Control-M Reviews

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.

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.

My main use case for Control-M is automating the deployment of ETL jobs which run periodically as batch processes, and also for deploying REST endpoint-based applications while ensuring that all required checks are performed and preventing unauthorized deployment by unauthorized personnel.

We have ETL jobs which run periodically and are fully configurable in our pipelines. These jobs pick up telemetry data available at a specific storage location, which is the telemetry data of Dell servers coming over the network. Since there are many such jobs, each targeting specific Dell offerings and corresponding telemetry data, we no longer need to manually monitor or trigger these jobs.

Control-M has automated the workflow, and we have specified all checks required for successful batch job triggering and for reporting any issues that arise. We find Control-M invaluable for relying on automated processes rather than manual intervention for triggering jobs and ensuring they run successfully with all checks passed according to our authentication requirements.

REST endpoints follow a slightly different flow since they are not deployed regularly. During release, when a feature is completed, REST endpoints are triggered, and this triggering of Control-M jobs is somewhat manual since release intervals are not fixed.

Before using Control-M, we had different environments including development, staging, non-production, and production. All deployments went through these environments with various integration tests, unit tests, and QA testing occurring whenever we moved from one environment to another. Previously, all of this was manual, and although we introduced some automation, it did not help as people still found ways to bypass the automation workflow.

Control-M has provided us with very strict controls that help us avoid failures caused by someone triggering jobs arbitrarily. We now have control, predictable execution and workflow, and we can rely on it to always work according to the checks we specified in the pipeline.

We have our own S3 storage and on-premises databases like PostgreSQL with applications also located on-premises in our Dell cloud or on-premises infrastructure. Since these are all on the same network, this integration does not pose any issues, and Control-M is able to trigger file transfers if required between all these components.

Our AI and ML workloads are in a nascent stage as we are still working on that. We will definitely explore the possibilities of introducing Control-M for our agentic workflow triggers.

Control-M has provided us with all improvements. First, a significant amount of work has been automated, allowing us to use our workforce for more useful purposes and saving on employee costs to some extent. Efficiency has improved since automation ensures that workflows run reliably. We have reduced time by eliminating the need to wait for someone to be notified to trigger workflows, as they are now automatically triggered. Availability is 24/7 due to Control-M automation, and error reduction has also been achieved.

Previously, we had a team of at least two or three people dedicated to executing workflows and notifying the team about failures. Now, the bandwidth from those three people working eight hours per day has been utilized for business-relevant work.

Beyond basic automation, we are implementing a next level of automation using Control-M agents. When we provide proper RBAC to a particular Control-M agent, it takes care of jobs, and they are now fully automated and monitored without any human touch. We have triggered alerts with Teams and Slack for any monitoring messages that may arise, indicating which team needs to know for debugging and fixing issues. Control-M automation combined with the latest Control-M agents feature has enabled us to deploy to our VMs and our Dell private cloud, which we use for deploying jobs and REST endpoints. The new Control-M agents feature is helping us eliminate the manual intervention that existed in earlier Control-M automation.

Every software now provides integration with notification mechanisms, and it is good that Control-M provides those as they are essential. Control-M has done a thorough job with governance and security, as we constantly see that agents could potentially access components they are not supposed to. Control-M agents have provided a mechanism to enforce that only authorized credentials provided for the agent can execute actions, and this is fully configurable and within user control. This is the best part.

Control-M has met our expectations. Our use cases were to trigger workflows without manual juggling, which was possible with manual triggering of Control-M jobs, but now with the AI agent, those are automated. We have not experienced any issues.

Audit trail is something we require for all workflows, and Control-M provides this very well.

Control-M is evolving day by day and is currently fulfilling all our needs. In the future, we may have more complicated requirements that I cannot anticipate now. However, Control-M is keeping pace with technology and customer demands. I am satisfied with what Control-M is offering.

Documentation is an area where some of my team members have struggled with following the documentation, and they frequently turn to experienced leads to understand issues that arise when configuring Control-M. While I have found the documentation very clear, I have received feedback from my junior team members suggesting that documentation could be improved.

