Control-M Reviews

Control-M's primary use case for our organization is scheduling jobs. We have daily manual work that previously required regular manual intervention, but by setting up Control-M jobs, we have eliminated this need and now run setup jobs on a daily basis that saves significant time.

Our team uses Control-M for scheduling jobs based on any requirement given by the business, and when we encounter repetitive tasks, such as extraction of reports from our database, we set up a job accordingly that extracts the required details and delivers them to our business people.

We have a daily batch with upstream and downstream feeds, and we have configured Control-M jobs including File Watcher jobs, pre-processing jobs, and loading jobs. Once loading is completed, we send reports to our downstream using Control-M jobs.

Control-M offers many features that benefit our operations. File Watcher jobs are particularly useful when we are supposed to receive a file that is not received on time, and we can configure alerts to reach out to the upstream people regarding delays.

Control-M also allows for quick delivery of reports across platforms. The cross-platform delivery feature stands out for our team because we are using a CD connectivity setup with Control-M to send reports from our Linux system to the mainframe system.

Control-M has features for holding a job when it fails due to a feed delay from upstream, and we can keep the job on hold until we receive the feed and then rerun it. We also have features for ordering jobs based on our configured calendar system for weekdays and weekends.

Control-M has positively impacted our organization by automating thousands of jobs, eliminating the need for manual intervention, which reduces the chance of human error.

By using Control-M, we save significant time. For example, it takes only two hours to trigger one hundred jobs compared to a full day without it, resulting in a reduction of thousands of errors in a month.

Control-M can be improved by enhancing the user interface, as some other batch schedulers are more user-friendly.

An additional improvement could be the inclusion of daily usage options on the homepage to facilitate regular work.

I have been using Control-M for eight years.

Control-M is stable.

Control-M is scalable, allowing it to cover one team to another. If we set it up for one team, it may take an hour, and for another team, it may take an additional hour.

Customer support for Control-M is very good, with quick responses and effective redressal mechanisms in place.

We previously used AutoSys but switched to Control-M because it is the best in the market, and the transition was smooth.

We have seen a return on investment, as using Control-M saves us seventy to eighty percent of the costs that would otherwise require one thousand dollars.

I have two to three years of experience with pricing, setup costs, and licensing related to Control-M.

Before choosing Control-M, we evaluated manual processes and other batch job schedulers, and ultimately chose Control-M for its better results.

Control-M is important for building, scheduling, managing, and monitoring production workflows, making it crucial for our Data Ops and Dev Ops initiatives, as it facilitates the delivery of requirements.

We depend entirely on Control-M as our production starts at midnight and completes within two to three hours, which is crucial for our business.

Many users in my organization use Control-M in various roles, including Consultant Specialist, Senior Consultant Specialist, Lead Consultant Specialist, Senior Software Engineer, Software Engineer, Project Manager, and Senior Project Manager.

Integrating Control-M with technologies for our Data Ops and Dev Ops processes can be challenging, but it plays a crucial role in transitioning to a cloud infrastructure and transferring files from one source to a destination.

The governance and security of Control-M entirely depend on how you configure your Control-M jobs, but I can say it is fully controlled and under compliance.

The reliability and output of Control-M are good, with no deviation expected from how it delivers outputs moving forward.

I advise others looking into using Control-M that it provides the best deliverables compared to other tools available in the market. I have rated this product nine out of ten.

My main use case for Control-M is batch scheduling for our company.

We use Control-M for scheduling batch jobs for the application team to process business trading data. Whatever happens during business federal hours, the data is processed during off-hours and must be completed within the stipulated SLA time. We use Control-M to build those jobs, track them, and monitor them.

We use an internal NDM, Native Data Mover, transmission file transmission system, and using that, we transmit data either from mainframe to distributed or from distributed to mainframe. That integration has been connected to Control-M via a batch job.

Control-M has impacted my organization positively as it is a platform with separate capabilities for mainframe and separate capabilities for distributed environments. Whenever there is maintenance for IPL on the mainframe, only the mainframe-related schedules get impacted, while the distributed applications do not experience impact because the maintenance window is very limited. Managing the maintenance of the mainframe and distributed in two different ways is considerably easier.

