Control-M Managed File Transfer

Control-M is used for MFT service MFT features in daily work because files are transferred from one server to the target, and it is used primarily for integration between two systems. It is also used for scheduling and managing SAP jobs.

One workflow managed with Control-M currently involves encrypting files and transferring them to the bank, where the source system is encrypted and the encrypted file is transferred, which is easier to analyze and prevents breaches of flat files.

Control-M is used for MFT-based managed file transfers across different businesses globally, and the features provided by MFT in Control-M are believed to be the best for transferring files between on-premise and cloud systems.

Approximately 20 to 30 people use Control-M in the organization, performing various roles such as job configuration, administration, and usage for MFT and SAP jobs.

Control-M usage is being increased and businesses globally are being engaged to expand its implementation.

The favorite feature of Control-M is MFT manage file transfer, which is easy to integrate with other systems. It is used daily, and the API is utilized for admin activities and triggering Control-M jobs.

The API in Control-M helps automate tasks, such as creating jobs automatically using code in Visual Studio, enabling workload policies, job creation, and sharing the API swagger with the business to trigger Control-M jobs.

Control-M is a good tool with the best features for SAP scheduling.

Control-M has positively impacted Saint-Gobain by reducing manual work in file transfers, allowing automation of tasks, improvement of SLA, and enhancement of daily work and workload.

Control-M has improved organizational functionality by providing one platform to monitor jobs easily and access detailed logs to track SAP and MFT jobs with end-to-end visibility of job dependencies.

One area for improvement in Control-M is the ability to encrypt and decrypt files without needing to install an agent on the other side, and better customization options for SharePoint access in line with Saint-Gobain policy would be appreciated.

DevOps integration into Control-M needs to be explored more, as it is currently not being used in the organization but the potential benefits are evident.

I have been working in my current field for almost 11 years.

Control-M is stable.

Control-M's scalability is good.

Customer support for Control-M is excellent, and that aspect is greatly appreciated.

Previously, scripting was used for file transfers, which did not allow proper monitoring, leading to the switch to Control-M for both file transfers and SAP.

Other options were not evaluated before choosing Control-M because its features and functionalities were recognized in advance.

Before Control-M, scripts had to be created manually for file transfers, which took a significant amount of time. With Control-M, jobs are simply set up through drag and drop, which has reduced effort significantly.

Control-M is used for MFT-based managed file transfers across different businesses globally, and the features provided by MFT in Control-M are believed to be the best for transferring files between on-premise and cloud systems.

Although specific data is not available, Control-M has saved time in future implementations of end-to-end flows, making monitoring easier.

Control-M pricing is good, though it is somewhat expensive; still, it offers great features.

Other options were not evaluated before choosing Control-M because its features and functionalities were recognized in advance.

I advise others looking into using Control-M to experience its ease of monitoring jobs on a single user-friendly platform, streamlining job creation and monitoring.

The biggest lesson learned from using Control-M is that it reduces manual effort and increases productivity.

Control-M is effective for scheduling, managing, and monitoring workflows, and it is crucial for DevOps initiatives as it provides a single platform for monitoring related jobs, helping to reduce SLAs.

Control-M is good for my needs, and I would rate this review as a five out of five.

Control-M is primarily used to automate and monitor critical operational and database-related jobs, such as backups, batch processing, and application workflows. It helps reduce manual interactions and provides centralized monitoring while improving reliability and ensuring that dependent processes execute in the correct sequence. Overall, Control-M is a valuable tool for maintaining operational efficiency and reducing scheduling-related risks.

The primary daily use case for Control-M is scheduling and monitoring automated jobs, such as database backup jobs, archive log backups, and maintenance tasks and batch processing workflows. It is also used to monitor job dependencies, track failures, and receive alerts so that issues can be resolved quickly with minimum manual interactions. Control-M is used daily to automate and monitor database maintenance jobs, backup workflows, and batch processes. The centralized monitoring and alerting capabilities help ensure that critical workflows complete successfully and on schedule.

