Audience

This data archival recommendation document is intended for the following users:

• SummitAI Administrators
• Data security management officials on customer/partner side

Scope

• These recommendations are provided based on internal testing and previous experiences of the existing customers.
• These recommendations are mainly for the SummitAI Administrators/Decision Makers for data retention on the customer side.

Definitions

• Data consists of transactional or irrelevant foundation data in the SummitAI modules, such as Service Management, Asset Management, and Availability Management
• Data is a record or a document.
• ‘Archiving’ is the process of moving the data that is no longer actively used to a separate storage device for long-term retention. Archived data consists of data that is still important to the organization and used for future reference as well as the data that must be retained for regulatory compliance.

Data Archival - Recommendations

• Data archival recommendations have been adopted by SummitAI to set out the principles for retaining and archival of the transactional data in SummitAI Application.
• Archiving data is an essential step in data management. It provides a way to remove obsolete records from your production SummitAI database using a regular, controlled, and predictable process. Archiving data also helps you to maintain system performance and to comply with your record retention policies.

Benefits

• Customers with linear growth will see performance gains by enabling archiving in services.
• Reduces the size of your production data.
• Improves overall system performance (for example, direct searches/page loads, faster executions, because they look only at production data and not at archived data).
• Enforces organizational data-retention policies.

Data Retention and Archiving

• The retention period for any record is for active use of 2 years unless an exception is obtained from the business unit or division or function (responsible for creating, using, processing, disclosing, storing the record in SummitAI application) to permit a longer or shorter active use of period.

• The retention period for the various data record categories are summarized as follows:
  

  Data or Record Category	Data or Record Sub-Category	Active Data Retention
  Service Management	Incident Management	2 Years
  	Service Request Management	2 Years
  Availability Management	Server_Alert_History	2 Years
  	Server_SwapBuff_Util	2 Years
  	Server_EventLogsLinux	2 Years
  	Server_Exch_Queue	2 Years
  	Server_Exchange_Health	2 Years
  	Server_Exchange_Status	2 Years
  	Server_ExchChange_Message	2 Years
  	Server_ExchStore	2 Years
  	Server_ZombieProcess	2 Years
  	Network_Device_Util	2 Years
  	Server_Health	2 Years
  	Server_HWEvents	2 Years
  	Server_HWHealth	2 Years
  	Server_HDD_Util	2 Years
  	Network_Device_Ping	2 Months
  	Server_Ping	2 Months
  	Server_Process_Util	2 Months
  	Server_SwapBuff_Util_30MinsSummary	2 Years
  	Network_Link_Error	2 Years
  	Network_Link_Utils	2 Years
  	Server_EventLogs	2 Years
  	Server_HDD_Util_30MinsSummary	2 Years
  	Server_Util	2 Years

  Note:

  Above are the data archival recommendations. However, the data archival policy should be defined by the DBA teams based on the customer infrastructure, data generated at the customer environment, and the customer-specific requirements in discussion with the SummitAI team.

Additional Notes

• In the case of tables with 2 years of retention, one-year data will be on the Primary database and one year on the Archival database.
• The archived data retention completely depends on the organization-specific data retention policy.
• Based on the configuration, SummitAI will run the scheduled job and ensure that data will be archived or purged.
• Please note this is SummitAI’s recommendation, however, if a customer wants to keep data for more than 2 years, the infrastructure where the SummitAI servers are hosted needs to be ramped up accordingly to avoid performance impacts.

Exceptions

• The reasons for exceptions of the records for data archival can be due to client requirements, business requirements, legal requirements, or vital historical purpose.
• The reason for the exception of the records of data to be archived can also be due to the relevancy of the records to be archived at the time of the archival.