I am involved with Control-M teams as the tech lead for the application development team, the batch processing team, and a few other areas. We work with Control-M all the time, and I am always involved in our workflows.

Control-M has been very stable for us.

We do not have many workloads that require us to scale Control-M itself. Whatever workloads we have, a single instance serves us sufficiently.

I have not encountered any issues that would require customer support.

Before Control-M, we used to deploy our applications, batch processing, or endpoints manually by triggering CI/CD pipelines. This type of automation was not available, which Control-M has now provided us.

We definitely achieve ROI. We need fewer employees, and we are saving both time and money.

We did not consider alternate solutions.

I would give Control-M a rating of nine out of ten. I am not giving ten because there is always room for improvement. Nine is perfect from my perspective.

Control-M stands out because of the numerous benefits we are receiving. Earlier, we struggled significantly with executing workflows in a standardized way with all security controls and ensuring all checks were done so that random people could not trigger workflows, which resulted in wasted time resolving issues later. Now, with Control-M, we are confident when it comes to executing workflows, allowing us to focus more on business requirements and development rather than worrying about who manages timely execution and monitoring. I would have liked to rate it ten, but I believe there is always room for improvement with any technology as new business requirements arise and the world evolves.

If you still do not have any sort of automation in your workflows, especially with agentic automation, Control-M is the solution. If your infrastructure or project management team is struggling with this, you definitely need to use Control-M.

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 job scheduling. As a specific example of how I use Control-M for job scheduling, we schedule daily jobs of the banking sectors for their transaction processing.

Managing the integration and sequencing of data processing across diverse platforms is somewhat challenging, but we maintain integrations from various data platforms to ensure a controlled process. We have our own AI ops strategy to help with this.

We are planning to use Control-M to support AI or ML workloads because AI will eliminate the manual effort currently involved in batch operations, thereby providing efficiencies.

Control-M has facilitated the integration of Kubernetes or cloud-native workflows with traditional batch processing. We faced difficulties with multiple applications in containerized platforms, but we overcame them with the support teams in our organization who had good knowledge.

For compliance requirements like SOX and audit trails, we have a different tool called Apexa to help with vulnerabilities, but we currently use Control-M solely for batch processing.

Control-M has positively impacted my organization by helping us manage jobs in a timely manner and contributing to customer success.

In terms of specific outcomes or metrics from using Control-M, it was basically about the time saved. If we had to normally run the jobs with manual effort, it used to take time, but scheduling has helped us save a lot. The output accuracy has also improved, helping our teams deliver jobs on time, which has increased customer satisfaction.

The best features Control-M offers are the scheduling features, and if there are any failures, it helps in troubleshooting and fixing it as well.

Control-M helps with troubleshooting and fixing failures by allowing us to check the results and track the logs whenever there are failures, which helps us to give the exact failure information so that we can proceed to get them fixed.

Regarding Control-M's AI capabilities, governance is always there. On the governance front, it is helping us provide a human-in-loop for validations and approvals on the process of actions, which helps us manage in a coordinated way.

The accuracy and reliability of Control-M's output is nearly 99%, which is excellent for the jobs we perform, providing us with the required output.

Control-M can be improved in the area of auto-remediation, where we are looking for improvements that can help eliminate the need for operations teams.

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

Control-M is stable.

Control-M's scalability is beneficial since it is available for cloud service providers, allowing us to apply across various service providers with whom customers are onboarded.

Customer support for Control-M is very good. Users are satisfied because the tool delivers the required output, with jobs running and scheduled on time.

Previously, we used a script-based method for normal batch processing, and we switched to Control-M because it proved to be more efficient and provided the required outputs.

We have experienced a return on investment with Control-M, reducing from almost 10 FTEs managing job processing and failures down to four FTEs after its introduction, yielding significant efficiencies.

My experience with the pricing, setup cost, and licensing of Control-M aligns with market standards, and I find the product to be reliable for our needs in getting the required jobs done.

Before choosing Control-M, we evaluated other options available in the market which we found to be not useful.