Beyond job scheduling, Control-M is used for end-to-end workload automation, monitoring critical business processes, and managing cross-application dependencies. It helps ensure that database maintenance jobs, backup processes, file transfers, and batch workloads execute in the correct sequence with minimal manual interactions. The centralized monitoring, alerting, and restart capabilities help reduce operational overhead and improve service reliability. Control-M provides good visibility into workflow status, making it easier for supporting teams to identify and resolve issues quickly. Control-M is a key tool for workload automation and operational monitoring. It helps automate repetitive tasks, manage job dependencies, provide proactive alerts, and ensure critical business processes run reliably. This has significantly reduced manual effort and improved overall operational efficiency.

Control-M is deployed as a centralized workflow automation platform that supports multiple applications and databases across several environments throughout the organization. Different application teams use it to schedule and manage their batch workloads, while operations and support teams use the centralized monitoring and alerting capabilities to track job execution and respond to issues. The platform enables workflow architecture across Windows, Linux, Unix, database, and application environments while providing a single point of control for all critical business processes.

Control-M is relatively easy to integrate with different technologies and operational requirements. One of its strengths is the broad support for multiple platforms, applications, databases, and file transfer processes. This helps organizations bring diverse workflows under a centralized automation framework. It provides integration capabilities that reduce the need for custom scheduling solutions and manual coordination between systems. As DevOps, one opportunity is to continue simplifying onboarding and integration.

Control-M has been integrated with the Oracle database environment to automate backup and log backup and maintenance jobs. This integration significantly reduced manual interaction, improved scheduling reliability, and provided centralized monitoring and alerting. As a result, the organization was able to identify and resolve job failures more quickly and ensure that critical database operations were completed on time. Database integration is most relevant to the role. ServiceNow integration has also been implemented. When critical jobs fail, alerts are tracked and managed more effectively through ServiceNow integration, reducing response times and improving operational visibility. Cloud integrations with Azure have been utilized. Integrating Control-M with Azure-based workloads enabled automation and monitoring of cloud-hosted processes alongside on-premises jobs. This provides a unified view of workflows and improves operational efficiency across environments. One of the most valuable integrations has been with the database environment.

The most valuable features of Control-M are its centralized monitoring, workload automation, job scheduling, job dependencies management, and proactive alerting capabilities. Control-M allows teams to schedule and manage complex workflows across multiple platforms from a single interface, improving visibility and operational control. It supports both calendar-based and event-driven scheduling and provides automated notifications for job failures. It enables quick recovery and rerun of jobs when issues occur. These features help reduce manual effort, improve reliability, and ensure critical business processes run smoothly.

The best features of Control-M are centralized job monitoring, workload automation, dependency management, proactive alerting, and cross-platform scheduling. These capabilities help automate critical business processes, reduce manual effort, improve operational visibility, and ensure reliable execution of batch workflows across multiple systems. The ability to quickly identify and troubleshoot and restart failed jobs is particularly valuable for operational teams.

Control-M is much more than a simple job scheduler. Its real value comes from workload automation, dependency management, and centralized monitoring across multiple systems and applications. Once workflows are properly designed, it can significantly reduce manual effort, improve operational reliability, and provide better visibility into critical business processes. Features such as automated alerts, job restart capabilities, historical tracking, and cross-platform integration make day-to-day operations easier and help teams respond quickly when issues occur.

Control-M is a reliable workload automation platform. There is an opportunity for improvement in troubleshooting failed jobs in complex workflows, as this can sometimes be time-consuming, especially when multiple dependencies are involved. Improved root cause analysis, more intuitive error messages, and enhanced reporting capabilities would help operations teams resolve issues faster. Additionally, a more modern and responsive user interface would improve overall user experience.

