Learning something new is always great. Initially this certification was not my goal. I was learning GCP to know different services it provides specially for hosting and Image processing for my project written in Angular and Java. Later I came to know about the certification and then though to get the Certification done.
I am writing this post to share my journey of getting certified in Google Cloud Architect and material that I found helpful. I hope this post will be useful for me later or others who are interested in this certification.
Exam Details
Exam Guide: Official exam guide link is here https://cloud.google.com/certification/guides/professional-cloud-architect/
Exam consists of 50 multiple choice questions.
Total Duration is 120 Minutes
Exam registration can be scheduled via WebAssessor
I got the exam result after 2 days via email.
Learning GCP In General
Since I was totally new to GCP I found the following courses from coursera very useful. The first course is good specially if new to GCP. The second course is about Networking in details with many hands-on labs.
Coursera GCP Architecture
https://www.coursera.org/specializations/gcp-architecture
Coursera Networking Google Cloud Platform
https://www.coursera.org/specializations/networking-google-cloud-platform
I also signed up for Google Cloud platform and took advantage of the 300 Usd credit to try and learn different products.
Preparation For the Exam
GCP is vast and it is getting more and more product and services.
Exam covers a lot of product and offerings from GCP but not all. Some of them goes deeper which needs good understanding of the product and when/how to use it. There are also questions which touches at surface level, for them having a over all idea is good to choose correct answer.
Understanding in Depth
Case Studies : Know the official case studies and prepare a solution. A lot of questions are asked from the case studies. Going though them before the exam would be helpful.
IAM and Billing : Good understanding of IAM, ACL etc, best practices etc, BigQuery IAM.
Cloud Storage : In-depth knowledge about Cloud storage, storage classes, Lifecycle management, How to delete/change storage class.
Compute Engine : Details about compute engine, Snapshots/Images and how to create vm from them. Preemptible VMs, Shielded VM’s. Now we also have Cloud GPU.
App Engine: Standard vs Flexible.
GKE and Kubernetes : Difference between GKE, Kubernetes, Creating cluster, common K8 commands. Nodes, Pods vs Containers etc. Minimum number of nodes/vms.
Encryption/Security with GCP : Knowledge of CMEK, CSEK, Encryption for Cloud Storage/Bucket etc.
Multi cloud connectivity : Peering, Direct Connect, VPN etc. Usecases when to choose one. Like VPN provides encryption, but for speed Cloud inter connect is better. Also what is the SLA?
VPC : Networking knowledge in depth, GCP provide a number of options/solutions for network design, Shared VPC etc.
Load Balancing
Different kind of LB’s available in GCP
Bigtable : It is proprietary NOSQL database, understanding when to use it and best practices.
BigQuery : When to use BigQuery, best practices, Indexes etc.
Cloud SQL : It is managed Relational Databases, understanding different offerings, configuring replica. Different products available as part of Cloud SQL.
Stack Driver
https://cloud.google.com/stackdriver/
Cloud Datastore : In-depth knowledge about Cloud datastore. How to create index. Google recently added two different mode Datastore mode and native mode.
Disaster Recovery : Design principal for disaster recovery in GCP, different kinds of replicas.
Cloud Pub/Sub: Understanding how and when to best use pubsub.
https://cloud.google.com/functions/docs/tutorials/pubsub
Deployment Manger
For the exam deployment manager is an important topic, understanding what it does and how to configure it would be good. Like Templating, CLI commands.
Different kinds of Deployments
General concepts like Canary deployment, Rolling deployment, Blue/Green Deployment, A/B Testing would be good to know.
Other topics that needs to be familiar with
Transfer Appliance and Data Rehydration
https://cloud.google.com/transfer-appliance/
Datalab
https://cloud.google.com/datalab/
Dataproc: It is GCP Managed Apache Spark and Apache Hadoop
https://cloud.google.com/dataproc/
Cloud DataFlow : It is based on Apace Beam SDK
Cloud Composer : It is based on Apace Air Flow
Cloud Armour
https://cloud.google.com/armor/
Data Loss Prevention API . How to classify and mask sensitive data.
https://cloud.google.com/dlp/
Compliance : Design for compliance PCI, HIPPA etc
Cloud Functions : Understanding of how cloud functions works.
https://cloud.google.com/functions/features/
Jenkins
https://jenkins.io/
Spinnaker
spinnaker.io
Cloud Build
https://cloud.google.com/cloud-build/
Cloud Run
https://cloud.google.com/run/
Cloud identity aware proxy
https://cloud.google.com/iap/
Cloud sql proxy
https://cloud.google.com/sql/docs/mysql/sql-proxy
Marketplace
It is like App Store for GCP. Look into marketplace in GCP Console
https://cloud.google.com/marketplace/
Cloud Directory Sync
We can sync with LDAP, reading about this service on GCP would be good enough.
Tools and Skd
Understanding and uses of bq, Cloud Shell, Gsutil, kubectl, gcloud etc.
Links to some materials for the exam
Best practices for IAM
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations
A GCP flowchart a day : Good to review how to choose right services
https://medium.com/google-cloud/a-gcp-flowchart-a-day-2d57cc109401
Sample Solution : Following is a sample solution on GCP site, they provide various other architectural solutions which are good to validate the concepts
https://cloud.google.com/solutions/migrating-a-two-tier-web-app-to-gcp
Sample Case studies
Coursera also host a certification preparation course. I did not get much time to complete the full course. But going though the sample case studies would be a good addition to validate own solution.
https://www.coursera.org/learn/preparing-cloud-professional-cloud-architect-exam
Summary
Areas like Compute Engine, Networking, Billing, AIM, Databases, Tools for Analytics etc. are very important. For them we need good understanding of the different options available while architecting a good solution or choosing the appropriate answer in the exam. Apart from that having a good knowledge of the other product/services will be helpful to answer properly.
I took notes so that before the exam i can go over them which is otherwise easy to forget.
Like which products are regional/zonal
Choosing network design for speed requirements.
Different database for capacity, transaction etc.
Network capacities.
Compute engine options.
Cloud Datastore options.
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