Exam Professional Cloud Security Engineer topic 1 question 46 discussion

https://cloud.google.com/bigquery#:~:text=BigQuery%20transparently%20and%20automatically%20provides,charge%20and%20no%20additional%20setup.&text=BigQuery%20also%20provides%20ODBC%20and,interact%20with%20its%20powerful%20engine. Answer is B. BigQuery transparently and automatically provides highly durable, replicated storage in multiple locations and high availability with no extra charge and no additional setup. @xhova: https://cloud.google.com/bigquery-transfer/docs/locations What it mentions here is once you create a replication. YOu cannot change a location. Here the question is about high availability. synchronous replication.

B. Cloud BigQuery Explanation: Cloud BigQuery is a fully managed data warehouse that automatically replicates data across multiple geographic regions to ensure high availability and durability. This aligns perfectly with the company policy requiring long-term data storage under these conditions. A. Cloud Bigtable: While this is a NoSQL database service that supports geographical replication, its design is more specific to big data workloads, and it may not align with a broad requirement for long-term data storage as specifically defined by the question.

Bigtable can replicate data across zones within a region and also replicate data across regions. https://cloud.google.com/bigtable/docs/replication-overview

Answer is D, becasue: A. Cloud Bigtable: This is a NoSQL database service, not designed for long-term data storage with automatic geographic replication. B. Cloud BigQuery: This is a data warehouse service, excellent for analyzing data, but it doesn't inherently replicate data for disaster recovery. C. Compute Engine SSD Disk: These are local disks attached to virtual machines, not designed for long-term storage or automatic replication.

BigQuery automatically stores copies of your data in two different Google Cloud zones within a single region in the selected location. https://cloud.google.com/bigquery/docs/locations

In my opinion the key word is "automatic" because BigQuery and BigeTable are by default store on one zone for a piece of data (no replication) Withe BigTable replication is automatic : https://cloud.google.com/bigtable/docs/replication-overview and copy dataset on Bigquery is not automatic https://cloud.google.com/bigquery/docs/managing-datasets#copy-datasets I go to A

this is geographic, not region, then the correct ans is D

Answer is A - Cloud Bigtable. Cloud Bigtable - Replication: This page provides a detailed overview of how Cloud Bigtable uses replication to increase the availability and durability of your data. Cloud BigQuery: From the BigQuery product description, you can see that it is mainly focused on analyzing data and does not mention geographic replication of data as a feature. Compute Engine Disks: The documentation for Compute Engine Disks explains that they are zonal resources, meaning they are replicated within a single zone, but not across multiple zones or regions.

Correct one is A, as BigQuery does not provide replication but multi location storage which is different

I am drifting towards D Regional persistent disk are safe from zonal failures. The question mentions different geo places ( not regions ) . So if zone seperation is done in 1 google region and we use regional persistent disk , the data will be safe from failure. Also why would someone move their DR to BQ ? persistent disk make more sense to me

Point not to be confused , Even with BQ multi region , data s stores in different ones in 1 region not different geographic regions. The question asks " different geographic places " which means essentially seperate zone storage will work. hence answer is B ( Big query ) either single region or multi region . Both suffice

I think answer is B First of reason is long-term data solution, it's suitable for Cloud Storage and BigQuery Second is that BigQuery dataset is placed to multi-region that means that two or more regions.

The answer is definitely A. Here's why: https://cloud.google.com/bigtable/docs/replication-overview#how-it-works Replication for Cloud Bigtable lets you increase the availability and durability of your data by copying it across multiple regions or multiple zones within the same region. You can also isolate workloads by routing different types of requests to different clusters. BQ does not do cross-region replication. The blue highlighted note in the two links below clearly says the following: "Selecting a multi-region location does NOT provide cross-region replication NOR regional redundancy. Data will be stored in a single region within the geographic location." https://cloud.google.com/bigquery/docs/reliability-disaster#availability_and_durability https://cloud.google.com/bigquery/docs/locations#multi-regions

Answer is A. the below statement is from the google cloud documentation. https://cloud.google.com/bigquery/docs/reliability-disaster BigQuery does not automatically provide a backup or replica of your data in another geographic region

B. Cloud BigQuery

I was about to select D, BUT: - the question says "long term data" -> which makes me think about BQ - the replication of persistent disk is between different ZONES, but the question says "different geo location" -> which means different regions (if you look at the zone distribution, different zones in same region are located in the same datacenter) but I still have doubt since the application data are not supposed to be stored in BQ , unless it is for analytics and so on. GCS would have been the best choice, but in absence of this, probably B is the 1st choice.

https://cloud.google.com/bigquery/docs/availability#availability_and_durability As per the link above BigQuery does not automatically provide a backup or replica of your data in another geographic region. It only stores copies of data in two different Google Cloud zones within the selected location. Reading through the link https://cloud.google.com/bigtable/docs/replication-overview It states that the Bigtable replicates any changes to your data automatically within a region or multi-region.