Breaking through the complexity of performance monitoring with Anomalytics
Many organizations across industries depend on the mainframe to support critical operations, leveraging this IT infrastructure to handle massive amounts of data and transactions in an agile and secure environment. Because mainframes are so critical, organizations need them to also be resilient and reliable. This is why it’s so important for IT teams to have solutions and practices to effectively and continuously monitor the mainframe to catch problems before they can manifest.
This is where a new set of challenges comes in.
Challenges to performance monitoring
Organizations today are grappling with two major challenges: a shortage of talent to support their rapidly expanding mainframe needs and the reliance on outdated tools for performance tracking and issue detection. The talent shortage hampers their ability to maintain and enhance mainframe systems. At the same time, outdated tools often lack the necessary automation and visibility into key performance aspects, making it difficult to anticipate and address potential issues.
Facing a shortage of talent to support the rapidly expanding mainframe needs among IT teams, many organizations have been relying on outdated tools to try and track performance and spot issues. However, those tools typically lack vital automation and visibility into key aspects of mainframe performance, making it more difficult to foresee any issues on the horizon.
Without the ability to accurately assess mainframe performance and forecast impending issues, IT teams can quickly find themselves facing unexpected obstacles. Even minor glitches can snowball into larger problems across an environment, from security issues to slower employee productivity or even a negative impact on customer satisfaction.
Failing to incorporate the right capabilities, like automation and visualization, leaves teams with an IT environment that is a constant chore and is incapable of supporting highly informed decision-making at the business level. There is a glaring need to simplify mainframe monitoring for IT professionals today. But where should they get started? The answer lies within Rocket Anomalytics.
Simplifying mainframe monitoring
The concept of mainframe monitoring solutions, like Rocket Anomalytics, is actually quite simple. At its most basic level, this application easily connects to and monitors mainframes continuously and automatically alerts IT teams when it detects anything unusual or, as the name suggests, anomalies. Anomalytics delivers real-time visual data analysis of mainframe performance, so IT gains stronger insights and forecasting without the manual legwork and required expertise of past generations.
Rocket Anomalytics connects to mainframes through APIs and then uses AI and machine learning (ML) to create a baseline for mainframe performance and activity. Once established, it continuously monitors the mainframe system’s performance, looking for issues. If an anomaly is detected, the software will automatically alert IT teams of its findings, so they are not caught off guard. This mainframe monitoring tool also provides real-time data visuals on the mainframe’s status and forecasts any future issues for clear and simplified data analysis and decision-making.
With modernized mainframe monitoring capabilities in place, IT teams are freed up to spend their time on other essential tasks. By providing clear data visualization, complex data becomes much easier to take in, so IT can make informed decisions faster without being an expert on complex mainframe systems.
Learn more about how Rocket Software can help boost your mainframe monitoring capabilities with Anomalytics.
