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BMC Announces Control-M Updates

BMC announced new cloud data services and open-source integrations for Control-M, its application and data workflow orchestration platform.

These new capabilities provide IT operations the ability to enable secure, automated self-service experiences for non-IT business partners.

New and updated capabilities include:

- Strategic integrations with Apache Airflow, Amazon Web Services (AWS), and Google Cloud. This further expands the Control-M solution’s reach into the public cloud and open-source ecosystem to help customers orchestrate application and data workflows across the technologies they choose.

- Enhanced Managed File Transfer and data orchestration features to help organizations seamlessly transfer files to and from cloud storage solutions with greater flexibility.

- Advanced functionality and self-service interfaces to improve collaboration between IT operations, developers, data engineers, and business users.

The newest updates will help businesses strengthen their automation capabilities, operate more efficiently, deliver data-driven insights faster, and improve both self-service and collaboration between IT operations and their internal customers.

“Businesses are focused on driving modernization initiatives and delivering transformative digital experiences for their employees and customers,” said Gur Steif, president, digital business automation at BMC. “We are committed to continuously innovating the Control-M platform to support our customers. The new functionality we announced today gives stakeholders across organizations freedom to collaborate to turn data into actionable insights faster, leveraging the latest cloud and data technologies.”

This update complements additional capabilities recently introduced to the Control-M solution, including Control-M Workflow Insights, the Control-M Python client, and the Control-M integrations with leading cloud data services.

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BMC Announces Control-M Updates

BMC announced new cloud data services and open-source integrations for Control-M, its application and data workflow orchestration platform.

These new capabilities provide IT operations the ability to enable secure, automated self-service experiences for non-IT business partners.

New and updated capabilities include:

- Strategic integrations with Apache Airflow, Amazon Web Services (AWS), and Google Cloud. This further expands the Control-M solution’s reach into the public cloud and open-source ecosystem to help customers orchestrate application and data workflows across the technologies they choose.

- Enhanced Managed File Transfer and data orchestration features to help organizations seamlessly transfer files to and from cloud storage solutions with greater flexibility.

- Advanced functionality and self-service interfaces to improve collaboration between IT operations, developers, data engineers, and business users.

The newest updates will help businesses strengthen their automation capabilities, operate more efficiently, deliver data-driven insights faster, and improve both self-service and collaboration between IT operations and their internal customers.

“Businesses are focused on driving modernization initiatives and delivering transformative digital experiences for their employees and customers,” said Gur Steif, president, digital business automation at BMC. “We are committed to continuously innovating the Control-M platform to support our customers. The new functionality we announced today gives stakeholders across organizations freedom to collaborate to turn data into actionable insights faster, leveraging the latest cloud and data technologies.”

This update complements additional capabilities recently introduced to the Control-M solution, including Control-M Workflow Insights, the Control-M Python client, and the Control-M integrations with leading cloud data services.

The Latest

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...