From an operational support perspective, complex dependency chains can be difficult to troubleshoot, and error messages could provide more actionable details. Reporting on dashboard customizations could be more flexible. The user interface could be more modern and user-friendly, and faster search and filtering capabilities for large job environments would be beneficial. While Control-M is a robust and dependable automation tool, troubleshooting failures in complex job workflows can sometimes be challenging. Improved root cause analysis, richer alert details, and enhanced reporting would further improve operational efficiency and reduce investigation time for support teams.

One improvement that would be valuable is the use of more intelligent monitoring and analytics capabilities. For example, predictive alerts that identify potential job delays and failures before they occur would help operations teams act proactively and enhance root cause analysis. Artificial intelligence assistance for troubleshooting recommendations and more customizable dashboards would improve efficiency. Additionally, simplifying the management of complex job dependencies and providing clear visual workflow views would make day-to-day operations easier.

I have been using BMC Control-M for the past six years.

Control-M should be highly rated for building, scheduling, managing, and monitoring production workflows. Its strength lies in providing a centralized platform where complex workflows can be designed, scheduled, and managed across multiple systems and applications. The dependency management capabilities help ensure that workflows execute in the correct sequence, while real-time monitoring and alerting provide visibility into job status and exceptions.

Control-M is extremely important for database and DevOps initiatives because many business processes depend on multiple interconnected systems, including applications, databases, and file transfers. Control-M provides a centralized way to coordinate these workflows and manage dependencies across different platforms. This helps ensure that tasks execute in the correct order and that downstream processes only begin when prerequisite activities have been completed. From a team efficiency perspective, it reduces the amount of manual monitoring and interaction required to manage complex workflows. Automated scheduling, centralized visibility, and a proactive alerting system support focus on issue resolution and process improvements rather than routine operational activities.

Control-M provides strong controls around user access and authorization, auditing, and workload management through role-based access. This helps ensure that users only have the permissions required for their responsibilities. Audit and activity tracking provide accountability and support complex requirements. Control-M also supports secure authentication, encrypted communications, and detailed monitoring of job scheduling, job execution, and workflow changes. The focus on governance and automation rather than uncontrolled oversight is appreciated. Control-M should be considered from governance and security standpoints. Features such as role-based access control and auditing demonstrate Control-M's emphasis on governance.

Based on my experience, the artificial intelligence-related capabilities appear reliable for operational assistance, workflow insights, and accelerating routine tasks. The outputs are generally useful and align with the information available within the platform. For business-critical activities, human review and validation remain important, especially when making operational decisions or implementing workflow changes. No major reliability concerns have been observed, but as with any artificial intelligence-enabled capabilities, external validation is necessary to ensure accuracy and context. What provides confidence is that Control-M combines artificial intelligence capabilities with governance, monitoring, auditability, and operational control. While outputs from artificial intelligence would still be validated for critical decisions, the combination of artificial intelligence with governance, auditing, and control mechanisms increases confidence in the platform's recommendations and outputs. I would rate Control-M an eight out of ten overall.

Control-M serves as my primary solution for enterprise workload automation and job scheduling. I use Control-M for running batch jobs at specified times and frequencies, ensuring that jobs execute in the correct sequence while coordinating jobs across applications, databases, APIs, cloud, and platforms, including the movement of files between systems. Control-M provides monitoring capabilities for detecting failed, delayed, or stopped jobs and for alerting the operations team when workflows breach conditions. Furthermore, it helps restart failed jobs based on predefined rules, allowing me to track whether business workflows will complete within the required time timeline, which supports SLA management. On the cross-platform automation side, Control-M coordinates between Windows, Linux systems, mainframe, databases, cloud, and SaaS workloads.

Control-M offers exceptional features including centralized monitoring, workflow orchestration, cross-platform compatibility, advanced alerting, and automated recovery. I particularly appreciate the end-to-end workflow orchestration, which connects jobs across applications, databases, cloud, data platforms, and infrastructure, and it is also relevant for AI-first IT operations, giving AI agents control execution.

