Turn observability into action: IBM Instana and Red Hat Ansible Automation Platform for AIOps

At Red Hat Summit 2026, I joined an AIOps panel during the Red Hat® Ansible Automation Platform product spotlight. We discussed the full AIOps journey—from the first signal, through automated resolution, to post-incident analysis.

The session opened with a question that we hear from customers every day. Observability platforms are surfacing more signals, context and intelligence than ever, and AI is accelerating that trend. The question is no longer, “What’s happening?” It is, “What happens next with all that intelligence?”

Many organizations already have the individual components: trusted playbooks, change-controlled workflows and observability platforms that generate the right signals. What they often lack is an execution layer that connects them.

That is where Red Hat Ansible Automation Platform fits. Teams can interact with the platform through APIs, Event-Driven Ansible, the web UI and the MCP server for Red Hat Ansible Automation Platform while maintaining a governed execution environment.

Better monitoring alone cannot solve the complexity of modern environments. Teams also need context that shows how services, infrastructure and changes are connected.

Instana®, through its architecture, is able to automatically discover and monitor technologies across applications, runtimes, platforms and infrastructure. Teams do not need to identify every running component or manually define all the relationships between them.

Instana discovers running entities, configures monitoring, maps dependencies and begins tracing requests. This approach gives site reliability engineering (SRE), platform engineering and IT operations teams a live view of how services, infrastructure and deployments connect without requiring weeks of manual instrumentation.

One of Instana’s latest capabilities is Intelligent Incident Investigation, powered by agentic AI. When performance degrades, it investigates relevant services, dependencies, infrastructure layers and events to identify the likely cause and impact. Adaptive thresholds learn the environment’s normal patterns, including seasonality, helping teams distinguish genuine anomalies from normal variation.

That context is the difference between an alert and an actionable response. Instana can provide the Ansible Automation Platform with information about what happened, what changed and where investigation or remediation should begin. This strategy reduces the manual effort required for initial triage.

Every IT leader faces a gap between wanting AI to act and trusting it to act. The panel agreed that confidence must be earned rather than declared.

Use a disciplined progression. Begin with humans in the loop, progress to humans on the loop, and eventually graduate proven workflows to supervised autonomy. When first connecting Instana to Ansible Automation Platform, start with a known failure pattern and insert an approval gate. A person still authorizes the action.

After a sustained period of accurate detection and successful remediation, teams can evaluate whether the approval step still adds value. This evidence-based progression from supervised execution toward greater autonomy is how trust is built in production.

Instana’s adaptive thresholds and investigation capabilities provide confidence in the signal. Ansible Automation Platform’s role-based access control, approval workflows and execution records provide confidence in the action. Automated responses run through a consistent execution environment with defined controls, logging and accountability. That consistency allows organizations to expand automation more safely.

Before automating remediation, make sure that the underlying observability data is rich enough to support a reliable decision. That includes detailed telemetry and a dependency model that shows how relevant services and infrastructure connect.

Instana delivers that automatically. When you see your environment clearly, pick one well-understood failure pattern, and wire it to an Ansible Automation Platform playbook your team already runs manually. Do not start by building new automation from scratch. Start with an Ansible Automation Platform playbook you already trust.

That first closed loop (even with an approval gate in the middle) changes the entire conversation about what is possible. It gives you the audit evidence to justify expanding, and it proves the model before you scale it.

A common use case that we see is service latency spike recovery, and it is among the costliest when handled manually. In most organizations, latency spikes sit in alert queues waiting for an on-call engineer to notice, diagnose and respond. Every minute in that queue extends the customer impact window.

By connecting Instana’s real-time detection and investigation capabilities with Ansible Automation Platform’s governed execution, teams can move from anomaly to validated remediation in four stages:

1. Detect. Instana’s adaptive thresholds detect the latency anomaly using learned baselines to distinguish genuine degradation from normal variation.

2. Diagnose. Instana investigates the probable cause across relevant services, infrastructure, dependencies and recent changes, giving the team the context needed to select an appropriate response.

3. Act.  Ansible Automation Platform executes a governed, pre-tested remediation playbook to run the proven recovery steps.. Depending on the workflow’s maturity and risk, execution can proceed automatically or pause for human approval.

4. Validate and document. After remediation, the workflow verifies whether the service recovered and records what ran, when it ran and the outcome. The resulting execution record supports operational review, governance and audit requirements.

The result is faster and more consistent remediation with a complete execution record. Mature, preapproved workflows can run automatically, while higher-risk or less-proven workflows can retain a human approval gate.

The value of AIOps does not come from detecting more problems. It comes from using reliable operational context to take the right action with the appropriate controls. By combining Instana’s automated observability and intelligent investigation with Ansible Automation Platform’s governed execution, organizations can create a more consistent path from detection to resolution.

Learn more about connecting observability, ITSM and governed automation across the AIOps stack

Read the solution guide for step-by-step guidance on joint use cases