Organizations are increasingly relying on their IT systems to deliver critical business functions 24x7x365. To accommodate demand, disaster recovery is quickly evolving, which makes the trends for 2022 even more interesting.

Artificial Intelligence (AI)

Artificial Intelligence is gaining steam in DR strategies. AI’s biggest strength is its ability to analyze data and make decisions more quickly than humans. It can predict when a system might fail, and respond accordingly. AI can better interpret large and varied data sets and automate repetitive tasks that are spread across a broad range of technologies.

AI can model the impact of various disasters, forecast disruptions and act as security surveillance. In the event of a disaster, AI can commence the DR response faster than any human can, saving valuable time and resources. More importantly with AI, it’s easier to predict when business operations will be restored to normal after a disruption.

Machine Learning (ML)

A subset of AI, machine learning (ML) algorithm is a type of computer program that learns to perform specific tasks based on various data rules provided by its designer. Mathematical models are applied to data to find patterns that humans would likely miss. ML doesn’t direct systems to take action without human intervention. 

When the right amount of information is inputted into a machine learning system, it can come back with useful insights that may make disaster recovery strategies more effective. For example, a ML system could analyze all the previous downtime periods and pinpoint contributing factors. More accurate knowledge and data sets makes it easier to implement better resilience strategies.

Internet of Things (IoT)

The traditional role of IoT enabled smart sensors to detect issues before they escalated and brought operations down. IoT devices, combined with machine learning and AI, record tremendous amounts of data on normal operations for any business. This data can be harnessed after a disaster to bring operations back to their last recorded level. Basically, IoT devices provide businesses with a shadow copy of their operations.

On the flip side, organizations need to develop DR plans that focus on where IT systems and IoT overlap to include planning for application, network and analytics risks from cyberattacks. The reach of IoT across manufacturing, healthcare, communication, energy and other sectors will only continue to grow.

Automation

Automation is quickly changing disaster recovery. To be truly effective, automation should be paired with built-in orchestration and analytics. Not long ago, the idea of using automated tools to orchestrate server recoveries was considered a game changer. But in today’s always-on world, organizations also need business processes and their mission critical applications to be resilient, not just the servers. A truly successful operation means the application logins are recovered quickly, not just server logins.

As the future of DR unfolds through AI, ML, IoT and automation, Recovery Point is ahead of the curve, addressing your needs. This is the motivation behind our fully automated DR solution called Business Process Resilience (BPR), which is built on the robust and patented Geminare Resiliency Management Platform (RMP). BPR uses sophisticated cross-platform application recovery automation and comprehensive monitoring and reporting features for heterogeneous deployments in internal infrastructure, public clouds, colocation sites, and within Recovery Point’s own enterprise data centers. To learn more about BPR, talk to a Recovery Point expert at 877-445-4333.

Understanding the roles each of these trends plays in disaster recovery often helps organizations craft stronger plans, making it easier to recover lost data when a disaster strikes.

To learn more about artificial intelligence, click here.

To learn more about machine learning, click here.

You Might Also Like

Leave a Comment