AIOps platform for real-time operations & automation
Take all data in one place and try code-base automation
AIOps platform
Look at a new approach to IT management
Just collect the data from all sources from monitoring systems to raw logs data in the MONQ. Get a new level of reliability and awareness of the status of your services. And start intelligent data processing with event automation. Run your own automation scripts. Make sure that the systems do not fall down, and if they fall, they recover themselves.
AIOPS Platform
MONQ Features
Get all data across systems, apps, and services
Dozens of ready-made connectors allow you to configure the collection and processing of data in minutes. If your data collection system or monitoring system is not in our ready-made connectors, do not worry. Three simple steps separate you from collecting data from any system.
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See UX through customer's eyes
A predictive synthetic transaction monitoring system will allow you to learn about anomalies in the operation of your services and business processes before your customers. Robots imitate any human actions, and you get analytics and automated actions.
Take business data to predict business-critical events
Collect and collate business data with technical data. You can predict the impact of various technical infrastructure and your resources on real business. An intelligent data clustering system will give you added value by reducing the processing time of big data.
Timeline and visual data analysis
You can select the required data levels and present them for viewing on one timeline. This is very useful when you want to look at data in time to find patterns. Further, the discovered patterns can be described in templates for generating integral events.
Search by logs and primary data
Analysts can get the flow of incoming data using powerful search tools. Further, choosing the data, it is possible to form patterns for the generation of intral events, by which automation can already be configured.
Machine Learning and Intelligent Assistant
Machine learning and mathematical analysis will help you get the real value of big data. Intelligent data aggregation, anomaly search and intelligent search for the root causes of problems and events.
Calculation of element statuses based on topology
Based on the topology, we can calculate the state of those elements about which we do not know anything. Having built a mathematical model, we will be able to obtain more accurate initial data, filter out unimportant events and calculate the influence of different elements on the business level.
Incident management with external service desks
If you use your own service desk, then to simplify the incident management process, you can assign incidents, view statuses and protocols through MONQ, without going into the service desk itself. Manual creation of incidents and alerts is available, as well as in automatic mode.
Code-base creating synthetic events and triggers
Working with primary raw and unstructured data and logs, including events created by monitoring systems and BI systems, you can easily create synthetic triggers on which new events are generated. You can create triggers using scripts or using the wizard.
Rule-Based Automation and BPM
Using complex If-Then logic you can describe the rules for launching various actions, which include scripted actions, alerts by templates, setting tasks, incidents, etc.
Flexible code-based automation
Using programmable logic, you can describe the rules for launching acts that include various actions that imitate a person (for example, go to the administrative interface and put a stub on the service mode), Rest requests, or scripts on Bash and SNMP.
Knowledge base
You can find out the latest news, information on the composition of releases and project documentation in our knowledge base.