Learn to create a Google Cloud free trial account, unlocking $300 credit for 3 months by signing in with your Google account, selecting your country, and entering billing details.

Discover how GCP regions and zones create resilient data centers across regions, enabling disaster recovery and high availability, while reducing latency via global deployments.

Explore structured, semi-structured, and unstructured data, detailing fixed schemas and SQL for structured data, flexible semi-structured schemas, and unstructured storage on cloud platforms.

Learn the key differences between oltp and olap: oltp handles many small transactions with cloud sql or cloud spanner, while olap supports complex analytics on a data warehouse using bigquery.

Explore vertical and horizontal scaling in cloud environments, contrasting upgrading a single machine's cpu and ram with deploying multiple machines to handle rising traffic, especially for databases.

Learn the difference between recovery point objective and recovery time objective, and how backups and downtime define data loss and system recovery in disaster recovery scenarios.

Evaluate latency, IOPS, data volume, and schema needs to select the right database in the GCP environment, considering structured, semi-structured, and unstructured data and in-memory options.

Explore the types of SQL and NoSQL databases, including relational SQL for OLTP and OLAP, and columnar, document, key-value, in-memory, and graph stores in GCP.

Explore GCP database products—Cloud SQL, Cloud Spanner, BigQuery, Bigtable, DataStore, Firestore, and Cloud Storage for Firebase—and learn a flowchart to choose the right database for structured, semi-structured, or unstructured data.

Explore relational database management on Google Cloud by comparing installing MySQL on Compute Engine with the fully managed Cloud SQL service that supports PostgreSQL, Oracle, and SQL Server.

Discover Google Cloud SQL, a fully managed relational database service that supports MySQL, PostgreSQL, and SQL Server for lift-and-shift migrations with built-in security, scalability, and read replicas.

Learn to create a Google Cloud SQL instance with MySQL 8.0, configure regional multi-zone deployment, set machine type, storage, backups, and point-in-time recovery, and connect via public IP.

Explore a Google Cloud SQL MySQL 8.0 instance, its public IP, connection name, and backup configuration. Examine connectivity and replica options.

Take a hands-on look at connecting a Google Cloud SQL instance using public IP. Authorize networks with CIDR ranges, and use a MySQL client from Cloud Shell.

Learn to connect to a Google Cloud SQL instance using the Cloud SQL proxy, including downloading the proxy, configuring permissions, and connecting via proxy with or without authorization.

Connect a Cloud SQL instance with a private IP within the same network by enabling private service access and using a compute engine in the default VPC to access it.

Add a built-in user and a Cloud IAM service account, then connect to a Google Cloud SQL instance using built-in credentials and IAM authentication, including using the Cloud SQL proxy.

Set up and enable SSL on a Google Cloud SQL instance, configure client and server certificates, and securely connect with SSL using the Cloud SQL proxy and client key.

Learn to authenticate to a Cloud SQL instance using a service account by generating a key and login token; then log in as the MySQL IM user with that token.

Viewers perform a hands-on lift-and-shift from a local MySQL database to Google Cloud SQL, exporting a dump and importing via a Cloud Storage bucket.

Perform a hands-on demonstration of zonal failover in a highly available Cloud SQL instance, switching from a primary zone to a standby in another zone with in-sync regional disks.

Explore automated backups, manual backups, and on-demand backups in a Cloud SQL instance, and learn how to restore to a previous backup to go back in time.

Export a Google Cloud SQL database or instance to SQL or CSV, selecting full instance or a specific database, and save to Google Cloud Storage with appropriate service account permissions.

Create and connect read replicas across regions, including cascading replicas, demonstrate read-only behavior, and explain regional failover by promoting a replica to primary when the main region fails.

Promote a read replica to become the primary instance for region failover and verify updates propagate without changing primary IP. Manage replicas by promoting and deleting extras to control costs.

Master Cloud SQL instance operations by starting, stopping, deleting, cloning, and restarting; adjust configurations, storage, backups, point-in-time recovery, and import or export data to Cloud Storage.

Explore cloud sql iam roles from viewer to admin and learn how to grant a cloud sql role to a user, reviewing permissions like get, list, create, update, and export.

