Control-M Reviews

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.

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

My main business use cases supported by Control-M involve working with healthcare, insurance, telecoms, and banking, both retail and investment, primarily to ensure things are working. Much of this is in regulated industries, so we have established the necessary processes and tools to ensure that Control-M code is properly controlled, allowing us to satisfy SOX audits and other similar regulatory requirements.

Host groups are one of the most valuable (and unrecognised) features in Control-M and allows you to make your code environment agnostic. They allow for load-balancing, simple scaling, and technology groupings. Control-M supports my DataOps and DevOps initiatives by providing a single pane of glass to orchestrate and manage workflows across numerous systems. With the integrations, I have access to all my on-prem and cloud-based applications, and I can write my own interfaces for systems that are no longer supported, such as managing Solaris machines which still run for some of my clients.

Control-M integrates with new or changing technologies within my DataOps or DevOps stack fairly easily. The BMC team consistently develops new integrations at a rate of two or three a month. If they have not already got an integration available, it is very straightforward for me to create one myself, even for older technology through agentless connections to unsupported systems.

Control-M enables new capabilities or business processes that were not previously possible. There is significant capability embedded in the tool, some of which is not immediately obvious. With some creative thinking, I can leverage these capabilities to improve performance and allow Control-M to handle much of the load balancing.

One key element where Control-M could be improved is in providing a better audit trail for converting from development through to test and then to production environments. The process can currently be done, but the XML version is difficult. JSON offers an easier approach and is going to be the standard moving forward, so some XML-related issues will resolve naturally. For those still on XML for source control, it is an ideal opportunity to review procedures within Control-M to ensure compliance.

I joined JP Morgan in 2007, which introduced me to Control-M, and I have essentially been working with Control-M ever since then, marking 18 years this year.

The stability and reliability of Control-M in my experience is commendable; it simply works if set up correctly. Proper analysis of infrastructure requirements, source code control, and growth expectations should be carried out before commencing the migration. Once those factors are right, the conversion should run very smoothly. It is important that the conversion is carried out by a collaboration between teams that understand the old and new systems.

Control-M orchestrates workloads across multiple environments quite easily. I find that the graphical interface is very user-friendly, and although I have traditionally used the desktop interface, the web interface in version 22 is now nearly as effective as the desktop.

My experience with pricing, setup costs, and licensing for Control-M raises interesting points. Pricing is often perceived as high, and the licensing model can be unclear. However, in the end, it is clear that I am paying for a top-end tool which rarely experiences issues, with most problems stemming from the applications being managed rather than the tooling itself.

Regarding other solutions considered before selecting Control-M, I have seen conversions from Redwood and witnessed attempts to convert out of Control-M into a cheaper product. These attempts often ended in failure, leading to a reversion back to Control-M. Currently, I am looking at conversions from TWS into Control-M SaaS, and Axway into Control-M SaaS, along with several other potential conversions.

With proper planning, setuo is straightforward.

The biggest return on investment I have experienced with Control-M is the reduction in support time. If I set things up correctly with appropriate alerting levels, my support team can proactively prevent incidents rather than waiting for something to go wrong. The most significant metric is the number of support tickets prevented, rather than the number of support tickets closed.

My experience with pricing, setup costs, and licensing for Control-M raises interesting points. Pricing is often perceived as high, and the licensing model can be unclear. However, in the end, it is clear that I am paying for a top-end tool which rarely experiences issues, with most problems stemming from the applications being managed rather than the tooling itself.

When considering the overall experience with the migration processes of my customers, I find that if they approach the process with proper planning and due diligence, it typically goes very smoothly. A common mistake is trying to lift and drop what they had in another tool into Control-M without considering process differences, as the tools do not function the same way.

My advice to other companies considering Control-M is to conduct due diligence, examining not just initial costs but also ongoing expenses. It is essential to consider anticipated usage duration and growth patterns, as a correct setup facilitates easy growth, whereas a faulty setup complicates matters.

I would rate Control-M overall as a 10 out of 10.

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 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)

My main use cases of Control-M involve workload automation, with two key areas being financial reconciliation and supply chain management. In financial reconciliation, a global financial services company pulls data from all its divisions around the world to perform end-of-day, end-of-month, and end-of-quarter reconciliation across a range of technologies, teams, and borders.

In supply chain management, manufacturers with retail stores need to ensure that the right stock is in the right places, which can be complicated. The third main use case relates to integration with SAP, making existing PA environments cheaper and less service-heavy. Those are the three main ones in my customer base.

