Manage Hyper-Converged Database (HCD) cluster operations
Mission Control is a comprehensive tool to manage your Hyper-Converged Database (HCD) cluster operations effectively. These operations are essential to maintain performance, ensure data integrity, and optimize resources.
Create a cluster
Creating a cluster involves setting up a group of interconnected database servers that work together to manage and process data. This operation enables horizontal scaling, ensuring that the database can handle increased loads effectively. For more information, see Install HCD.
Restart a cluster
Restarting a cluster can be necessary to apply updates or resolve issues. For more information, see Restart the cluster.
Back up data
Regular data backups are essential for disaster recovery. Mission Control automates backup schedules, allowing DBAs to define frequency and retention policies easily. This ensures that critical data is protected and can be restored quickly when needed. For more information, see Back up data.
Restore a data backup
Restoring data from backups is a crucial operation, especially in the event of data loss or corruption. Mission Control provides intuitive restoration options, allowing DBAs to select specific points in time or full backups. For more information, see Restore a data backup.
Clean up a node
Cleaning up a node involves removing unnecessary data or optimizing resources to enhance performance. This process can include clearing out old logs, purging stale data, or reallocating resources. For more information, see Clean up nodes.
Upgrade SSTables
Upgrading SSTables (Sorted String Tables) is vital for maintaining performance and ensuring compatibility with new features. Mission Control facilitates the upgrade process, providing tools to manage schema changes and optimize data storage without disrupting service. For more information, see Upgrade SSTables.
Remove a database cluster
When a database cluster is no longer needed, it must be removed to avoid data loss and ensure that resources are freed up efficiently. For more information, see Terminate a cluster.