Control-M Reviews

My main use case for Control-M involves managing various jobs created, such as OS jobs, MFT, file transfers, and Microsoft Fabric database jobs. We handle batch job operations via Control-M.

For a specific example of using Control-M in batch operations, we create a file transfer job triggered by the application's need to start its transfers whenever a file is received. We assist in creating and scheduling those jobs to ensure subsequent jobs perform the business tasks after the transfer is completed.

Regarding my main use case, I worked on migrating Control-M from an older on-premises version 7 to AWS version 9.0.21, overcoming multiple challenges during this significant upgrade and successfully migrating the application to AWS.

Managing integration and sequencing of data processing across various platforms involves using Control-M integrations. We connect multiple applications, whether in the cloud or on-premises, via agents installed on the specific Control-M server.

Currently, there are no plans to use Control-M for AI or ML workloads, but I will be working on bringing AI workflows into Control-M soon.

To meet compliance requirements, we utilize Control-M's Audit and Annotation feature, which helps us pull regular audit reports to ensure complete auditing and compliance with our tasks.

Control-M positively impacts my organization by providing complete workflow automation without manual intervention, which is a significant improvement from previous tools that required much more manual input.

In terms of metrics, I have noticed substantial error reduction thanks to AI features that help identify and fix setup or configuration issues. Control-M's ability to integrate with various applications also reduces costs by eliminating the need for multiple tools.

Control-M offers impressive features, including a good dashboard view where I can easily monitor job status and current progress. With the introduction of AI, it saves time in troubleshooting issues and retrieving reports effortlessly.

In the dashboard view, I can see the status of every job, including their types and execution states. Using AI helps to quickly identify if a job has failed or to generate reports for jobs running within a specific timeframe without manual checks.

As for other features, I find Control-M Workflow Creator quite useful for job creation; however, it seems the team is not fully aware of its capabilities, which is a hidden gem that facilitates automation from setting up templates to creating job scripts.

Regarding improvements, I see that the Jet feature needs better functionality for understanding plain language queries. While dashboard improvements are notable, I believe better AI comprehension in Jet would enhance user experience.

On the topic of needed improvements, I wish for better automation of administrative tasks via Jet and functionality regarding scheduling inquiries as it is currently lacking in support.

I chose nine because some improvements in AI performance and the SaaS version's frequent disconnections prevent it from achieving a perfect score.

I have been working in my current field for more than 15 years.

Control-M is stable.

Control-M's scalability is commendable. With our current smaller setup, we can scale up the environment and job counts according to our needs.

Customer support is a concern because inquiries go to R&D, resulting in delayed responses. Often we are required to replicate issues in production, which is not feasible.

Previously, we used a workload automation tool, but we switched to Control-M for its superior features, capabilities, and AI support.

Regarding pricing and licensing, there is a concern as the cost can be high for additional features, with each extra capability being charged separately.

We did not evaluate other options before choosing Control-M as our experience with the tool led us to directly select it.

I would rate Control-M a nine.

In terms of governance and security, I observe that BMC takes these matters seriously, and they prioritize governance within Control-M.

The accuracy and reliability of Control-M's AI output are almost spot on, achieving about 90 to 95% accuracy. The main challenge lies in its ability to understand the questions posed.

My organization uses the SaaS version of Control-M.

For others considering Control-M, it is essential to explore its multiple options and features, making effective use of what is available to save time and improve efficiency.

My main use case for Control-M is software delivery. I use Control-M to automate and manage an automatic CI/CD workflow.

Control-M offers impressive and highly beneficial features. Control-M is the world's number one best platform I have ever seen, and I have never encountered a platform comparable to Control-M. I am truly a fan of Control-M product, and I hope my team and I will continue forward exclusively with Control-M.

I have witnessed the positive impact of Control-M on my organization, which has saved time, reduced errors, and improved productivity.

I have experienced many positive aspects of Control-M. I am explaining only three of them, but I know my team in my company has experienced many more benefits from Control-M.

When integrating with third-party LLM, I experience latency issues, scalability issues, and concurrency issues, which are critical for my development workflow. I am very interested in understanding how these issues are being solved.