I would rate Control-M a nine on a scale of one to ten. I gave it a nine because the tool has become so sophisticated and improved a lot since we started using it, and now it meets our requirements, which has helped improve our customer scores. I suggest others consider trying Control-M over other tools like Autosys since it provides a strong return on value.

Like any other batch scheduler, Control-M is what we're really using for the various workflows that we have to either do on a daily or hourly or whatever basis. We run them all through there.

I've worked with other ones, and I think the certain simplicity to how Control-M lets you set up a schedule or workflow is excellent. It's very easy to build everything together.

Most of my complaints have ever been with support for Control-M, not with the product itself. I can't really think of anything that I strongly dislike about the product.

Sometimes my gripes with the support relate to them being a little slow to get back on either a query or a problem issue. That's my biggest gripe on the support side. There are some people in the support area that are fantastic, and then there are others that feel like I'm being pushed off to the side. I don't know what's going on in the back shop, so I can't say for certain.

I'm currently fighting with support on one issue right now with Control-M, but it's not the overall product, it's just one sub-piece that's being problematic. It's the SAP interface with Control-M.

My usage has definitely been more than ten years. I go back to release three or something.

I've never really seen much of a problem with scalability for Control-M. I'm sure there is an upper limit to how many agents and how many jobs you could run, but I haven't hit that yet. Where I am right now, we load probably about three thousand jobs a day, but we run a lot more than that because you can load a job and run it hundreds of times.

I'm going to give Control-M's support an eight on the scale from one to ten, with ten being the highest. That rating is mostly because of the reasons I've already mentioned.

I've used plenty of alternatives for Control-M in the past. Though some of them don't exist anymore or they probably still do. One of my former employers was a big CA-7 shop on the mainframe side, and on the distributed side, I used the IBM tool Workload Scheduler.

The setup for Control-M is not horrible. Once you get the server built out correctly initially, it installs relatively easily. There are some things in the update format that I don't favor. They used to have an update and migrate model, which would allow you to move from one system to a new system if you needed to upgrade your operating system or switch to a different platform. Going from Windows to Linux, or from SUSE Linux to RHEL Linux was easy to do. That migrate model was very good, but they went to an upgrade in place model. You can't do it that easily anymore because what you have to do is upgrade in place where you are and then build a new box and then move the data over, which is a bit of a pain. It was one-stop shopping previously. They stopped that at version 9.18.

The implementation is handled by me and maybe one other person who are specifically doing the deployment and maintenance of Control-M.

I don't really have any thoughts about the pricing for Control-M. I don't deal with that, or I haven't in a very long time. I know one of the pricing models is based on workload, specifically how many tasks you load in a day. I don't know if there are any other pricing models other than that. That's the only one I'm familiar with.

Control-M does require some maintenance on your end, as with any software. There are fix packs released or patches, and you need to be aware of that. BMC is very good about notifying you when they post out new patches or fix packs. It usually requires a downtime, but it's a very short downtime. It takes longer to take the product down than to apply the patch for Control-M. You have all the processes to shut down, apply the patch, and bring them all back up, and the up and down takes longer than the actual patch application sometimes. I would rate this review a nine out of ten.

I have been working with Control-M for about six months as part of my role. During this time, I have mainly used it for monitoring and managing batch jobs and automated workflows.

Our main use case for Control-M is managing and monitoring batch workflows across different systems. We use it to schedule jobs that run scripts, database processes, and ETL-related tasks. We make sure they execute in the correct order based on dependencies. On a daily basis, I mostly work with monitoring job runs, checking job statuses, and troubleshooting failures when a job does not complete successfully. We also review logs, rerun jobs when needed, and make sure the workflows complete within the expected time windows. Control-M helps centralize all this so we can track and manage automation more efficiently instead of handling tasks manually.

One of the examples for centralized monitoring in Control-M is the ability to view the status of all the scheduled jobs from a single dashboard. Instead of checking multiple systems individually, we can see whether jobs are running, completed successfully, or failed in one place. For example, if a job that runs a database script fails during the night schedule, we can quickly identify the failure from the monitoring interface, review the logs, and rerun the job if needed. This helps the team respond faster and keep the workflow running smoothly.

