Running mainframe backups- 2018 Summary


What's inside

Mainframe Backups and Disaster Recovery in 2018-ICON Running mainframe backups- 2018 Summary

IT management teams in 2018 are expected to contain backup and archiving costs while ensuring minimum downtime in general, and in disaster recovery situations in particular. Furthermore, they must meet strict regulatory requirements regarding the security and privacy of the data that their organization controls—in transit and at rest, in active use and archived.

 The costs of downtime are staggering. According to a 2017 survey conducted by Information Technology Intelligence Consulting:

  • 98% of organizations said that one hour of downtime costs over $100,000
  • 81% indicated that an hour of downtime costs their business over $300,000
  • 33% reported that one hour of downtime costs their firms $1–5 million.

And although full-blown disasters may be rare, costly outages and interruptions are not. Surveys indicate that it is not unusual for organizations to lose one or more critical applications, virtual machines, or important data files for hours or even days.

The direct and indirect costs of non-compliance with data security and privacy regulations due to improperly conceived and executed backup and recovery policies are getting higher all the time. When the European Union’s General Data Protection Regulations (GDPR) come into effect on May 25, companies that collect and store personal data on European residents will be subject to stiff fines for non-compliance (2% of annual turnover or €2 million, whichever is higher) and even stiffer fines (4% of annual turnover or €4 million, whichever is higher) for actual breaches.

In this article, we examine how to manage the costs associated with mainframe backup and recovery, how to improve availability in mainframe shops, and how to raise confidence in disaster recovery processes. We also look briefly at the importance of robust data governance for addressing regulatory requirements, and for cost-effectively managing the lifecycle of data assets.