The best features Control-M offers include Batch Impact Monitoring, which is one great feature I admire, and also the latest dashboard that was released in version 9.22, which was extremely useful. Now each application is starting to build their own dashboard, while Control-M, the platform that runs all the application batch jobs, provides a dashboard that is very useful for Control-M core users as well as the application team who monitor the jobs via Control-M.

Batch Impact Monitoring and the dashboard have made things easier for my team by allowing us to tie any critical path job that has to be monitored to a batch impact monitor pallet. Whenever the job gets loaded in the monitoring tool, we can track where the batch is held or where the path currently is. Any failures or long-running delays can be tracked using Batch Impact Monitoring.

Control-M has facilitated the integration of Kubernetes or cloud-native workflows with traditional batch processing within my organization, and I find it much easier to maintain compared to on-premises, Linux, or Windows machines. We also have our own assembly packages where we can customize our own processes, which helps us.

Control-M can be improved by reducing the frequency of patch releases, as frequent patches create more stress for the organization to maintain a large Control-M environment. If patches are released weekly or biweekly, it becomes very difficult for a large organization like ours to implement new releases frequently, which requires coordination with the application team and is challenging to manage. A quarterly release or semiannual release would be much better.

I have been using Control-M for the last five years.

Control-M is stable.

Control-M's scalability is much higher.

Customer support for Control-M is very impressive, with immediate responses for any escalations.

I would rate the customer support a ten on a scale of one to ten.

Previously, we used one of the Broadcom tools, which was hosted entirely on the mainframe. Since that system required the mainframe to go down for a couple of hours during weekly maintenance, even the distributed applications were impacted. After moving to Control-M, during the maintenance window, only the mainframe batch gets impacted while the distributed applications can run without any interruption, and the distributed applications are much more satisfied with this approach.

We evaluated only Control-M and proceeded with it, as it is the only tool that supports both mainframe and distributed environments.

I would rate Control-M a nine on a scale of one to ten.

I chose nine because I like the options that have been provisioned to the users, which impresses me, but I could not give it a ten because some improvement is required from Control-M.

Control-M's latest features regarding managing the integration and sequencing of data processing across diverse data platforms and cloud environments appear beneficial.

We use a third-party KPMG audit to meet compliance requirements such as SOX, audit trails, and regulatory reporting.

I advise others looking into using Control-M to use the tool as it has everything they need, and to be smart and utilize it as much as possible.

On-premises

My use case for Control-M includes file transfer and workload balancing, but it is mostly focused on workflow management.

I love Control-M's reliability and ease of use. It offers ease of adaptability for upgrades, and the GUI features have been enhanced for better readability. Their reporting improvements are notable, and they developed software that helps manage licensing effectively.

Control-M is incredibly reliable, rarely having issues from an administrative standpoint. The high stability means I am rarely surprised by problems. Additionally, time-saving is significant; previously, scheduling involved paper and took much longer. Control-M reduced the scheduling time drastically, taking only about five to ten minutes to add a new job to the workflow.

One area that has room for improvement is support. Early on, support was fabulous, with efficient issue resolution processes. However, since approximately 2015, support has been lackluster, relying too much on email. I would suggest a return to hands-on support engagement.

Aside from the support aspect, I cannot think of anything else that needs improvement.

I started using Control-M in 2000.

Regarding stability, I would give Control-M a ten. Control-M is such a reliable piece of software. I rarely, if ever, have to do anything from an administrative point of view. When someone calls me with a Control-M problem, it surprises me as it is mostly stable.

Control-M is scalable. The easiest way to express this is regarding licensing; as you are scaling up, you should keep up with your licensing. BMC does an annual review, and your account representative will reach out for a licensing software run that generates a report using all Control-M components.

From one to ten, with ten being the best, I would rate their technical support about a seven.

Positive

Concerning Control-M, I previously started out with scheduling package software back in the old Uccel, which was bought by Computer Associates and called CA-7.

Installing Control-M was really quite easy; you simply download it and do the installation. The biggest thing is the front-end work prior to installation, such as deciding which database you will use.

My relationship with BMC is probably transactional. I rarely have to reach out to them.

The BMC service team could be better at being more involved in mapping out migration strategies, though they have a really good process called AMIGO that yields positive outcomes.