I believe we should understand data better, ensuring it is real and considering what occurs during production time, especially regarding security and threat landscape, as these vulnerabilities are critical issues that must be taken seriously. Focusing on data governance, AI governance, and security improvements is essential.

Regarding Control-M's AI capabilities, these are the critical issues that need to be addressed.

When discussing the accuracy and reliability of Control-M AI output, I can identify areas where further improvements can be made regarding errors.

Control-M is doing a great job, and we can still focus on improvements in security and data governance as these are critical issues, especially in production.

I have been using Control-M for two years in my own project.

We deploy Control-M in our organization through AWS, utilizing Amazon Bedrock for our deployment.

We have deployed Control-M primarily through the AWS platform, along with on-premises solutions and GCP, as most of our data sits on AWS.

I would rate Control-M 9.5 out of 10 or a perfect 10 out of 10, as I have never seen a tool for workflow automation that is better than Control-M and my organization has experienced improvement after using it.

I chose to rate Control-M 10 out of 10, or even 9.5 out of 10, due to the significant improvements my organization has experienced in workflow automation using Control-M.

My main use case for Control-M is workload automation. I use Control-M for scheduling jobs, automating workflows, automating business processes, and automating manual tasks.

I can provide a specific example: we automated large data factory pipelines and automated specific applications with B2B processes using Control-M.

The integration and sequencing of data processing across diverse data platforms and cloud environments depend on the business requirements for how we process the data.

My organization is currently working to improve our environment to integrate Control-M to support AI or ML workloads.

We have not used any Kubernetes functionalities of Control-M at the moment for facilitating the integration of Kubernetes or cloud-native workflows with traditional batch processing.

My organization uses Control-M reporting for audits, specifically for extracting reports to address compliance requirements such as SOCs and regulatory reporting.

The best features Control-M offers are that BMC is mainly focused on integration these days, and the automation capabilities are really increasing. BMC is focusing on AI at the moment, and I love the AI capabilities it has.

Regarding Control-M's AI capabilities, we are getting decent output that meets the required output for accuracy and reliability.

Automating processes with Control-M helped my team by saving a lot of man-hours. Post-automation, it has completely come down to zero man-hours, as it is fully automated. In case there is an issue with the workflows, we get notifications.

Regarding my main use case, it has saved us strong dollar benefits in terms of saving man-hours.

Control-M has positively impacted my organization by improving efficiency for people, and productivity has been increased. Manual tasks and doing things manually have come down, so productivity has been greatly increased.

We have been able to reduce man effort for errors by at least twenty to thirty percent.

Control-M can be improved by BMC focusing on new integrations, as there are many integrations that are still not available. I know that BMC is focusing on integrations very much, and the more integrations we get to solve everything within Control-M would really be beneficial.

In terms of needed improvements, I would like to see enhancements in applications, integrations, and capabilities of how they can do things.

I think BMC is improving its AI capabilities, but I believe they can still improve in terms of security aspects and governance.

I have been using Control-M for almost twelve years.

Control-M is very stable.

The customer support is really good, and the BMC team reaches out as soon as possible. I would rate the customer support at nine on a scale of one to ten.

We are currently using Control-M and have no plans to switch from it.

Currently, I would say there is not much return on investment. If the pricing can go down, that would be really helpful.

My experience with pricing, setup cost, and licensing for Control-M indicates that it is at a higher price at the moment in the market. If its pricing can go down, that would be helpful.

We have been using Control-M for the last fifteen years without evaluating other options before choosing it.

I would rate Control-M at ten on a scale of one to ten. I chose ten as my rating for Control-M because I have worked on different tools, and the way Control-M has emerged with its user interface and what it does has been phenomenal.

Control-M is deployed in my organization for development in a cloud environment, and production is on-premises. For cloud development, we use Azure Cloud.

My advice for others looking into using Control-M is to go ahead and start using it without looking for any other options outside.

My main use case for Control-M is staging letting. A specific example of how I use Control-M for staging letting is generating business solutions.

Control-M is very efficient for my needs; it is a very good product. I manage the integration and sequencing of data processing across diverse data platforms and cloud environments in-house only, with no public cloud involved.

