Control-M Reviews

Control-M is a scheduling software for scheduling jobs, and I have been using it for four to six years.

The best feature of Control-M is that it is a SAP module we use to schedule jobs in SAP for the delivery of goods, and mainly it's time-oriented. Time-oriented features and whatever reports we can fetch are very easy in Control-M.

It is easy to integrate Control-M with technologies for DataOps and DevOps. Currently, our next project is underway regarding the integration.

Control-M supports DataOps and DevOps initiatives by enabling us to update batches we get from the BMC tool, and we are currently using both for development and testing purposes. I hope it will be beneficial for us moving forward. If we implement a DevOps project in our application, it will save significant time by reducing human intervention as jobs will be scheduled automatically.

Currently, the solution saves us around 15 to 20% time during the primary phase.

Regarding areas for improvement, there are some additional features that you must give concerning the available features. The job scheduling time is a little bit consuming, and it should be simplified into very straightforward steps, such as a web-based application for all the scheduling jobs, as this would be helpful.

There are a few bugs I found while implementing Control-M, which are minor issues. We can minimize those bugs, such as applications not running at scheduled times. If there's a time schedule, we might get a report with logs, and 98% of the time it runs on time, with only 2% being slightly problematic regarding job execution.

Regarding stability, Control-M application is stable, and there is no second thought on this. If any error arises from a job that hasn't run, we simply need to address that issue. I rate its stability as eight.

I rate scalability as eight.

I rate the support for the solution as a seven, around 7 to 8, specifically a 7.5.

I have not yet migrated from Broadcom or Redwood or any similar solutions, but we have conducted workshops and other preparations for that.

It is simple to integrate Control-M, particularly in the cloud. We need to have the host or an agent to run commands with the application name, and it is comparatively easy when compared to others.

It's not cheap; it's a little bit costlier compared to others due to database processing and finishing jobs, which have some dependencies, so I don't think it's cheaper.

Control-M, which is the BMC workload automation tool, is mainly used for scheduling. When we integrate Control-M into a SAP basis, we can automatically fetch records. We have to schedule and run jobs at a particular time, going through phases such as initial phase, build phase, and delivery phase. In that process, we handle job scheduling, workload management, creating OS and file transfer of database jobs, and reporting and configuration management involving automation capabilities.

Currently, our client is using BMC's Control-M software, so we must go as per the client's requirements. We are not in a position to decide whether we can proceed with it or not because the client uses Control-M for batch scheduling.

I definitely recommend BMC; Control-M is excellent for handling very large batch scheduling jobs. We have many jobs to complete in our daily activities, and this is one of the best tools. I would also recommend it to my partners for different clients who need batch scheduling; Control-M is a very good tool or application.

Primarily for email and SNMP, as well as monitoring tools, we use Control-M compared to other solutions or vendors. I would rate this product an overall eight out of ten.

We are a system integrator specializing in document digitization and DMS applications, and we encounter various workflows within documents and data. I have been using Control-M for less than one year, primarily on workflow process applications where we work with clients on digitizing backlog conversion projects. We use it when there are complex structured documents with AI-enabled workflows. We encountered this orchestration platform where we need to work across documents and applications to integrate whenever there is a critical business workflow.

The best features of Control-M are the seamless and simple process that any business user can understand and adapt to. Control-M also provides low-code and no-code capabilities that allow business users to work on workflow orchestration in a straightforward manner.

I assess Control-M as having ease of use and being simple to deploy and configure at a business level. When workflows are structured, it appears simpler and easier to create and integrate data pipelines for on-premises and cloud environments. For complex workflows, we need to fine-tune and understand the system before deployment.

Control-M currently saves approximately 15 to 20% of time compared to our previous support system.

The areas that have room for improvement for Control-M include integration and different data structures. Additionally, whether the deployment is on-premises or hybrid requires careful consideration. Both applications we worked on were on-premises, and we did not work on any cloud applications. The challenge regarding latency and other connectivity integration will likely be a key challenge for Control-M, and understanding how this will impact ease of use and deployment will be important.

I have been using Control-M for less than one year, primarily on workflow process applications where we work with clients on digitizing backlog conversion projects. We use it when there are complex structured documents with AI-enabled workflows. We encountered this orchestration platform where we need to work across documents and applications to integrate whenever there is a critical business workflow.

