Unleash the true power of AIOps with BigPanda New Generative AI
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. However, it didn’t take long to realize that the lofty ambitions were more hype than substance.
Given the technological and financial capabilities of the time, previous generations of AI in ITOps were very limited in focus, primarily working to identify patterns in complex data to identify signals so response teams could work proactively.
But as Generative AI emerged, we wondered if this could be the missing piece: could it finally fulfill the immense potential of AI in ITOps? We tested several large language models and were blown away by our initial experimentation. But we knew the results were just a taste of Generative AI’s true potential.
BigPanda new Generative AI capabilities fulfill a decade-old promise of incident automation
Fast forward to the present, I’m excited to announce a new era of AI and automation that fulfills, reimagines, and expands upon that elusive promise for AIOps. Now we are announcing the General Availability of Automated Incident Analysis, a revolutionary new Generative AI capability that provides ITOps teams with fast, accurate and consistent insights into every incident, making it possible to identify the impact and probable root cause across distributed IT systems faster and easier than previously possible.
Our first three capabilities for this feature include:
- AI-generated summary and title
- AI-proposed incident impact: Reliably identify the relevancy and impact of incidents across distributed IT systems in clear, natural language within seconds. Easily identify priority actions for L1, L2, and L3 response teams across all incidents at scale.
- AI-suggested root cause: Automatically surface critical insights and details hidden in lengthy and complex alerts to quickly identify the probable root cause of an incident as it forms in real-time.
BigPanda Generative AI is in many ways like an experienced full stack IT expert who can work at lightning speed. Generative AI works in near real-time to automatically add the correlated alerts’ summary, title, and root cause analysis to ITSM tickets or chat collaboration channels with specific L1/L2/L3 teams – without manual intervention.
To be clear, this isn’t about replacing human expertise but augmenting it. Getting another set of eyes on alerts is a practical reality and the first step to reducing stress, saving time and ultimately mitigating the risks of human error, making incident triage shorter and less stressful.
Can Generative AI help ITOps teams make the right call?
When a Level 3 engineer is assigned an escalated incident from a Level 2 engineer, they typically verify the findings of the L2 engineer. It’s not a lack of trust in their abilities but rather the engineers’ burden of accountability. Engineers know that a wrong call could cost a company significant amounts of money, damage their professional reputation, and turn a prolonged P3 incident or outage into an emergency that causes the company to scrutinize their ITOps department.
BigPanda AI-generated analysis is built with expertise in IT infrastructure and systems and provides operational awareness and context to reliably identify where a problem started, what changed, and how systems are related to suggest where and how to fix issues.
BigPanda does this by ingesting six sources of relevant enrichment. The descriptive metadata and cross-domain enrichment of alerts augment Generative AI’s understanding of application topology and can go far beyond simple logic like “What failed first?.” These relevant data enrichment sources can instead form highly accurate assumptions and identify the position of incident impact across distributed IT systems.
Generative AI for Automated Incident Analysis has shown remarkable accuracy in our beta testing phase, delivering 95% accuracy in determining causality. Now, I challenge you, can you find a person who is correct 95% of the time when viewing an incident at first glance?
BigPanda drives reliable AI outcomes using contextual data
We knew that any Generative AI solution for AIOps platforms must ingest existing descriptive metadata from distributed IT systems. Using solely metrics, logs or correlated alert data would provide a limited understanding of potential root cause based on changes or impact beyond a single application or service.
Simply put, would you make a call without all the facts present during an outage? That’s why using the right enriched, contextual data sources makes AI outcomes more reliable and gives your IT teams a lot less stress and uncertainty – and a lot more ‘a-ha’ moments.
Generative AI with customer data protection at its core
In the realm of Generative AI and information security, two common concerns emerge:
1) Data usage and privacy: We ensure that our deployment of Generative AI does not use any customer data to train other models used by others. BigPanda adheres to a zero data retention policy which safeguards your privacy and information security.
2) Use of public-facing chat interfaces like ChatGPT: The reality for enterprises requires BigPanda to use a secure, enterprise-grade system with dedicated and secure API’s to transact and retrieve answers.
We follow industry and international best practices such as SOC 2 type II, CCPA, CPRA for data privacy, data protection, data usage, and data retention. We also adhere to a zero data retention policy, meaning that the data you provide doesn’t feed into training other models, safeguarding your privacy and information security.
We also require that our customers opt-in to use BigPanda Generative AI, that data residency is in the United States, and that an Enterprise Agreement and Data Processing Agreement (DPA) is in place. You can read about our Data Security and Compliance information and get more information by visiting our security documentation page.
With Generative AI evolving at exponential speed, companies should expect AI solutions to use industry and international data best practices. But as IT moves faster than ever, those who use Generative AI will keep their competitive edge. Those who don’t risk falling farther behind as Generative AI becomes profoundly integrated throughout tech and consumer landscapes.
A future with faster incident resolution – and without stressful outages
Imagine reducing up to 10 minutes needed for each incident. And then think how quickly this can add up for IT teams bombarded with nonstop incidents. Take it from our customers, like Jeremy Talley, Lead Operations Engineer at Robert Half International. When asked what it’s like to use Automated Incident Analysis, he shared the following.
“BigPanda Generative AI empowers our Ops teams by providing faster incident detection and independent resolution. The rapid, automated extraction of meaningful insights from our complex IT alert environment not only makes us better at L1 response, but also reduces escalations to our L2 and L3 experts.”
In my two decades working in IT, I know how stressful it is for IT teams to manage never ending alerts. But there’s a better way that’s finally made possible by Generative AI.
BigPanda Generative AI erases the extra noise and uses enriched data to let your ITOps teams quickly and automatically deliver clear incident descriptions, estimate incident impact, and suggest root cause faster than ever.
I am incredibly proud to see what our product team has developed. I am excited to see what our Generative AI roadmap will bring as we identify even more ways to enhance Automated Incident Analysis and strengthen other BigPanda capabilities with generative features.
Discover what’s possible with BigPanda Generative AI
Generative AI lets ITOps teams sift through the noise to find untapped AI value and makes incident management more accurate, more consistent, and radically faster. If you’re curious to learn what Generative AI Automated Incident Analysis could do for you and your organization, I encourage you to attend our webinar or contact us to schedule a demo to speak specifically to your use case. See for yourself how we did it or give it a try – and get ready to level up your business and ITOps teams with exceptionally accurate, reliable and faster incident analysis.