Cisco Supercharges Observability with Agentic AI for Real-Time Business Insights

Cisco announced agentic AI-powered Splunk Observability, an AI-native approach to observability that sets a new standard for how customers can strengthen their resilience. The enhanced Splunk Observability portfolio unifies observability across environments, surfaces actionable business context, and deploys AI-powered agents across the full incident response lifecycle, while monitoring both its performance and quality. Through integrations across Cisco technologies with Splunk, customers gain unmatched visibility and correlation of data insights across their networks, infrastructure, and applications to improve the reliability of their entire digital estate.

“Our mission is clear – to help organizations put AI applications and agents to work, while retaining visibility and control,” said Patrick Lin, SVP and GM of Splunk Observability. “With the latest innovations in Splunk Observability, we are empowering enterprises to proactively monitor their critical applications and digital services with ease, resolve issues before they escalate, and ensure the value and outcomes they derive from observability are commensurate with the cost.”

Agentic AI is reshaping what it takes to build a leading observability practice. As AI-assisted coding gains steam, applications will be built with less human involvement. At the same time, a new wave of AI-enabled applications and AI agents demand specialized telemetry to confirm models are performing as intended – aligned to business purpose and cost. To keep pace, organizations need unified, in-context, visibility across all of these environments to prioritize issues based on business impact.

Agentic Al-powered observability: proactive detection, investigation and resolution

Splunk is advancing Cisco's Agenticops vision through an enhanced Splunk Observability portfolio, supercharged by new agentic AI innovations. These innovations will deploy AI agents to automate telemetry collection and alert configuration, detect issues, identify root causes, and recommend fixes – freeing ITOps and engineering teams to focus on innovation. These advancements include:

As organizations integrate AI and large language models into their applications and deploy AI agents, they need specialized analytics to help ensure their AI is behaving as intended. Splunk helps teams proactively monitor the health, security, and cost of their AI application stack, including agents, LLMs, and AI Infrastructure, with:

Cisco is bringing the best of Splunk AppDynamics and Splunk Observability Cloud together to provide a unified experience across three-tier and microservices environments, and deepening integration with Cisco ThousandEyes so ITOps, NetOps and Engineering teams can pinpoint the network's impact on application performance and end-user experience. The innovations include:

“Through the new agentic AI innovations within Splunk Observability, Cisco offers organizations more proactive visibility and actionable insights into both their digital operations and AI system health and performance,” said Torsten Volk, Principal Analyst, Application Modernization, Enterprise Strategy Group. “These kinds of capabilities are critical as enterprises look to scale AI in a controlled and reliable manner.”