I rate the stability of Control-M as seven. I rate it a seven because it is still in the initial phase. We need to deploy other workflows and observe how the application scales and how the stability of the whole application with an increased number of users deployed across different locations will perform.

I rate the scalability of Control-M as eight.

I rate the technical support of Control-M as a seven on a scale of one to ten.

I did not migrate from Broadcom, CA, or Redwood because this was a straightforward implementation of the application from the start.

I did not encounter any challenges with Control-M or with the deployment process because this was just an initial starter pack to begin with. It was a small project and was straightforward.

It is difficult to assess how easy or difficult it is to integrate Control-M for our DevOps and DataOps processes because we have not done any integration. It was a standalone use of the application. Our scope was limited and we have not encountered the integration part.

We had only one specialist working with Control-M, and we hired third-party resources to work on the project.

Resource-wise, we have realized approximately 20% value from Control-M, but financially, it is premature to assess regarding ROI.

Regarding the pricing of Control-M, I believe it looks competitive compared to other vendors. Whether it is a SaaS application or an on-premises application varies, and they have different structures such as a starter pack or a value pack. We went with the starter pack.

I cannot compare Control-M with other solutions or vendors because this request came from the end user, so I cannot provide live feedback.

Currently, we do not use Control-M to orchestrate workloads across multiple environments; all usage is on-premises.

I have not used the Control-M Python client or API because no API was within our scope, so I cannot comment with any correct feedback.

Control-M's main use case within my organization is automating and scheduling business-critical batch jobs like pipelines and workflows across multiple systems from a centralized platform. For example, we extract customer transactions from databases, run ETL jobs to load data into data warehouses, generate regulatory and financial reports, and transfer report files to downstream systems, along with sending email notifications when processing completes.

Beyond this primary use case, I have worked on data warehouses and ETL automations using Informatica, Talent, SSIS, Databricks, and Hadoop jobs. Additionally, I have experience with financial end-of-day processing, ERP and SAP job scheduling, file transfer automation, and cloud and DevOps workflows.

For managing the integration and sequencing of data processing across diverse data platforms and cloud environments, we perform application integration using SAP, Oracle, SQL Server, Informatica, Hadoop, Databricks, and AWS. We also handle API integration, file transfer, data integration, CI/CD pipelines, and event-driven integration.

Control-M is already being used to support AI and ML workloads within our organization.

Control-M has demonstrated excellent capabilities for integrating Kubernetes and cloud-native workflows with traditional batch processing. Common use cases include data pipeline automation, AI/ML workloads, and microservice operations.

The platform enables running health checks, scaling workloads through Kubernetes APIs, executing and maintaining jobs, and deploying containers.

Regarding compliance requirements such as SOX, audit trails, and regulatory reporting, Control-M provides complete audit trail functionality, change management, and records documenting who created, modified, approved, and executed jobs. The platform includes role-based access control, execution logs, and comprehensive compliance reporting features.

Control-M has impacted my organization positively through various factors. It manages ETL pipelines and data warehouses for critical business operations, improves service level adherence, reduces operational efforts, and provides issue resolution support. The platform enables large-scale client engagements and facilitates data-driven decision-making.

Control-M has achieved significant improvements across multiple dimensions. It has reduced operational effort, accelerated issue resolution time, and enabled support for large-scale client engagements while automating critical business processes. The platform has proven beneficial in enabling data-driven decision-making in numerous ways.

Control-M offers ten outstanding features: centralized job scheduling, workflow orchestration, real-time monitoring, alerting and notifications, file transfer automation, SLA management, cloud and DevOps integration, self-service portal, audit and compliance, and high reliability.

In my day-to-day work as a technical lead, I rely most on job monitoring, which helps verify that scheduled jobs complete successfully and enables investigation into job failures and rerunning them when needed. Workflow dependency management, scheduling alerts and notifications, and restart and recovery capabilities are essential for monitoring ETL jobs and rerunning failed jobs.

Additional features worth highlighting include scheduling daily, weekly, monthly, and event-based job executions, along with the ability to restart failed jobs from the point of failure rather than rerunning entire workflows.