In terms of time savings with Control-M, I spend maybe thirty minutes a week, if that, on Control-M compared to other software products I have dealt with.

I did not have much engagement in the pricing area.

Regarding other solutions, Redwood was the only one I was familiar with. I saw a demo on that before 2010 when management was looking at maybe replacing Control-M.

Deployment is on a Windows platform in a high availability environment.

I would recommend Control-M to others looking to implement it, but it is essential to ensure it fits your environment, so doing a proof of concept is always beneficial.

On-premises

Over the years, I have worked with various firms to install and configure this system. The primary use case is automation, but the file transfer feature is also a valuable integration. Many people quickly understand the file transfer aspect because it is easy to set up. Therefore, automation is our top priority, followed by file transfer as a close second.

The solution has positively impacted my organization by allowing me to point to a single screen and say, 'That's the state of play in our batch operations.' Most sites do things in the daytime, so overnight, there'll be some batch processing running, and then they'll get file updates in the morning. If you can just look at the screen and see we're running 30,000 jobs overnight and this is where the problems are, you can just point to the three little red boxes that are what we need to fix. It's a very good way of being able to tie everything together and say, 'We know what's running, what's not running, and where the problems are.' Also, statistically, you can go back into history and say, 'This thing has been failing several times in the last three months, and we can see where our issues are and where we need to concentrate.'

The best features of Control-M include the fact that you can easily connect different platforms. For anybody coming to it, if you needed to script a solution that connected Windows and Unix and mainframe, that would be difficult. But with Control-M, you can just sit back and connect a COBOL program running on the mainframe, trigger something on the Windows platform, then do a file transfer on Linux. That's all basically just drag and drop. You can just indicate that these lines between these boxes perform those actions. The fact that you can tie different platforms together, including the cloud now, which many people are starting to use extensively, is very helpful.

Integrating Control-M with technologies for Data Ops and DevOps processes can be easy or difficult depending on the site. Many people have embedded methods for these things, so it can be difficult sometimes at various different sites to get it to integrate. It's not the tech or Control-M itself that's the issue; it tends to be the processes at different locations. It is very good at handling DevOps and the change management on the operations side.

Areas of Control-M that have room for improvement include the reporting feature. The reporting on Control-M hasn't changed much over the years, although it is in a different internal format. It used to be Crystal Reports, and now they've upgraded that. It would be better if that was really flexible where you could define your own reports. You can customize it a little bit, but when people come in with complex questions, you should be able to use that tool and access anything in the database.

Control-M has two internal databases that are core to the product. You can go in and do your own SQL queries against the database, but this reporting tool should really be able to do everything that you can do with SQL, and give you good information. Instead, you end up having to export to spreadsheets and then change and update them. It can be very labor-intensive to get this information out.

Other than the reporting, they've addressed most things over the years. Control-M is a tool that's been around for more than 30 years, so they have actually fixed most issues that you would encounter. They have a request for enhancement process that most users have sent requests to, but it doesn't move very quickly. The other challenge is they're supporting so many different platforms; BMC just wants it to be a trouble-free release. When users request new features, such as improved reporting, BMC's priority remains maintaining a clean-running system.

I have been using the product for approximately 24 years.

Control-M is very stable. I would rate it a nine out of ten. It very rarely has anything that goes wrong. It has to be stable; if it wasn't stable, then we wouldn't be using it.

Control-M is scalable for business requirements and needs. On the SaaS side, they've given certain limits which wouldn't allow for moving the entire batch currently to their cloud-based solution. But on-premises, it is completely scalable. Other customers are running a million jobs per day without issues. If you did have issues, you could add servers on the side that would handle the extra workload.

We have around 20 active users logging into the system daily. These users are responsible for managing the cache within the system. This leads to approximately 500 users who receive the messages. Additionally, there are millions of customer names involved. In summary, there are about 20 users logging into the system and around 500 business application users receiving the data.

Their support is excellent. If you encounter an issue that affects your business, you can call them at three o'clock in the morning, and they will help you find a solution.

I would rate the technical support a solid nine out of ten.

