PostgreSQL is a great open-source database for most of the traditional relational database workloads. Many of the customers we work with who use PostgreSQL database, especially the developer teams, appreciate open-source tools for source control, container support, and application performance management. However, we work a lot with the database administrator teams and we’ve seen some common threads of challenges that they face with PostgreSQL deployments.
Due to the pure open-source distribution of PostgreSQL using on-premise or cloud deployments may force your application development team to straggle together various extensions for high availability, disaster recovery, database replication, and auditing. Our DBMSys platform can help you avoid these problems. DBMSys provides reports on whether servers do or do not comply with these best practices. We also recommend running PostgreSQL database in the cloud using a managed service which handles automatic backups, database replicas, and other manageability features for improved business continuity. These include Azure Database Service for PostgreSQL, Amazon RDS/Aurora for PostgreSQL and Google Cloud SQL for PostgreSQL.
Moving PostgreSQL databases to a managed service like Azure Database Service for PostgreSQL, Amazon RDS/Aurora for PostgreSQL, and Google Cloud SQL for PostgreSQL is a great idea! However, how do I make a choice on what can move based on applications needs and what it will cost? Again, DBMSys to the rescue. DBMSys monitors your PostgreSQL database performance using metrics like CPU, disk latency, network latency, memory usage, along with features used to quickly identify which of your PostgreSQL databases are “cloud-ready” based on the different capabilities of Azure, Amazon, and Google Clouds. DBMSys then creates a detailed report that recommends how you should deploy to the cloud and how much it will cost. Specifically, it can make recommendations to go with a virtual machine running the database platform, or used one of the managed services that are correctly sized based on actual usage.
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