Raising the Intelligence in AIOps
AIOps solutions are only as good as the data and context fed into them for model creation. Netreo’s AIOps: Autopilot integrates two decades of pragmatic use cases that have made a difference in real-world deployments when deciding how to tune your Netreo application. With Netreo, network and system administrators can spend less time tuning their NMS platforms and spend more time supporting end-users, engineering, and meeting committed service-level agreements (SLAs).
How Can AIOps: Autopilot Help My Organization?
AIOps: Autopilot builds on Netreo’s solid backbone of other AI- and ML-based technologies, such as anomalistic behavior detection, automatic dependency mapping, and event correlations.
Join us for a webinar to learn how and why AIOps: Autopilot helps your team spend more time engineering and less time fire-fighting.
View On-demand WebinarThe Technology of AIOps: Autopilot
Data Sources
Real-Time Processing
Rules and Patterns
Domain Algorithms
ML/AI
Automation
Netreo’s AIOps: Autopilot extends the capabilities of the Netreo full-stack IT management solution, which enables enterprises to easily measure the state, impact and operation of IT resources, so they can focus on their core business. The add-on works with both the on-premises and native-cloud versions of Netreo’s solution, including Netreo Cloud.
Always On. Always Analyzing.
AIOps: Autopilot runs in the background of a Netreo deployment and constantly scans the configuration to make sure it is always tuned properly. When issues or potential improvements are found, AIOps: Autopilot will either automatically fix the problem or provide engineers suggested remediations using AI and ML algorithms applied against previously gathered historical data.
AIOps: Autopilot automatically learns from every successive execution so that it can both reduce unnecessary alerts and preemptively correct more issues over time.
Extending Netreo’s Full-Stack Capabilities
AIOps: Autopilot builds on Netreo’s solid backbone of other AI- and ML-based technologies, such as anomalistic behavior detection, automatic dependency mapping, and event correlations. Although it gets better at its job the longer it runs in an environment, AIOps: Autopilot also comes with an array of extensions out-of-the-box to give operations teams a head start. These extensions provide the ability to:
Automatically baseline thresholds against historical values and exceptions to minimize false-positives and alert noise.
Model all metrics against best-practice key performance indicators (KPIs) to ensure there are no blind spots.
Learn system and environment changes, and change the monitoring infrastructure to automatically adapt.
