BigPanda announced Generative AI for Automated Incident Analysis, a new capability that uses advanced AI to estimate incident impact, suggest likely root causes, and provide clear, natural language incident titles and summaries.
BigPanda’s Generative AI taps into large language model (LLM) technology to automatically and quickly deliver accurate and consistent incident analysis that is easy to understand, reduces mean time to identify (MTTI), and vastly improves incident resolution speed.
ITOps teams often struggle to quickly analyze incidents and determine their impact on the tech stack. Identifying the probable root cause is time- and resource-intensive, even when specialists are available. Further, critical insights and details hidden in lengthy and complex alerts often go unnoticed, causing downstream staff and systems to struggle when incident details are poorly communicated or described. BigPanda Generative AI eliminates these common pain points with clear and concise incident analysis that gives ITOps teams clear visibility so they can act quickly and reduce downtime.
“We were already the leader in intelligent IT Operations — AIOps — and the latest innovations in Generative AI have taken our platform to a new level,” said Assaf Resnick, CEO and co-founder of BigPanda. “Customers that have used early versions of our Generative AI report it helps accelerate incident triage while reducing the number of tickets escalated to senior staff. This results in not just saved resources, but makes their systems more reliable and helps drive their businesses forward.”
The Future of AIOps is Here Today
BigPanda’s Generative AI combines AI with correlated and enriched alerts to deliver an accurate interpretation — natural language summaries — of combined alerts across multiple systems. The correlated alerts’ summary, title, and root cause analysis can automatically be added to ITSM tickets or chat collaboration channels with specific L2/L3 teams without manual intervention.
Key benefits include:
- Faster incident resolution, fewer escalations, and ITSM tickets
- Reduced reliance on skilled staff for incident analysis
- Standardized communication across all stakeholders
- Up to seven minutes saved per ticket during an escalation
- Accurate causality 95% of the time (during beta testing)
“BigPanda’s AI-powered Generative AI empowers our ITOps teams by providing faster incident detection and independent resolution using generative AI,” said Jeremy Talley, lead operations engineer at RHI. “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.”
The Latest
Broad proliferation of cloud infrastructure combined with continued support for remote workers is driving increased complexity and visibility challenges for network operations teams, according to new research conducted by Dimensional Research and sponsored by Broadcom ...
New research from ServiceNow and ThoughtLab reveals that less than 30% of banks feel their transformation efforts are meeting evolving customer digital needs. Additionally, 52% say they must revamp their strategy to counter competition from outside the sector. Adapting to these challenges isn't just about staying competitive — it's about staying in business ...
Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey ...
SLOs have long been a staple for DevOps teams to monitor the health of their applications and infrastructure ... Now, as digital trends have shifted, more and more teams are looking to adapt this model for the mobile environment. This, however, is not without its challenges ...
Modernizing IT infrastructure has become essential for organizations striving to remain competitive. This modernization extends beyond merely upgrading hardware or software; it involves strategically leveraging new technologies like AI and cloud computing to enhance operational efficiency, increase data accessibility, and improve the end-user experience ...
AI sure grew fast in popularity, but are AI apps any good? ... If companies are going to keep integrating AI applications into their tech stack at the rate they are, then they need to be aware of AI's limitations. More importantly, they need to evolve their testing regiment ...
If you were lucky, you found out about the massive CrowdStrike/Microsoft outage last July by reading about it over coffee. Those less fortunate were awoken hours earlier by frantic calls from work ... Whether you were directly affected or not, there's an important lesson: all organizations should be conducting in-depth reviews of testing and change management ...
In MEAN TIME TO INSIGHT Episode 11, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Secure Access Service Edge (SASE) ...
On average, only 48% of digital initiatives enterprise-wide meet or exceed their business outcome targets according to Gartner's annual global survey of CIOs and technology executives ...
Artificial intelligence (AI) is rapidly reshaping industries around the world. From optimizing business processes to unlocking new levels of innovation, AI is a critical driver of success for modern enterprises. As a result, business leaders — from DevOps engineers to CTOs — are under pressure to incorporate AI into their workflows to stay competitive. But the question isn't whether AI should be adopted — it's how ...