IT leaders are thrilled about the potential of Generative AI for IT Operations. But they also want to know how it works, why it works, and what it will do for them before taking the leap and adopting this new technology. Allow me to share my perspective on the hype and the truth behind Generative AI. I’m the Field CTO for BigPanda, Operational Intelligence and Automation driven by AIOps.
Today, the majority of organizations operate under a hybrid cloud structure. Due to this, operations are consistently met with daily infrastructure and software changes and updates, which are also the primary cause of incidents and outages. Long gone are the days when a tech stack could be represented by a single dependency model. Microservices, CI/CD, and containers across multi-cloud make it extremely difficult to track all the changes and connect them to incidents.
Finding the root causes of IT anomalies can be challenging, but the rewards are worth it. By identifying the root cause or causes of an incident or critical failure, response teams can resolve incidents faster and determine the best steps to avoid having them recur. This can drive down both the frequency of service interruptions and their duration.
AI has revolutionized the way we engage online in 2023. From Chat GPT and AI Art Generators to healthcare, finance, and business, you can hardly read the news without reading the latest proclamation of how AI is poised to change every aspect of our lives. AI has brought fundamental changes to how we live and work, and we’re still scrambling to understand the impacts of these changes. Especially where their work is concerned, change can be difficult for people to embrace.
Every day, BigPanda is transforming the way our customers operate. Our advanced AIOps technology redefines incident management, prevents service disruptions, and elevates customer satisfaction – and I couldn’t be more thrilled to see industry experts take notice. I’m particularly proud to see BigPanda mentioned in nine of the highly esteemed 2023 Gartner Hype Cycle reports.
Transnetyx is an automated genotyping company dedicated to providing biomedical researchers with faster, easier, and more accurate results worldwide.
Dell’s recent acquisition of Moogsoft is the most recent validation of the growing market for automated ITOps – also known as AIOps. When legacy companies such as Dell recognize the importance of AIOps it proves the technologies behind automating ITOps are now mainstream and a vital part of every modern IT management stack. We look forward to seeing how Moogsoft’s integration into Dell will play out over the coming years.
Datadog’s modern observability empowers development engineers with full-stack visibility, comprehensive instrumentation generation, and proactive alerts to accelerate software development releases and address potential incidents. While Datadog gives teams end-to-end visibility, it works even better together with AIOps from BigPanda – development teams gain insights into outside application dependencies and reliance on other systems.
Overwhelming volumes and varieties of observability data most businesses encounter on a daily basis is impossible for IT operations teams to manually sift through successfully. This can be a troubling reality when frequent high-value business data is required to consistently maintain the uptime and integrity of your services and applications.
IT response teams find themselves battling against an overwhelming onslaught of incidents. Frustratingly long response times, challenges with prioritization, and the relentless pursuit of root cause are formidable adversaries that test even the most skilled teams. I remember customers’ electrifying anticipation with AI and automation a decade ago. They hoped AI could be used to instantly decode the business impact of incidents and automation to respond to incidents without human intervention.
