Google Associate Cloud Engineer

My Google ACE Certificate Link

My Google ACE Badge Link

 

The below courses are part of Coursera Specialization - Architecting with Google Compute Engine Specialization

 

Coursera Course	My Completion Certificate
Google Cloud Platform Fundamentals: Core Infrastructure	Coursera Completion – GCP Core Infrastructure
Essential Google Cloud Infrastructure: Foundation	Coursera Completion – GCP Foundation
Essential Google Cloud Infrastructure: Core Services	Course Completion – Core Services
Elastic Google Cloud Infrastructure: Scaling and Automation	Course Completion – Scaling & Automation
Reliable Google Cloud Infrastructure: Design and Process	Coursera Completion – Design & Process
Preparing for the Google Associate Cloud Engineer Exam	Preparing for the Google ACE

 

I will request you to take a look at a recent blog by Mohamed Ismail’s blog here – How did I pass my Google ACE!!

I want to mention one thing right away that I feel there is no course available in the market that can really prepare you for the exam. I would compare GCP ACE exam with the same difficulty level of AWS SysOps Administrator exam only with a lot of complete Kubernetes Scenario.

Apart from the intense amounts of the links that follow, I used the following sometimes on a daily basis to check and recheck if Google’s documentation was accurate ???? (IKR…)

• ·         A GCP Flowchart a day Or Grumpy Grace’s GCP Flowcharts
• ·         Sathish VJ’s GCP documentation on Github  – Awesome GCP Services & Youtube Channel
• ·          YouTube GCP playlist
• ·         Compare AWS Services with GCP
• ·         Gsutil and gcloud command guide and usage across projects

 

Here are some helpful official links for Google ACE:

·         Associate Cloud Engineer certification main information page

·         Associate Cloud Engineer practice exam

·         Google Cloud main documentation page

 

Associate Cloud Engineer certification exam guide

I have reproduced this section from cloud engineer documentation guide. The main thing is to practice each section as much as possible and ensure that you ask following questions and either document the answer or if you are not sure please ask the certification community or add a question in the comments section below:

• 1.       While provisioning any resource can you share the resource across projects, if yes, how will you do it (creating default custom role/service count) versus an IAM policy?
• 2.       Is this resource global/regional or zonal and again can you share the resource type based on what kind it is across projects/organizations etc.
• 3.       As always, remember there are small hints in the question itself so always use the process of elimination if you do not know the answer at all.
• 4.       PRACTICE, PRACTICE, PRACTICE 

GCP Cloud Engineer Guide
1. Setting up a cloud solution environment

1.1 Setting up cloud projects and accounts. Activities include:

·         Creating projects

·         Assigning users to predefined IAM roles within a project

·         Managing users in Cloud Identity (manually and automated)

·         Enabling APIs within projects and sharing provisioned services across projects.

·         Provisioning one or more Stackdriver workspaces

How would you configure a single workspace for VM’s running in multiple projects/across projects?

1.2 Managing billing configuration. Activities include:

·         Creating one or more billing accounts

Managing resources in a project across multiple departments in an organization

Managing billing in an organization across multiple departments using projects.

·         Linking projects to a billing account

Understand creating multiple billing accounts in an organization or se

·         Establishing billing budgets and alerts

·         Setting up billing exports to estimate daily/monthly charges

Analyzing billing data by creating billing sink to BigQuery.

1.3 Installing and configuring the command line interface (CLI), specifically the Cloud SDK (e.g., setting the default project).

 

2. Planning and configuring a cloud solution

2.1 Planning and estimating GCP product use using the Pricing Calculator

2.2 Planning and configuring compute resources. Considerations include:

• Selecting appropriate compute choices for a given workload (e.g., Compute Engine, Google Kubernetes Engine, App Engine, Cloud Run, Cloud Functions)
• Using preemptible VMs and custom machine types as appropriate

2.3 Planning and configuring data storage options. Considerations include:

• Product choice (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Bigtable)
• Choosing storage options (e.g., Standard, Nearline, Coldline, Archive)

2.4 Planning and configuring network resources. Tasks include:

• Differentiating load balancing options
• Identifying resource locations in a network for availability
• Configuring Cloud DNS

 

3. Deploying and implementing a cloud solution

3.1 Deploying and implementing Compute Engine resources. Tasks include:

• Launching a compute instance using Cloud Console and Cloud SDK (gcloud) (e.g., assign disks, availability policy, SSH keys)
• Creating an autoscaled managed instance group using an instance template
• Generating/uploading a custom SSH key for instances
• Configuring a VM for Stackdriver monitoring and logging
• Assessing compute quotas and requesting increases
• Installing the Stackdriver Agent for monitoring and logging

