Cisco announced agentic AI-powered Splunk Observability, an AI-native approach to observability that defines how customers can strengthen their resilience. The 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 organisations 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.”
The new 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:
- AI Troubleshooting Agents: Offered in Splunk Observability Cloud and Splunk AppDynamics, these agentic AI features automatically analyse incidents and surface potential root causes, helping users to quickly act on issues.
- Event iQ: Offered in Splunk IT Service Intelligence (ITSI), Event iQ helps teams easily set up automated alert correlation to quickly reduce alert noise and gain clear context on grouped alerts.
- ITSI Episode Summarisation: In conjunction with AI-driven alert correlation through Event iQ, Episode Summarisation in Splunk ITSI automatically provides overviews of grouped alerts, including trends, impact and root cause, to help troubleshoot faster.
Observability for AI to Monitor The Performance of AI Agents, LLMs, and Infrastructure
As organisations integrate AI and large language models (LLMs) into their applications and deploy AI agents, they need specialised 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:
- AI Agent Monitoring: Monitors the quality, security, and cost of LLMs and AI agents to determine whether models are performing at the right price and as intended, to align with business goals.
- AI Infrastructure Monitoring: Proactively monitors the health and consumption of AI infrastructure by alerting on bottlenecks and spikes across services to manage costs.
“Through the new agentic AI innovations within Splunk Observability, Cisco offers organisations more proactive visibility and actionable insights into both their digital operations and AI system health and performance,” said Torsten Volk, principal analyst, Application Modernisation, Enterprise Strategy Group.
“These kinds of capabilities are critical as enterprises look to scale AI in a controlled and reliable manner.”
