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By Sam Osborn
Picture a familiar scene: a critical application goes down during peak business hours, and your on-call engineers scramble to restore service. Two weeks later, the same application fails again, frustrating your teams with the same symptoms, the same scramble, and the same customer frustration. If this pattern feels familiar, your organization may be strong at IT incident management, but underinvested in IT problem management.
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By Sam Osborn
Enterprise IT has reached an inflection point. Your teams are responsible for hybrid cloud infrastructure, microservices, third-party dependencies, and shipping AI-generated code at unprecedented velocity. IT environments are becoming more complex faster than traditional tools and processes can keep pace. Alert volumes keep climbing. Institutional knowledge keeps walking out the door. And the pressure to do more with flat or shrinking budgets isn’t letting up.
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By BigPanda
Mean time to resolution (MTTR) measures the average duration to restore regular operation for an application, service, or infrastructure component. It’s a key performance indicator (KPI) for IT incident management. To tie MTTR directly to customer satisfaction, you first need to understand how it affects service and application reliability and availability. From there, you can make informed decisions, operate efficiently, and provide a seamless customer experience.
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By Carlos Gutierrez
Agentic IT operations have arrived. It’s no longer a question of if enterprise IT departments will adopt agentic ITOps, but how quickly. Every year, IT environments grow more distributed, complex, and difficult to monitor with legacy tools and processes. At the same time, the pace of AI development is accelerating the volume of changes and incidents, straining teams that are still trying to manage them manually, reactively, and one alert at a time.
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By Rachel Pearson
Enterprise IT operations leaders are realizing that legacy incident management processes cannot keep pace with today’s sprawling, hybrid-cloud enterprise environments. Enterprise IT doesn’t look anything like it did even five years ago. Hybrid cloud architectures, distributed microservices, and increasingly rapid CI/CD cycles have increased the speed and complexity of IT operations by orders of magnitude, leaving ITOps teams struggling to keep up.
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By Sam Osborn
Enterprise ITOps leaders are realizing that legacy incident management processes are collapsing under the weight of today’s sprawling, hybrid-cloud enterprise environments. Monitoring and observability tools generate a relentless flood of alerts across cloud platforms, infrastructure, applications, and services. The signals are there, the volume of noise makes it harder than ever to identify what’s urgent.
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By Travis Carlson
When an incident occurs, an L2/3 engineer or SRE can spend 20–30 minutes investigating across alert consoles, combing through change records, and pinging teams on Slack or Microsoft Teams. When you multiply that time spent across thousands of incidents per year by the cost of an IT outage at $14,056 per minute, the cost is staggering. Enterprises can’t afford to waste time searching across disparate tools.
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By Katie Petrillo
We recently brought together IT operations leaders from across financial services, healthcare, airlines, media, and other industries for BigPanda 26, our annual customer event. The theme that emerged above all others during the event’s conversations is that our industry is no longer debating whether AI belongs in ITOps. The debate now is about how quickly it can be implemented, how to measure it, and who’s accountable when it acts. Here are some key learnings from BigPanda 26.
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By BigPanda
Imagine you’re in the middle of a critical project, and suddenly, your system crashes. Or it’s the middle of the night, and your server goes down, affecting countless users. While no enterprise can avoid all IT incidents, how you handle them can significantly reduce their impact. Fast, effective IT incident management is critical, as major incidents are increasingly costly.
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By Nathan Bao
Every enterprise IT leader facing the spiraling complexity of modern IT environments has a version of the same conversation. How can we manage the increasing complexity of more services, more dependencies, and more layers of observability and monitoring? Their answer would add headcount to the NOC, sign another Global System Integrator contract, and buy your organization another year.
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By BigPanda
Alert correlation solved the noise problem. But noise was never the whole problem. Today’s most disruptive incidents cascade across networks, infrastructure, applications, and services simultaneously, without clear visibility into the true root cause. As a result, L1 teams are left manually piecing together context from multiple dashboards and tools to find the primary root cause while SLA clocks keep ticking and end user tickets add up.
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By BigPanda
AI incident assistant from BigPanda gives L2, L3, and SRE teams instant answers to resolve incidents faster without manual triage or tool-switching. IT teams lose critical minutes during incidents because context is scattered across Slack threads, bridge calls, monitoring tools, and historical tickets. The BigPanda AI Incident Assistant fixes that by surfacing relevant knowledge exactly when and where responders need it. It gives responders evidence-based resolution paths drawn from historical incidents and live system data, without leaving your workflows.
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By BigPanda
AI Incident Prevention from BigPanda stops change-related outages before they occur by leveraging risk scores, trend analysis, and guided remediation steps. Manual IT changes are still a leading cause of IT outages and disruptions. BigPanda AI Incident Prevention addresses this by automatically scoring change requests against historical data, flagging high-risk changes before they go live, and surfacing the recurring problems that cause service degradation.
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By BigPanda
AI ticket assignment, automated. See how BigPanda L1 Agent routes incidents to the right team in seconds. Enterprise IT teams spend the bulk of L1 capacity on manual triage — connecting fragmented context across tools and routing incidents that often land on the wrong team anyway.
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By BigPanda
The best incident is one that never happens. The BigPanda team recorded a live demo of the AI Incident Prevention & AI Incident Assistant as part of ITSM Week, hosted by the Service Desk Institute. ITSM teams are measured by how effectively they prevent disruption. Yet many teams still spend too much time reacting to noisy, low-context incidents after impact has already begun. Watch this on-demand session to learn how leading organizations are moving beyond manual firefighting to autonomous operations with Agentic AI.
