Cognitive Observe Manager
Cognitive Observe Manager
Seaford is an AIOPs potentiality that perceives the well-being of varied infrastructure elements, applications, and services. It collects organized and unorganized data from unique infrastructure sources including physical machines, virtual machines, containers, servers, databases, applications, and business services. It employs extensive learning techniques to detect events, incidents, anomalies, and complex event processing to spot explicit IT problems and their root causes.
Cognitive skills help in interpreting the data, remembering team goals, paying attention during an important meeting, and more. It has high-speed processing that quickly interprets information and applies it to a certain task. The strengthening skill of this process helps in improving productivity efficiently and effectively.
Features: Cognitive Observe Manager
Log and KPI collection Solutions
Gathers KPIs and logs from different IT origins including virtual machines, servers, containers, clusters, pods, micro-services, databases, and business services.
Dynamic threshold and pattern matching
Able to find the divergence and irregularity from KPIs and logs using AI-based dynamic thresholding and pattern matching approach.
Log and KPI anomaly detection
Using neural networks and extensive learning methodology to discover anomalies from log streamlet and single variate/multivariate KPIs.
Contextualization, incident reduction, and causal analysis
Advanced machine learning-based clustering and complex occurrence processing systems minimize noise events and point to an actual complication with root causes. Machine learning-based clustering and occurrence processing can detect anomalies and patterns missed by traditional methods, providing deeper insights and process improvements.
Log analytics and visualization with anomaly overlay
Helps you to explore and envisage log details from different IT infrastructure elements and components with overlaid anomalies and inaccuracy patterns.This enables organizations to identify potential issues quickly and take proactive measures to optimize their IT operations, improve system reliability, and enhance the user experience.
KPI analytics and visualization with event and anomaly overlay
Accredit you to examine and envision KPIs, anomalies, events, and different IT infrastructure components into a graph or heat map.Accredit you to examine and envision KPIs, anomalies, events, and different IT infrastructure components into a graph or heat map. This provides organizations with a comprehensive view of their IT operations.
Advanced analytics capabilities
Cognitive Observe Manager has advanced analytics capabilities that enable organizations to gain a holistic view of their operations, make more informed decisions, and achieve better business outcomes. It helps organizations gain deeper insights into their operations, identify potential issues, and make data-driven decisions to optimize their performance. Additionally, Cognitive Observe Manager can help organizations detect and mitigate potential risks .
Dynamic and runtime cloud native topology
Aid you to model the process using runtime dynamic graph-based technology for better causal analysis and occurrence reduction. By utilizing this technology, organizations can gain deeper insights into their processes, identify potential bottlenecks, and optimize operations for increased efficiency. With the ability to visualize the entire process flow in real-time, they can proactively identify issues and take corrective actions to minimize downtime and reduce costs.
Multi-source data integration
Cognitive Observe Manager can integrate data from multiple sources, such as IT systems, social media, and other external sources. This enables organizations to monitor their operations from a variety of angles and gain a comprehensive view of their performance. Overall, the ability of Cognitive Observe Manager to integrate data from multiple sources is a critical feature that enables organizations to gain a deeper understanding of their operations and drive better business outcomes. This information can then be used to optimize processes.