Your organization requires that metrics from all applications be retained for 5 years for future analysis in possible legal proceedings.
Which approach should you use?
Your organization requires that metrics from all applications be retained for 5 years for future analysis in possible legal proceedings.
Which approach should you use?
To meet the requirement of retaining metrics from all applications for 5 years for future analysis in possible legal proceedings, you should export the data to Google Cloud Storage. This is because Cloud Storage offers cost-effective long-term storage solutions such as Coldline or Archive storage classes, which are designed specifically for infrequently accessed data that still needs to be retained for extended periods. These storage classes provide high durability and can significantly lower storage costs compared to BigQuery, which is optimized for data analysis rather than long-term storage.
D is correct and best practice for long term log storage
+1. For archival purposes, Customer should use Cloud Storage. BigQuery is a datawarehouse, and could eventually import data from Cloud Storage if necessary.
+1 Due to long term storage, cloud storage is better answer than BigQuery
same for me. The best approach for the long time log is to export it from monitoring to Cloud Storage Archival type
A and C can be quickly ruled out because none of them is solution for the requirements "retained for 5 years" Between B and D, the different is where to store, BigQuery or Cloud Storage. Since the main concern is extended storing period, D (Correct Answer) is better choice, and the "retained for 5 years for future analysis" further qualifies it, for example, using Coldline storage class. With regards of BigQuery, while it is also a low-cost storage, but the main purpose is for analysis. Also, logs stored in Cloud Storage is easy to transport to BigQuery or do query directly against the files saved in Cloud Storage if and whenever needed.
point : organization requires that metrics from all applications be retained for 5 years
I mean answer : D
If you have 2 viable solutions (B&D), then always chose the one that is cost optimised - I chose D
Bigquery long term storage cost: $0.020 per GB Cloud Storage archive cost: $0,0012 per GB Only if metrics need less than 10 GB (free service part on Bigquery) then the correct solution will be B... But all metrics for all applications during more than 5 years... I think never will be the case :D
The question is about metrics, not logs. I'd go for B. See https://cloud.google.com/solutions/stackdriver-monitoring-metric-export
This is a good example. thanks. But, we can easily change that implementation to dump the metrics to buckets to save lots of money. And, when talking about legal purpose, 1 hour interval may not be enough. You may have to keep more frequent metrics. So, only cold line or archive work for that purpose.
second that! like the way u explained..
... for 5 years for FUTURE analysis in POSSIBLE legal proceedings ... "FUTURE" and "POSSIBLE" are the key words. So Cloud Storage Coldline storage class is the best option. When analyses are needed, the data can be imported into BigQuery D is the correct answer
Definitely D, as long as you've seen it's stored for 5 years and Cloud Storage would be the best candidate.
The keyword here is "long term log storage" so it is D. If keywords like "log analysis and storage" were used I would say BQ. But for this question answer is "D"
D is correct
You can compress and upload the data to a storage bucket. Since the data is not active, you can even use the archive or coldline storage type. Therefore the answer is D
for future analysis in possible legal proceedings. When it come to storage and ANALYSIS , the answer is straight forward BQ.
Answer is D. Data that needs to be stored for 5 years can be put in GCS and when needed the same can be imported in to BQ. Why should the data be stored in BQ for 5. years ?
D - Correct B. Configure Stackdriver Monitoring for all Projects, and export to BigQuery: This approach can work, but it may be expensive since BigQuery charges for the storage and processing of data. Additionally, you may need to configure a specific retention policy to retain the data for 5 years, which can further increase the cost. D. Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage: This approach is the most appropriate because it allows for the configuration of retention policies that meet the requirement of retaining metrics for 5 years. Also, Google Cloud Storage is a cost-effective solution for long-term data storage. Exporting the logs to Google Cloud Storage can be automated and scheduled for regular intervals, reducing the manual effort required to ensure compliance with the retention policy. The exported logs can then be analyzed using various tools, including BigQuery, if needed.
This should be D. The tool lists option B as correct option which doesn't sound right. Bigquery export is fine for analysis but not for long term storage for 5 yrs.
Cloud storage is appropriate for long term storage
"organization requires that metrics from all applications be retained for 5 years" means cloud storage
I think B is the right answer because transferring the data could be a basis for discrediting the data for legal use. Since BIg Query can store the data and retain it with all the metadata intact, I will go for it.
best practice for long term log storage
Google Cloud Storage for 5 years storing legally.
I mean, "for possible future legal proceedings", I think that immutable storage that grants data integrity is the best option here, what's more, it's also the cheapest one...