Positive

I have always used Control-M. I've worked at sites where they've installed Control-M as new and then migrated various things from CronTab. CronTab is just a Linux tool that comes with the Linux boxes to schedule, but it's the Linux native scheduling. It tends to be quite simple these days. BMC supplies scripts to do the conversion. Problems start to arise when people have created their own solutions on their own platforms, where 90% of the stuff is easily migrated, but 10% will be something specific to Broadcom or other schedulers, requiring script changes in Control-M. The same situation occurs when moving from Control-M, as people often leverage specific features that become problematic when trying to move to different solutions.

It's on-premises. The organization I work for has IT operations in about 60 different countries around the world. We use Control-M in at least 15 or 16 of those locations, and each site can be quite different. For instance, in Paris, they only use it for the mainframe. Our main office is in Germany, where they are starting to use the test version, and they would like us to explore the SaaS version as well. 

If I were to start looking into this, I think a hybrid approach would be the most logical way to organize things. This would allow us to have a clear view of both our on-premises and cloud environments, enabling a gradual migration to the cloud instead of making a major switch all at once. I've seen BMC presentations on this, and it looks promising. The advantage is that I wouldn't have to worry about where each workload is processed; everything can be monitored and managed from a single screen, which is very powerful.

Additionally, I've spoken with users who utilize cloud workloads, and their primary concern is cost rather than the specific platform. Control-M is effective at managing this. For example, if you're planning to deploy a workload on a specific server, the scripts can easily handle the transition to Amazon's cloud the following week. If a provider has a special offer in a month, like Google, it's straightforward to switch our workload to run there instead. With Control-M, this process is transparent and uncomplicated.

The maintenance is complicated. There is patching to consider on both the Control-M service side and for the agents and modules. When it comes to file transfers, you need a specific module from the Managed File Transfer (MFT) service. Typically, every few weeks, we need to install a new set of updates, whether due to a security issue or the introduction of a new feature. If you go to the Application Center (AC) and use that version with your account, you don’t have to worry about caching, as they manage that on the systems. You could use it in a controlled manner, perhaps on a Sunday morning. However, using a basic version might present some challenges for us.

Usually, the Linux team handles the patching, but it's also necessary to conduct tests. Sometimes, the latest version can alter certain behaviors that might not be acceptable in a production environment, so testing is crucial. It does require a separate environment dedicated to that. Overall, managing patches is a significant task. One key selling point of the SaaS solution is that you won’t have to worry about it in the future; BMC takes care of that for you. However, some of my colleagues are concerned that implementing a SaaS version could mean losing a significant portion of their work to automation, particularly the patching responsibilities. It’s definitely a complex situation.

It's hard for me to determine, but at the current location, we did conduct a study. We use Control-M to run a data warehouse, and an external company evaluated our setup. They concluded that the way we operate with our existing tools and at our current scale is actually more efficient and cost-effective than purchasing a packaged data warehouse product, like Informatica.

At my previous employer, we performed a similar study, and the results showed that the product paid for itself within the first year. Moving forward, it continued to be very cost-effective. The benefits tend to be hidden—people often overlook them because these processes run in the background, handling file transfers and other tasks. If I had to hire a developer to script these operations, those costs would be substantial, along with ongoing maintenance.

With Control-M, you define the processes once and then let them run. The operations team can monitor it, which means it integrates seamlessly with existing systems. In terms of return on investment, it pays for itself quite quickly. However, because these advantages are often invisible, people don't fully appreciate the costs and savings involved. You really need to consider the expenses of hiring a developer or operations staff specifically for these tasks. If you use Control-M, those costs effectively disappear, and people tend to just assume that everything is functioning as it should. It's definitely worth noting the return on investment. I'm sure BMC would be happy to provide those figures, demonstrating that it quickly offsets its initial costs, even if there can be significant upfront expenses at times.

Pricing for Control-M depends on the licensing model, with different options such as the per-agent model or the per-job model. BMC is phasing out the per-agent model in favor of per-job licensing, which can be expensive. The Control-M Helix SaaS version will only be available with per-job licensing. Currently, some implementations use a flat rate based on the number of agents. The shift to per-job licensing could have significant cost implications.

Control-M tends to be more expensive compared to other solutions, but users get great value from it. Organizations have invested considerable effort in developing for Control-M, making migration away from it less desirable. Competitors may offer fewer features at a reduced price, which could be a deciding factor for some companies.

