Making the Most of Automation: How To Maximize Investment and Accelerate MTTR

Artificial intelligence (AI) has become one of the biggest buzzwords of the last decade, as businesses spanning every sector are seeking ways to innovate and transform their operations. The crucial question they must ask is: what outcomes do businesses want to achieve by adopting AI? To fully harness its potential, AI must perform meaningful actions that deliver tangible benefits.

One significant application is automation, which IBM defines as “the use of technology to perform tasks where human input is minimized.” This is particularly appealing to IT teams and the C-suite for several reasons.

Why automate?

Automation enhances IT delivery by automating manual processes that traditionally required human input. It also enables organizations to gain observability over their infrastructure, applications, and devices, facilitating improved content processing and management; workflow streamlining; data-driven decision-making; cost optimization; network performance enhancement; and proactive incident management.

Perhaps the most desired benefit is this last one: self-healing. As IT leaders take a more prominent role in the boardroom and face increasing scrutiny around digital transformation efforts–efforts that profoundly impact how business value is created and delivered–self-healing brings countless advantages.

It can reduce unplanned outages and eliminate performance issues from user journeys, elevating the customer experience. It can help businesses overcome forecasting challenges, optimizing resources to cut software and infrastructure overcapacity. And it can drive the development of higher-quality applications, reducing testing needs so organizations can bring products to market faster.

However, the path to self-healing isn’t as simple as installing an automation solution and waiting for something to happen, as presumed by many–who are then disappointed in the process when it doesn’t work as planned. To reach an optimum level of maturity and realize their goals, companies should ensure several key elements in the automation process are secured and understood.

It starts and ends with data

Automation is not only a result of AI but also a driver. Any intelligent tech is only as smart as the data you feed it, and to maximize its potential, this data must have clarity, integrity, and fidelity. Plus, it must be fully extracted across all your domains–from your infrastructure and networks to your apps and logs–to build a complete picture and accurate machine-learning model. After all, correlation based on incorrect or fragmented data is nothing more than coincidence.

Take, for example, the financial management apps currently growing in popularity. These connect to your mobile banking accounts and give insight into what you’re spending, where and when. If, let’s say, you have a current account, savings account, and debit and credit cards, it’s critical the app pulls in data from each of these to provide the whole reality of your expenses and lifestyle. Then, you can see what can be improved upon and which spending habits need to change.

This may seem unwelcome news, as so many organizations battle legacy systems that can’t communicate with each other and disparate data stored in silos. Ironically, the ultimate outcome of automation–observability–needs to be present to begin with to unify this fragmented data and get outdated tech talking. Luckily, there are solutions on the market, like Riverbed’s unified observability portfolio, which can do exactly this while unlocking all the advantages of automation.

Building a baseline

The first step on any business’s journey to self-healing is harvesting quality data, and plenty of it. Next, it’s imperative to set a baseline to understand and record what’s usual across systems and devices, so anomalies can be identified and addressed. It’s akin to going to the doctor for a blood test; without keeping accurate and timely medical records, all they could tell you was whether they’d found anything of note in that one particular sample, regardless of how well or unwell you were feeling. By examining your record and taking samples over time, healthcare professionals can detect deviations in data points, identifying if anything is amiss based on your unique baseline. They seek out one-off or recurring problems and prescribe medication to get you back to full health.

A baseline tends to be established based on mathematical machine-learning formulas, which aren’t one-size-fits-all. Application data, network data, end-user data and infrastructure data are all different, and should be treated and tracked as such. That’s why, for over 20 years, Riverbed has carried out packet analysis that gives us the flexibility to use the best formulas and data science in the best possible places, driving the incident correlations businesses need.

Next stop: self-healing

Once an effective baseline is established, automation can finally start. But to automate the healing process, businesses must first automate the detection process, introducing scripts that alert to incidents and where they’re coming from. This helps avoid false positives and human errors while allowing for the correlation of individual issues, identifying bigger problems and their roots to accelerate mean time to detect (MTTD) or mean time to know (MTTK). Then, finally, the self-healing process can begin.

After streamlining data collection, baseline setting, and incident detection and correlation, most of the hard work is done. Now, automation scripts can be used to speed up mean time to fix (MTTF) or mean time to repair (MTTR)–addressing situations before users complain and driving ongoing optimizations.

In summary, to receive the highest quality output from any automation system, it’s vital that businesses take the time and make the investment to give AI models the greatest possible input. Businesses must prioritize comprehensive problem management and continuous system feedback to achieve reliable self-healing capabilities.

Do you have the robust data and effective machine-learning mechanism you need to achieve foolproof self-healing? If not, Riverbed can help. Get in touch with us today to learn how.