.com/kubernetes-engine
GKE monitoring and logging https://cloud.google.com/kubernetes-engine-monitoring
3.3 Deploying and implementing App Engine, Cloud Run, and Cloud Functions resources.
· Deploying an application, updating scaling configuration, versions, and traffic splitting
· Deploying an application that receives Google Cloud events (e.g., Cloud Pub/Sub events, Cloud Storage object change notification events)
Difference between Standard and flexible environments, programming languages they support, Application versioning, Traffic splitting, Traffic Migrating use case, pricing, etc. https://cloud.google.com/appengine
Understand Cloud run integrations and pricing, and it's getting billed to the nearest 100ms. This is one of the best serverless, fully managed platforms to deploy your highly scalable containerized applications.
Using OCN with GCS. https://cloud.google.com/storage/docs/reporting-changes
3.4 Deploying and implementing data solutions.
· Initializing data systems with products (e.g., Cloud SQL, Cloud Datastore, BigQuery, Cloud Spanner, Cloud Pub/Sub, Cloud Bigtable, Cloud Dataproc, Cloud Dataflow, Cloud Storage)
· Loading data (e.g., command line upload, API transfer, import/export, load data from Cloud Storage, streaming data to Cloud Pub/Sub)
Know-how of how to Initialize data-related products. More info on their overview here: Data lifecycle — Solutions.
3.5 Deploying and implementing networking resources.
· Creating a VPC with subnets (e.g., custom-mode VPC, shared VPC)
· Launching a Compute Engine instance with custom network configuration (e.g., internal-only IP address, Google private access, static external and private IP address, network tags)
· Creating ingress and egress firewall rules for a VPC (e.g., IP subnets, tags, service accounts)
· Creating a VPN between a Google VPC and an external network using Cloud VPN
· Creating a load balancer to distribute application network traffic to an application (e.g., Global HTTP(S) load balancer, Global SSL Proxy load balancer, Global TCP Proxy load balancer, regional network load balancer, regional internal load balancer)
Hands-on experience and connected labs to complete all these listed exam guide topics.
Difference between Custom mode VPC, Shared VPC, and VPC peering and its use cases.
Must watch the Video series of #NetworkingEndtoEnd
3.6 Deploying a solution using Cloud Marketplace.
· Browsing Cloud Marketplace catalog and viewing solution details
· Deploying a Cloud Marketplace solution
Understand how Marketplaces gives us SaaS on GCP. https://www.youtube.com/watch?v=H8rRUUxoxoM
Put your hands on it by creating some simple WordPress site/ anything using Marketplace. Earlier, this was called “Launcher” by GCP, JFYI! 😊
3.7 Deploying application infrastructure using Cloud Deployment Manager.
· Developing Deployment Manager templates
· Launching a Deployment Manager template
Marketplace connects to CDM behind the scenes! Create a template — DIY! https://www.youtube.com/watch?v=gEzlEg-XtsE
Explore various sample codes available on Github https://github.com/GoogleCloudPlatform/deploymentmanager-samples
Section 4: Ensuring the successful operation of a cloud solution
General guidelines to watch this series if you are a visual learner or even otherwise! Get cooking in the cloud! It covers the overall aspects of this section in an exciting way. If possible, try out these demos as well.
4.1 Managing Compute Engine resources.
· Managing a single VM instance (e.g., start, stop, edit the configuration, or delete an instance)
· SSH/RDP to the instance
· Attaching a GPU to a new instance and installing CUDA libraries
· Viewing current running VM inventory (instance IDs, details)
· Working with snapshots (e.g., create a snapshot from a VM, view snapshots, delete a snapshot)
· Working with images (e.g., create an image from a VM or a snapshot, view images, delete an image)
· Working with instance groups (e.g., set autoscaling parameters, assign instance template, create an instance template, remove instance group)
· Working with management interfaces (e.g., Cloud Console, Cloud Shell, GCloud SDK)
Hands-on, Hands-on, Hands-on!
I have covered the usage of these topics in my earlier links. Explore cloud to describe commands for VM inventory and the options.
4.2 Managing Google Kubernetes Engine resources.
Understand pod, node, cluster, service, and deployment in a better way with K8s 101!
· Viewing current running cluster inventory (nodes, pods, services)
· Browsing the container image repository and viewing container image details
· Working with node pools (e.g., add, edit, or remove a node pool)
· Working with pods (e.g., add, edit, or remove pods)
· Working with services (e.g., add, edit, or remove a service)
· Working with stateful applications (e.g., persistent volumes, stateful sets)
· Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)
Must watch — K8s essentials from GCP and GKE
4.3 Managing App Engine and Cloud Run resources.
· Adjusting application traffic splitting parameters
· Setting scaling parameters for autoscaling instances
· Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)
Explore scaling in the App engine. — An overview blog might help understand app engine scaling
4.4 Managing storage and database solutions.
· Moving objects between Cloud Storage buckets
· Converting Cloud Storage buckets between storage classes
· Setting object life cycle management policies for Cloud Storage buckets
· Executing queries to retrieve data from data instances (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Datastore, Cloud Bigtable)
· Estimating costs of a BigQuery query
· Backing up and restoring data instances (e.g., Cloud SQL, Cloud Datastore)
· Reviewing job status in Cloud Dataproc, Cloud Dataflow, or BigQuery
· Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)
Understand slots and when to use them in Bigquery? Ondemand v/s flat rate use cases. Estimating using the Dry run option of BQ.