Years ago, I was involved in a lot of Proof of Concepts (POC). Back then, IBM's Tivoli and Control-M were quite similar and difficult to differentiate. However, over the years, it’s become clear that IBM has not developed Tivoli to the level that Control-M has achieved. In my opinion, Control-M is now the clear market leader.

These days, you never know what new solutions might emerge that could disrupt the market. Nevertheless, Control-M has a robust footprint—it can integrate with many legacy systems, making it hard for competitors to come close to its capabilities.

While there may be newer solutions out there, I’m not fully aware of all the latest developments. Control-M does have advanced workload balancing in the cloud, but I still believe it remains the top choice for me. I may be biased since I've always worked with Control-M, but when you compare it to alternative tools, you often question whether they can accomplish specific tasks or integrate with various third-party products. You soon discover that many alternatives simply don’t offer the same level of functionality or integration, and even if they plan to provide those features in the future, they haven't yet delivered them.

Overall, I am quite confident in saying that Control-M is the number one product in the market. Of course, if you visit a potential customer site and they have unique requirements—especially if they are primarily Windows-based—they might find another product that better meets their needs than Control-M. However, in general terms and across most scenarios, I firmly believe that Control-M is the market leader in 90% of cases.

Our relationship with BMC has been transformative. However, I get the feeling that we are moving towards a more transactional relationship. Previously, they were very concerned about us using the products, growing with them, and deriving value from them. This was a refreshing attitude from a software company. That said, they are restructuring, and I get the impression that in the future, they may want to accelerate revenue generation. So, the nature of our relationship could change. At present, though, it remains transformational. They have been very helpful, with excellent support, but who knows what the future holds?

I absolutely would recommend BMC Control-M to other users. My only reservation would be with the new licensing structure. If you are going to be paying per job and your batch process was very granular without the ability to restructure, then cost might be an issue. Also, it is the serious high-end scheduling solution, so smaller enterprises might want to consider whether they need all the features that come with Control-M. For small or medium-sized enterprises, different solutions might be more appropriate. 

Overall, I would rate Control-M a nine out of ten.

On-premises

I mainly use Control-M for scheduling jobs according to my requirements, which allows me to include holidays or exclude Saturdays, Sundays, or any specific time.

I also use cyclic jobs that run in a recurring period and can set up prerequisites before the job runs.

I can implement a File Watcher to establish a rule that a particular job can only run after the upstream job is completed.

I have created several new jobs using these capabilities.

Within Control-M, I use smart folders and jobs, and I can approach scheduling the way I want, so I have used it fully from start to end.

Control-M is straightforward for building, scheduling, managing, and monitoring production workflows.

I use the XML side for configuration, which requires importing, and I find it user-friendly.

Control-M has been used for building, scheduling, managing, and monitoring production workflows, especially at JPMorgan Chase Bank where most production support is monitored through Control-M.

I worked as a developer, developed jobs, and sent them to production, and the process was seamless.

My favorite feature about Control-M is the rule-based calendar feature.

The initial deployment of Control-M is straightforward, as it involves a simple installation of a Control-M agent within the server.

Control-M demonstrates strong scalability.

My application alone uses approximately 65 jobs, and for each folder, there are thousands of jobs that can load immediately in production.

When using a filter, the search is quick, and overall scalability has been excellent.

After migrating to Control-M, the positive effect on business-critical applications is evident: whenever a job ends successfully or fails, notifications are sent immediately.

These notifications go to EventBridge, alerting the team to any critical jobs.

High-priority jobs trigger alerts to engage developers immediately, ensuring there is no delay in response.

One area for improvement in Control-M could be in the logs, as they only show when the job started and whether it ended successfully or not.

Since the Control-M agent is running on the servers, we could pull up logs and display the actual error to aid in debugging.

I have been using Control-M for approximately eight to nine years in my career.

Regarding stability, I do not experience any lagging, crashing, or performance issues with Control-M.

Control-M demonstrates strong scalability.

My application alone uses approximately 65 jobs, and for each folder, there are thousands of jobs that can load immediately in production.

When using a filter, the search is quick, and overall scalability has been excellent.

I have never contacted technical support or customer support from BMC regarding Control-M because we have sufficient in-house expertise to share knowledge about it internally.

