Continuous transformation in IT operations is more than just an industry buzzphrase. In fact, continuous transformation is a critical survival tool for any cloud and IT solution landscapes today. To achieve continuous transformation, innovation must continue well beyond a migration to the cloud. This continuous innovation during day-to-day IT operations is the most critical aspect to achieving month-over-month best-in-class operational benefits.

Simply “lifting and shifting” systems to the cloud without modernizing precludes most of the key benefits that your systems can potentially deliver over the long term. For example, some of the outcomes of this approach, including bug fixes and other common errors, cause downtime and delays that businesses cannot afford in these highly competitive environments. In addition, unplanned downtime and disruptions impact revenue and can damage brand reputations, both of which detract from a business’s ability to compete and win in their market.

Proactive vs. Reactive 

To stay ahead of the pack, companies must shift from a reactive to a very proactive posture. Error prevention is far more effective than fixing errors and resolving issues as they happen. To this end, companies should be leaning on service providers that proactively cover the entire application and infrastructure landscape, end to end, through customized, out-of-the-box solutions. For example, proactivity is rapidly enhanced by including predictive analytics and other fault-finding algorithms in software, such as:

• Analytical anomaly detection.
• Cloud-enhanced and optimized monitoring templates.
• Self-healing automated reaction, from disk extensions, cluster and scaling groups to ensure an issue does not result in downtime, simply a post-event investigation.

A company’s IT needs are also continually changing as business landscapes evolve. For example, being on the cloud and using service level agreement (SLA) measurement has now advanced to become mission-critical in two areas: bottom-up technical SLAs (as per usual) and now, more importantly, top-down business transactional SLAs.

Here are some ways IT could streamline its operations and deliver the most value back to the business:

• Operations Analytics – An operations analytics tool allows for capacity planning, monitoring usage trends and patterns over time. Should deviations from the anticipated usage occur, IT teams can react immediately, implementing remedies before the situation escalates to an incident. This early intervention could be done either manually or automated. Automated scripts, triggered by predictive alarms, can restart services and adjust virtual resource allocation or any other remedial action necessary.
• Predictive Analytics – Future planning is essential to successful business operations. Predictive analytics improves on this by using precursor and antecedent information to predict system failure with an associated confidence level. IT teams know when resources operate outside their anticipated range and how likely they are to fail within the next period. System failure is usually associated with a surge in user activity. This is not easily predicted, driving the need for advanced predictive analytics. Armed with this information, IT teams can carry out preventative maintenance on data centers and associated systems, such as that done for manufacturing machines in industrial applications.
• Automated Self-Healing Systems – By combining artificial intelligence and machine learning, digital innovation has made it possible for business systems to self-heal. Advanced, automated software packages monitor business systems, finding errors and fixing them without human intervention. These systems address performance variations and restore outages as well.

Through self-learning algorithms, the software learns and understands the normal business operations and its reactions to irregularities and errors. Using this information, the software reacts appropriately when it detects errors, automatically restoring the business system to normal operations. These automated, exponential self-healing packs utilize innovative, continual logic learning as part of their standard software package. These systems also resolve issues in a fraction of the time it takes through traditional manual intervention. Typically, the end user doesn’t even realize that an error has occurred, improving the user experience dramatically.

The implementation of self-healing systems is relatively quick and can be done in as little as four weeks. As a result, IT teams will have access to advanced troubleshooting and automated diagnostic, enabling fast, root-cause analysis of any errors that occur—implementing the solution through guided prompts, documents the resolution for future reference. And, if the same error occurs again, the solution will automatically be executed.

Automated self-healing systems offer a range of benefits, including business and IT cost reduction, decreasing unplanned downtime and risk-free digital footprint expansion for continuous transformation. IT professionals can work strategically, delegating mundane and repetitive tasks to automated processes, freeing time and resources to carry out more advanced tasks aligned to business goals.