My organization is currently using Control-M to support AI or ML workloads, and it performs very well. We address compliance requirements such as SOX, audit trails, and regulatory reporting, maintaining everything according to government standards.

Control-M offers excellent user-friendly features and an interactive dashboard.

Regarding Control-M's AI capabilities, the accuracy and reliability of output are good and reliable. Control-M has facilitated the integration of Kubernetes or cloud-native workflows with traditional batch processing within my organization, and the SAP module is particularly effective.

Control-M has positively impacted my organization by performing very well and by reducing considerable manual work. I estimate that almost 30% to 40% of work has been reduced.

Control-M can be improved with more AI agentic implementation and automation of certain work processes.

I gave it a nine because agentic improvement stands out as a notable area, and I feel there can still be more automation. Regarding Control-M's AI capabilities, governance and security are currently good, but as more agents are coming, governance needs to be a little more robust.

I believe everything else is perfect, and I don't think there are any other improvements needed that we haven't discussed.

I have been using Control-M for one year.

Control-M is stable.

Control-M's scalability is very good.

Customer support is very good. I would rate customer support on a scale of one to ten as a ten.

I previously used a different solution before choosing Control-M.

As of now, I haven't seen a return on investment, but I will update you by the next financial year.

My experience with pricing, setup cost, and licensing has been good.

We evaluated other options, including many solutions from SAP, before choosing Control-M.

On a scale of one to ten, I would rate Control-M overall as a nine. My advice to others looking into using Control-M is that it is very user-friendly and a very good, reliable product.

I primarily use Control-M for scheduling workload automation to ensure that jobs and schedules run according to the specified time and dependencies across different environments including Windows, UNIX, and SAP.

Multiple servers previously required jobs to run sequentially on a manual basis. Control-M provided a user interface where agents could be installed to run jobs sequentially rather than manually. Once the Windows job completed, the UNIX job ran, followed by the SAP job, and then the Windows job ran again.

Control-M's pipeline integrations are a valuable tool that is utilized on a daily basis.

Control-M's best features are the ease of scheduling, the user interface, and the ability to integrate with numerous tools.

The user interface is intuitive and the primary integration utilized is ServiceNow, which helps create incidents and establish a data pipeline between ServiceNow and Control-M.

Control-M has ensured that schedules and job batches run on time with no organizational impact or delays, including critical processes such as payroll.

Since implementing Control-M, a significant reduction has been noticed in billing process times. Billing processes that previously took approximately two hours are now completed within one hour, resulting in substantial savings of full-time equivalents.

Control-M pricing is on the higher end, and if the cost could be reduced, it would be beneficial.

I have been using Control-M for around two years.

Control-M is stable.

Control-M's scalability is strong, and the support for scaling is also strong. Scalability has not been an issue.

Support for Control-M is excellent.

IBM Tivoli was used previously before switching to Control-M, which provided a better solution and superior integration capabilities.

The deployment of Control-M took three months.

Two hundred fifty staff are required for deployment and maintenance, divided into teams at levels L1, L2, and L3. Some team members are responsible for monitoring, some for creation of new jobs, and others manage the administrative tasks of the controller.

A return on investment has been achieved. After deployment and product stabilization, staffing was reduced from thirty full-time equivalents to twenty full-time equivalents, resulting in a significant reduction. Additionally, because jobs have been streamlined, many manual processes have been automated, resulting in savings of approximately five hundred thousand pounds.

The pricing, setup cost, and licensing for Control-M are good.

Other options were evaluated before choosing Control-M, including Redwood RunMyJobs.

Control-M support is excellent and the user interface is outstanding. For those seeking a stable and dominant tool in the market for scheduling and workload automation, Control-M is the recommended choice. This review has been given a rating of nine out of ten.

Control-M serves as our main business use case for business application batch job scheduling. Control-M is not a user-interacted system; it is a batch scheduling system where our applications interact with Control-M rather than users. We do not use Control-M as a DevOps tool, but we utilize it for all our applications, which are batch-based applications. Control-M orchestrates workloads across multiple environments. Control-M is handling complex data pipelines and analytics processes effectively.