My customers use Control-M to orchestrate workloads across multiple environments. Control-M orchestration is capable of handling complex data pipelines or analytic processes, which is key for some of our financial services customer use cases and is a relatively core part of their requirements.

My banking customer that moved some capabilities to the cloud uses Control-M for both on-premises and cloud technologies, so that's my awareness regarding the creation and automation of data pipelines across those environments.

The features of Control-M that I find most appealing, and that I've heard customers appreciate, include the file transfer capability, which is very unsexy but fundamentally important. It's what it's all about—extracting data and moving it to different places.

The relationship between Control-M and my clients' DataOps and DevOps initiatives is complex. Most of our customers have their DevOps initiatives somewhat divorced from the Control-M elements. However, this is slowly changing as DevOps starts to incorporate both customer-facing aspects and the internal legacy parts of their business. They are gradually integrating, and that agile way of working is coming closer together.

The measurable benefits or improvements my clients have seen with Control-M relate to compliance, particularly in financial reconciliation. There are significant financial penalties for errors in this area, so it's crucial to develop a robust integration with ITSM systems to ensure that tasks perform as intended and meet the right SLAs.

Control-M can be improved by continuing the trend of being both a mature product and one that is not standing still, as evidenced by the ongoing improvements we've seen. The file transfer piece is particularly popular, and it's essential to keep up with the demands that customers place on it.

I suspect a lot of my customers aren't pushing the boundaries of what Control-M can scale to, but the job scheduler approach allows for immense scalability. Many of our customers are only beginning to explore its capabilities.

I have been selling Control-M for one and a half years.

I don't believe any of my customers have reported issues around the availability of Control-M regarding stability and reliability.

I suspect a lot of my customers aren't pushing the boundaries of what Control-M can scale to, but the job scheduler approach allows for immense scalability. Many of our customers are only beginning to explore its capabilities.

I haven't heard any complaints about BMC's service team support; as far as I know, customers feel comfortable about it. Of course, I can't speak from personal experience.

Neutral

There is a competitor to Control-M that many of my customers consider; the big one is IBM's IWS. There is some anecdotal evidence of dissatisfaction among customers regarding support since it has moved to HCL. I recently spoke to someone about exactly that scenario.

The overall experience of the migration and deployment process for my customers tends to be a horror show because migrations are critical and touch everything. The biggest challenge people face is unpicking the complexities involved. Thus, it's often hard to simply migrate, especially while maintaining a good relationship with the existing vendor.

On the topic of pricing, setup cost, and licensing for Control-M, everyone moans about it. We work with some customers on optimizing their job structure to deliver proper value for money. This is significant work, as getting value for money is a challenge we constantly address.

The biggest return on investment for users of Control-M in the financial sector can be fairly straightforward: you can easily state how much performing tasks manually would cost in person-hours. By avoiding financial penalties from regulations, the business case essentially writes itself. In manufacturing, it's more complex, as you look at how to minimize manual costs and whether Control-M helps reduce customer churn and ensures stock is in the right location. Extracting this information aids in making the business case.

On the topic of pricing, setup cost, and licensing for Control-M, everyone moans about it. We work with some customers on optimizing their job structure to deliver proper value for money. This is significant work, as getting value for money is a challenge we constantly address.

There is a competitor to Control-M that many of my customers consider; the big one is IBM's IWS. There is some anecdotal evidence of dissatisfaction among customers regarding support since it has moved to HCL. I recently spoke to someone about exactly that scenario.

In my company, zero users interact with Control-M because we don't actively use it; we just sell it. My customer base ranges widely, with some cases having a small batch team of a few dozen users up to hundreds, probably more in rough figures. I wouldn't have huge visibility on that.

I have heard of the Control-M Python client or API very recently. My experience selling the Control-M Python client or API is relatively new to me. It's not entirely new, but it hasn't come up much in my customer base. However, as DevOps and Control-M are becoming better together, I am seeing more of that.

Regarding metrics or data on how my customers perceive Control-M, I don't have any off the top of my head, and I probably would be privileged to know.

My advice to a company considering Control-M is to bring us in to help with the assessment work. Go through a value stream exercise to clarify what you're trying to accomplish and examine the entire end-to-end process. Control-M and workload automation is a solved problem; it's something you should buy rather than build yourself. That would eliminate undifferentiated heavy lifting. Certainly, we can assist clients with automation and value chain assessment, especially beyond the BMC space, which often presents a messy and complex landscape. I would rate this product a 9 out of 10.