3.2 Deploying and implementing Google Kubernetes Engine resources. Tasks include:

• Deploying a Google Kubernetes Engine cluster
• Deploying a container application to Google Kubernetes Engine using pods
• Configuring Google Kubernetes Engine application monitoring and logging

3.3 Deploying and implementing App Engine, Cloud Run, and Cloud Functions resources. Tasks include, where applicable:

• 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)

3.4 Deploying and implementing data solutions. Tasks include:

• 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)

3.5 Deploying and implementing networking resources. Tasks include:

• 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)

3.6 Deploying a solution using Cloud Marketplace. Tasks include:

• Browsing Cloud Marketplace catalog and viewing solution details
• Deploying a Cloud Marketplace solution

3.7 Deploying application infrastructure using Cloud Deployment Manager. Tasks include:

• Developing Deployment Manager templates
• Launching a Deployment Manager template

 

4. Ensuring successful operation of a cloud solution

4.1 Managing Compute Engine resources. Tasks include:

• Managing a single VM instance (e.g., start, stop, edit 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)

4.2 Managing Google Kubernetes Engine resources. Tasks include:

• 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)

4.3 Managing App Engine and Cloud Run resources. Tasks include:

• Adjusting application traffic splitting parameters
• Setting scaling parameters for autoscaling instances
• Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)

4.4 Managing storage and database solutions. Tasks include:

• 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)

4.5 Managing networking resources. Tasks include:

• 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)

4.6 Monitoring and logging. Tasks include:

• 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)

 

5. Configuring access and security

5.1 Managing identity and access management (IAM). Tasks include:

• Viewing IAM role assignments
• Assigning IAM roles to accounts or Google Groups
• Defining custom IAM roles

5.2 Managing service accounts. Tasks include:

• Managing service accounts with limited privileges
• Assigning a service account to VM instances
• Granting access to a service account in another project

5.3 Viewing audit logs for project and managed services.

 

You will find a lot of links across a lot of helpful site and it is very easy to get lost in them. However,

·         Google Cloud Platform Overview:  https://cloud.google.com/docs/overview/

·         Google Cloud Identity:  https://cloud.google.com/identity/

·         Google Cloud Pricing Calculator:  https://cloud.google.com/products/calculator/

·         Google Cloud Billing documentation: https://cloud.google.com/billing/docs/

·         Cloud SDK installation and quick start   https://cloud.google.com/sdk/#Quick_Start

·         gcloud tool guide   https://cloud.google.com/sdk/gcloud/

·         Google Cloud Pricing Overview:  https://cloud.google.com/pricing/

·         Google Cloud Pricing Calculator:  https://cloud.google.com/products/calculator/

·         Google’s Pricing philosophy: https://cloud.google.com/pricing/philosophy/

·         Compute Engine Documentation:  https://cloud.google.com/compute/docs/

·         Choosing the right compute option in GCP:  https://cloud.google.com/blog/products/gcp/choosing-the-right-compute-option-in-gcp-a-decision-tree

·         Choosing a compute option: https://cloud.google.com/docs/choosing-a-compute-option

·         Storage Classes:  https://cloud.google.com/storage/docs/storage-classes

·         Cloud Storage Options:  https://cloud.google.com/storage-options/

·         Load Balancing:  https://cloud.google.com/load-balancing/docs/load-balancing-overview

·         Compute Engine:  https://cloud.google.com/compute/docs/

·         Cloud Source Repositories   https://cloud.google.com/source-repositories/docs/

·         Deployment Manager   https://cloud.google.com/deployment-manager/docs/

·         Instance Groups:  https://cloud.google.com/compute/docs/instance-groups/

·         Autoscaling:  https://cloud.google.com/compute/docs/autoscaler/

·         Instance Templates:  https://cloud.google.com/compute/docs/instance-templates/

·         Create VMs from instance template:  https://cloud.google.com/compute/docs/instances/create-vm-from-instance-template

·         Creating groups of managed instances with templates:  https://cloud.google.com/compute/docs/instance-groups/creating-groups-of-managed-instances

·         Using VPC networks:  https://cloud.google.com/vpc/docs/using-vpc

·         Deployment manager fundamentals:  https://cloud.google.com/deployment-manager/docs/fundamentals

·         VM Images:  https://cloud.google.com/compute/docs/images

·         Creating, deleting, deprecating custom images:  https://cloud.google.com/compute/docs/images/create-delete-deprecate-private-images

·         Creating snapshots:  https://cloud.google.com/compute/docs/disks/create-snapshots

·         How App Engine instances are managed:  https://cloud.google.com/appengine/docs/standard/python/how-instances-are-managed

·         Object lifecycle management:  https://cloud.google.com/storage/docs/lifecycle

·         Expanding subnets:  https://cloud.google.com/vpc/docs/using-vpc#expand-subnet