Regarding Control-M's AI capabilities, key features include predictive service level agreements, anomaly detection, intelligent root cause analysis, event-driven automations, AI ops integrations, and automated remediation. These features deliver business benefits including reduced operational effort, faster incident resolution, better service level compliance, reduced downtime, and improved productivity of support and operations teams.

Control-M's accuracy ensures jobs run with correct dependencies and sequencing, reduces human errors caused by manual execution, provides consistent and repeatable workflow execution, and improves data accuracy by automating ETL and reporting processes.

The platform's reliability delivers consistent job execution across environments, supports automatic restart and recovery of failed jobs, provides real-time monitoring and alerting, and helps maintain high service level compliance and business continuity.

Control-M can be improved in several ways. Key innovation areas include developing a simpler user interface, enhancing cloud-native support, implementing AI-driven predictive analytics, accelerating DevOps integration, expanding self-service features, and providing cost optimization insights.

More specific improvements would include creating more interactive dashboards for executive and operations teams and implementing better workflow dependency visualizations to make Control-M more business user friendly.

I have been using Control-M for the past three years. Control-M functions as an enterprise workload automation and job scheduling tool that automates, manages, and monitors batch jobs and workflows and business processes across different platforms. It automates scripts, applications, database jobs, ETL processes, and file transfers.

Control-M is stable.

Control-M demonstrates very high scalability.

The customer support is 100 percent good. I would rate the customer support as a 10 out of 10.

I have worked with different solutions previously. Various solutions have been created with multiple screens addressing return on investment and client values. These previous solutions included monitoring, planning, forecast, history, reporting, and alerts and notification capabilities.

Control-M is commonly deployed on-premises within our organization, though we also utilize private, hybrid, and cloud-hosted Control-M deployments across Azure, GCP, and AWS.

Control-M has delivered strong return on investment. The software achieves 50 to 90 percent reduction in manual scaling effort. The platform has improved service levels, reduced production issues, enabled faster recovery from failures, and strengthened audit and compliance capabilities.

Regarding pricing, setup cost, and licensing, my experience has been very positive. The pricing, cost, and licensing structure is excellent.

Before choosing Control-M, I evaluated many alternative options including alert listings, workload change manager, MFT, self-service portal, configuration management, dashboard view, and BIM.

I would rate Control-M 10 out of 10 overall. Control-M stands out due to its various features that facilitate better engagement for everyone. The platform enables fast execution and delivers numerous benefits. I use all three major cloud providers with Control-M.

My advice to others looking into using Control-M is that the platform offers 10 to 15 valuable features that provide comprehensive workload automation capabilities. Control-M is the best solution in its category.

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.

My main use case for Control-M is file transfer, SAP jobs, process optimization, flow control, and batch execution. In the project, we have several SAP steps that run and create a file, and these files are transferred to servers where they are consumed by other applications.

Control-M made things easier because we were migrating from Decisys to Control-M, which allowed us to gain more visibility into the transfer and into the processes. The best features that Control-M offers me in my day-to-day work are flow monitoring, environment control, and ease of troubleshooting. I work with the administration of Control-M, and these features help us because we can monitor the flow end to end. The ease of using reporting, reports, job history, querying job history, and the organizational structure of the jobs in the scheduling mesh helps tremendously in making it easier to administer and monitor the environment.

Control-M could be improved by not selling Insight separately; it should be part of Monitor.

I have been using Control-M for about four years.

Control-M is stable in my experience, although we had some difficulties in the implementation because our environment is very complex.

Increasing demand for Control-M in my environment is simple. We cannot increase demand when we reach the license limit per job per task, as we are limited by tasks, but as long as we have tasks, the scalability is straightforward and easy.

Control-M's customer support is very good and has met our needs so far.

The company previously used Decisys, which is a tool that is just a scheduler. We are moving to Control-M for a more robust tool with several plugins that can serve various areas and give better flow to the processes.

There are three of us involved in the implementation and maintenance of Control-M: one technical lead and two analysts.

During the migration, Control-M had a positive impact on my organization because we were able to optimize several file transmission flows where I used to have several steps and could only accomplish them with several jobs. With Control-M we can run it with a single step and a single job.

We managed to reduce around 30 percent of the jobs in the migration as an improvement metric.