My primary feature is end-to-end workflow orchestration, but I also find the secondary feature of event-driven automation valuable, where jobs can be triggered by events, files, conditions, or external signals, not just schedules. This functionality is helpful for sequencing jobs and triggering them at the right point when the business is ready for the process to follow, allowing me observability in terms of events to initiate operational workflows. Other notable features include automated recovery remediation, real-time monitoring, and integration with ecosystems like SAP, databases, AWS, Azure, Snowflake, Databricks, and Informatica.

The AI-assisted workflow creation is fantastic, as Control-M capabilities include AI-assisted creation of workflows from natural language intent, which is useful for moving towards AI-first operations. Control-M has taken the right step in bridging the traditional world with the new AI-first approach. Additionally, the orchestration of complex business workflows is significant for my operations as it connects what is otherwise a collection of independent jobs. The dependency and impact intelligence feature knows what depends on what, which is extremely valuable when an upstream job fails or is delayed. This impact intelligence becomes handy for complex integrations or workflow processes needing connection.

Finally, the predictive SLA management feature can identify when a workflow is at risk of missing its business SLA, making my management predictive and not just preventive, which helps in rectifying issues proactively. Furthermore, the event-driven automation in the closed-loop automation helps me act as soon as I detect an anomaly in the system. Monitoring systems detect the issues, Control-M orchestrates it while I use my ITSM or any service management tools to govern all these steps.

Throughout my organization, Control-M has positively helped establish certain capabilities by providing centralized workflow orchestration that replaced the fragmented scheduling and manual coordination that was previously required. This shift has eliminated repetitive operations by implementing automation, significantly reducing manual intervention and operator dependency for routine batch activities. As a result, I manage dependencies much better, ensuring complex upstream and downstream processes execute in the correct sequence. This enhanced dependency management has led to improved reliability, with reduced missed schedules, reduced incomplete workflows, and fewer failures needing correction through human involvement.

Control-M has also contributed to faster recovery procedures by creating standardized recovery processes to eliminate knowledge dependency on individual operators. Beyond this, I have transitioned from merely monitoring jobs to managing business processes, ensuring operational personnel have a comprehensive view of the business processes' impacts, bolstering operational visibility. Cross-platform integration has connected legacy distributed databases, file transfers, and workloads through a common orchestration mechanism, minimizing the tool sprawl that previously required excessive investment. Operational standardization from Control-M has created repeatable ways of scheduling, monitoring, escalating, and recovering workloads, which has significantly enhanced the outlook on processes. Finally, operational visibility has provided a consolidated view of workflow execution and dependencies, expanding the understanding of processes without requiring extensive discussions with business teams, instilling confidence in IT operations.

The areas for improvement in Control-M involve four key dimensions: observability, intelligence, integration, and automation. I strive to shift from job monitoring to business service monitoring and integrate with enterprise observability tools like Dynatrace. I aim to incorporate AI-driven root cause analysis to avoid manual examinations of multiple jobs by allowing an AI agent to analyze job histories and dependencies. I envision improving recovery processes by making them more autonomous, where AI diagnoses failures and Control-M executes necessary actions with subsequent verification. Enhancing SLA management with predicted outcomes is essential to help me intervene proactively. I want to reduce operational noise by collecting intelligence around job failures and achieving a self-healing candidate factory.

I have not used Control-M's AI capabilities to the extent I would desire, as the accuracy was not very impressive. Insights for failure and performance analysis are not reliable. The AI workflow creator serves as a productivity accelerator, but generated workflows need thorough review and testing. AI monitoring is moderate in usefulness for summarizing logs, while root cause analysis should be treated as a hypothesis rather than a certainty. The AI pilot for planning is similarly moderate in that it assists in generating jobs but requires human validation for production changes. As for autonomous remediation, trust remains a concern as it necessitates deterministic policies and verification. While data-grounded AI capable of querying operational data is somewhat reliable, the interpretive nature of natural language queries leads to susceptibility to incomplete inferences, resulting in hallucinations. Therefore, I cannot consider Control-M AI a reliable root cause analysis engine at this stage.

