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BigPanda Releases Event Enrichment Engine

BigPanda revealed the power of its Event Enrichment Engine that enriches raw alerts with rich topological and operational context to create high-quality incidents.

This key capability of BigPanda’s AIOps platform moves organizations beyond simple alert noise to turbocharging the effectiveness of event correlation, root cause analysis, and automation.

Many organizations are investing in AIOps to sift through and correlate alerts across observability and monitoring platforms to detect incidents in real-time before an incident turns into an outage. Unfortunately, many AIOps tools fail to convert raw alerts into context-rich, high-quality incidents because of their inability to easily tap and parse into all sources of contextual data that can be added to incidents as context, at scale.

“Many AIOps projects fail to live up to their promise because alerts don’t get enriched with operational, topological or other contextual data, making it difficult to separate noisy alerts from meaningful alerts, and then eliminate the noise,” said Elik Eizenberg, Co-founder and CTO at BigPanda. “Our Event Enrichment Engine is critical to improving NOC productivity and L1 resolution rates by correlating interrelated alerts into context-rich, high-quality incidents that easily describe what the problem is, what’s causing it, and what action to take.”

Cross-domain enrichment ingests and aggregates messy data across fragmented tools covering observability, monitoring, change and topology systems. These alerts are enriched with the collected topological and operational information across all technology domains, which is the linchpin for AI/ML to detect incidents in real-time as they form, surface probable root cause, and kickoff automatic workflows.

“BigPanda’s Event Enrichment Engine helps structure our event data and adds more context to alerts for our Operations team to triage issues quickly and achieve better alert compression rates,” said Samy Senthivel, Senior Digital Enterprise Monitoring Services Manager at Autodesk. “The element tagging capabilities within the Event Enrichment Engine also provide a clear correlation across events based on service topology and relationships.”

Capabilities of BigPanda’s Event Enrichment Engine include the ability to:

- Extract context buried inside incoming data streams and use it to enrich alerts

- Add topology data from external sources, including asset, inventory, orchestration, APM, configuration management and CMDB sources

- Configure, monitor and modify enrichment logic within a drag-and-drop UI

- Perform millions of enrichment actions every day

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BigPanda Releases Event Enrichment Engine

BigPanda revealed the power of its Event Enrichment Engine that enriches raw alerts with rich topological and operational context to create high-quality incidents.

This key capability of BigPanda’s AIOps platform moves organizations beyond simple alert noise to turbocharging the effectiveness of event correlation, root cause analysis, and automation.

Many organizations are investing in AIOps to sift through and correlate alerts across observability and monitoring platforms to detect incidents in real-time before an incident turns into an outage. Unfortunately, many AIOps tools fail to convert raw alerts into context-rich, high-quality incidents because of their inability to easily tap and parse into all sources of contextual data that can be added to incidents as context, at scale.

“Many AIOps projects fail to live up to their promise because alerts don’t get enriched with operational, topological or other contextual data, making it difficult to separate noisy alerts from meaningful alerts, and then eliminate the noise,” said Elik Eizenberg, Co-founder and CTO at BigPanda. “Our Event Enrichment Engine is critical to improving NOC productivity and L1 resolution rates by correlating interrelated alerts into context-rich, high-quality incidents that easily describe what the problem is, what’s causing it, and what action to take.”

Cross-domain enrichment ingests and aggregates messy data across fragmented tools covering observability, monitoring, change and topology systems. These alerts are enriched with the collected topological and operational information across all technology domains, which is the linchpin for AI/ML to detect incidents in real-time as they form, surface probable root cause, and kickoff automatic workflows.

“BigPanda’s Event Enrichment Engine helps structure our event data and adds more context to alerts for our Operations team to triage issues quickly and achieve better alert compression rates,” said Samy Senthivel, Senior Digital Enterprise Monitoring Services Manager at Autodesk. “The element tagging capabilities within the Event Enrichment Engine also provide a clear correlation across events based on service topology and relationships.”

Capabilities of BigPanda’s Event Enrichment Engine include the ability to:

- Extract context buried inside incoming data streams and use it to enrich alerts

- Add topology data from external sources, including asset, inventory, orchestration, APM, configuration management and CMDB sources

- Configure, monitor and modify enrichment logic within a drag-and-drop UI

- Perform millions of enrichment actions every day

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Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

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My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

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APMdigest's Predictions Series continues with 2026 DataOps Predictions — industry experts offer predictions on how DataOps and related technologies will evolve and impact business in 2026 ...

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