Database migration and modernization
1. Database migration and modernization
Running modern applications on legacy, on-premises databases requires overcoming expensive, time-consuming challenges around latency, throughput, availability, and scaling. With database modernization, organizations can move data from traditional databases to fully managed or modern databases with relative ease. There are different ways that an organization can migrate or modernize their current database in the cloud. The most straightforward method is a lift and shift platform migration. This is where databases are migrated from on-premises and private cloud environments to the same type of database hosted by a public cloud provider, such as Google Cloud. Although this solution makes the database more difficult to modernize, it does bring with it the benefits of minimal upheaval, and having data and infrastructure managed by the cloud provider. Alternatively, a managed database migration allows the migration of databases from SQL Server, MySQL, PostgreSQL, and others to a fully managed Google Cloud database. Although this migration requires careful planning and might cause slight upheaval, a fully managed solution lets you focus on higher priority work that really adds value to your organization. Google Cloud’s Database Migration Service (DMS) can easily migrate your databases to Google Cloud, or Datastream can be used to synchronize data across databases, storage systems, and applications. Let’s look at a real life use case. With 18 fulfillment centers, 38 delivery centers, and a catalog of more than 22 million items, the online retailer Wayfair needed a way to quickly move from their on-premises data centers, which ran on SQL Server, to Google Cloud. This had to be achieved without inconveniencing their team of over 3,000 engineers, their tens of millions of customers, or their 16,000 supplier partners. So, the goal was to lift and shift their workloads as quickly as possible with minimal changes, and then use cloud databases to modernize those workloads. Wayfair chose Google Cloud because of the clear path for shifting workloads to the cloud by using Cloud SQL for SQL Server. Google Cloud provided the flexibility to be deliberate about which engine and product to run Wayfair’s systems on going forward. They liked how they could run SQL Server on virtual machines (VMs), for example, but could also benefit from database offerings like Cloud SQL and Spanner. Now that migration is complete, they also use Google Kubernetes Engine (GKE) and Compute Engine VMs to host the services built by the Google Cloud team. They also use Pub/Sub and Dataflow for sending operational data to their analytical store in BigQuery.2. Let's practice!
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