Google Professional Cloud Architect Certification: 4. Designing Storage Systems - Important Things To Know

GCP provides four types of storage systems: object storage using Cloud Storage, network-attached storage, databases, and caching. Cloud Storage is used for unstructured data that is accessed at the object level; there is no way to query or access subsets of data within an object. Object storage is useful for a wide array of use cases, from uploading data from client devices to storing long-term archives. Network-attached storage is used to store data that is actively processed. Cloud Filestore provides a network filesystem, which is used to share file structured data across multiple servers.
Google Cloud offers several managed databases, including relational and NoSQL databases. The relational database services are Cloud SQL and Cloud Spanner, Cloud SQL is used for transaction processing systems that serve clients within a region and do not need to scale beyond a single server. Cloud Spanner provides a horizontally scalable, global, strongly consistent relational database. BigQuery is a database designed for data warehousing and analytic database applications. The NoSQL managed databases in GCP are Bigtable, Datastore, and Firestore. Bigtable is a wide-column database designed for low-latency writes at petabyte scales. Datastore and Firestore are managed document databases that scale globally. Firestore is the next generation of document storage in GCP and has fewer restrictions than Cloud Datastore.
When designing storage systems, consider data lifecycle management and network latency. GCP provides services to help implement data lifecycle management policies and offers access to the Google global network through the Premium Tier network service.
 

1. Understand the major types of storage systems available in GCP. These include object storage, persistent local and attached storage, and relational and NoSQL databases. Object storage is often used to store unstructured data, archived data, and files that are treated as atomic units. 2. Persistent local and attached storage provides storage to virtual machines. Relational databases are used for structured data, while NoSQL databases are used when it helps to have flexible schemas.
3. Cloud Storage has multiple tiers: multiregional, regional, Nearline, and Coldline. Multiregional storage replicates objects across multiple regions, while regional replicates data across zones within a region. Nearline is used for data that is accessed less than once in 30 days. Coldline storage is used for data that is accessed less than once a year.
4. Cloud Filestore is a network-attached storage service that provides a filesystem that is accessible from Compute Engine and Kubernetes Engine. Cloud Filestore is designed to provide low latency and IOPs so it can be used for databases and other performance-sensitive services.
5. Cloud SQL is a managed relational database that can run on a single server. Cloud SQL allows users to deploy MySQL and PostgreSQL on managed virtual servers. Database administration tasks, such as patching, backing up, and managing failover are managed by GCP.
6. Cloud Spanner is a managed database service that supports horizontal scalability across regions. Cloud Spanner is used for applications that require strong consistency on a global scale. Cloud Spanner provides 99.999 percent availability, which guarantees less than 5 minutes of downtime a year. Like Cloud SQL, all patching, backing up, and failover management is performed by GCP.
7. BigQuery is a managed data warehouse and analytics database solution. BigQuery uses the concept of a dataset for organizing tables and views. A dataset is contained in a project. BigQuery provides its own command-line program called bq rather than use the gcloud command line. 8. BigQuery is billed based on the amount of data stored and the amount of data scanned when responding to queries.
9. Cloud Bigtable is designed to support petabyte-scale databases for analytic operations. It is used for storing data for machine learning model building, as well as operational use cases, such as streaming Internet of Things (IoT) data. It is also used for time series, marketing data, financial data, and graph data.
10. Cloud Datastore is a managed document database, which is a kind of NoSQL database that uses a flexible JSON-like data structure called a document. Cloud Datastore is fully managed. GCP manages all data management operations, including distributing data to maintain performance. Also, Cloud Datastore is designed so that the response time to return query results is a function of the size of the data returned and not the size of the dataset that is queried. The flexible data structure makes Cloud Datastore a good choice for applications like product catalogs or user profiles. Cloud Firestore is the next generation of GCP-managed document database.
11. Cloud Memorystore is a managed Redis service. Redis is an open source, in-memory data store, which is designed for submillisecond data access. Cloud Memorystore supports up to 300 GB instances and 12 Gbps network throughput. Caches replicated across two zones provide 99.9 percent availability.
12. Cloud Storage provides object lifecycle management policies to make changes automatically to the way that objects are stored in the object datastore. Another control for data management is retention policies. A retention policy uses the Bucket Lock feature of Cloud Storage buckets to enforce object retention.
13. Network latency is a consideration when designing storage systems, particularly when data is transmitted between regions with GCP or outside GCP to globally distributed devices. Three ways of addressing network latency concerns are replicating data in multiple regions and across continents, distributing data using Cloud CDN, and using Google Cloud Premium Network tier.