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Main Database

The Database instance is responsible for storing and maintaining all your TagoIO data, including profile configurations and device data. If the database becomes unavailable, the API will not be able to retrieve stored data, which directly impacts all project functionalities.

Backup & Scaling​

Backup Scheduling​

Regular backups are essential to prevent data loss or corruption. You can configure automated backups to run at intervals aligned with your operational needs. Each backup is preserved based on a defined retention period, which controls how long it's stored before deletion—allowing a balance between data protection and storage management.

For detailed instructions, refer to the Backups guide.

Automatic Backup Process​

Backups are created automatically every day to ensure consistent data protection and contain the following key features:

  • Daily Schedule: Backups run automatically on a daily basis
  • Configurable Timing: You can select the specific time of day for backup creation
  • Automatic Cleanup: Backups are automatically deleted after a configurable number of days to manage storage usage
  • Retention Settings: The retention period can be customized based on your needs

Scaling Your Database​

As application demand grows, you may need to scale the database to handle increased read/write operations:

  • Vertical Scaling (Machine Tier): Upgrade your database instance with more CPU and RAM. This is useful when handling large data submissions or high write/update activity.
  • Horizontal Scaling (Reader Instances): Add read-only instances to improve performance on read-heavy operations and increase overall service availability.

Monitoring & Performance​

To ensure stability and diagnose issues, monitor the following key metrics:

CPU Utilization: As data is read from or written to the database, CPU resources are consumed to process the data and execute all associated database pipeline operations, including data validation, transaction management, and integrity checks. CPU utilization may exhibit significant spikes during resource-intensive queries, such as aggregate operations that calculate daily averages over an entire month. Similarly, update operations involving large entity or device datasets can also result in noticeable CPU usage peaks.

Freeable Memory: This parameter represents the amount of memory currently available to the database instance. By default, the database attempts to cache frequently used queries, utilizing approximately 90% of the freeable memory. As new queries are cached, the system automatically evicts older cache entries to make room for newer ones. If the database instance is consistently consuming all available memory, this typically indicates that the volume or complexity of incoming requests exceeds the database’s ability to efficiently manage cache eviction and allocation. In such cases, performance may degrade as the database struggles to balance memory usage between active queries and cache management.

Database Connections: Displays the number of active connections to your database, including connections from API instances and other services that communicate with the database.

Read/Write IOPS: Displays the number of input and output operations performed each second. When investigating spikes in CPU or memory usage, correlating these peaks with read and write operation metrics at the same timestamps can help identify potential causes. Monitoring IOPS alongside resource utilization provides insight into whether increased disk activity is contributing to observed performance issues.

Network Throughput: Displays the volume of data in bytes transmitted to and from the database.

For environments supporting up to 10,000 devices, the following setup is recommended:

  • Machine: 2 vCPU / 4GB RAM
  • Reader Instances: 1
  • Backup Retention Period: 7 days