Backup and recovery automation, for many organisations, has long been nothing more than an aspiration for IT departments. Backup has historically been seen as a necessary evil due to its manual nature – an essential task few want responsibility for as it becomes more complex and essential to protect the business from all types of interruption from server failures to a full-blown disaster recovery scenario.
AI and machine learning make backup and recovery “cool” again
In recent years the backup market has seen a paradigm shift, new players in the market are changing the way backup is performed. The technology being adopted deliver seamless integration into the wider IT operations and is enabling us to make the aspiration of automation a reality.
As well as the new players, many traditional vendors are looking to leverage ‘AI’ to help automate – there is an argument to say that AI is actually machine learning but let’s leave that discussion for another day.
So, if you think about the backup environment today, every night that you run a backup you are not just protecting data, but you are also creating it. Every time a file is restored, a disaster recovery test is run or an application is recovered to another environment for dev/test needs, you are creating data – operational data on how technology and the machines associated to it are working. Many solutions record lots of statistics and report these back to you – statistics such as rates of change, speed of access, performance insights and bottlenecks – this is essentially AI and machine learning which can then be used to help you automate with predictability.
AI and machine learning advance enterprise backup, recovery and DR solutions
AI is not just for autonomously-powered self-driving vehicles, trucks or behavioural algorithms for automating robots to build out machines. AI is the next step in taking the highly-complex solutions used for protecting and recovering today’s IT environments and creating a smart, self-learning system that can dynamically adjusting to your needs and outcomes.
Using machine learning in the backup & recovery area of your business can ensure that if certain jobs are running slower or need more frequent recovery points to meet your service level agreement (SLA), you will be able to change priorities and adjust schedules accordingly to help ensure the end RPO/RTO can be achieved.
Evolving backup and recovery with a power of AI
Introducing AI and machine learning makes this type of consistent tuning of your environment an automated and data-driven process, without your intervention.
The fact that many of the next generation, hyper – converged backup & recovery solutions (as well as some of the more traditional ones) integrate into IT service management tools such as Servicenow means that the visibility & management of this automated environment has never been more accessible to senior management – the access & visibility is crucial when the senior leadership team have a degree of liability when it comes to data loss, availability and reliability of systems.
Technology evolves – your backup and recovery should, too.
It would be fair to state that we are at the very start of what AI & Machine Learning can do to automate backup and recovery processes but, so far, the initial positive impact would suggest that this can continue to deliver massive improvements in business outcomes as the vendors find more ways to leverage their own data.
To take advantage of all the opportunities that AI powered backup and recovery can deliver to your business, consider the incorporation of AI as criteria for your next backup and recovery solution.