In this episode of The More You Monitor, we’ll dive into AIOps and the benefits you can expect from implementing AIOps within your organization.
Thanks for joining me for this episode of The More You Monitor. I’m Dondy Aponte, a Lead Sales Engineer here at Logic Monitor. Today, we’ll be talking about AIOps and observability and why these aren’t just hyped up buzzwords. In this episode of The More You Monitor, we’ll dive into AIOps and the benefits you can expect from implementing AIOps within your organization.
As architectures scale and become more complex, visibility into the health and performance of these infrastructures and services becomes increasingly difficult. This is where observability becomes essential. Your IT team is most likely relying on an array of disjointed monitoring, tracing and log tools that don’t integrate with one another, adding an additional layer of complexity and confusion to your daily workload. But in today’s fast-paced landscape, your business needs end-to-end observability to gain an efficient and accurate pulse on the health of your infrastructure, applications, and business systems. For monitoring metrics and applications to log data, you must be able to put all of this information in context with one another, to see the full picture in real time.
Into AIOps. AIOps isn’t only about issue mitigation. It’s also about the continual optimization of your systems and processes. With machine learning doing the heavy lifting, your infrastructures and processes are continually being improved upon with very little effort from your team. Platforms that include AIOps capabilities can help your organization ingest multiple types of data from an array of sources and vendors to provide a holistic view.
Conduct proactive analysis in real time to quicken response to issues. Provide context against historical analysis of stored data. Surface only the most relevant alerts and suppressing distracting data with machine learning algorithms. And using automation to initiate the response to issues through insight and analytics to dramatically quicken MTTR.
Using AI and machine learning also allows organizations to spend less time addressing outages and slowdowns and more time providing innovative solutions for the broader business. Shortening MTTR, Mean Time To Repair, should be one of your organization’s top priorities in today’s fast paced landscape because even a temporary slowdown of a business critical system can dramatically affect the company’s bottom line.
Being proactive is key to ensuring constant uptime and a stellar customer experience. Getting ahead of issues before they result in IT outages or brownouts is even more important for businesses that rely on technologies and revenue streams, such as e-commerce mobile offerings and IOT based services.
AI algorithms make being proactive easier by performing complex analysis automatically on a wide range of data types and sources. This allows you to address any issue that surfaces quickly before it evolves into a full-blown outage or disruption.
One of the key value drivers of AIOps is its ability to provide your organization with an early warning system of sorts. An early warning system not only alerts you to issues within your infrastructure, but it also identifies key patterns or anomalies with your data using machine learning and advanced algorithms. There are four key pieces to any good, robust early warning system. One, anomaly detection. Two, dynamic thresholds. Three, root cause analysis. And four, forecasting capabilities. Look for a platform that contains all of the above functionality.
A single platform solution not only helps to sort through the noise of all of this data and provide meaningful, actionable alerts, but it also simplifies the entire process and experience. When a potential issue or troubling pattern is identified within your systems, AIOps can detect and alert you to the issue before it affects the stability, reliability, and responsiveness of your IT infrastructure and applications. Whatever AIOps solution you select, it should not only be powerful, but it should also be relatively easy to set up and use through an intuitive interface out of the box.
AIOps is all about having a bird’s eye view of your entire IT landscape and seeing the big picture contextually, no matter the resource or application type or location. This is more important than ever as companies pivot from on-premise solutions to software-as-a-service delivery models. With an AIOps solution that is rooted in the cloud, you can ensure flexibility, agility, and scalability within your IT operations.
For more information on how AIOps can help your organization with its digital transformation journey, download Logic Monitor’s AIOps eBook. What is AIOps for Monitoring? at logicmonitor.com/resource/what-is-aiops-for-monitoring. Also, keep an eye out for the next iteration of this AIOps series, where we will be diving more in-depth into how to use AIOps for monitoring and understanding core elements of an early warning system. I’m Dondy Aponte, signing off for Logic Monitor. Thanks for tuning in to this episode of The More You Monitor.