Читать книгу Google Cloud Certified Professional Cloud Architect Study Guide - Dan Sullivan - Страница 74

It is also important to understand how long data will be stored in various storage systems. Data may first arrive in a Cloud Pub/Sub queue, but it is immediately processed by a Cloud Function that removes the data from the queue, transforms the data, and writes it to another storage system. In this case, the data is usually in the queue for a short period of time. If the ingestion process is down, data may accumulate in the Cloud Pub/Sub topic. Since Cloud Pub/Sub is a managed service, the DevOps team would not have to allocate additional storage to the queue if there is a backup of data. GCP will take care of that. They will, however, have to consider how long the data should be retained in the queue. For example, there may be little or no business value in data that is more than seven days old. In that case, the team should configure the Cloud Pub/Sub queue with a seven-day retention period.

If data is stored in Cloud Storage, you can take advantage of the service's lifecycle policies to delete or change the storage class of data as needed. For example, if the data is rarely accessed after 30 days, data can be stored in Nearline while Coldline storage is a good option for data accessed not more than once in 90 days. If it is accessed once a year or less often, then Archive storage is an appropriate choice.

When data is stored in a database, you will have to develop procedures for removing data when it is no longer needed. In this case, the data could be backed up to Cloud Storage for archiving, or it could be deleted without keeping a copy. You should consider the trade-offs between the possible benefits of having data available and the cost of storing it. For instance, machine learning models can take advantage of large volumes of data, so it may be advisable to archive data even if you cannot anticipate a use for the data at this time.