Minimum days for object movement in storage classes. CLI /SDK way of executing commands.
4.5 Managing networking resources.
· Adding a subnet to an existing VPC
· Expanding a subnet to have more IP addresses
· Reserving static external or internal IP addresses
· Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)
When do we create a Secondary IP address and Expand subnet? Importance of Static IP v/s External IP v/s Internal IP
4.6 Monitoring and logging.
· Creating Stackdriver alerts based on resource metrics
· Creating Stackdriver custom metrics
· Configuring log sinks to export logs to external systems (e.g., on-premises or BigQuery)
· Viewing and filtering logs in Stackdriver
· Viewing specific log message details in Stackdriver
· Using cloud diagnostics to research an application issue (e.g., viewing Cloud Trace data, using Cloud Debug to view an application point-in-time)
· Viewing Google Cloud Platform status
· Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)
Everything about monitoring and Logging you need to know: You must watch series: StackDoctor and do try out these demos!
Some old naming videos were referred to as “Stackdriver” but connected to “Operations”.
Section 5: Configuring access and security
One of the heavily tested modules w.r.t Roles, IAM security, Service accounts, cross-account access, Principle of least privilege, Google Recommended Practices.
5.1 Managing identity and access management (IAM).
· Viewing IAM role assignments
· Assigning IAM roles to accounts or Google Groups
· Defining custom IAM roles
· Understand when to use Primitive/ Basic, Predefined and Custom roles. https://cloud.google.com/iam/docs/understanding-roles
https://cloud.google.com/iam/docs/understanding-custom-roles
5.2 Managing service accounts.
· Managing service accounts with limited privileges
· Assigning a service account to VM instances
· Granting access to a service account in another project
· Understand the need for Service account, especially when working with multiple projects and granting access like BigQuery, Billing, Compute engine service accounts etc.
· Know difference between jobuser and data viewer roles of Bigquery
https://cloud.google.com/bigquery/docs/access-control
https://cloud.google.com/iam/docs/understanding-service-accounts
5.3 Viewing audit logs for the project and managed services.
Sharing audit logs via GCS or BQ https://cloud.google.com/logging/docs/audit
Official Learning — Hands-on avenues
Google provided official learning course via Qwiklabs, study guide, and Coursera, and practiced exams too.
- Official Exam Guide: Google provides an official exam guide for the ACE exam. This is the same exam guide deconstruct I provided above
Associate Cloud Engineer Certification | Certifications | Google Cloud
2. Qwiklabs [ Enabled free courses for Partners via Alliance courses] — www.qwiklabs.com
Qwiklabs provides hands-on experience for topics related to the ACE exam. Some of the must-do quests
3. Coursera provides a full learning path, ‘Cloud Engineering with Google Cloud Professional Certificate’, for preparing for the ACE exam. www.coursera.org
Cloud Engineering with Google Cloud
This learning path consists of 6 courses which will give you all details about GCP services & the last course will provide details about ACE Certification.
4. Official Study Guide
Dan Sullivan’s Official Google Cloud Certified Associate Cloud Engineer Study Guide covers all the topics in the exam guide. It's available on Amazon for purchase and also on Udemy as a course.
Official Google Cloud Certified Associate Cloud Engineer Study Guide
5. Official GCP Practice Exam
Google provides a practice exam with around 20 questions which will familiarize you with the types of questions you may encounter on the certification exam and help you determine your readiness or if you need more preparation and experience. These are retired questions from QB.
Tip: You can skip the candidate ID and enter your details if you are taking GCP exams for the first time.
Associate Cloud Engineer Sample Exam Questions | Certifications
6. Other Learning/Practice Options — There are various Practice exams available on ACloudGuru, Udemy, Whizlabs, ExamTopics, etc which can be explored at your own risk as I’m not sure about pattern and answer validation on these sites.
Booking/scheduling your exam
Check out my blog on end to end process of Google Cloud exam booking to sharing results.
Congrats!
Glad that my blog kept you hooked till now! These tips will help you clear your exam in the first go! Do leave a comment on how this blog helped you learn GCP and clear your certifications.
All the best for the Google Cloud Associate Cloud Engineer Certification exam. I wouldn’t mind if you want to connect with me at Ramesh Rajini, and you can hit the clap button as often as you want!😄
Check out my other Google Cloud-related blogs here:
1. How to become Cloud Digital Leader?
2. GCP PCA All in one guide and GCP PCA Exam guide mapping
3. GCP Professional Cloud Developer- Exam guide mapping
See you Safe until next time!