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

I am currently working as a Data Engineer at Cognizant. I have been using Control-M for the past eight months since I joined Cognizant as a Data Engineer. As a Data Engineer, my job is to monitor jobs and maintain pipelines, and Control-M is a scheduler tool which we use to schedule jobs by linking the jobs as predecessors and successors so that the flow of the data pipelines continues without human interference.

The daily important task which we are monitoring is the SaleRPT report, which gives business users the sales that happened the previous day in a restaurant at our project in Cognizant. The jobs are connected in such a way that starting, there are replication jobs, and then they are connected to SQL Server to transform the data and load it into Oracle SQL. From there, again, the data is loaded into our data warehouse tables, and the final target tables are Essbase. So this total flow has around 17 to 18 jobs which are scheduled to run twice a day when we get EOD clearance for each site. So these are the latest tasks for which I used Control-M to schedule jobs in a sequential manner.

In our legacy system, there are some Informatica jobs and some SnapLogic jobs. For example, there are three sets of jobs which are from Informatica, and the next successor jobs are from SnapLogic. Control-M allows us to link these Informatica jobs to SnapLogic. If the Informatica job is completed, it would automatically trigger the SnapLogic pipeline. So it allows the usage of multiple tools. For DataOps and DevOps, it is quite important to use Control-M, as it is a scheduler which schedules multiple jobs based on our requirement. We can easily change the schedule for a particular day if we have a lesser number of data. And if there is any data miss, we can also easily reprocess using Control-M by putting a few jobs on hold and running the jobs manually. So I think it is quite extensively important to use Control-M for a Data Engineer at any level.

There are multiple teams which are using Control-M. I think there are nearly 80 to 90 employees who are using Control-M tool in my organization in my current project at Cognizant. Mostly, 60 to 70 percent of them are Data Engineers. Some are from the BI ETL, Business Intelligence ETL team, and some are from the DevOps team, and some are part of the development team also. And some are part of the Aloha Insight team. These are the teams which I know which are currently using Control-M.

I have been using Control-M to monitor and maintain pipelines. It helps us schedule jobs by linking them as predecessors and successors, ensuring the continuous flow of data without human interference. Control-M is the most used tool in my current project and is essential for job scheduling and checking job failures. Its easy interface makes it beginner-friendly.

Control-M's ability to link jobs from different tools such as SnapLogic, Informatica, and GCP DAGs enhances its functionality. The scheduler, ad hoc runs, and job linking features are particularly useful. It allows job connections to various tools and notifies us via email of any job failure, providing logs for quick rectification.

It can save us significant time, reducing errors and the time taken to rectify them. Automatic failure notifications enable rapid response, facilitating efficient job management. Control-M enables development on various platforms, which is essential for DataOps and DevOps operations.

Its user-friendly nature allows quick learning and management of tasks, with significant time savings compared to manual processes. We now receive automated failure notifications, which streamline error rectification and job reruns. Control-M's integration with Informatica and SnapLogic further exemplifies its efficiency.

One thing I find challenging is if a job is executing and we put it on hold, then if a job is an Informatica or SnapLogic job and we put it on hold, the corresponding pipeline in Informatica or SnapLogic would still be executing. We need to again go to that tool and kill the job. Rather, it would be easier if we kill the job in Control-M and it would automatically be killed in Informatica or SnapLogic.

In some cases, some jobs go into a waiting state. So again, we need to change the Control-M settings for that particular job manually to transform it into the normal flow. These are the two things that if they are changed, Control-M would be an even better tool.

I have been using Control-M for the past eight months since I joined Cognizant as a Data Engineer.

We have never experienced any licensing or any security issues from Control-M. My manager and the other members of my upper hierarchy manage the pricing. Since I have been using Control-M for the past almost one year, I have never experienced any security or software issues in it.

Control-M is easily scalable. I would rate it a nine out of ten when it comes to scalability of Control-M.

I have not used customer support until now, as the monitoring and the management of Control-M is done by another team. However, the other team which currently manages Control-M has helped us a lot.

When I was deployed into this project, Control-M was already in use, so I have not chosen or compared Control-M with other tools. Since I have been using it, I have not experienced any flaws or any issues.

For development, maintenance, and changing, I think around four to five people are enough for monitoring. For development, we need quite a lot of them. Once it is developed, only three to four people can easily manage Control-M.

