In today’s world of hybrid environments and AI-driven applications, networks are more distributed, complex, and mission-critical than ever. AI systems require rapid, uninterrupted access to data, but most networks aren’t equipped to keep pace—leading to costly disruptions. The Cisco 2025 Networking Research report notes that 77 percent of IT leaders surveyed report major outages in the last two years. That’s a big hit to revenue, productivity, and growth.
To ensure resilience, security, and performance, organizations need more than just visibility—they need integrated, AI-augmented network observability and assurance focused on the user experience.
Observability vs. assurance: Why you need both
- Observability helps you see and understand: It provides telemetry and context about what’s happening across your infrastructure, applications, and services—collecting metrics, logs, events, and traces to understand system health and behavior. This enables teams to monitor key performance indicators (KPIs) like latency, throughput, and error rates, and diagnose issues before they escalate.
- Assurance helps you maintain consistent performance: It verifies that your network and services are working as intended. Assurance uses policy, automation, and telemetry to detect issues, ensure Service Level Agreements (SLAs) are met, and proactively optimize performance.
Together, observability and assurance enable digital resilience—your organization’s ability to withstand, detect, and recover from disruptions in real time. In a technical landscape filled with AI services, multi-cloud architectures, and globally distributed users, resilience is not optional—it’s the outcome that, more than ever, matters most.
Cisco’s unified vision for assurance and observability
At Cisco Live 2025 in San Diego, Cisco unveiled the next chapter in its strategy: a Unified Cloud Platform that brings together networking, security, observability, and AI.
Unified Cloud Platform (Meraki + Catalyst + AI)
Cisco is simplifying infrastructure management by merging Meraki and Catalyst networks under one AI-powered dashboard, with deep integration across:
- Campus, WAN, Data Center, and Industrial IoT
- Cisco ThousandEyes for end-to-end visibility and assurance
- Cisco XDR for security telemetry
- Cisco AI Assistant and Cisco Canvas for natural language insights and network-wide visualizations
Why it matters: This platform breaks down silos across domains and tools (à la DevOps), reduces complexity for IT teams, and enables consistent policy, visibility, and automation from the access layer to the cloud edge.
Cisco is focused on delivering a ‘Unified, Simplified, and Future-ready’ experience. And it’s not just about better visibility or automation—it’s about enabling resilient digital operations at scale.
Observability in the AI era: powered by Splunk and ThousandEyes
Splunk has moved beyond the acquisition phase to become the backbone of Cisco’s resilience-first observability strategy. Meanwhile, ThousandEyes remains Cisco’s flagship assurance platform, validating performance from the end user all the way to the cloud.
Recent integrations and innovations include:
- Splunk + ThousandEyes Integration: As detailed in this Cisco Blog, this bidirectional integration brings together observability (via Splunk) and assurance (via ThousandEyes), connecting insights across the full digital stack—from application, to infrastructure, to network.
- Splunk IT Service Intelligence (ITSI) + ThousandEyes integration: Provides AI-driven event correlation and service health monitoring with enriched network insights, enabling faster root cause analysis and proactive incident management.
- Cisco ThousandEyes App for Splunk: Allows vivid, impactful visualization of ThousandEyes data within Splunk dashboards, delivering rapid insights and unified operational views.
- Splunk Machine Learning Toolkit 5.6: This update enables seamless connection to external large language models (LLMs) from providers like OpenAI, Anthropic, Google Gemini, Amazon Bedrock, Groq, or local models such as Ollama—directly within the Splunk search interface. This empowers analysts at all skill levels to ask natural language questions, generate summaries, surface trends, and explore data without writing complex queries or sifting through logs.
- AI and LLM Monitoring in AppDynamics and Splunk Observability Cloud: Cisco has enhanced real-time monitoring capabilities across AppDynamics and Splunk to support generative AI platforms—covering orchestration layers, foundational models, and cloud infrastructure. These tools now provide deep observability into model behavior, latency, errors, and data drift in production environments, helping IT and engineering teams ensure performance and scalability of AI services.
Why it matters: These innovations are about more than monitoring — they ensure that even as complexity grows, IT teams maintain the clarity and control needed to keep users connected, services performing optimally, and risks mitigated.
With Splunk, Splunk Observability Cloud, and AppDynamics, IT teams gain deep telemetry, correlated insights, and full-stack context across infrastructure, applications, and AI services—delivering advanced observability. With ThousandEyes, they validate performance across networks, cloud paths, and user experiences—providing assurance. Together, these tools offer the clarity, confidence, and control needed to operate resilient, AI-powered infrastructures at scale.
See more:
- Cisco and Splunk: Strengthening Digital Resilience in the AI Era
- Unified Observability: Splunk Meets ThousandEyes
Learn the skills that power this vision
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Start your journey toward digital resilience
Cisco has turned its bold vision into reality—offering a single-pane-of-glass platform that uses AI and telemetry to deliver end-to-end visibility, proactive insights, and closed-loop assurance.
Whether you’re troubleshooting performance, deploying AI models, or managing a hybrid environment, network observability and assurance are your foundation for success—and digital resilience is the outcome.
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