I started on TWS, Tivoli Workload Scheduler, which is an older tool with a poor user interface.

After transitioning to Control-M, I have been very satisfied with it.

I have not identified pain points until now because the use cases I addressed were fully satisfied by Control-M's capabilities.

Whatever use cases I needed, they were fulfilled by the product.

I used Tivoli Workload Scheduler earlier, but now the company has standardized on Control-M without using any other schedulers.

The initial deployment of Control-M is straightforward, as it involves a simple installation of a Control-M agent within the server.

Only one person is required for deployment, and it can be completed without needing a team.

For both job deployment and software installation, one person typically handles it, as we use an automation process with no manual work, making it a self-service operation.

I have personally used TWS as an alternative to Control-M.

I prefer Control-M over TWS.

The biggest difference between TWS and Control-M is that TWS has a poor user interface, while Control-M has an excellent user interface and alerting capabilities.

TWS requires monitoring on one page without navigation directions, whereas Control-M uses smart folders with parent and subfolders, maintaining a clear graph structure and allowing the creation of custom workspaces.

Regarding data pipelines, I have not explored integrating them via Control-M.

Non-technical users or business users do not need to use Control-M, as they primarily rely on developers or application support.

Currently, all employees at JPMorgan use Control-M for everything except mainframe jobs, which are monitored and developed through Control-M.

For maintenance, a patching team manages it, and I do not experience any downtime with Control-M.

I might not notice maintenance communications since they could be performed behind the scenes or during off-business hours.

I would rate this review an 8 out of 10.

My main use case for Control-M involved jobs and automated jobs where monitoring was not required for extended periods and we could schedule them. This is a scaled version of what we have with Linux called Cron, but it does significantly more and has substantially more management capabilities and control capabilities that help us manage scheduled jobs.

A specific example of a job or process I automated with Control-M was when we had a production data store, database, or file location, and we wanted to have synchronization between the production and development version of it so that the development version could be tested with real-time data as possible. We scheduled the job using Control-M to sync it every few hours so that the people testing on it would actually test it on production data from just a few hours back and kept it up to date to those few hours back in time, allowing them to have the most current data to test, validate, and run their tests rather than running it on some read-only file from production data.

Another example of my use case with Control-M would be to periodically collect and put data metrics into a file location for another application to read. This helped us visualize the data and metrics in an almost real-time manner and in regular frequencies where it could be propagated to the administrators, application developers, or management as well.

We do not use many cloud environments. Most of our infrastructure is on-premises, but we have our own data pipelines and CI/CD pipelines and workflows defined internally as part of our architectural design, which we standardize and follow.

My organization might be using Control-M for AI or ML workloads because I personally am not sure which divisions are using it, but there could be some divisions using Control-M, although it could be very minimal. Mostly, the AI and ML capabilities would be for data analytics and observability metrics, as well as log analysis and faster data migrations or synchronization.

My organization addresses compliance requirements, such as SOX, audit trails, or regulatory reporting with Control-M, as all of that is based on the regulatory dictates given by the regulators. Most of the controls are managed internally by our internal security team, and I would not be able to give more specifics; it is as per the law followed across regions and data sovereignty rules.

Control-M has positively impacted my organization by reducing the manual mundane work of syncing data or propagating data from one place to another, helping our teams work faster and deliver better and quicker results to the end users and clients. It is a significant time-saver and reduces toil.

Approximately, I know a particular team who started using Control-M and saved almost thirty to forty percent of their time which they were using in their day-to-day work that involved regular syncing of data, copying and analyzing that, as well as error management and handling.

The best features Control-M offers, based on my experience, include the scalability, the ease of scheduling things, and a common dashboard to view these scheduled jobs and alerting based on how these jobs work and application error logs management.

Out of those features, the ease of scheduling had the biggest impact for me, and it helps us automate significantly more at a faster pace, while the log analysis part of it and alerting aids in analyzing that data, highlighting any failures or scheduled issues which help us analyze the error logs and take quick action in remediating that.

In terms of improvements for Control-M, one thing I would like to see better is the integration between the scheduling platform itself versus the SDLC lifecycle, which is managed within an organization. The UI is good, but we need better API integration as well as ease of controlling using the command line, so there are no big complications or complex rule sets or syntaxes that need to be used. Basically, better integration and API interoperability are needed.