·         Introduction to Alerting:  https://cloud.google.com/monitoring/alerts/

·         Managing alerting policies:  https://cloud.google.com/monitoring/alerts/using-alerting-ui

·         Google Cloud IAM:  https://cloud.google.com/iam/docs/

·         Cloud IAM Overview:  https://cloud.google.com/iam/docs/overview

·         Understanding IAM roles:  https://cloud.google.com/iam/docs/understanding-roles

·         Understanding Custom IAM roles:  https://cloud.google.com/iam/docs/understanding-custom-roles

·         Granting or changing access in IAM:  https://cloud.google.com/iam/docs/granting-changing-revoking-access

·         Understanding Service Accounts:  https://cloud.google.com/iam/docs/understanding-service-accounts

·         Service Accounts:  https://cloud.google.com/iam/docs/service-accounts

·         Cloud Audit Logging overview: https://cloud.google.com/logging/docs/audit/

Services that product Audit Logs:  https://cloud.google.com/logging/docs/audit/#services

...

Hi All, 

Today i just went for the exam and i passed it. The exam wasn't easy at all based on the experience i had in taking many exams before in my life. There is no way to tell how much you scored and i was only given a provisional status of pass. After doing some researches just now right after my exam, the Google FAQ actually mentioned that Google is using certain way to evaluate the responses of the questions and use some "algorithms" to produce result instead of based on the numerical scores came straight from only 1 answer. so i believe the boarder line between pass or fail is based on a par based on analysis of the answers which i strongly believe every answer you responded comes with a certain entity/value/point contributing to the algorithms that make up the final status of your exam. to be honest, during the exam, there were rare answers that i chose made me feel 100% confident that it is the best answer. in fact i was even quite assured that the status of the exam stands high chance that it is a "fail" but turned up to be "Pass" that led me relate the study of how Google produce result. 

As for the preparation from my side, i found none of the things i did as mentioned really help to directly help me pass my exam. it is a combination and i during exam and looking at the questions i felt that i should have done more. so my advice is really practice more and if possible cover more on google documentation as the questions are way beyond that pluralsight, qwiklabs*(despite i did more than 100 labs), ACE Exam Guide... these are really supplementary materials for you to build solid foundation. there are a lot more from things came out from google documentation. 

my next plan is PCA.

Good luck all

...

This particular exam is nominated as entry level but the basics are also important as they are not covered by the professional exams. These are more high level and this is like a hands-on training. So keep that in mind.

As always with Google training I started with Coursera that has 5 courses with qwiklabs. That means that besides the videos you need to do exercises in a real GCP environment and often they are graded. So the progress you make in those labs is measured and only if everything is done correctly the score is maximum. After main modules you get some quiz answers that you are supposed to know from the material that was covered before. To succeed you need 2/3 right at least. After every course you get a congrats mail with a link to a certificate. It is nice but only the real certificate when you pass the exam has some value i.m.h.o.

After that I took the Pluralsight course for preparing the ACE exam. It is not so specific as Coursera and takes less time but every subject is touched so it helps you to find out if you remembered everything from Coursera. Keep in mind, as said, that almost every basic GCP component is addressed.  If you are studying for data engineer the focus will be on ML and AI as well as all the different data and storage options. You don't get questions about how you manage an app engine e.g.

Google practice exam

This practice exam from Google itself will give you some insight of the kind of questions you can expect. Not the content but the way questions are put. Be prepared for questions with the words: the best, the most efficient, NOT, etc.

Because often you can mark 2 answers as not valid (if you studied ;-)  otherwise everything could make sense) there are 2 more to choose from. Sometimes you need to fill in more than 1 option and those are the trickiest ones as you could have 2 out of the 3 answers right. I don't know how Google handles those questions/answers. But most of them are single answers and you need to read them carefully. Sometimes one word can make the difference. And sometimes they both seem right but then you take into accout the words in the question such as "the best".

Everytime I needed some more explanation on subjects I used google for Wikipedia or any other source to help out. Also for translations because I am not a native English speaker so this is always a problem with the exams. If you don't know the meaning of a word or more (in the questions or answers) you have a problem. You then need to decide if the context is enough to get the right answer., More time is not a solution; a dictionary is but it is not allowed.

The last thing I did was Linux Academy. The have this course also and in my opinion it is even better because they are more focussed on the exam. You watch the videos and at the end you have a full practice exam. It's great although don't think that you will get the same questions.

Because I plan my exams beforehand there is also some time pressure for me to study; it works for me. Maybe other people want to be ready and confident before planning it. That's personal.

On the day itself I make sure that I had a good night rest and have eaten before I start. You will get 2 hours and that's enough. If you think the question is too dificult or time consuming skip it for the time being and mark it so you can go back at the end. Otherwise you will be nervous when the time counter is ticking away and you still have a lot of questions to answer. If you need more than 2 minutes for the questions go to the next one and I am sure that a lot of them can be answered within 30 seconds. Then at the end you have more time  to read the marked questions again carefully.

