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Best Practices for Data Connector

The information provided in this topic is for reference only. It represents the results of lab testing in a controlled environment focused on individual protocol services. Enabling additional protocols, services, cache hit ratio for recursive DNS, and customer environment variables will affect performance. To design and size a solution for a production environment, please contact your Infoblox Solution Architect.

Using Data Connector in the Cloud

For a successful Data Connector deployment in the Cloud, consider the following best practices:

  • Before you deploy Data Connector, ensure that the server on which you intend to run the Data Connector service meets the minimum system requirements and has access to the appropriate ports and IP addresses, as specified in NIOS-X Server Connectivity and Service Requirements.

  • For bare-metal deployments, make sure that the Secure Shell (SSH) port on the server is changed from the default port 22 to a different port address, as the default port is used internally by Data Connector when NIOS is the source.

  • Do not run any other services on the server where the Data Connector service is running.

  • Always use a high-capacity image (750 GB Infoblox image) for deploying Data Connector.

  • The Data Connector VM has two hard disk drives. Hard Disk 2 is used for data storage, and you may substitute it for a larger drive to expand the data storage space.

  • Infoblox recommends that customers use the list of publicly used IP addresses found on the Data Connector Admin guide to determine the needed access to the internet.

  • If you need to change the IP address of the server after the configuration, you must restart the system for the change to take effect.

  • For the Data Connector service to function properly in OVA deployments on ESXi servers, ensure that you specify the NTP server during deployment. If you do not specify the NTP server, ensure that you open the UDP 123 port for time synchronization with the Ubuntu NTP servers.

  • If you need to re-deploy a Data Connector service as a container on the same server, you must manually clean up the /Infoblox directory on the server before re-deploying Data Connector.

  • Optionally, you can add ETL (Extract, Transform, Load) filters to extract specific source data before Data Connector sends the data to the configured destinations or sends specific data to the destination depending on the ETL expression added in traffic flow.

  • Multiple Data Connector deployments can be used to balance the load and optimize data transfer to the configured destination.

Using Data Connector with NIOS

For a successful Data Connector deployment with NIOS, consider the following best practices:

  • The NIOS Grid user that you added to the Data Connector configuration should have API access. Depending on your configuration, Infoblox recommends adding a “Superuser” to the Grid, so Data Connector can send WAPI calls to the NIOS Grid Master to obtain data.

  • Ensure that “Object Change Tracking” is enabled in the NIOS Grid if Data Connector is configured to pull IPAM metadata and DHCP lease information from NIOS.

  • If Data Connector is transferring IPAM data from NIOS to Infoblox Platform, ensure that you enable the NIOS Object Change Tracking feature to reduce the quantity of data transferred. When you enable this feature, the appliance tracks the changes that are made to NIOS objects and periodically synchronizes changed objects.

  • When using FQDNs instead of IP addresses in either the NIOS sources or destinations, ensure that Infoblox server is added as a local resolver for FQDN resolution.

  • Multiple Data Connectors can be registered in the NIOS Grid to balance the load and optimize data transfer to the NIOS reporting destination. Note that NIOS version 8.5.0 or higher is required.

  • The NIOS IP meta configuration flow directed to the Infoblox destination requires a minimum of 16 GB of RAM for servers where IP meta flows are set up. If there are frequent database object updates, it is advisable to increase the RAM size further, depending on the database size. In such cases, the memory can be doubled from the previous limit, resulting in a total of 32 GB (i.e., 16 GB * 2).