There are no improvements needed for Control-M that we have not already discussed.

I have not used Control-M for quite a while because we have other control platforms and things for managing our client, but I worked on a firm which used Control-M very long back, maybe more than seven or eight years ago.

Control-M is stable in my experience.

Control-M's scalability from my perspective seems to be developing. We have not scaled up to a larger enterprise level because we use multiple platforms but are slowly ramping up. I think there are many organizations that use Control-M at an enterprise scale, so I would not doubt that. I am just more concerned about the stability. Because of that, we may need to do extensive load and regression testing on the abilities of Control-M in managing an enterprise scale-up environment.

Customer support for Control-M is good. I would rate the customer support as eight out of ten.

Before Control-M, we used multiple solutions such as AutoSys, Cron, or some internally developed tools which we used for scheduling.

While I would not be able to give extensive examples, the integration of Control-M with Kubernetes or cloud-native workflows has involved the adoption and integration of an external vendor tool into the current environment. Because it is a BPSA, we need to have significant scrutiny around what product we are onboarding for scheduling since that can be a lengthy process. Once onboarded, it is about finding how we can better use Control-M while following the security guidelines and making the whole system more secure and effective.

I would not be able to tell on the money saved from using Control-M, but definitely, as I mentioned regarding the teams in my earlier experience, they had saved almost thirty percent of their manual efforts in using Control-M and scheduling things. That is time saved, which is almost equivalent to money saved on a larger scale and in reducing toil and improving employee experience.

The technological committee adopted this based on tests, POCs, and pricing.

On a scale of one to ten, I would rate Control-M overall as a seven.

I give a seven because the factors which I mentioned include ease of interoperability and better API integration, which are where the challenges are. Control-M eases a lot of things for regular users, but given the current technological advances, I feel it could be better improved and better scaled so that at an enterprise level, this adds more value.

Regarding Control-M's AI capabilities, I have not firsthand used Control-M's AI security or AI capabilities, but I would like to understand more through Control-M Innovation Day as well, so I am looking forward to it.

My advice to others looking into using Control-M is that it is a great product, but they should do their testing and analysis, and talk to the Control-M experts within their organization as well as Control-M, to get a better understanding and start spreading out use cases while giving up data, ensuring that extensive testing is done before trying it in the POC phase itself, allowing for course correction or adoption of best practices from Control-M.

On-premises

I'm Graham Burns, and I currently work in IT for a government offshoot section. I use Control-M to perform all batch scheduling and automation of critical business processes. Our organization has been operating for about 40 years, though we were externally managed before. We've recently transitioned to an in-house team.

Data is really important for us, so we work with a lot of external partners and vendors. Getting that data in timely manner and absorbing it into our environment, enriching it, and sending it out to our partners is essential. Control-M helps us do that with data integrity and security.

We are not using Jet yet, but we are at version 9.2.2, and we're going to install the plus patches to be able to use Jet. We're really excited about that because we think it's going to help. We do use AI for a lot of in-house processing, but not in the Control-M space yet, though we will be very soon.

The most exciting thing that we'll be using AI for in Control-M is batch optimization. We're looking to really speed things up and understand how the jobs are running and how we can get them to run quicker and faster to complete the tasks.

We do not use integrations of Kubernetes or cloud-native workloads with traditional batch processing.

Since implementing Control-M, it's still very new as we've only just ported it over.

In terms of benefits, we're still waiting to see because we just implemented it, but we expect improvements in how we reduce the number of exceptions and handle them quicker. I hope that Control-M will deliver on that.

I don't have specific metrics or percentages by how much we've reduced those exceptions or by how faster we are dealing with those problems.

We needed a solution that was easy and accessible for everybody to see and understand with good graphical user interfaces, but also rich functionality underneath. Our existing solution was end of life, so Control-M gave us all the functionality that we had and everything that we thought we might need going into the future.

Probably the most important feature of Control-M is a centralized graphical user interface that allows us to represent all of the enterprise. We can automate all the batches across the whole company and manage it from there. Most importantly, exception management allows us to handle any failures, escalate them through to on-call teams, and have people work on them live in real time, getting the issues resolved quickly.

