I wrote a few tips in my last blog about studying for the Google Cloud Platform (GCP) Professional Cloud Architect (PCA) exam. I’m following up today by writing a few more things that I’ve learned while studying.
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Unlike Amazon Web Services (AWS) or Azure, there isn't an abundance of study materials for Google Cloud Platform (GCP). This is understandable given GCP's third-place position in market share, with AWS leading and Azure following. Interestingly, though, many cloud learning resources are platform-agnostic. For example, I demystified complex topics like pub/sub by watching AWS videos. When studying cloud technologies, if a concept doesn't immediately click, try finding explanatory videos from alternative platforms.
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To make sense of difficult topics, I've found a helpful technique: using generative AI/LLMs (like Gemini, Claude, or ChatGPT) to explain complex concepts in simple terms. For instance, I gained a clear understanding of the difference between a VM and a container by asking an AI to explain it as if I were a child. I recommend giving this approach a try!
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Watching system design talks has been instrumental in deepening my understanding of cloud architecture. I discovered several enlightening presentations by Google Developer Experts (GDEs) at Google Developer Group (GDG) events. These talks provide invaluable insights into the reasoning behind architectural decisions and the various trade-offs involved.