Control-M Managed File Transfer

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.

My main use case for Control-M  is to control the batch for the day by scheduling the jobs, ensuring that all jobs run on time, and verifying that all conditions are met. Sometimes I force complete the jobs or rerun failed jobs by fixing the JCLs, and I ensure all batches are completed on time and all SLAs are met.

A specific example of a batch process I manage with Control-M  is a weekly job which runs from Monday to Friday on all working days, and I ensure the job is completed on time. I also verify that if any files are pending to process which that job needs, the file is available so that the job can run once the file is available. Such scenarios are common in my work.

Regarding my main use case, I work on automation and ensure that there are no human errors. Everything we use is up to date, and we make sure to follow the SOPs perfectly.

Control-M offers several best features, including its user-friendliness. Compared to TWS and CA 7, Control-M is a tool wherein if you get training for 10 to 12 days, you can learn almost everything, and it is very good and simple to use.

What makes Control-M user-friendly for me is that we connect through the client interface, which is easy to log in to, and there is no downtime for it. Control-M is only recycled weekly. It is straightforward to define and monitor the jobs and to get insights from the zoom panel. The coloring shows us in yellow if a job is executing, red if it has failed, and other colors for different conditions, making it simple.

Control-M has positively impacted my organization, especially when new team members join as their first assignment. It is a tool we can explain quickly, giving them a few sessions to work in production or development environments faster compared to other tools like CA 7 or TWS.

In our organization, we work for a banking client where we handle 10,000 jobs running on Control-M daily. Managing those jobs would be difficult with other tools due to visibility issues. With Control-M, it is easier to manage workloads and handle abends, and the chances of missing things are significantly less compared to command-based tools like CA 7.

Control-M can be improved in several areas. Last week when creating a job, I found that the option for global conditions could be more streamlined, as well as the in and out conditions, which are a bit complicated. Integrating more AI options, such as automatically marking jobs that are known to fail as complete, would be beneficial.

I have been using Control-M for the last 16 years.

Control-M is 100% stable.

Regarding scalability, I would say it is good and there are always possibilities for scalability.

Customer support from BMC, who owns Control-M, is excellent. They provide good support for critical issues, and I would rate it 99% out of 100.

I have experience working on CA 7 and TWS. While CA 7 is a good tool, Control-M is better due to its simplicity and less complicated nature.

To deploy Control-M, I would say two resources would be sufficient for proper installation and defining architecture, security levels, and access control.

In our team, approximately 24 users utilize Control-M, with 15 members working 24/7 for batch operations and nine members focusing on scheduling tasks during business hours.

Regarding return on investment, training a resource on Control-M allows them to handle two or three clients at the same time, thus saving costs for the company and making it easier to train.

Those things are managed by the sales team. I do not have much visibility regarding pricing, setup cost, or licensing.

We evaluated Jobtrac, CA 7, and TWS before making our decision.

The biggest lesson I have learned from using Control-M is time management, reliability, and the tool's availability, which makes our work easier.

I advise that if you have banking or insurance requirements or operate in a small industry, you can definitely consider Control-M as your first option.

I provided this review with an overall rating of 10 out of 10.

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.