Since we have a lot of government data in our system, data security is really important for us. Control-M is controlling that for us, ensuring that the information is safe in transit and at rest, which is really important.

We need to know that the data is on Australian shores, not offshore and not available outside of Australia. It's locked down, secure, and safe, and we're not sending it out anywhere unprotected. Control-M helps with that file transfer by keeping it protected and encrypted at rest.

Getting to these sorts of events and seeing all the roadmap that's coming forward is valuable. There are some features that we're not using at the moment that would make things better if we could use them, but Control-M is certainly doing the job for us at the moment, so there's not too much that we're going to be able to improve right now, though perhaps soon.

I've been using BMC for about six months now. What was externally managed before is now in-house, and we needed a solution that was going to be best for us in a modern approach, which is why we went with Control-M.

I assess the stability and reliability of Control-M as very stable, and it's been very good. We are on-premises at the moment, in-house, and we're not SaaS. I'm not sure if we're ever going to get there, but we have it fully installed in-house with production, non-production, and high availability. We've not had any stability issues at all, and it's been great.

Control-M is able to scale up for us. We've flexed up a little bit for proof of concepts and load testing, and we have it right-sized at the moment for our production environment. We're on cloud using AWS with Linux, which allows us to flex up and down, and Control-M supports that as well, being very flexible and allowing us to do everything we want at the right price.

We work directly with BMC for customer support. We have logged a few cases and always received very good support, often locally or at least from the Asia Pacific region. We've even had a lot of help overnight in the past from the international team, and it's always been fantastic.

The local guys servicing the account also provide good access and are always willing to come out and visit us, which adds a lot of value, especially in helping us deliver that value up to the C-level. Having those guys come in at that level and talk to them is fantastic as well. We receive great support on the ground locally.

We needed something that was going to fit the modern need. The other solution that was being used was quite old and wasn't updated, so we were able to go to market when we went in-house, and that's when we selected Control-M.

I wasn't involved in the deployment, but Control-M is simple, out of the box, and easy to replicate. We've actually got it running in at least four different environments, all of them alike and similar, so we've got production and non-production environments, all installed nice and easy.

By next year, I will have been there five months as this is all still new. I would rate Control-M a 10 out of 10. I love it. It's fantastic as it helps me do my job, which involves managing the batch, and that's exactly what it does.

On-premises

Amazon Web Services (AWS)

My main use case for Control-M is job scheduling. I use Control-M for job scheduling by scheduling jobs for the asset team, like OS jobs, MFT jobs, and AFT jobs. I exclusively use Control-M for scheduling.

The best features Control-M offers include monitoring, planning, and forecast. Planning stands out the most for me in Control-M, as it helps me to schedule jobs.

Control-M has positively impacted my organization by allowing us to automate a lot of manual activities, so we are saving time.

Control-M can be improved with GUI features such as job failure monitoring, where the duration can be increased from 30 days to one year so that we can monitor long durations of job failures.

I have been using Control-M for 11 years.

Control-M is stable.

The scalability of Control-M is good.

The customer support for Control-M is fine.

Negative

I did not previously use a different solution.

My experience with pricing, setup cost, and licensing indicates that it is cheaper than other automation tools in the market.

We require five staff members for deployment and maintenance, and they all are consultants.

I have seen a return on investment, specifically in terms of money saved. We are saving a lot of time, as many activities that used to take around three to four hours by manual activity have been reduced to 30 minutes to one hour.

My experience with pricing, setup cost, and licensing indicates that it is cheaper than other automation tools in the market.

Before choosing Control-M, I did not evaluate other options.

My advice to others looking into using Control-M is that it is easy to use, flexible, and stable. The features in Control-M are good, and the GUI of Control-M is actually very fantastic.

Currently, 500 users are using Control-M in my organization, where the majority of them are from the application team and a few are admin and schedulers. Control-M is currently used extensively, and while we do not have plans to increase its usage, we are using Control-M in different domains.

The biggest lesson I have learned from using Control-M is that it makes automation easy. It is easy to integrate Control-M with technologies for my data ops and DevOps processes as things change. I have automated activities on the Linux server while integrating with Control-M.

I would rate this product a 10.

Private Cloud

Amazon Web Services (AWS)

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.

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.

Private Cloud

Microsoft Azure