Unlocking Context-Aware Network Observability with New AI & Integrations

In today’s hybrid, AI-embedded, and fast-moving IT environments, the biggest visibility gaps aren’t caused by outages, but by missed connections and poor decision making context. A slow app may look healthy until you trace it to a failing switch, or a degrading service could go unnoticed until it impacts your customer’s pocketbook.

That's why Splunk’s new releases deliver observability that is as focused on outcomes as it is uptime.

With integrations, event intelligence, and observability for AI, teams can unlock network-aware business visibility across the stack and the rest of Cisco to solve the right problems, fast. Whether troubleshooting a dropped packet or monitoring AI-enabled apps, Splunk equips teams to streamline root cause analysis with less manual effort and more contextual troubleshooting.

Correlated Network Visibility with IT Service & Business Health

A slow checkout isn’t just an app problem, just like a dropped packet isn’t only a network issue. The organizations of tomorrow need connected visibility across networks, services, and app layers in a way that doesn’t just show degradation, but why it matters to the business and how to fix it. From AI-powered event correlation to unified observability across AppDynamics, ThousandEyes, ITSI, and more: our latest innovations deliver earlier, more accurate detection that transforms observability into intelligent decision making no matter where problems arise.

ITSI + ThousandEyes Integration

The new ThousandEyes integration brings together events, alerts and metrics data from ThousandEyes into ITSI. This helps identify problematic network and app synthetic tests, accelerate troubleshooting and understand services contributing to the business’ health.

This helps teams answer questions like: Are any upstream CDN or ISP bottlenecks impacting our customer-facing services? Which regions or customers segments are impacted by packet loss or latency, and how?

ITSI Content Pack for Enterprise Networks

Expand observability across your hybrid network environments with deep visibility into campus and branch networks via Catalyst Center managed device and interface health, and Meraki-managed infrastructure (including switches, gateways, and access points), all correlated with IT service metrics to identify the most business-critical network issues, pinpoint root cause and restore services quickly.

Splunk Observability Cloud integration with ThousandEyes

Network and application engineering teams now gain unified visibility across Splunk Observability Cloud and ThousandEyes, to quickly understand if issues are stemming from poor app or network performance, reducing finger-pointing and improving collaboration to solve issues faster.

Unified Observability (across AppDynamics & Observability Cloud)

You don’t have to settle for siloed monitoring with a unified troubleshooting experience across AppDynamics and Observability Cloud, we’re reducing complexity for teams managing both modern and legacy workloads.

Unified Observability Experience

Splunk Observability Cloud and Splunk AppDynamics provide a seamless troubleshooting experience, reducing complexity and streamlining root cause analysis for teams managing both modern and legacy workloads in three-tier & microservice environments.

AppDynamics DEM Session Replay

Access a detailed, visual replay of real customer actions correlated with comprehensive performance metrics to reveal how user behavior impacts web & mobile applications, and contributes to issues. This feature empowers teams to troubleshoot hard-to-reproduce issues, optimize user journeys, and gain actionable insights into both user experience and security events.

Observability for AI

AI systems introduce new telemetry layers and complexity across the stack. Organizations need turnkey visibility into how AI workloads behave, perform, and impact downstream systems. From monitoring AI infrastructure, to tracking model interactions, or querying performance using agentic AI – we’re delivering purpose-built observability for AI-enabled systems all from within Splunk Observability.

Monitoring for AI Infrastructure in Observability Cloud (In Preview)

Provides real-time component monitoring of AI-orchestrators, vector databases, app platforms, cloud model platforms, base language models and model computation infrastructure, so teams can manage performance and scale of their GenAI platforms.

This helps teams answer questions like: which resources are over or under utilized? Where do component bottlenecks exist? Which components are failing or where are requests being queued from?

Trace-Level Integration for AI-enabled Apps in Observability Cloud (In Preview)

LLM service monitoring provides deep visibility into all AI-application transactions, so you can understand which ones are healthy, the root causes of performance problems, and attain your service level objectives.

AppDynamics LLM Monitoring (In Preview)

Monitor GPU infrastructure, LangChain orchestration, and vector database performance – and correlate with AppDynamics and Splunk APM for complete model-aware observability.

AI in Observability

While observability for AI focuses on monitoring the AI stack, observability powered by AI transforms how teams investigate and respond to incidents. These innovations bring powerful AI Assistance into root cause analysis, anomaly detection, and event correlation to reduce toil and deliver faster, more accurate detection and remediation.

AppDynamics Anomaly Detection for Databases

Automatically surface database anomalies before they impact Business Transactions. ML-powered detection requires no manual configuration or manual thresholds to auto-detect and alert on Calls per minute (CPM), Number of connections, and Time spent in execution metrics. Tunable AI-driven alerting allows you to set model sensitivity to meet business needs and reduce noise.

AppDynamics Root Cause Analysis (RCA) for Infrastructure

Automatically identify and pinpoint the root cause of infrastructure degradation impacting app performance. Empower every team, from platform engineers to junior SREs with recommendations to resolve problems faster.

This helps teams answer questions like: Was the change in our app performance caused by infrastructure, code, or the network? Which component introduces the biggest impact on performance?

AppDynamics VA (On-Prem) – Automated Transaction Diagnostics

AI-powered analysis contextually examines hundreds of transaction snapshots to surface anomalies, and makes it easier to reduce MTTR across on-prem workloads.

EventIQ

AI-driven alert correlation helps ITOps teams dynamically filter out noise, group related events, and highlight critical incidents that require immediate attention. With the ability to dynamically infer interesting fields, further configure event correlation conditions and plain-text explainability, it’s now easier and faster for teams to focus on what matters the most.

This helps teams answer questions like: What performance problems are the most urgent, and what’s the most probable root cause? Are these incidents isolated or part of broader service health issues? Which incidents should bubble up to our exec dashboard?

Don’t forget – experience your observability data in a new, less querysome way, with Splunk’s recently released AI Assistant in Observability Cloud: Powered by agentic AI technology, the AI Assistant in Observability Cloud is ready to help answer questions about your cloud application and infrastructure. Type in your prompts and the AI Assistant will analyze your logs, metrics, and trace data in seconds, surface key insights about potential root causes or performing gaps, and provide suggested actions to troubleshoot IT incidents. This AI Assistant is available in select realms in the US, Australia, and Europe.

Get more details here, and check out this video on how you can use the AI Assistant to debug problems in Kubernetes more quickly.

Intelligent Outcomes, with Uptime

With deeper integrations across Cisco platforms, AI-embedded insights, and visibility tailored for AI workloads, Splunk helps turn your observability best practices into an engine for intelligent decision-making. Whether managing complex hybrid environments, deploying LLMs, or troubleshooting a dropped checkout, these innovations are ready to help you find the signal, act faster, and stay ahead of what’s next.