I have been using Control-M on and off for about ten years.

Control-M is stable.

Control-M's scalability has met my business demands, supporting organic growth efficiently. I have not pinpointed any significant issues as my preparatory measures have allowed for both horizontal and vertical scaling.

I feel customer support could use improvements, not as a complaint but as an observation. Enterprise clients typically require more attention to hasten new feature implementations without acquisition barriers.

I have utilized Control-M for almost a decade now, and while alternative, non-enterprise solutions existed, their footprint has considerably diminished, with Control-M remaining my primary orchestration solution. When searching for a solution, I evaluated various competitors and believe I made a commendable choice selecting Control-M, which continues to expand in usage since.

My deployment of Control-M took about six to nine months, significantly influenced by my focus on standardization and numerous discussions regarding necessary amendments for partner integrations, which impacted SLA management and governance features requiring their own cycles of standardization and acclimatization.

I maintain a 360-degree relationship with the vendor, contributing certain features not necessarily related to the core product but within the ecosystems.

Regarding return on investment, I am witnessing a favorable trend toward realizing significant ROI through standardization where numerous inefficiencies have been addressed. My aim is to bring standardization across automation, which has curtailed tool sprawl considerably. Control-M's automation features are now treated as essential enterprise-grade solutions, driving alignment and significant cost reductions across various departments. In addition, centralized AI usage aids in managing token costs, which I find beneficial.

Pricing, setup costs, and licensing can be complex. The licensing has generally been acceptable in value, but it requires careful planning since costs can greatly vary based on deployment models and environmental scales, as well as the number and type of workload integrations being consumed.

When searching for a solution, I evaluated various competitors and believe I made a commendable choice selecting Control-M, which continues to expand in usage since.

Control-M is currently used significantly within my organization, largely due to my early adoption as legacy systems are centered on it. I have plans to increase its usage further as I experience more mergers and acquisitions, particularly in integrating smaller-scale entities into my main workflows. Thus, as I navigate diverse environments, enhancing integration remains a priority while minimizing the impact of security challenges and optimizing operational tasks. Control-M is highly effective when processes are somewhat homogeneous. Organizations should leverage its features to ensure full advantage of what Control-M offers, as my learning experiences have shown that a solid understanding of the solution supports effective business service management. I would rate Control-M as an eight out of ten. I choose an eight out of ten because I still have steps to cover in implementing broader intelligence from large language models into Control-M's features. Control-M is evolving toward an AI-native approach to IT operations, and I would like to see it embody that more fully. From a governance standpoint, I rate it as an eight, as there are areas needing evolution to become a very enterprise-grade application. Security-wise, I want to see a stronger AI-first methodology for operations, indicating there is ample opportunity for enhanced security features within Control-M.

We are partners with Control-M, and I believe we have recently elevated to platinum status, though I am not entirely certain about that partnership level. We are partners with BMC, including both Control-M and Alex.

What I appreciate most about Control-M is the automation steps of how things are automated and scheduled. Our relationship with BMC is more transformative than transactional since we have been BMC partners for a long journey, almost more than ten years. We work closely with all partners on the BMC side and actively engage with all stakeholders, not just for the sake of the client, but we are closely involved with the respective stakeholders of BMC.

Regarding areas for improvement with Control-M, I would need to go into the depth of detail and provide specific feedback. If you share a form, I will have corrections and additional input from our team. Using the code option is better overall, but I believe better capacity planning can be done.

Unfortunately, to provide meaningful feedback regarding room for improvement, we need to identify something Control-M can do better or something they can add in a future release.

Throughout my career, I have been using Control-M for almost more than six or seven years. From my perspective, I have recently taken on the lead role for Control-M for two years.