I would recommend Control-M to most people. When it comes to metrics, I am not sure on how much the tool has saved us, but I am quite sure that it saved us a lot of time.

For scheduling, Control-M is the first tool which I have used. Along with Control-M, I am also using DAG monitoring, which is already enabled in GCP, which is almost similar to a scheduler.

We can easily depend on it to schedule the jobs and monitor them. I am already using it quite much for my daily tasks for my project. I am satisfied with the way I am using it and the features it is allowing me.

One thing is how easy it is to use. Anyone, if they open Control-M and look at the jobs, they can easily know how to run a job, how to kill a job, how to put it on hold, how to check the logs, when it started, when it ended, whether it is running fine, or if there are any anomalies in the job. So I would recommend it. I advise them that it is a good tool. I would rate this product an eight out of ten.

On-premises

Other

Control-M is used to run Oracle scripts with scheduled jobs including monthly, weekly, and yearly schedules. Around 50 or more jobs are run every week. Control-M connects to the database, triggers all procedures, performs the operation, and generates the final report. The log is sent to mailboxes detailing how the process went, any issues, or any errors. If there are issues, the mailbox is checked; otherwise, a message indicating successful completion is received along with statistics such as how much time the process took and which processes were run. Jobs are scheduled once, Control-M jobs are created, timing is set up, and the jobs fire automatically at the particular time.

Control-M is used to connect to Oracle products, and through Control-M, a Tableau dashboard is maintained. Most of the scheduling jobs use Control-M to schedule. Control-M helps all products, making it a utility that can be used wherever scheduling features are needed. It is not just for DevOps, databases, or front-end applications; it can be used anywhere without manual intervention to perform particular activities. Wherever there is an opportunity for scheduling jobs, Control-M is the first option.

For migration, Control-M is considered very good. Once all the source and target details are configured in Control-M, it can automatically migrate data. It requires proper configuration and specifying the necessary changes for target technology along with the source system scripts. If properly configured, the complete migration can be triggered end to end. Data migrations and reporting, along with all scheduling activities, can be efficiently managed.

The best features in Control-M include sending emails to mailboxes after the process is completed and providing proper acknowledgement reports. The timing is impressive; it connects very fast and performs activities efficiently. The UI is very friendly, making it easy to configure jobs in Control-M. If core technology scripts are available, creating Control-M jobs is a five-minute task. The GUI is very friendly, which simplifies task assignment, scheduling, canceling, and all these operations, making it easily navigable.

Every week, 50 jobs are run using Control-M. If those 50 jobs were being run manually, it would take more than a week. Through Control-M, the jobs are able to be scheduled within two days, saving around five days of effort.

Before Control-M, jobs would be run on Friday evening so that the process would end by Sunday night, allowing the business to start on Monday. Without Control-M, everything would have to be run manually throughout the week. Thanks to Control-M, around five days are being saved. Otherwise, old data would be received for the current week's business, but now the latest data is received.

Control-M has room for improvement in displaying dashboard-like graphical reports once processes are completed. For example, after scheduling 50 jobs, if a dashboard showing the completed scripts, status, and time taken is displayed within Control-M itself, it would be very helpful. Currently, mailboxes are checked for reports; if it were in Control-M, anyone could check it. Only those configured with specific mail IDs receive emails, so if a few members are not set up, they will not see the reports. If it were available in Control-M, those users could directly check the dashboard.

Control-M has been used for the last two years from the beginning of the project level. Earlier, it was already there in Control-M that the client was using.

The same score for stability is a nine out of ten.

Control-M is capable of handling a large volume of processing if the necessary memory space is provided to the server.

Great support is received, with a rating of nine out of ten.

Positive

Control-M would definitely be recommended because it saves a lot of time. If everything were being done manually, it would take a lot of time to run and validate scripts. If everything is configured in Control-M, even non-experts like front-end staff can trigger jobs, making it simple. It is a one-time configuration, and anyone can trigger it. That is the best part; significant time is saved, and there is no waiting time; the next process starts immediately once the current one is completed. If dependencies are set in Control-M, it starts the next task automatically. That is why Control-M is highly recommended for scheduling.

The client is a big enterprise client.

Control-M requires occasional maintenance, maybe yearly or once every six months for upgrades. A Control-M team manages activities such as maintenance every six months or once a year, including cleaning up scripts or memory.

Around 15 members are using Control-M.

The overall review rating for Control-M is ten out of ten.

On-premises