Release 1.4.0 -Jan 2023
What’s New
- CMDB admin page: In this page the user can add/edit/delete the asset node and can create the relationship between each node. There are three types of the relationships
- Parent-Child
- Peer-to-Peer
- Run-On mode, and then the topology will show only when the alert of the node is asserted.
- Metric data: In this page the user can select the metric data from each node that they want and ingest to the asset node on N-AIOps(Compatible with NNMX at this). At this time we start with five metrics, 1.CPU Utilization 2.Memory Utilization 3.Disk Utilization 4. Input Traffic 5.Output Traffic
- Alert Ingestion: In this feature the user can setup NNMX and forward the alert that they want to N-AIOps system. Note: There are 14 types of alarm which the user can set and select from NNM.
- Correlation page: In this page the user can see the data which were enriched from CMDB asset. The node which meets the alarn will be show along wiht the CMDB asset detail.
Release 1.3.0 -Sep 2022
What’s New
- Data Ingestion Integration: This allows user can easily ingest alerts, then normalize and enrich them with information to help you understand and response faster to production issues. This release we provide the integrations as below:
- Datadog: user can easily send all Datadog alerts to N-AIOps with a native integration.
- AWS CloudWatch: User can use the Amazon Simple Notification Service (SNS) to send CloudWatch Alarm data to N-AIOps.
- Azure Monitor: User can use native webhook notification channel in Azure Monitor to forward alerts to N-AIOps.
- Workflow Automation: This allows user can create automations even faster with our workflow engine. And user can also automate your repetitive task by using N-AIOps that will help you save your time
- CMDB Topology view: This release adds enhancement to this view. Now user can search information based on tag and also easily to drilldown to see alerts detail or the metric charts that related to that node.
- Predictive Analytics: This release adds enhance create view to easy to use by adding user input fields instead of configuring by using JSON format
Bugs fixed
- Fix alert Elasticsearch mapping template.
- Fix minor bugs
Release 1.2.0 -June 2022
What’s New
CMDB Topology view: this allow user can view the alerts data in topology view based on CMDB data. N-AIOps enriches alert with information from your CMDB. user can view the summary of alerts in your system. and use this panel to drill-down into detail easily.
Release 1.1.0 -Mar 2022
Features and enhancements
- Anomaly Detector Management: A detector is an individual anomaly task. In Anomaly Detector page, you can define multiple detectors, and all the detectors can run simultaneously, with each analyzing data from different sources. This enable user to easily create the anomaly detector to analyze data by themself.
- Correlation Suggestion: This feature will help user analyze historical event data and suggest the best correlation tags in their system. It helps user to reduce time to implement correlation rule in their system.
Bug fixes
- Add/Edit Correlation Table System tags can automatically update docker-compose (container : naiops-correlation-engine) data.
- Add/Edit steps Super custom tags can update information. docker-compose automatically
- Edit Suggestion correlation Enter standard deviation = 0 with tag Output NaN value
Release 1.0.2 Jan-2022
Features and enhancements
- Event Enrichment : User can enrich ingested event with additional information. Enrichment can provide more flexibility for clustering alerts as the user want.
- Event Correlation : N-AIOps aggregates, normalizes and enrich events and correlate that events into the view that user can easily actionable
- NSDX Integration : N-AIOps correlation view can integrate with NSDX. User can create an incident from the correlation view. With correlate information, it help support team to investigate & prevent incidents impact by restoring the service to normal as quickly as possible. And with automation capability on NSDX, user save a lot of time to do the repetitive tasks by using the rule-based routing to auto run the playbook when the incident is created.