Fujitsu Enterprise Postgres for Kubernetes

Enterprise Security

Powerful tools to protect your organization from database security threats – Transparent Data Encryption to protect data at rest, Data Masking to redact data in-flight, confidential management automation to reduce human error and minimize security risks and Dedicated Audit Log to record database access and monitor suspicious/unauthorized activity. Backed up with Fujitsu Warranted Postgres Code.

High Availability

Ensure your data availability from pre-configured, high available PostgreSQL cluster. A master and two replicas enabling automated failover, manual switch over, auto recovery. Async and sync replications are supported, with flexibility by dynamic configuration.

Disaster Recovery

By using OSS (pg_BackRest) functionality to store backup data in object storage, data can be migrated to a database cluster in a different OCP environment. It is also possible to continue operating in a different OCP environment in event of a disaster By operating the container environment for the production site and the container environment for disaster recovery in hot standby configuration, you can implement disaster and restore business systems more quickly in the event of a disaster.

Backup and Restore

Backup available with Point-in-time-recovery. Configurable for daily, weekly, monthly or any day/time backup, incremental and full backups to meet your critical business requirements. On-demand backups can also be taken at any time other than a predetermined schedule, such as before planned maintenance or after configuration changes.

Monitoring

Provides monitoring of health, performance and unauthorized access to data of cluster components using metrics and alert rules. Secured metrics collection endpoints block unauthorized access to data. All important functionalities can be monitored, including Server, Backup, and Connection Pooler. Easy monitoring using Grafana dashboards.

Auto Scaling

Automatically increase Fujitsu Enterprise Postgres cluster capacity using scale-out upon detection of higher system load - e.g., surge in the connections to the database beyond the configured threshold.