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By BigPanda
Most AI tools recommend the next step. BigPanda's AI specialists take it — autonomously, inside ServiceNow and Now Assist. Watch how BigPanda and ServiceNow work together to detect, triage, investigate, and resolve incidents end-to-end.
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By BigPanda
In a crowded MSP market, standing out takes more than great service. See how BigPanda customers are using AI-driven operations to differentiate their offerings, boost profitability, and maximize their ServiceNow investment.
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By BigPanda
When a problem spans multiple domains, L1 teams only see part of the story. BigPanda incident correlation connects the dots automatically, identifying how incidents relate across teams and systems, surfacing the blast radius, and pointing directly to the root cause so teams can triage faster and escalate smarter.
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By BigPanda
When end-users report a problem, L1 teams shouldn't have to manually connect the dots. Service desk correlation automatically correlates service desk tickets with active BigPanda incidents, surfacing end-user impact instantly so teams can prioritize and triage with the full picture.
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By BigPanda
Autonomous operations based on AI lets IT operations teams quickly identify the root cause of incidents in today's hybrid computing environments. Learn how to evaluate AIOps solutions and pick the one that best meets the needs of your organization.
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By BigPanda
Stretched thin and relying on legacy IT Ops tools, IT Ops, NOC and DevOps teams are unable to effectively support today's highly complex, dynamic IT stack. This is causing a rising tide of outages, poor app performance and service disruptions. What's the answer? AI and ML-driven IT Ops automation.
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By BigPanda
Grounded in the latest market research, this new report, The Modern NOC: IT Ops Predictions for 2018, features 9 key predictions for our industry. Whether you are an executive, manager or engineer, this report examines issues and trends that affect the enterprise at all levels.
- July 2026 (7)
- June 2026 (4)
- May 2026 (3)
- April 2026 (4)
- March 2026 (5)
- February 2026 (2)
- January 2026 (3)
- December 2025 (4)
- November 2025 (2)
- October 2025 (8)
- September 2025 (6)
- August 2025 (1)
- July 2025 (1)
- June 2025 (4)
- May 2025 (2)
- April 2025 (3)
- March 2025 (2)
- February 2025 (11)
- January 2025 (9)
- December 2024 (4)
- November 2024 (6)
- October 2024 (10)
- September 2024 (9)
- August 2024 (8)
- July 2024 (10)
- June 2024 (6)
- May 2024 (5)
- April 2024 (5)
- March 2024 (8)
- February 2024 (4)
- January 2024 (8)
- December 2023 (11)
- November 2023 (9)
- October 2023 (9)
- September 2023 (2)
- August 2023 (3)
- July 2023 (4)
- June 2023 (3)
- May 2023 (3)
- April 2023 (5)
- March 2023 (11)
- February 2023 (8)
- January 2023 (6)
- December 2022 (4)
- November 2022 (2)
- October 2022 (6)
- September 2022 (10)
- August 2022 (14)
- July 2022 (1)
- June 2022 (6)
- May 2022 (4)
- April 2022 (4)
- March 2022 (5)
- January 2022 (1)
- December 2021 (2)
- November 2021 (5)
- September 2021 (1)
- July 2021 (2)
- June 2021 (3)
- May 2021 (4)
- April 2021 (2)
- March 2021 (8)
- February 2021 (5)
- January 2021 (1)
- December 2020 (15)
- November 2020 (4)
- October 2020 (5)
- September 2020 (2)
- August 2020 (1)
- July 2020 (2)
- June 2020 (5)
- May 2020 (3)
- April 2020 (4)
- March 2020 (2)
- February 2020 (3)
- January 2020 (1)
- December 2019 (3)
- November 2019 (2)
- October 2019 (7)
- September 2019 (4)
- August 2019 (4)
- July 2019 (4)
- June 2019 (3)
- May 2019 (7)
- April 2019 (5)
- March 2019 (3)
- February 2019 (3)
- January 2019 (2)
- December 2018 (2)
- November 2018 (5)
- October 2018 (6)
- September 2018 (1)
- August 2018 (1)
- July 2018 (2)
- June 2018 (1)
- May 2018 (2)
- March 2018 (1)
- November 2017 (2)
- September 2017 (1)
- April 2017 (1)
BigPanda Autonomous Operations platform helps IT Ops, NOC and DevOps teams detect, investigate, and resolve IT incidents faster and more easily than ever before.
Powered by Open Box Machine Learning, BigPanda correlates IT noise into insights, automates incident management, and unifies fragmented IT operations. Customers such as Intel, TiVO, Turner Broadcasting and Workday rely on BigPanda to reduce their operating costs, improve service availability and performance, and de-risk and accelerate their digital transformation initiatives. Founded in 2012, BigPanda is backed by top-tier investors including Sequoia Capital, Mayfield, and Battery Ventures.
The intelligent automation your IT Ops team always wanted:
- Correlate: BigPanda's Autonomous Operations platform intelligently correlates alerts from all your monitoring, topology, change and other tools into a handful of context-rich incidents. This lets your ops teams quickly and easily focus on what matters the most to your customers and your business.
- Automate: BigPanda's Autonomous Operations platform intelligently automates responses to your IT incidents across their lifecycle. This lets your ops teams handle more incidents faster and more effectively than ever before.
- Streamline: BigPanda's Autonomous Operations platform intelligently streamlines workflows across your Level 1, 2 and 3 team members, and across your ticketing, service desk and collaboration tools. This lets your ops team rapidly resolve incidents, before they affect your customers and your business.
Autonomous Digital Operations. Intelligent Automation for IT Incident Management.