The features of Control-M that I prefer most are Control-M/EM, Control-M/Server, and Control-M/Agent, which make up the Control-M batch scheduling system.

Control-M is easy to use because our key application is a batch-based application, so Control-M performs the job for us by handling all the automation and related tasks.

The measurable benefits my company has achieved with Control-M include improved SLA and reduced errors, as manual batch job runs lead to numerous errors and failure to meet the SLA.

Since we have been using Control-M from day one for batch scheduling, we do not have a percentage showing improvement because we have not used manual scheduling at all.

Regarding AI or automation, we would appreciate the opportunity to explore the AI functionalities because the application we are currently using does not support AI. It would be beneficial in the future if Control-M were to have AI capabilities.

I have been using Control-M for around eighteen years.

Control-M is a stable product stability-wise, and we do not encounter many issues. The only problem occurred when we upgraded to the latest version, which resulted in CPU spikes in Java, and this was resolved with support and a patch.

The support for that issue was adequate. We called support and eventually received a solution after reaching out multiple times, and the issue is now fixed.

Control-M's scalability is adequate. It is a scalable product, and we have not over-engineered it, so it meets our business needs.

We provide direct feedback to our support partner for Control-M, so nothing comes to mind at the moment. I consider the current support to be adequate.

On a scale from one to ten, I would rate customer service and technical support as seven. A score of seven is decent enough. I am not saying Control-M support is a perfect ten, but I consider seven to be a good rating.

Positive

It has been a long time since we looked at other solutions, so I do not remember what we considered.

We do not handle Control-M deployment ourselves. We simply install it, and it is a stable environment, so we do not keep deploying it regularly.

BMC's service team supports our deployment and migration strategy well, with professional service and good support during our recent upgrade.

The biggest return on investment when using Control-M is ensuring that all batch jobs for our business applications meet the agreed SLA, which justifies our investment since we use this tool for a critical application.

Control-M is not inexpensive. Looking at other tools in the market, they are offering competitive prices, but Control-M, as a BMC product, is definitely not inexpensive, and BMC could improve their pricing strategy.

We have looked at other products when considering switching, but I cannot name them. I do not see a major difference between the products we looked at while considering Control-M. Pricing-wise, the other products were less expensive.

I would rate Control-M as a seven as a product. My advice to other companies considering Control-M is based on all our lessons learned, especially regarding issues we encountered during migration and implementation, which should be taken into account. I have assigned a review rating of seven to Control-M.

My main use case for Control-M is that we support a database and also SAP products. Generally, we use SAP for BW processes and the database for the online transactions.

We manage the integration and sequencing of data processing across diverse data platforms and cloud environments by using pipelines from Azure. The means of the source is where data is being driven from their databases, such as Oracle and SQL Server.

For compliance requirements such as SOX, audit trails, or regulatory reporting, we have already enabled audit features where the login, logout, and the job process running is automated, and we check in every quarter.

The best feature that Control-M offers is the dashboard. What I appreciate most about the dashboard is its ease of use.

Control-M has positively impacted my organization because we were using other tools such as UC4, and the license cost was very high. When we converted to Control-M, the license cost reduced significantly. Control-M has been saving approximately 50 lakhs per annum.

Control-M has already been improved, and I don't suggest anything else at this time.

I have been using Control-M for three years.

Control-M is stable.

We don't have much scalability concern after the implementation of Control-M. Whatever the execution count of 500 per day is stable from the past one year.

Customer support was great, and I would rate it around seven out of ten.

UC4 was the solution we were using earlier, and it was a legacy process that was implemented around 15 years back.

Control-M saves a lot of time, but relating to ROI, return on investment, I don't see any improvement on that.

The setup cost was for 500 executions, around $4,000 for the setup, and there is no increase in the cost for this year.

We didn't evaluate other options.

On a scale of 1 to 10, I would rate Control-M overall as 10. I gave it a 10 because we are not breaching any SLAs after the implementation of Control-M.

I have not gone through AI capabilities in detail, but according to the demo, it shows great capacity. The governance and the kill switch AI that Control-M provides is great.

