Google Professional-Cloud-Architect - Google Certified Professional - Cloud Architect (GCP)

https://cloud.google.com/endpoints/docs/openapi/about-cloud-endpoints?hl=en_US & _ga=2.21 787131.-1712523161.1522785064

https:/ /cloud.google.com/endpoints/docs/openapi/architecture-overview

https://cloud.google.com/storage/docs/gsutil/commands/test

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From scenario:

Business Requirements

Decrease unplanned vehicle downtime to less than 1 week, without increasing the cost of carrying surplus inventory

Support the dealer network with more data on how their customers use their equipment to better position new products and services

Have the ability to partner with different companies – especially with seed and fertilizer suppliers in the fast-growing agricultural business – to create compelling joint offerings for their customers.

https://cloud.google.com/community/tutorials/pci-tokenizer Deterministic output means that a given set of inputs (card number, expiration, and userID) will always generate the same token. This is useful if you want to rely on the token value to deduplicate your token stores. You can simply match a newly generated token to your existing catalog of tokens to determine whether the card has been previously stored. Depending on your application architecture, this can be a very useful feature. However, this could also be accomplished using a salted hash of the input values.

Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and availability.

More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the end users.

All this redundancy and caching means that Multiregional comes with overhead to sync and ensure consistency between geo-diverse areas. As such, it’s much better for write-once-read-many scenarios. This means frequently accessed (e.g. “hot” objects) around the world, such as website content, streaming videos, gaming or mobile applications.

The Google Cloud database migration path follows a " like-for-like " managed service strategy. Cloud SQL is the recommended destination for MySQL and SQL Server workloads that do not require the massive horizontal scale of Spanner, fitting Cymbal’s " Technical Stack Modernization " goals. Memorystore is the managed service for Redis, and Firestore is the native NoSQL replacement for MongoDB.

For the image storage requirement, Cloud Storage Coldline is the mathematically correct choice for data accessed " less and less frequently " with a retention period exceeding 90 days . According to Cloud Storage documentation , Coldline is specifically designed for data accessed at most once a quarter (90 days). Using Object Lifecycle Management to move images from Standard to Coldline allows Cymbal to " reduce costs " while keeping images " immediately accessible " (unlike Archive storage, which may have different trade-offs). Option C is less optimal because Nearline is intended for 30-day access patterns; given the images stay for 90+ days and usage drops significantly, the deeper savings of Coldline are preferred. Option A is over-engineered (Spanner for all) and expensive, while Option B contradicts the requirement to " reduce costs " by increasing operational overhead

According to the Google Cloud Architecture Framework: Performance Excellence , Local SSDs are the optimal choice for " scratch " space, temporary files, and workloads requiring the lowest possible latency and highest IOPS. Unlike Persistent Disks (Option C) or Filestore (Option B), which are network-attached, Local SSDs are physically attached to the server that hosts the virtual machine instance.

This physical proximity eliminates network latency, providing sub-millisecond access times which are critical for " frequently accessed and modified " temporary files during AI training and inference. For generative AI, where data shuffling and checkpointing are intensive, the high throughput of Local SSDs prevents the storage layer from becoming a bottleneck for the expensive GPU/TPU accelerators.

While the data on Local SSDs is ephemeral (lost if the VM is deleted or undergoes certain maintenance events), this perfectly matches Cymbal ' s requirement for " temporary files. " Furthermore, Local SSDs can be more cost-effective than provisioning high-performance Persistent Disks of equivalent speed, as their performance is not tied to the disk size. Cloud Storage (Option A) is unsuitable for this specific use case due to the significantly higher latency of object-based storage compared to block-based local storage.