I did not participate in the selection process for Control-M. I was only hired to do the migration and continue working with Control-M in the company.

Control-M is a complete tool with several plugins for various applications, though the flaw is not having Insight included rather than sold separately. My advice to others who are thinking about using Control-M is to do a thorough survey of what they have and where they are going in order to make an accurate calculation of the number of licenses, foreseeing license increases gradually.

Control-M is a very versatile and robust tool that is worthwhile for large companies. It has stable support, allows management on various platforms, provides flow management, and enables management of time and flow lifetime. I would rate Control-M overall an eight out of ten.

Control-M is one of the scheduling tools where we can schedule the jobs overnight in contact center operations. I do not have any hands-on experience with Genesys Cloud CX. I have experience with Genesys on-premise. So far, I have not had an opportunity to work on the cloud. As of now, I'm working in one of the ANZ banks, which is located in Australia, where we are migrating from on-premise to cloud, and it is in progress. In the last quarter, they initiated the migration's first phase. It will take around two years to complete the migration. Until then, we are part of on-premise engage support.

With Control-M, I use it to automate jobs overnight. For example, if there is database purging, we will automate the job. We will set up the job in Control-M, and the job will initiate the process. Overnight, it will complete the process as per the schedule. To reduce manual work, we automate the scheduling jobs in Control-M. Not only in the database, there are a couple of Genesys jobs as well. CMI data processing and a few dialer jobs are placed on Control-M. This is for dialing processing to update the contact history data and calling list data. We will upload this data to the BH, and then to Control-M. Control-M will process the job as per the schedule, say eleven o'clock or eleven thirty. There are three schedules in the present environment. It will run automatically. If there is any patching on the Control-M servers or database servers on the end-user application side, we have to stop the applications and stop the job. Once the activity is completed, we will resume the jobs and reorder the jobs.

In my organization, Control-M is deployed on the cloud, and they recently migrated from on-premise to cloud. The console is the same, but where we are trying to access the application, we are using the CPC, the cloud environment variables. We try to launch the bank using Azure.

Control-M is one of the best solutions to automate jobs, and it should optimize manual work. It processes with the automation scripts, which helps the contact center operations run smoothly. That is the main purpose we use it for: following the schedule for callbacks and automating the scripts where it is necessary for the operations.

From my operations end, Control-M is worthy. I am not sure about the exact pricing, but it is very valuable. Control-M is the only asset where we can run all contact center operations for automating the scheduled jobs. There is a separate team that handles all the admin and maintenance processes. We are authorized only for our applications, our Genesys applications. We have restricted access where we can access our Genesys and nice jobs. For these two clusters, we have visibility to access the jobs, and we can manage them from our application end.

The positive impact I have seen from using Control-M so far is quality. It has smooth operations and scalability. Even though it is more optimized, optimization is a necessary requirement. The benefits would be to reduce manual efforts. It is flexible to operate technically and to understand the platform and solutions.

Control-M could be improved or enhanced in some areas. There are several optimization solutions out there, but Control-M is feasible. We can easily adapt and learn it. It is easy to operate in scheduling, operating, and monitoring, so it is easy to access. Even though the user interface is simple, it is very familiar to techies who can handle it. If we had complete control of the console, then we could deep-dive on the restricted access and have the specifications of restrictions. That way, we would gain more knowledge on it. As of now, it is user-friendly.

To improve the scalability, the user access controls are important. For the failover jobs, where we can see the output and the log section, there are a lot of redundancy events. We would appreciate it if they could improve event generation and optimize the log events to read the applications. If they update that, it would be great. Our market is different from the outside. Based on the initial integrations and commitments, they have been configured in such a way. Different organizations might be following different norms.

I have used Control-M for the last four years.

I would rate the scalability of Control-M a seven out of ten. It is feasible.

We are not authorized to engage with customer support from Control-M. There are teams that do. Usually, if anything comes to us, we review it on our side. If there are any errors related to our application and if it is not, then we straight away engage with the Control-M team. They will reach out to the support team if required. Otherwise, if they have the knowledge to resolve it, they will resolve it.

Initially I worked on an HSBC project where they were using the same Control-M. In previous organizations, they were not using any scheduling tools. It was an insurance company. As of now, I have only used BMC Control-M.