One of the best features of Control-M is its ability to manage complex job scheduling and dependencies across different systems from a single platform. It makes it much easier to automate workflows and monitor job execution in real-time. The centralized monitoring and alerting help us quickly identify failures and take action, which improves reliability and reduces manual effort.

Control-M has had a positive impact by improving the automation and reliability in our batch processing workflows. It helps ensure that jobs run in the correct sequence and reduces the need for manual intervention. The monitoring and alerting features have also made it easier to detect failures early and resolve issues quickly, so it helps keep our scheduled processes running smoothly.

One area that could be improved is the user interface. While the platform is very powerful, the UI can sometimes feel complex for new users, and it may take time to become familiar with all the features. Improving it and making the navigation more intuitive would help teams adopt it more quickly.

Another improvement could be simplifying the initial setup configuration process for organizations that are implementing Control-M for the first time.

I have been employed for almost four years, approximately three years and ten months.

Control-M is definitely stable. In my experience, once workflows and jobs are properly configured, it runs reliably and handles scheduled processes consistently. Most issues we encountered are usually related to the jobs themselves rather than the platform, and the monitoring tool helps identify and resolve them quickly.

Control-M is quite scalable in my experience. It can handle a large number of jobs and workflows across different systems without major performance issues. As the workload grows, it is possible to expand the environment and manage additional processes while still maintaining centralized monitoring and control.

Customer support has generally been good. The support team is responsive and provides helpful guidance when issues arise. The documentation and knowledge base resources are also useful for troubleshooting common problems.

Before using Control-M, some workflows were handled through basic scheduling tools and manual scripts. Moving to Control-M helped centralize job scheduling and monitoring, making it easier to manage dependencies and automate processes more reliably.

The biggest lesson I learned while working with Control-M is the importance of properly defining job dependencies and workflows during the initial setup. When dependencies are clearly configured, the automation runs smoothly and requires less manual intervention. It has also highlighted how valuable centralized monitoring is because it allows teams to quickly identify and resolve issues before they impact downstream processes.

We are just a user.

For return on investment, we have experienced improved automation and reduced manual effort. In terms of operational efficiency, automation through Control-M has reduced manual overhead by around twenty to thirty percent, especially for routine batch job monitoring and scheduled tasks.

I have no idea how the pricing, setup, and cost licensing is done. It is done by the finance department.

We saw the working methodology of Control-M, how batch jobs are handled, and how the automation works, so we just went for Control-M.

With job scheduling and workflow automation, this automation has increased the scheduling time by fifty percent. The monitoring task has been reduced by twenty to thirty percent. Instead of going on multiple tabs, we can view it at once. Workflow management through the technologies is a bit of a complex task. As we have used this, we can implement it. For new users, it might be a bit complex.

Currently, we have been using this for the past six months. We are seeing good, positive results. The automation workflow is also good, and the batch scheduling jobs are definitely good. We will still want to try it on different platforms and then decide on any further usage or increase in usage of Control-M.

In production, this workflow is mainly through the monitoring and reporting features in Control-M. We check the job status to make sure the scheduled process completes successfully within the expected time window. If the job fails or is delayed, we review the logs again, analyze the dependency chain, and rerun or troubleshoot the job if needed. This helps ensure that the overall production workflow continues without impacting downstream processes.

One piece of advice I would give is to spend time planning the job dependencies and workflows carefully during the initial stages. If the workflow is well-structured, Control-M can automate processes very efficiently and reduce manual intervention repeatedly.

Overall, Control-M has been a reliable solution for managing automated workflows and scheduled jobs. It provides good visibility into job execution and helps teams maintain operational stability. I gave Control-M a rating of eight because it is a very reliable solution for scheduling jobs and automating workflows, and it helps me manage complex job dependencies and provides good monitoring capabilities, which makes it easier to track and troubleshoot batch processing. The reason I did not rate it higher is that the interface can feel complex for new users, and the initial setup and learning curve could be improved. With some improvements to the user interface and onboarding experience for new users, it could become even more effective.