Control-M Reviews

Control-M is similar to Stonebranch and Redwood. It is a workload automation system that automates steps typically defined by humans. Previously, if humans performed 100 steps to complete a task, they can now input these steps into Control-M and let the system run them automatically. 

The most common use case is in banking. In banking operations, there are daily transactions between customers that need to be processed, closed, summarized, compiled, and sent to the core banking system for execution. Manually, this process could take more than eight hours per day. With Control-M automation, this time can be reduced to one hour or even 30 minutes. Before the cutoff time at 12:00 a.m., Control-M performs the batch job or end-of-day process, executes it, passes it to the core system, and marks it as a finished job for the day.

Control-M makes it simple to create, integrate, and automate data pipelines. Essentially, you have a single dashboard where you can manage everything. You can create the job, perform quality checks before promoting it to development, and then execute it in production. You can also monitor the jobs to see if they fail or trigger any alerts that require attention. Overall, the process is very straightforward and simple.

It is pretty easy to integrate with technologies for data operations and DevOps processes as things change. Control-M is API ready, so as long as the other side also has an API, it’s a done deal.

Stability is crucial in the banking or financial sector, where operational downtime must be minimized. Control-M provides exceptional stability compared to competitors such as Redwood, Stonebranch, or Perpetuity. The second valuable feature is the user-friendliness of the tools, making it easy to learn and use.

Control-M can execute batch jobs and monitor the jobs it executes, though it does not monitor servers or other systems.

Since the system is stable, clients don't typically request rapid improvements. However, one area that could be improved is the AI capability and AI generative features, as these are becoming increasingly important in modern systems.

I have been working with it since late 2010, approximately 15 years.

After migration to Control-M, there is an initial stabilization period. Once properly implemented, the system becomes very stable, which is one of its strongest attributes.

It is a scalable solution. Our clients are enterprises. About 85% of banks in my country use Control-M.

I would rate their support an eight out of ten.

There was a previous solution from either Redwood or Stonebranch, and another tool called Perpetuity. Customers were successfully persuaded to migrate from these solutions to Control-M. The success rate of migrations is usually more than 97%, and it may even be almost 100%.

Implementing it is not straightforward. It requires careful installation, customization, and configuration. Unlike simply installing Microsoft Windows or Office, this solution demands significant effort and time. It is not as simple as it may seem.

Technical migration can be completed in a few months, but full implementation including user adoption and socialization typically takes about a year. This is because the tool has various users beyond IT, including business users, trade finance users, and branch users who need time to learn and become comfortable with the system.

We have previously attempted to work with the services team from BMC and found their design to be good. However, we prefer not to proceed with the actual on-site implementation. Their prices are quite high, and their approach is too rigid for our needs. Therefore, we believe it is better for us to handle the implementation ourselves.

Automation can benefit customers in many ways, particularly when it comes to saving money. For example, if we rely on human workers, we may face long Recovery Point Objective (RPO) times, which could extend up to 88 hours a day. Additionally, humans are prone to making mistakes. Let's consider a scenario where an operator is manually summarizing transactions from a single branch. If that branch has 10,000 transactions in one day, it can be quite challenging for the operator to keep track. This may lead to issues like double data entry, where the operator mistakenly inputs the same data twice. Such errors can be disastrous for a bank, potentially resulting in financial losses. By implementing automation tools, you can minimize human errors and improve efficiency.

The Total Cost of Ownership (TCO) for Control-M is more economical compared to other solutions. While competitors might offer lower initial prices, they often include hidden costs that emerge after the first year. Control-M maintains a straightforward pricing model based on license count, implementation, and training, without unexpected future costs.

Control-M uses a simple pricing model based on the number of jobs per license, where one job equals one license. After assessing customer needs, proposals typically include the required number of job licenses plus implementation fees. The implementation fee covers installation, customization, configuration, job building, testing, and execution until the solution is running perfectly.

When you purchase a license, it's typically through a subscription model. Some people refer to this as a subscription type or ops type. If a customer opts for a subscription, it's similar to renting a car; you must renew it each year. It's important to note that there may be an annual price increase determined by BMC, and the specifics will be decided by the principal.

BMC is an important strategic partner for our company. Around 70% to 80% of our business comes from working with BMC, or more specifically, from selling BMC products.

The biggest lesson learned is the importance of providing perspective to customers rather than simply following their requests. It's crucial to understand and discuss their requirements thoroughly, such as questioning why they need a specific number of jobs.