Regarding stability, I rarely observe any lagging, crashing, or downtime when I use Control-M. That very rarely happens based on memory space or statistics. With respect to resolution management and ticket management systems, BMC always responds first. We would appreciate improved feedback on solution response time, which would be beneficial for us, the clients, and BMC as well.

I believe Control-M is scalable. Control-M is indeed scalable, and technically I need to verify this with the correct details and share them with you.

Control-M does not require any maintenance on my end, such as updates. I think BMC is doing a fantastic job with tenant updates and periodic knowledge updates, whereby they provide training sessions as well. Recently, BMC has separated into two categories, and Control-M also has a separate wing. The tenant and the helpline are very good, but we have to continuously review the material released by BMC.

I have not used any alternatives or similar solutions to Control-M. We have heard about some products, but we are not using any alternative. Alex ITSM is a different platform. Control-M is the only solution we are using with respect to the client side.

Regarding the initial deployment of Control-M, I need to check with my solution architect because I am not involved on the daily operation side. From a high-level perspective, I observe that the initial setup and most of the configuration and other aspects are done, but better port level and prerequisite level automation or a more comprehensive checklist provided to partners would make the setup easier rather than complicated during the initial stage.

Our technical team members continue to contact our respective project stakeholders, though this is not from my side. I am overseeing the Control-M use overall.

Control-M is scalable and does an excellent job overall. The approximate number of people using Control-M is around fourteen or more. I am not the appropriate person to ask about the pricing of Control-M; a direct person from the sales team would have direct visibility of the pricing side. Regarding how well Control-M integrates with other solutions in our stack, I do not have the correct technical answer. My rating of Control-M overall is eight point five out of ten. The two reasons for not giving a ten out of ten are that the initial setup configuration can be better, though our team is working on it, and everything else is good. Do you have any mechanism to route questions about technical integration to the technical person leading this area?

Control-M offers excellent scalability. One person can deploy it, though a team deployment is also an option. The quality and speed are both very good.

My relationship with BMC is more transactional. I am primarily paying them for the service rather than experiencing active involvement from their team.

We work with both Control-M and another solution. I use Control-M in my company with eight people overall using it. I do not have any official partnerships with BMC, and we are not resellers. We are simply a customer of theirs. I would rate this product an overall seven out of ten.

Control-M is a fantastic product in terms of automation. It is predominantly used for task scheduling, and it is one of the finest products available. We use it especially for task scheduling, and most BFSI customers are using it for transaction settlement. We have used it for credit card transaction settlements.

Control-M is a fantastic product in terms of automation. It is predominantly used for task scheduling, and it is one of the finest products available. We use it especially for task scheduling, and most BFSI customers are using it for transaction settlement.

There is nothing disliking about it. To be very frank, it is one of the finest products that came after IBM high frames. The use cases are predominantly in BFSI. If it could do something in manufacturing, it would be helpful where we could do automation using Control-M or something that focuses on domain-specific needs in manufacturing.

Control-M is a fantastic product in terms of automation. It is predominantly used for task scheduling, and it is one of the finest products available. We use it especially for task scheduling, and most BFSI customers are using it for transaction settlement.

It is quite easy and not a big challenge. It is pretty simple and not complicated. It just requires an understanding, and it is plug and play. Wherever we are implementing it or it is getting implemented, it is smooth and running.

Control-M is definitely a scalable product. There are no two thoughts on it. Scalability is amazing.

Any product will have some concerns. It depends on implementation and integrations and how we are doing it, and support here is decent enough.

The pricing is acceptable. It is not that heavy compared to other products like ServiceNow and SAP.

UiPath can be used to a certain extent, but Control-M has its own flavors. If it is invoice processing or if robotic automation is needed, I would go for UiPath. If task scheduling or something related to BFSI is needed, I would use Control-M. It depends on use cases.