I did not have the privileges for the complete initial installation and configuration of Control-M. I initiated our application jobs, where we initiate the scheduling of new jobs, making orders, progressive, and taking over from the monitoring phase. We can do that from a specific application cluster. For a complete installation, I think it would be easier. If we get control over things, it is easier for learning quickly.

With Control-M, I have learned that there are depending teams. Control-M is one of the best solutions. Each team has several jobs. Each application might have built the jobs. If there is any cycle, like patching windows, in the specific cluster, if our Genesys jobs are running on the cycle, those jobs might failover. There are dependency applications we have to engage with, and ask them to follow up. Dependent applications might be impacted. It is a challenge to communicate with the vendors and collaborate with all the relevant application stakeholders and inform them to put their jobs on hold. If there are any jobs related to them, we have to engage with them and follow up to hold the process. Once the activity is completed, we have to roll back the application and resume the jobs. There are some challenges while performing the monthly cycle patching. They recently migrated to cloud, but we may not involve them in the cloud. That would be the best solution on the cloud. All those optimizations mean we may not need to follow up with communications. We will just inform them via email or inform all the restricted users and permissions. It is easy. Once the cloud is in place, these are all challenges.

Overall, there are challenges in communicating with internal and external teams and coordinating. That requires manual resources to follow up on every cycle patching. Before Control-M, I would use something that is easily accessible and can integrate with BMC Control-M. Rather than other solutions, I would prefer Control-M.

When I was deploying the applications, there would be a lot of permission relevancy. Based on those permissions, we have to engage with the admins, the Control-M team who have the privileged access. We ask them to join us on the deployments, and we try to gain the privileges. We take over from our application configurations. Once it is completed, they revoke the access. For change deployments, we gain privilege access, admin privilege access, from those who are authorized in the bank. We have specific teams. We cannot control their applications. Each team has their own privileges. Whatever we require, we usually ask them to provide the privilege access, and we will take it from there. Overall, we are not authorized in Control-M, for four years in the market. We are just on the application side; we are end-to-end Genesys operations. There are a couple of jobs in Genesys, and those we deploy in Control-M. From our Genesys applications end, we have a pretty good experience using Control-M, where we can schedule the jobs, run the jobs, and troubleshoot the jobs if required. I have this much knowledge about scheduling, monitoring, and troubleshooting the jobs. For the specific applications, each application is required for the specific operations, permissions, and privileges. If I get the opportunity, we will go through it end-to-end. I have completed the certification, the initial Control-M certification, where we can gain access. I would rate my overall experience with Control-M a seven out of ten.

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.

We use Control-M for enterprise workload automation, cross-platform job scheduling, and orchestration of critical banking processes. One of our most important use cases is End-of-Day (EOD) processing, where Control-M coordinates and monitors complex job dependencies across IBM i, Linux, Windows, databases, and core banking applications. It provides centralized visibility, improves operational efficiency, and reduces manual intervention and operational risk.

Control-M has significantly improved our visibility into end-to-end business processes that span multiple platforms and systems. It has enabled faster identification and resolution of process execution issues through centralized monitoring and alerting. Additionally, by automating tasks that were previously performed manually, Control-M has substantially reduced operational errors, increased process reliability, and improved overall operational efficiency.

Control-M is a very robust solution. The product is stable and robust, providing reliability in operations.

One area where Control-M could be enhanced is by providing native scripting capabilities directly within the platform. Today, when we need to perform complex logic, data manipulation, or multi-step workflows, we must develop scripts externally (for example in Bash, Perl, Python, or other languages) on the target execution server and then invoke those scripts from Control-M. It would be valuable to have a built-in scripting environment that allows users to develop and execute workflow logic directly within Control-M, without relying on external scripts or operating system dependencies.

For example, a workflow could execute a query against an Oracle database, process the results, generate an Excel report, send it by email, and then trigger additional processes on other platforms such as IBM i (AS400), Windows, Linux, or cloud environments—all orchestrated through a native Control-M scripting language.

This functionality would reduce implementation complexity, improve portability, simplify maintenance, and provide greater flexibility for advanced process automation.
Additionally, greater access to variables, conditional logic, and workflow programming constructs within the platform would make Control-M even more powerful for organizations managing complex enterprise workloads.

