ITRS, the leading provider of real-time IT monitoring, today announces the launch of Obcerv AI to augment its application and infrastructure monitoring solutions with AIOps and observability capabilities.
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Real-time IT observability tools have traditionally applied their AIOps capabilities in Software-as-a-Service (SaaS) configurations, leading to various issues such as increased data costs and significant latency in the monitoring they offer. ITRS Labs, the company’s technology innovation hub, built Obcerv AI to address these challenges. It is the first machine learning engine for real-time monitoring that can be deployed on-premises or in your cloud with no impact on latency.
This is a game-changer for any institution that deploys its monitoring and observability on-prem for IT security or latency reasons — such as capital markets firms — whereby near-zero latency monitoring is a requirement for business-critical IT services. ITRS’s AIOps capabilities are developed centrally in Obcerv AI and made available across its entire portfolio, which can be deployed on-prem, in the cloud, or as SaaS.
“With Obcerv AI, we’re not only enhancing our product portfolio; we’re fulfilling our mission of delivering IT observability with a purpose,” says Guy Warren, Chief Executive Officer at ITRS. “For the first time, machine learning is being applied to real-time monitoring across complex hybrid environments without the usual trade-offs, such as high costs and impact on latency. We have solved the problem of needing complex software stacks to capture and analyse large quantities of data, while also making it simple to install and use on-premises. None of our competitors can do that — indeed they refuse to bring their AI engines inside the firewall. That generates the big challenges of cost to the customer and delays in analysis.”
Warren continues, “AI should be accessible and easy to use with no need to navigate through convoluted interfaces or train complex algorithms for weeks — and this is exactly how we have designed Obcerv AI. It provides a foundation on which we can build a broad set of AIOps capabilities and we’re already working on several upgrades to ensure we continually improve the experience and value we offer our customers.”
Obcerv AI aims to significantly enhance the resilience, security, and efficiency of firms’ IT operations. Its key features include:
• Dynamic thresholds – Unlike static thresholds, which are fixed and predefined, dynamic thresholds adjust in real-time to account for variations and seasonality in usage patterns. These thresholds set evolving baselines around normal operating performance, enabling smart alerting and minimising false positives.
• Noise reduction – Based on dynamic thresholds, noise reduction capabilities filter out irrelevant or low priority data and alerts, reducing alert fatigue and enhancing operational efficiency.
• Anomaly detection – As defined by dynamic thresholds, machine learning identifies patterns in data that deviate from expected behaviour, enabling early detection of issues before they escalate into significant incidents.
• Forecasting – Predictive analysis harnesses historical data to forecast future trends and behaviours, helping to anticipate future resource consumption, potential outages, or traffic spikes.
ITRS Labs has seamlessly embedded Obcerv AI into the solutions ITRS customers already use and has built it to begin supporting monitoring tools with as little as one day of data.
Obcerv AI is available today in ITRS Geneos 7, the latest version of the company’s real-time application monitoring tool for financial services and ITRS Opsview, its hyper-scalable IT infrastructure monitoring solution.
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