The basics of the AI Ops offering
The service AIOPS Cloud Temple doesn’t just monitor: it takes action. It is an operational intelligence platform designed as a Virtual Site Reliability Engineer (vSRE) which works round the clock alongside your teams.
By grounding the power of generative and predictive AI models in the reality of our Intelligent Hybrid CMDB, the service provides “contextual awareness” of your information system. It goes beyond simple alerts to ensure the Self-Healing (self-repair) of common incidents — autonomous execution in Stackfull, support for teams in Stackless (by default) — reducing operational noise and freeing your human experts from the strain of unnecessary on-call duties.
Designed for production engineers and Site Reliability Engineers (SRE), AIOPS integrates natively with ITSM tools: it acts as a co-pilot which interfaces with tickets to provide context, suggested solutions and automation of administrative tasks. It does not replace the expert — it enhances their work, leaving them to focus on high-value technical troubleshooting.
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The Benefits of Cloud Temple’s AI Ops offering
Responsiveness & Self-Healing
Shifting from a ticket-based approach to a resolution-based approach.
Depending on the mode selected, the AI either suggests (Stackless) or automatically applies (Stackfull) known patches within seconds, drastically reducing MTTR.
Reducing Cognitive Fatigue
Noise filtering
By filtering out noise from 90% and managing the current “run”, AIOPS frees up your senior engineers’ time.
Operational Calm
From reactive to proactive
Transforming a “firefighter” (reactive) approach into an ‘architect’ (proactive) approach through the early detection of anomalies.
Passing on skills
AI as a catalyst for skills development
AI shares the expertise of senior engineers with junior staff by suggesting best practices and tried-and-tested runbooks.
Key features of the AI Ops offering
Contextual Correlation
Intelligent aggregation of alerts by topology to put a stop to “alert storms”.
AI-assisted RCA
Automatic identification of the faulty component (Root Cause Analysis) within the dependency chain.
Semantic Parsing
NLP analysis of backup and batch logs to understand the meaning of errors (beyond just the return codes).
Anomaly Detection
Learning baseline behaviours and alerting to subtle deviations.
Self-healing Engine
Execution of autonomous repair scenarios (reboot, clean, restart) protected by safeguards — Stackfull mode ; in Stackless, execution remains the responsibility of the teams.
Automated Sorting & Routing
Instant categorisation of the incident and routing to the right team or expert, eliminating errors caused by manual re-routing.
Proposed solutions (Context Awareness)
Cross-reference the incident against the knowledge base and the history of resolved tickets to suggest tried-and-tested runbooks and probable causes.
Technical specifications
Do you need to automate your IT operations?
Find out how AIOps helps your teams reduce alert noise, speed up root cause analysis and improve the reliability of your operations through AI-enhanced monitoring.
Our experts will work with you to assess how AIOps can be integrated into your environment and to determine the deployment approach best suited to your needs.
Use cases
AIOps is an operational intelligence platform that applies artificial intelligence to IT operations in order to improve monitoring, incident analysis and the automation of operations. It utilises an intelligent hybrid CMDB to provide context for events and support operations teams.
The service is aimed at operations teams, production engineers, Site Reliability Engineers (SREs) and CIOs looking to improve service quality and reduce repetitive operational tasks.
No. AIOps acts as a co-pilot for IT teams. In Stackless mode, it supports engineers by providing analyses, recommendations and suggested solutions. In Stackfull mode, it can execute remediation scenarios in line with ITSM processes.
AIOps integrates natively with leading monitoring solutions (Nagios, Centreon, Prometheus, Zabbix), ITSM tools such as ServiceNow and Jira, as well as Azure, AWS and VMware environments.
The service automatically correlates alerts, identifies root causes, enriches tickets with contextual information, suggests appropriate runbooks and automates certain administrative tasks in order to speed up diagnosis and reduce the mean time to resolution.
Yes. AI model inference is carried out on SecNumCloud-certified infrastructure in France. The data is hosted in Cloud Temple data centres and remains isolated for each client.
Yes, when Stackfull mode is enabled. In this mode, AIOps can execute predefined remediation scenarios under ITSM governance. In Stackless mode, it merely provides recommendations and leaves the execution to the teams.