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BMC AMI Operational Insight Unveiled

BMC unveiled BMC AMI Operational Insight, an AI-driven, forward-looking solution that uses machine learning to detect anomalies and maximize lead time for remediation to mitigate mainframe issues before they become business problems.

The BMC AMI Operational Insight solution provides the intelligence for mainframe experts and newer employees alike to support every organization's journey to an Autonomous Digital Enterprise with the modern mainframe.

"Managing the mainframe has never been more critical to serving customers and ensuring uptime. It is imperative that companies have the capabilities to proactively manage the platform and anticipate problems before they happen," said John McKenny, SVP of ZSolutions Strategy and Innovation at BMC. "By applying AIOps to the mainframe for better availability and performance with BMC AMI Operational Insight, our customers can reclaim their valuable time and shift resources to focus on the strategic priorities that will allow them to become Autonomous Digital Enterprises."

The BMC Automated Mainframe Intelligence (AMI) AIOps suite envisions a three-part workflow – detect, find, and fix – designed to greatly reduce mean time to repair (MTTR) so operations teams spend less time reacting to issues and more time advancing high-level business initiatives. With BMC AMI Operational Insight, users gain a solution that utilizes machine learning to learn what is normal, detect anomalies, and maximize lead time for remediation, avoiding downtime or system degradation.

Key benefits of BMC AMI AIOps include:

- Faster detection: Notifications alert users of anomalies, allowing them to proactively solve problems impacting systems before they cause any downtime.

- More accurate predictions: Multivariate analysis looks across all KPIs simultaneously instead of in silos, to ensure no KPI anomalies are missed, resulting in fewer false positives.

- Data science and domain expertise built-in: Knowledge of which metrics to watch quickly fills the gaps left by a retiring workforce and expedites the learning curve for new staff. In addition, getting rid of the guesswork of collecting and evaluating extraneous metrics eliminates the waste of costly MIPS.

- Out-of-the-box predictive problem detection: Minimal configuration required means users can install, add data, and realize value immediately.

- Improved and adaptive intelligence for systems: Continuous consumption of deep and broad data sources helps add intelligence to complex systems, while continuous learning ensures teams can keep up with rapid pace of change.

As part of the new BMC AMI AIOps suite, the BMC AMI Operational Insight solution ensures mainframe uptime that allows organizations to meet the growing demands of digital business growth. BMC continues to invest and innovate for the mainframe with new product introductions, as well as the recent acquisition of Compuware. BMC now offers a full suite of mainframe software development, delivery, and performance solutions that empower organizations to scale Agile and DevOps with a fully integrated toolchain.

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BMC AMI Operational Insight Unveiled

BMC unveiled BMC AMI Operational Insight, an AI-driven, forward-looking solution that uses machine learning to detect anomalies and maximize lead time for remediation to mitigate mainframe issues before they become business problems.

The BMC AMI Operational Insight solution provides the intelligence for mainframe experts and newer employees alike to support every organization's journey to an Autonomous Digital Enterprise with the modern mainframe.

"Managing the mainframe has never been more critical to serving customers and ensuring uptime. It is imperative that companies have the capabilities to proactively manage the platform and anticipate problems before they happen," said John McKenny, SVP of ZSolutions Strategy and Innovation at BMC. "By applying AIOps to the mainframe for better availability and performance with BMC AMI Operational Insight, our customers can reclaim their valuable time and shift resources to focus on the strategic priorities that will allow them to become Autonomous Digital Enterprises."

The BMC Automated Mainframe Intelligence (AMI) AIOps suite envisions a three-part workflow – detect, find, and fix – designed to greatly reduce mean time to repair (MTTR) so operations teams spend less time reacting to issues and more time advancing high-level business initiatives. With BMC AMI Operational Insight, users gain a solution that utilizes machine learning to learn what is normal, detect anomalies, and maximize lead time for remediation, avoiding downtime or system degradation.

Key benefits of BMC AMI AIOps include:

- Faster detection: Notifications alert users of anomalies, allowing them to proactively solve problems impacting systems before they cause any downtime.

- More accurate predictions: Multivariate analysis looks across all KPIs simultaneously instead of in silos, to ensure no KPI anomalies are missed, resulting in fewer false positives.

- Data science and domain expertise built-in: Knowledge of which metrics to watch quickly fills the gaps left by a retiring workforce and expedites the learning curve for new staff. In addition, getting rid of the guesswork of collecting and evaluating extraneous metrics eliminates the waste of costly MIPS.

- Out-of-the-box predictive problem detection: Minimal configuration required means users can install, add data, and realize value immediately.

- Improved and adaptive intelligence for systems: Continuous consumption of deep and broad data sources helps add intelligence to complex systems, while continuous learning ensures teams can keep up with rapid pace of change.

As part of the new BMC AMI AIOps suite, the BMC AMI Operational Insight solution ensures mainframe uptime that allows organizations to meet the growing demands of digital business growth. BMC continues to invest and innovate for the mainframe with new product introductions, as well as the recent acquisition of Compuware. BMC now offers a full suite of mainframe software development, delivery, and performance solutions that empower organizations to scale Agile and DevOps with a fully integrated toolchain.

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

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Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...