UiPath can be used for any kind of use cases in terms of automation, but Control-M has its own flavor. ServiceNow as a platform is a great enterprise platform. UiPath has its own automation flavors, and Control-M has its own scheduling and task automation. Everything comes with its own flavors and provides output. It depends on the use case.

I am comfortable with the feedback I have provided. I rate this product an eight out of ten.

Control-M is used for centralized monitoring and management of job scheduling across multiple platforms, and it serves day-to-day automation use cases, including file transfer and FTP and ERP jobs to be scheduled.

Multiple applications are supported, and with regard to file transfer, multiple files are received from the upstream and processed. When the file watcher successfully finds the files in the upstream, it transfers them to the downstream application, where multiple applications consume that file for their activities, including business warehouse management and day-to-day invoice processing, as well as file drive utilization.

Control-M is used for payroll, workflow management, ERP, supply chain, and file transfer, as well as HR portal management.

Control-M performs very well in building, scheduling, managing, and monitoring production workflows, and this workflow orchestration is important for DataOps and DevOps teams because it enables centralized scheduling activity and automation of complex workflows, thus improving operational efficiency and ensuring better governance and compliance.

Control-M has multiple benefits; it has improved ROI, and all KPIs have been met by implementing Control-M, resulting in a large reduction in the number of incidents. Before using Control-M, approximately 100 to 150 incidents occurred daily; now it has reduced to 10, and ROI and KPI targets are now met, indicating performance is in the green, whereas before it used to be in amber or red.

Control-M offers best features such as reducing manual effort for SLA compliance through its visual monitoring tool, minimizing operational error, and providing end-to-end workflow visibility; incident resolution can also be faster thanks to its GUI.

Control-M licensing is somewhat expensive for smaller organizations, and companies are hesitant to adopt BMC Control-M; the initial setup and implementation require a lot of admin work, so reducing that requirement would be greatly helpful.

The accuracy and reliability of Control-M's AI capabilities need improvement; AI in Control-M is not used much, so detailed commentary on this aspect is limited.

I have more than 10 years of experience in this field.

Control-M is very stable.

Control-M can be rated nine out of ten when it comes to scalability; it is very scalable and allows adding jobs and processes easily.

Control-M pricing is on the higher side; the cost should be reduced to onboard multiple customers, especially since open-source options are emerging. However, BMC customer support is very helpful and assists with licensing and everything.

Autosys was previously used before switching to Control-M because it offers a better visual experience, customer support, and more features.

Control-M takes one week to deploy, including setting up the environment, the agent, and the EM server.

A return on investment has been observed.

Before choosing Control-M, options like Apache Airflow and some of the processes in BizTalk were evaluated, but Control-M was found to be superior.

Control-M's governance and security are being worked on, and governance and audit capabilities exist, with all EM servers and Control-M servers being able to be hosted locally, so there are not many issues on the governance part.

Integrating Control-M with technologies for DataOps and DevOps processes has been a moderate experience; while a few CI/CD pipelines have been included in Control-M, deploying DevOps has not been easy, but a few features have been added, including using Control-M stats.

Control-M should be considered by those looking to use it because it offers enterprise-grade reliability, strong module integration with tools like Informatica and AWS, better support, and scalability compared to other schedulers. I would give this review an overall rating of 9.

I have been working with Control-M for eight years. Control-M was simply used for batch scheduling. I use Control-M on a day-to-day basis. Control-M allows me to automate the process of running the JCLs. From my perspective, Control-M works well, and I would say that it is a very good tool for building, scheduling, managing, and monitoring production workflows. Control-M is very important to my DataOps initiatives due to the specifics of the functioning of the logic of IT business processes in a bank. I am not in DevOps, but I think it is not so difficult to integrate Control-M with technologies for my DataOps and DevOps processes as things change.

That is a difficult question because I do not actually know any other tool that would be competitive with this one. I appreciate Control-M because it is a very reliable tool and it is easy to work with. I cannot imagine my work without Control-M; it is a core tool in banking systems, so I think that without it, it would be difficult to run a bank itself.