Create a Cloud SQL PostgreSQL instance and connect from the Cloud Shell using psql, illustrating a public IP connection and the default postgres user.

Use the Google Cloud pricing calculator to compare a Cloud SQL one instance setup with Compute Engine, including 100 GB SSD storage, backups, and high availability.

Learn to use the gcloud command line to interact with a Google Cloud SQL instance from the cloud shell, including listing, connecting, and managing databases and users.

This lecture explains deploying Oracle, SAP HANA, and IBM DB2 on Google Cloud using bare metal solutions when there is no managed service, with Google Cloud Interconnect to on-premises.

Explore how Google Cloud Spanner enables horizontal, globally distributed, strongly consistent databases for large relational workloads beyond Cloud SQL limits. Get started with the fundamentals of Cloud Spanner.

Google Cloud Spanner is a native, fully managed, horizontally scalable distributed database on GCP that enforces a schema, offers five nines availability, and supports regional deployments with backups and recovery.

Avoid hotspots in Google Cloud Spanner by designing primary keys that distribute load; reverse the order of user ID and last access, or use a sharded ID to spread data.

Start a hands-on session with Google Cloud Spanner by creating a spanner instance and a database, defining author and book tables, populating data, and querying with Python.

Create a Cloud Spanner database library db, add author and book tables with a composite primary key, and interleave book in author with on delete cascade; insert sample author data.

Learn to model and query data in Cloud Spanner with author and book tables, enforce constraints, and run selects. Explore export, dataflow, and observability for performance insights.

Fetch data from Google Cloud Spanner using Python by creating a spanner client and querying the book table. Print results and review export to cloud storage and authentication steps.

Open Cloud Shell and use the gcloud CLI to create and manage Google Cloud Spanner instances, databases, and backups, exploring regional and multi regional configurations.

Discover AlloyDB for PostgreSQL, a fully managed PostgreSQL-compatible database on Google Cloud, delivering four times faster transactions, 100x faster analytical queries, and decoupled compute and storage with built-in ML autopilot.

Create an AlloyDB instance with a highly available cluster and read pool, configure a primary and a read replica, and select region and encryption for Postgres workloads.

Connect to an AlloyDB Postgres instance using a postgres client, explore the primary and read pool with a private IP, and observe data being reflected to the read pool.

Explore pricing for AlloyDB for PostgreSQL using the Google Cloud pricing calculator, configuring primary and read replica instances, memory, vCPU, storage, backups, and high availability to estimate monthly costs.

Explore Google Cloud's NoSQL databases, starting with DataStore and Firestore. Learn big table and memory store for low-latency in-memory data.

Explore the evolution of Datastore and Firestore, from Google App Engine origins to Firestore's two modes—native and Datastore mode—plus project and region constraints.

Explore Google Cloud Datastore, a highly available, serverless NoSQL database for web and mobile apps with schema-less design and SQL-like queries and asset transactional support.

Explore cloud datastore hands-on: select region, create entities and kinds, run google query language queries, understand indexing, and access datastore from python with example code, while comparing datastore and firestore.

Explore cloud datastore basics by creating a user profile entity with flexible properties, practice gql-like queries, and learn why composite indexes are needed for multi-column queries.

Create and deploy composite indexes for Cloud Datastore by writing an index.yaml, using gcloud to apply it, and running multi-property queries on user_profile data.

Explore exporting and importing Cloud Datastore data with Cloud Storage buckets, manage location constraints and service account permissions, and use gsutil in Cloud Shell to move data between regions.

Understand import and export with service accounts in Cloud Datastore, including the Cloud Firestore service agent role, permission management, and accessing datastore data from Python.

Install the Google Cloud Datastore library, create a Python datastore client, and query the user_profile kind to retrieve all entities in a few lines of code.

Discover Cloud Firestore in native mode, a scalable NoSQL database using collections and documents with real-time updates and mobile-friendly client libraries.

Explore Datastore and Firestore pricing in a serverless setup, including daily free quotas for reads and writes, regional vs multi-regional costs, and using the pricing calculator to estimate expenses.

Interact with datastore and firestore via the gcloud command line utility to manage indexing, import/export, and database operations; switch projects and export data to a cloud storage bucket.