Notes from my beta Google Cloud Professional Cloud Developer Exam

6 min readJan 8, 2019

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Update on Jan 24th, 2019: The Professional Cloud Developer exam is now out of beta. Also, I passed the exam!

Immediately after the exam I do a memory dump as notes. Hence it is also quite unordered. This is a sanitized list that gives general topics and questions I encountered. The intention is not to give you the questions, but to give you topics that you can be prepared for. I was often stumped by some questions; hopefully you can be more prepared based on my experience. Wish you the very best!

I didn’t really prepare for this exam. There was no material to prepare with either (at the time that I wrote the exam). But I hoped my preparation for the other three certifications would carry me through on this one. The results are out only in a few months and I cannot be certain I passed yet. Btw, because it was a beta exam, there were 102 questions for me and 4 hours to do it in. In the notes below I’ve mentioned topics from the exam outline.

Identity aware proxy. What is the use-case for this? How do you set it up in the network? Where do users connect from?
https://cloud.google.com/iap/
Endpoints. What are the services you can use Endpoints with? How do you do authentication/authorization with it?
https://cloud.google.com/endpoints/docs/choose-endpoints-option
Stackdriver. Tracer vs profiler, what additional things you get when you install the monitoring agent, what API permissions do you need after you install it, how do you get data from GKE or GCE into stackdriver logs, Transparent SLIs, etc.
https://cloud.google.com/stackdriver/
IAM. Google Groups, Service Accounts, BigQuery job permissions. Basically, learn everything about IAM permissions for each product/service. Remember you don’t need to by-heart all the roles, but get key concepts and nomenclature that you can reapply to many situations.
BigTable keys. Best practices for key schema and how to avoid hotspotting.
https://cloud.google.com/bigtable/docs/schema-design
Big Query. Batching. Advantages of using batches instead of single queries.
https://cloud.google.com/bigquery/batch
Datastore. Working with batches. Ways to optimize insertion and queries. Ways to avoid hotspotting. Working with transactions. Is ACID possible with Datastore?
https://cloud.google.com/datastore/docs/best-practices
AppEngine. Using memcache with AppEngine.
https://cloud.google.com/appengine/docs/standard/python/memcache/
Memcache. How do you work with memcache and flush it?
https://cloud.google.com/appengine/docs/standard/python/memcache/using
Cloud SQL Proxy. When is it used and how? How to connect from various environments.
https://cloud.google.com/sql/docs/mysql/sql-proxy
GKE. Scaling deployments.
https://kubernetes.io/docs/concepts/workloads/controllers/deployment/
Managed Instance Groups. Scaling and updating deployments.
https://cloud.google.com/compute/docs/instance-groups/updating-managed-instance-groups
Deployment Manager. Learn how to write templates, how to use references, environment variables, etc.
https://cloud.google.com/deployment-manager/docs/how-to
GKE . Learn how to check the health of VMs, pods, and services.
https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-readiness-probes/
Stackdriver. Learn how to check the health of resources.
https://cloud.google.com/monitoring/uptime-checks/
BigQuery. Learn how to work with arrays and structs. How do you join them?
https://cloud.google.com/bigquery/docs/reference/standard-sql/arrays
BigQuery + IAM. How do you provide/restrict access? Remember that you cannot restrict access at table level. It is only at dataset level. Also look up what Authorized Views are.
https://cloud.google.com/bigquery/docs/access-control
GDPR. Know what GDPR, HIPAA, COPPA, etc. is at a fairly high level.
Resource Manager. Look up how you can work with Resource Manager programmatically.
https://cloud.google.com/resource-manager/
Data Loss Prevention API. Learn what this is used for.
https://cloud.google.com/dlp/
Integrating with GSuite/GDrive/etc. How do you write an app that has permissions on GSuite products?
GKE+gcloud+kubectl. How do you diagnose pods and containers? Know the limits of gcloud when it comes to GKE, and what all kubectl does. I would suggest you take an entire course in kubernetes.
gsutil. Know all the different commands when using gsutil. Know recommended practices when using it.
https://cloud.google.com/storage/docs/gsutil/commands/acl
Cloud Armor vs Cloud Security Scanner. What are their use cases? How do you use them and for what kind of protection?
Cloud Identity Proxy. (Edit: I would assume this has become more important than it used to be when I wrote the exam.)
Java was the language of code examples. Most code was for AppEngine and one for Cloud Functions in JavaScript. (Since I wrote the exam, Go and Python have been added as options for Cloud Functions.) Java, being verbose (ugh), sometimes took a long time for me to read and understand the code. Don’t focus too much on learning all the languages — you should be able to fairly interpret code from any language.
Deployment Manager.
DNS, not Cloud DNS, but DNS in general in connection with some GCP resources.
As I’ve mentioned in all other notes also, as a Professional Developer you are expected to know just GCP but also tools, technologies, and processes from all software development.
BigQuery. Did you know BigQuery also has DML statements? Which ones? How and when should they be used?
https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language
Managed Instance Groups. Scaling MIGs based on various parameters.
https://cloud.google.com/compute/docs/autoscaler/scaling-cpu-load-balancing
Cloud Storage. Standard storage, nearline, coldline, signed urls, using SSD. What use-cases are they relevant for and setting policies.
https://cloud.google.com/storage/docs/storage-classes
Cloud Storage. Bucket limitations and quotas. How can you optimize for heavy load?
https://cloud.google.com/storage/docs/best-practices
Cloud Storage. Apart from the above, what are the best options to transfer various amounts of data.
https://cloud.google.com/storage/quotas
Cloud Composer. (Edit: this solution was still in early stages when I wrote the exam, but this would have become more important now). This is the GCP managed solution for Apache Airflow.
https://cloud.google.com/composer/
Case studies: Know the case studies properly and work through the solutions, but don’t by-heart them.
https://cloud.google.com/certification/guides/cloud-developer/casestudy-hiplocal
Cloud Spanner. Under what circumstances and for what use cases is Cloud Spanner a good fit?
Cloud SQL. Know that this is regional.
https://cloud.google.com/sql/docs/mysql/locations
Cloud CDN. Learn about caching, deleting cache, setting it up.
https://cloud.google.com/cdn/docs/
NAT. Brush up your general networking.
Cloud Build. Relation to Container Registry. Setting up continuous builds.
https://cloud.google.com/cloud-build/
PubSub.What are the use cases and preferred architecture for and when using PubSub. Know your PubSub fundamentals.
https://cloud.google.com/pubsub/docs/overview
Cloud Tasks.
https://cloud.google.com/blog/products/application-development/announcing-cloud-tasks-a-task-queue-service-for-app-engine-flex-and-second-generation-runtimes
Key Management Service. Note that there is a default key management where Google manages all the keys, then there is a customer managed encryption keys, and also a customer supplied encryption keys.
https://cloud.google.com/kms/docs/
A general knowledge of kubernetes and microservices is useful for a cloud developer.
Know the various types of testing — Canary, Blue/Green Testing, Rolling, etc.
AppEngine+Testing+Rollout. How to do some of that testing on AppEngine.
Datastore. Know the difference between strong and eventual consistency. What are the use-cases for them and how does it affect your choice of database?
https://cloud.google.com/datastore/docs/articles/balancing-strong-and-eventual-consistency-with-google-cloud-datastore/