Enhancements

1. Predictive-Analysis Enhancement

The previous version did not have the capability to display historical data, which made it difficult for users to evaluate the accuracy of the predictions.

Figure 1, Predictive-Analysis Enhancement

To solve this in Fig 1, we introduced the ability to view historical data together with predicted values. This enhancement improves accuracy through new calculations and provides users with a comprehensive dashboard. The dashboard showcases both predicted data and historical data, allowing for easy comparison and evaluation. Additionally, the dashboard includes corresponding confidence intervals, providing users with insights into trends, seasonal patterns, and outcomes.

The benefits of this enhancement include the ability for users to make informed decisions for efficient operations, enhanced accuracy, and reliability in predictions, and streamlined operations. Overall, these improvements empower users to optimize their decision-making processes and improve operational efficiency.

2. Metric Ingestion improvement Capability

The previous version did not have the capability to display historical data, which made it difficult for users to evaluate the accuracy of the predictions.

Figure 2, Metric Ingestion from NNMX

3. Alerts Optimization in CMDB Management Feature

The goal is to enrich alerts with CMDB information to the specific event or issue being flagged. This means that when an alert is generated, it will include additional information from the CMDB that is related to the problem at hand. Figure 3, Metric information in the CMDB from NNMX, which includes specific metrics such as staff name, location, series number, and more. By incorporating these additional metrics into the alerts, users can ensure that they are ingesting accurate and relevant data for analysis.

Figure 3, Alert Ingestion from NNMX

For example, by including the staff name metric in the alerts, users can easily map, and correlate alerts related to staff names. This allows for more detailed analysis and insights into various aspects of staff performance, distribution, or any other relevant factors. The availability of this additional information enriches the alerts, making them more informative and easier to understand.

4. Topology Alert Phase 2 [in Feature: Topology Map]

The CMDB Topology Map now provides enhanced visualization for CMDB connections, allowing users to easily identify connections between nodes and gain a better understanding of the network infrastructure. The new capabilities to assist users in analyzing their network connections. These tools enable users to perform relationship analyses, identify dependencies, and evaluate the impact of a connection on the overall network performance. By leveraging these features, users can gather valuable insights for network planning, optimization, and troubleshooting.

Figure 4, CMDB Topology Map

Bug Fix

– Unable to handle large topologies.

What’s New

>> NEW Features <<

Include the new feature that were added during this release.

Topology Ingestion

This feature enables the ingestion of network topology data from multiples sources, including Netka Logger(NLG) and Dynatrace, providing. This will be a valuable addition to our N-AIOPs, enabling IT teams to gain deeper insights into their IT infrastructure and optimize performance More comprehensive view of the IT infrastructure.

Key features of Topology Ingestion include:

Easy Integration: Our platform can seamlessly integrate with other platforms to ingest the network topology via webhook, ensuring a smooth and easy deployment.

Real-Time Updates: The topology network is updated in real-time, enabling IT teams to quickly identify issues and make informed decisions to optimize performance and reduce downtime.

Comprehensive Visibility: With Topology Ingestion, IT teams have a comprehensive view of the IT infrastructure, including physical and virtual networks, devices, and applications. This enables them to quickly identify and troubleshoot issues before they impact end-users.

User Interface update.
This new theme color provides a more colorful, unique, and clear look, making it easier for users to navigate the platform and access key information. The the updated theme color will be a valuable addition to our platform, improving the overall user experience and making it easier for users to access the information they need.

Key features of the updated theme color include:

Improved Clarity: The updated theme color provides better contrast and readability, making it easier for users to read text and identify important information.

Enhanced User Experience: The new theme color provides a more modern and engaging user experience, making it more enjoyable and satisfying for users to interact with the platform.

Brand Identity: The new theme color aligns with our brand identity, creating a consistent

>> BUG FIX <<
Correlation Page:

• Incorrect correlation count displayed.
• Correlated logs not appearing on the display page.

Predictive Analysis:

• Script frequently stops running.
• Script fails to create tables.

Metric Ingestion:

• Unable to create metric with same node name.
• Wrong mapping index.

Grafana Alert Rule:

• Unable to query any OpenSearch data.

What’s New

>> NEW Features <<

Include the new feature that were added during this release.

Enhance Admin Menu

The “Enhanced Admin Menu” feature provides users with the ability to add, edit, delete, and customize the menu bar in their admin menu. This feature empowers users to tailor their menu to fit their specific needs, improving their productivity and overall experience. With the ability to add new menu items, edit existing ones, and delete unnecessary options, users can streamline their navigation and focus on the tasks that matter most. Customization options include the ability to reorder menu items, change their labels and icons, and control access permissions for different user roles. Overall, the Enhanced Admin Menu feature is a valuable tool for enhancing the usability and functionality of any admin menu.

API Integration with new integration

The new integration feature allows seamless integration with other vendors, enabling users to easily migrate their existing log data and analysis workflows to the logger tool. This feature makes it easy to import notification/alert/alarm from third-party systems and applications into N-AIOps. Once the data is ingested, N-AIOps performs real-time analysis and feeds this information to the system, serving as the foundation for other features.

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
  1. Parent-Child
  2. Peer-to-Peer
  3. 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.

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

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.

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

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.