Another area for improvement is licensing flexibility. Some capabilities that many customers may consider part of the core workload automation experience, such as extended log retention and archiving, currently require additional licensed components. A more integrated approach could provide greater value and simplify adoption.

One improvement that could be made to Control-M is the way jobs captured through SBMJOB on IBM i (AS/400) are handled. On the Extractor side, it would be helpful to have a more flexible and efficient way to manage extraction rules.

On the Interceptor side, having a single folder per AS/400 library is not very practical. It makes it more difficult to organize jobs, use conditions effectively, and manage our workflows, especially when they are affected by the New Day process

Our institution has been using Control-M since late 2022. However, I have been familiar with the product and its capabilities since 2010 through my professional experience managing enterprise workload automation and job scheduling environments.

Control-M is very stable for us and very robust.

Control-M has proven to be highly reliable and capable of supporting large-scale enterprise workloads. From a scalability perspective, I would rate it around 8 out of 10.
The platform scales well in terms of the number of jobs, workflows, and systems that can be managed centrally.

However, when integrating new applications or platforms, significant development effort is sometimes required on the target systems. Complex automation scenarios often require external scripts or custom integrations, which can increase implementation and maintenance effort.

For this reason, while Control-M is highly scalable from an operational and workload management standpoint, I believe there is room for improvement in simplifying integrations and providing more native workflow development capabilities. Reducing the dependency on external scripting would make onboarding new systems faster and further enhance the platform's scalability.

We typically work through our implementation partner, who serves as our primary point of contact for support and manages most interactions with BMC on our behalf.

Overall, I would rate BMC's technical support 7 out of 10. The support quality is generally good, and issues are ultimately addressed. However, we have observed longer-than-expected response times in some cases, particularly when incidents require escalation to higher support tiers. The escalation process can be slow and sometimes extends the overall resolution time.

Despite this, the expertise of the support teams has been satisfactory, and we have no major concerns regarding the quality of the technical assistance provided.

Yes. Prior to adopting Control-M, the institution used HP Operations Orchestration for the automation and orchestration of core business processes, as well as IBM Advanced Job Scheduler for IBM i workload scheduling. We transitioned to Control-M to consolidate workload automation across multiple platforms, improve end-to-end visibility, enhance monitoring and dependency management, and provide a more centralized and scalable enterprise scheduling solution.

The initial implementation was relatively complex. A significant part of the effort was not the Control-M installation itself, but the application and process changes required to adapt our existing workloads to operate within the Control-M framework.

Many of our existing processes had to be modified to integrate with Control-M, which increased the complexity of the initial deployment. This was especially true for legacy applications and workloads that were not originally designed for centralized workload automation.

However, once the foundational integration work was completed and standards were established, onboarding new applications and developing new automated workflows became much easier and more efficient. Today, implementing new processes is significantly more agile than during the initial adoption phase.

Yes. As the customer, we worked with a BMC Business Partner that provided both the software licensing and the implementation services. Our experience was positive overall, as they supported the deployment, knowledge transfer, and initial configuration activities, helping us successfully adopt the platform within our environment.

Control-M does not sell any perpetual licenses right now. I have to constantly renew my contract as a software subscription license. I think the pricing is a little high, but the solution is very robust and stable. I mean, I am paying for a Mercedes, and I am getting a Mercedes. My overall rating for Control-M out of ten for the solution overall is a seven. It is pricey, but it is stable. On the other hand, I have to work a lot to adapt my software to run with Control-M.

Control-M did consolidate job scheduler tools in my organization by pulling it all in one place.

What I like the most about Control-M is the task management, specifically the ability to integrate with multiple products and successfully complete repetitive tasks with ease.

It is easy to integrate Control-M with other technologies as my DataOps and DevOps processes change.

Control-M is excellent for building, scheduling, managing, and monitoring production workflows, but I would not use it for monitoring purposes.

The feature I would like to add is related to the licensing model, which I find challenging. The licensing model is based on the number of repetitive runs rather than the number of tasks. Sometimes it is difficult to understand how many runs we may have in a particular requirement.

I have been using Control-M overall for the last year.

Control-M is pretty scalable based on what we are currently using. However, what we intend to do is try to reduce its application and use it more effectively rather than scaling it.