In my organization, we maintain Control-M on-premises and also on the public cloud. It's a BMC-provided solution, and we are using the SaaS model.

My advice to others looking into using Control-M is that automation and the AI implementation of Jeters is very straightforward for creating a workflow.

Control-M provides automation workflows for the telecom environment. A specific example of how I use Control-M to automate workflows in my telecom environment includes application workflows such as billing, billing systems, infra setup, backup, storage, and requests, all of which are taken care of by Control-M.

With the 9.21 version of Control-M, I find quite good features with MFT and API integrations, as well as Azure and Kubernetes.

MFT has made the biggest difference for my team; it has been the main feature we are using as of now, with a lot of configurations with managed file transfer in place.

Having a secure file transfer is very crucial in today's world of cyber security threats; that is the additional part or the best functionality available with Control-M.

Control-M has positively impacted my organization by providing a platform to automate the workflows in complex environments while having data security in place, which has really helped the organization grow positively.

For Control-M to improve, the vendor support can be more improvised. If a solution is not existing, providing a patch for a vulnerability would be more helpful than always stating to move on to the higher version of the application.

I have been using Control-M for the past 13 years.

Control-M is stable.

Control-M's scalability is good.

Customer support is good.

We migrated from Autosys, CA Autosys to Control-M.

We switched to Control-M from Autosys because Control-M has better integration options and the GUI is far better.

My deployment took place around 14 years ago; it is a very old deployment that we are using, and we have been upgrading the system now and then.

The migration was smooth, so we were able to migrate on time and on budget without any disruptions.

We have around 1600 Control-M users in our organization for our particular license; the users vary from first level support to monitor jobs, some application users with browse access, and a few admin users.

A part of the admin team of Control-M, around 25 members, takes care of deployment and maintenance.

I do not have experience with the usage and investment calculations myself; however, discussing benefits, the employee count is reduced, and we can achieve quite a lot of FTE saving by having Control-M integrated.

My experience with pricing, setup cost, and licensing indicates that the pricing is on the higher side with respect to the license, but overall the tool is good.

We finalized Control-M without evaluating other options.

The biggest lesson I think I have learned from using Control-M is that the technology is vast, and we need to keep exploring, learning, and integrating more to ease out our life.

Control-M is used widely in our global environment; we have a licensing of around 75K, and currently, we do not plan to increase the usage.

I assess Control-M as a good tool for building, scheduling, managing, and monitoring production workflows; it is important for my DataOps and DevOps initiatives, but I have not explored DevOps deeply.

I assess Control-M as a good platform tool for modernizing and transforming our business; it removes human dependencies for mundane tasks and eases out the workload, which is easily possible with Control-M.

It is very crucial to free up IT personnel to focus on essential operations; this allows them to focus on the latest technologies and also implement POCs for the latest technology integrated with Control-M, which ultimately helps optimize the complete workflows.

I would advise others looking into using Control-M to explore Control-M. I rate this product an 8 out of 10.

My main use case for Control-M is that my team is in charge of all the alerting and monitoring, as well as the scheduling and creation of all schedules within Control-M.

The scheduling my team creates with Control-M serves all the IT audience within the company, so we have a mix of everything. Any need from developers, database administrators, or anyone from the infrastructure or development teams is handled, such as transferring files or updating databases. We deal with all requests within the company related to scheduling.

Within my team, we have around 10 people using Control-M who are focused on monitoring and reacting to alerts, as well as creating all schedules and doing all scheduling work. Beyond that, we have developers, DBAs, and others who check Control-M to review the performance of their jobs and logs. We have around 50 people total, though I don't know the exact number.

The best features Control-M offers are the stability and ease of use.

The interface of Control-M is easy to use and it is a very stable and reliable application. Control-M has a very high positive impact on my organization as it is a reliable tool that is very stable. We usually don't have issues related to the application itself, so there is a very high impact.

Control-M can be improved by including more options for automating things from an alerting handling perspective.

Reporting features are a field that we would like to have more statistics about, including jobs, usage, and errors. We definitely would also like to have more options to integrate Control-M with other applications such as JSM, ServiceNow, OmniCenter, or other monitoring tools that can provide information from Control-M. There is always room for improvement for any application.

