Overview ​

I recently completed 3 Google Cloud Professional Certifications, which was after completing a 100-day challenge, and I still feel like I'm barely scratching the surface. GCP continues to evolve with new services, features, and paradigms. My learnings are more project-based now, but I will leverage this section to capture pertinent ideas and trends to stay relevant.

GCP Architecture Blueprints: ​

(Reference link architecture)[https://cloud.google.com/architecture]

Vertex AI ​

• A Stroll Through Google's Model Garden by Charlie Guo: Summary: Model Garden - hundreds of available models including open-source models and task-specific models. Generative AI Studio is a playground for designing prompts and fine-tuning a model model via example-based & RLHF. ML Ops & infrastructure - why OpenAI + Azure is a common compliment.

Analytics Lakehouse ​

The following article lays out an end-to-end vision of where analytical systems are heading (have headed). Analtyics Lakehouse Medium Article

BigQuery ​

My Medium articles:

• JSON Data Types
• BigQuery UDFs
• Remote Functions

Articles

• Technical Overview of JSON Type

BigLake ​

• BigQueryover Iceberg

Cloud Storage ​

Autoclass is generally recommended, unless known use case for a specific storage class or if other Google Cloud services regularly read data from the bucket (e.g. Sensitive Data Protection);