Regarding technical support, we have a support contract, and when we reach out to them, the response is always very fast. Whatever we need gets addressed quickly.

Before Control-M, we were using Ansible.

The initial deployment of Control-M was fairly easy. I don't exactly remember how long it took the first time, but I think it was set up entirely in two hours.

I have used alternatives, but nothing comes close to Control-M because the advantage that Control-M has is the ability to convert business applications data integration into other IT-related solutions that we use. In other cases, we would have to use multiple middleware. There are products evolving in the market that we are seeing that could be utilized here, but nothing is completely replacing Control-M fully. We really have to look into custom development to plug those gaps.

I have been working in my current field as a professional for the last 18 years.

Control-M does require maintenance on my end. The overall server management involves ensuring that patches, vulnerability validations, and related tasks are properly handled because we have it in an on-premises deployment. Many deployments need this level of attention when it comes to patch management and vulnerabilities. Those are the types of maintenance and version controls required.

I would give Control-M an overall score of 8.5 out of 10.

Our primary use case for Control-M at UniSuper is workload automation and orchestration, which involves different business processes such as getting a file from a third party, extracting some data from that file, and finally uploading that file to the database.

In this way, the primary use case is managing the workload and being a central point of scheduling in UniSuper.

Currently, our usage of cloud environments is very limited, as we are migrating Control-M from an on-premises environment to a SaaS environment.

After we migrate to SaaS, we will be more focused on utilizing cloud integration or cloud-based features.

Control-M is playing a major role in UniSuper for integrating with different applications.

We have integrated Control-M with CyberArk for security purposes, ensuring that all passwords are stored securely and retrieved automatically rather than being copied as plain text.

We are also in the process of integrating Control-M with Azure Key Vault to securely manage connection profiles for transferring files to Azure Blob storage, which is a best practice.

In the future, we are planning to integrate Control-M with AI and ML workloads, utilizing AI features mainly for workload automation, such as using the inbuilt AI agent, Jet, to create jobs, dependencies, and workflows.

Control-M plays a very critical role in UniSuper's compliance, especially with PayDay Super coming in Australia by July 2026.

Control-M is essential for processing employer contributions from third parties and ensuring timely responses under the SLA.

Some benefits which we have seen by using Control-M is that it serves as a central point of scheduling in UniSuper.

Previously, I saw different applications running jobs individually, with dependencies on other applications.

If a job inside a particular application failed, the other application SME had to check the issue.

After bringing in Control-M, it has become centralized, meaning if a first job for X application fails, the second job will not run, and we will know why it has not run, allowing us to easily identify and fix the reason for the failure.

Personally speaking, I value the Managed File Transfer functionality of Control-M the most because we have been using it vastly in our organization, as we receive a lot of files from third parties, process them, and send back the files to the third parties.

Apart from that, we also run OS jobs, which are basically running some commands and running scripts on Control-M.

Control-M is a well-maintained platform, but one improvement I can suggest pertains to the administrative part.

As we are migrating Control-M from on-premises to SaaS, easier methods for migrating all components such as calendars and connection profiles would be beneficial.

I have been using Control-M for five years.

Control-M has great reliability and stability.

After we move to SaaS, we will experience zero downtime during upgrades, facilitating continuous workflow operations, which is a significant improvement over on-premises environments.

In 2025, 50% of people at UniSuper were not aware of what Control-M is beyond being a scheduler.

After increasing visibility and scaling by 20% in the number of jobs created over a year, we believe moving to SaaS will enhance our use of Control-M features.

I have worked with BMC Support, and I would rate their support nine out of ten.

They help us resolve issues quickly, and their documentation is self-explanatory, often allowing us to solve problems without direct support.

From an operational perspective, there is a huge benefit and vast increase since we brought Control-M into the picture, centralizing all individual scheduled jobs that were previously managed by different applications.

For operational purposes, having a centralized point of monitoring and scheduling is very important.

If one job fails for a certain application, a centralized point allows us to easily identify which job has failed, its related application, and what the issue is.

Control-M serves as a central point for workload automation and orchestration, aiding in the creation and monitoring of business workflows.

The only improvement I see is the need for better migration methods.

I rate Control-M nine out of ten.