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Nitrate™ - AIOps Framework that Works

Nitrate™ leverages Artificial Intelligence (AI) and Machine Learning (ML) to understand the correlation and causality of operational incidents. It provides a holistic view of applications, analyzes the system’s health, detects anomalies, and constantly learns to keep the applications performance-optimized. Nitrate™ also has a built-in ML-driven ChatOps framework that helps teams in reducing dependencies on manual ‘search and react’ aspects of production operations.

Platforms Landscape

Problems with managing operations at cloud scale

The complexity in IT operations has drastically increased with a higher number of IT systems operated from the cloud, resulting in more ‘points of failures’ and opaque set of dependencies between the systems. The increased volume and accelerated velocity of data make it a massive task for the human workforce to comprehend and react in time to avoid any aberration. Although sophisticated monitoring tools are available to create alerts, the risk of human errors multiplies with a larger workforce trying to monitor them, which doesn’t allow them to focus on priorities.

Services Health

Leveraging AI/ML to enable auto-detection capabilities

Nitrate™ is built using AI/ML techniques and algorithms to detect potential failures and take corrective actions proactively. It enhances the operations team’s ability to increase the system availability and reduce any chance of missing out on any anomaly detection, eventually avoiding business downtime without disrupting the customer experience.

Nitrate AIOps Architecture

Focus on self-healing with AIOps

Nitrate™ is an in-house AIOps platform developed by GSPANN that provides an end-to-end solution for augmenting Support, Engineering, and DevOps teams with the capabilities of AI and ML. Along with AIOps functionalities, Nitrate™ also offers integrated Nitrate-ChatOps solution as virtual assistance or Autobots that self-heals and remediates. Nitrate’s vision is to enhance the whole monitoring system with well-trained AI/ML models to make the system smart, faster, and efficient.

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