I can not give away questions with answers but be prepared that, although you do all of it above, there are questions about things you probably never heard of. Sometimes they are test questions that don't count anyway but you don't know that. Even if you don't know those answers I am confident that your score can be high enought to pass. But to be ready for those questions you should have some background knowledge of the counterparts from the GCP resources. So what is used on prem (VM's, Storage, Network, Databases) is often compared with what GCP has to offer and especially for migration purposes.

Hopes this helps a bit; I know that a lot of this information is somewhere available on the internet but now you get it directly from me :-)

I wish you all a lot of success with the exam

...

Hey there!

Looking to get into Cloud, or Specifically into the Google's Cloud Product. Well I can give you some info, Let's get on to it.

Well, I have been an Oracle DBA with getting some tasks on the AWS Platform here and there. Then there, came a day in my Organization which was giving out an opportunity to get certified in Google Cloud. I took it, let me tell you it wasn't easy at all, and again it wasn't an Mountain you couldn't climb.

With little to no knowledge about the Google Cloud, I went into it. There are some resources like Linuxacademy, Acloudguru, Coursera courses which will help you into getting certified. I would recommend just don't dive into the certification race just for the sake of it. Develop a interest in it, go through the Hands-On labs on Qwiklabs, LinuxAcademy, it will help you. Create a free Google Cloud account, create your own architecture, make changes, do daily activities on the platform, it will surely help you a lot. 

In short, Hands-On is very very important, I don't know how much I should stress on it, it will let you get insights into the services which the courses would not tell you. 

My preparation required me 3 odd months. I started out by creating a free account, signing up on the Qwiklabs platform, & the Linuxacademy course. I would learn about a platform for 1 day, then would do the hands-on the next day. 1-2 weeks for each service to get the perfect understanding. 

Then soon came the week for the examination. I didn't still knew if I was ready, there is that self doubt I guess which led me to ask me everytime, Do I need to do more? Is anything left?. Well you certainly won't get any dumps for Google Cloud Associate Engineer exam or any other Google exam. So, how do you know if you are ready?

Practice Exams!! You can get Practice Exams on LinuxAcademy which I used personally a lot. There are some on Whizlabs, those are good, but comparatively LinuxAcademy's was the best.

I gave practice exams everyday till I got an consistent 95+% in the exams, there isnt an number or a passing percentage mentioned by Google for the exam, hence I set the bar a little higher!

Final tip: Relax on the night before the exam, it helps. 

The exam would be an awesome experience, After all the above stuff, I would place a bet that you would definitely pass, it. If you did the hard work, without any complains. 

 

ALL THE BEST!!

...

It took me 2 months to prepare for the exam, I used 3 study materials and I have explained them below how to use them:

1. coursera specialization course on Google cloud associate, the course is of 5 weeks it contains theory and labs as well so do it all.

2. After you complete the course solve questions on linux academy Google exam preparation course, they test your preparation.

3. The Official Google Cloud Certified Associate Cloud Engineer Study Guide Book by Dan Sullivan is very helpful it covers everything that is needed for the exam, read the book thoroughly and solve it's questions also.

Most importantly the more you have spent time on cloud console the better prepared you are.

 

 

...

This exam will assess your ability to:

1. Set up a cloud solution environment
2. Plan and configure a cloud solution
3. Deploy and implement a cloud solution
4. Ensure the successful operation of a cloud solution
5. Configure access and security

90%+ questions were scenario-based and good questions of infrastructure and good IAM questions, a small portion of networking and rest, we have to choose Google Recommended Practice or Best Practice or cost-effective solution or flexible solution.

Without hands-on and industry exposure, the paper will be little tricky and confusion for you as in some questions 2 or 3 answers was also correct but we have to choose the smallest steps to take to achieve this or cost-effective or best answer or proper method solution.

As I'm DevOps Engineer so these part were easy for me because that's I do daily 5 days in a week, so I suggest to get some hands-on experience to tackle those questions.

For learning and preparation: 

Architecting with Google Compute Engine Specialization

Linux Academy Google Associate Cloud Engineer

Udemy Google Cloud Certified Associate Cloud Engineer Practice Exams

...

I recently cleared Google Cloud Associate Cloud Engineer certification. I felt the complexity was medium. Most of all the peripheral components were covered in the exam. Almost every question was scenario-based, which tests the realtime decision making based on given circumstances (They expect us to make the best decision out of multiple choices.) I have over one year of experience in GCP which helped me a lot in the examination. I think it's a good starter for the one who wants to pursue further certifications. If you are the one... Best of luck....