I do not see any improvement needs for Control-M at this time. There are not really any features that are missing in Control-M at the moment that I would like to see included in the future or enhanced somehow. I am not sure if this is the case, but perhaps the knowledge of how to use Control-M should be more propagated or better accessed. It can be used in other aspects than my needs, so it is also valuable to know.

I have been working with Control-M for eight years.

Control-M is quite stable; I have not had any crashes, downtimes, or performance issues with it.

I have never had a need to scale Control-M, so I cannot tell you if it is difficult because I have never had a need to do this.

I did not migrate from Broadcom CA, Redwood Technologies, or any other similar solutions to BMC. I have not switched from a different product; I started using Control-M straightforwardly.

From my perspective, to start working with Control-M, you need to learn, but it is not difficult to get a grasp of how it works.

I do not know because I did not set Control-M up. I did not have an internal team or any partners, consultants, or BMC representatives help me with the setup.

It is difficult to say how many users are using Control-M in my environment; probably over a thousand, but different roles, I would say. I have it across different locations and different departments.

Given my experience with Control-M, I would recommend it. Control-M is a good, reliable tool, and I do not think that there is much of a competitor for this in terms of banking solutions.

My main use case for Control-M is job orchestration throughout the company. A specific example of how I use Control-M for job orchestration in my organization is the management and coordination of the sequence of business-critical jobs that need to be run on a regular basis.

Control-M has positively impacted my organization by simplifying the existing routine and making it very easy to manage jobs. Control-M has saved time, reduced errors, and provided other measurable benefits, especially in terms of time when a business customer requires a new job flow, as it is very easy to customize and implement. I believe time saving is the best output we have achieved now.

The best features Control-M offers are that it is SaaS and very easy to manage. It has a very user-friendly interface, is very easy to customize, and allows me to check the result of the jobs' outcome.

The user interface stands out to me because it is specifically designed for the particular user's needs, making it not so complicated to change or update anything within the system.

As of now, we do not have any major requests, complications, or complaints about Control-M. Everything we have received from our internal clients can be implemented with existing tools and features, and if something new arises, the BMC team is putting it into backlog and providing us with a timeline for implementation, so I cannot say that something really critical exists right now that needs to be improved.

I have been working in my current field for more than fifteen years.

Control-M is stable.

Control-M's scalability is at a very high level.

If we are talking about direct support from BMC, it is quite good. I would rate the customer support an eight out of ten.

I previously used another solution, and we decided to replace it with Control-M because the strategic direction has changed.

I would say the pricing and setup process is quite straightforward.

The biggest lesson I have learned from using Control-M is that it can be implemented with the right team in very fast and quick terms, given specific expertise.

Control-M has saved time, reduced errors, and provided other measurable benefits, especially in terms of time when a business customer requires a new job flow, as it is very easy to customize and implement. I believe time saving is the best output we have achieved now.

I would say the pricing and setup process is quite straightforward.

I previously used another solution, and we decided to replace it with Control-M because the strategic direction has changed.

We are working with the integration with Ansible, for instance, and with other platforms in order to increase our automation processes and simplify any manual routine work.

I would rate Control-M an eight out of ten because it is quite simple, easy to scale, understandable, and it is a friendly user platform.

I would rank Control-M's AI capabilities, particularly its governance and security, at a pretty high level. In terms of Control-M's AI capabilities, its accuracy and reliability of output are high standard; I would call this platform quite reliable compared to other systems.

Control-M is extensively used by my organization, we have thousands of jobs, and it definitely is one of our strategic directions.

I need to split the users into admin users and those who are requesting to update some jobs; there are dozens of them in each department.

I advise others looking into using Control-M to be very accurate and specific with the scope. The cloud provider we use for our hybrid deployment is open information that you can find easily on your own. My overall rating for Control-M is an eight out of ten.