It is easy in theory, but I find it challenging to integrate Control-M with technologies for my data ops and DevOps processes as changes occur. There have been a few efforts to integrate Control-M with other applications like Ansible, JSM, and OmniCenter, and it has been very challenging. From a DevOps perspective, I am not aware of any efforts, so I don't have information about that. However, related to the ones that I mentioned, it has been very challenging because there are not many options to integrate with Control-M. I'm not sure if this is due to a lack of training or application knowledge from our side or if it is something that the application itself is not providing.

I have been in my current field for 20 years.

Control-M is stable.

Its scalability is challenging.

Control-M has very good customer support.

We don't have a metric for return on investment from a Control-M perspective. We are expecting to see some of that if at some point Control-M starts integrating AI features and AI functions into the application.

The biggest lesson I have learned from using Control-M is the importance of having a reliable and stable scheduler.

My advice for others looking into using Control-M is that training is key to learning how Control-M works behind the scenes and in the scheduling part. I also advise looking for stability and implementing the HA environment.

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

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

Control-M handles enterprise-level data properly through a ground-up design. It features a distributed architecture with lightweight agents that decouple the load. The server handles overarching scheduling logic, policies, and dependencies, while Control-M agents execute and distribute workloads across local servers and cloud environments, enabling horizontal scaling.

When workload grows from thousands, capacity can be simply deployed on additional agents or containerized agents. This prevents the central server from becoming a performance bottleneck. Microservice modernization optimizes CPU and memory properly, so during peak times the financial team's month-end processing will not experience issues. Multi-tenant and cross-department isolation allow an admin to segment the environment logically, enabling teams to manage their own localized workload and permissions within a unified platform without degrading global performance.

Control-M's scalability varies in both horizontal and vertical directions effectively. It is engineered for large enterprises and can scale workload for millions in a day while ensuring new platforms are added seamlessly.

A classic scenario for Control-M scalability is during financial close of the month or quarter. In high-pressure scenarios, processes must scale from normal operations to running more than 50,000 or about a million jobs, with each process needing to be properly followed. Control-M agents deployed on clusters can be easily leveraged while flexing the environment, with Kubernetes pods working properly to absorb heavily computational load. Prioritization and throttling prevent resource crashes when resources are exhausted. The distributed architecture allows the operation team to dynamically adjust the resource pool, providing more data for the financial compliance team when they need more requirements with time-sensitive backgrounds.

The central servers coordinate while distributed agents handle heavy lifting in execution, preventing bottlenecks. During massive searches in real-time on a dashboard, depending on the task, the cache can be cleared at any time and run anonymously. Without this level of horizontal scaling, a search would typically cause a job queue, but Control-M enables the IT and ops team to operate effectively.

Control-M has a global support center that operates under the follow-the-sun rule with 24/7 coverage. They offer an escalation pathway for faster resolution. For premium support, 24/7 assistance is available, though standard support has more limited coverage.

Control-M maintains extensive technical resources with a proper document library and community forum. Control-M has matured into a long-standing enterprise platform with many repositories for troubleshooting and guides. Self-service support resolves issues with REST API and others effectively, suggesting appropriate outputs. Escalation support is available as we purchased Control-M directly from BMC, which provides additional leverage. When issues become bottlenecks to resolve, faster response times and more effective diagnosis of complex issues are possible.

Overall, the customer support is robust and excellent for a Tier 1 enterprise vendor. I would rate Control-M's customer support at eight out of ten. The reason for this rating is that they provide extensive documentation for everything, maintain proper rules to follow, and offer strong support during emergency situations.

For anyone considering Control-M, I would definitely recommend embracing Jobs-as-Code. For small enterprises, I would recommend starting with Control-M even though it may be costly initially, as it will help significantly in the long run. Control-M supports GitOps integration along with JSON and YAML, making it much better long-term. I would strictly recommend implementing it from day one to have all access available from the start and plan costs accordingly. Although it is costly initially, it pays off quite well in the long run by saving the association resources. I would also recommend going with hybrid boundaries to implement it properly.