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

In my previous project, we were using Control-M, and we automated the data pipelines using SQL Server Agent jobs and created the Databricks workflow. We had some data available in SQL Server and some in Databricks, and because we had two systems, the orchestration process was completely different, and we were not able to manage or create a dependency because both tools were different. That is why we implemented Control-M in the past project and automated all the SQL Server jobs and the Databricks workflow using Control-M. By using a single platform, Control-M allowed us to create a dependency between the SQL Server and Databricks data. On the reporting side, we were using the Tableau dashboard as well, and for Tableau, we were using the extract to display the data. We were refreshing the Tableau extract using Control-M. In my last project, overall all the data pipelines including the Tableau extract refresh were done using Control-M.

We expanded a lot because previously we were using multiple tools for the same orchestration purpose, such as Databricks workflow and SQL Server Agent. Now, we are using the same product or a single tool for multiple tasks, which is very helpful for developers as well as business stakeholders.

I appreciate Control-M because of the dependency it offers. As I mentioned, we had some data available in SQL Server and some in Databricks, and it was hard to create a dependency when we were working on different tools. That is why we chose Control-M so that we could create a dependency, and we had some highly critical banking data in that project. The SLA was very minimum, and we had to get the dashboard refreshed every morning at 7:00 a.m. Due to the SLA features in Control-M, we chose it in the last project.

I find that Control-M provides a single UI platform where I can monitor all the jobs. Previously we had different jobs, so we had to monitor each job individually. With Control-M's single platform UI, we can monitor all jobs. The main benefit is that Control-M has a retry functionality, so if any job fails during execution or due to bad data quality, we can retry the job. Once we receive the data, the job can execute automatically. The alert mechanism also triggers emails to business stakeholders whenever any job fails. These are the main features I prefer about Control-M.

Previously, we set up alerts so that whenever there was a delay in the file, it automatically sent alerts to business stakeholders indicating the file's unavailability. Whenever there was a delay, it triggered an email to notify that we were expecting the file at a certain time. Additionally, we set up a file-based trigger. Since the time of file arrival is not consistent, we configured the job to execute automatically when the file arrives, ingesting the data into our final database. This file-based trigger was a key feature we explored.

I think the pricing is a factor, and it is high. I am currently working in a multinational company that has purchased the premium enterprise-level license for all developers, so it is not a big deal for our project. However, someone in a small company or startup might face pricing constraints while implementing Control-M, as the pricing seems a bit high compared to other tools such as Airflow.

One area for improvement in Control-M could be pricing, and another is the learning curve. I feel that when someone starts working with Control-M, they need at least one month to onboard and understand all the features. Although documentation is available, understanding all features takes time. Another recommendation would be for UI improvements, as I felt the UI seemed outdated.

I feel that it is a little bit difficult to integrate Control-M with technologies for DataOps and DevOps processes, especially initially, as I needed about one and a half months to understand the complete features and flexibility of this tool. From a developer standpoint, it is not very user-friendly. However, once I become skilled in this tool, it provides great flexibility.

I have been working with Control-M for six plus years.

I faced a performance issue once because we created a very large data pipeline with multiple dependencies in Control-M. So, we narrowed down one workflow into multiple sub-workflows, which improved performance. Processing a large amount of data can be complex and time-consuming.

I can raise a support ticket for BMC software whenever I have any technical issues, and they respond within a three-day SLA, providing full support.

I would rate the tech support of Control-M as 8.5.

I evaluated Airflow before choosing Control-M. In Airflow, we faced a similar situation because we had to create different cron jobs for each Python script. We had 100 plus Python scripts fetching data from multiple source systems, and in Airflow, creating dependency between each cron job was very hard. That is why we switched from Airflow to Control-M.

The initial setup process was done by our infrastructure team. I worked as a developer to create jobs, but the actual setup was quite good and well-supported by BMC software.

Our initial setup was completed with full support from the infrastructure team. After that, the workflow creation and job creation in Control-M were entirely managed by our developers.

The initial setup process was done by our infrastructure team. I worked as a developer to create jobs, but the actual setup was quite good and well-supported by BMC software.

Our initial setup was completed with full support from the infrastructure team. After that, the workflow creation and job creation in Control-M were entirely managed by our developers.

I think the benefit is very high. If a company does not have any budget constraints, they should definitely explore Control-M because it allows for end-to-end orchestration of the project without needing separate projects for the data pipeline and downstream applications such as reporting. All tasks can be accomplished using one product, providing significant value if budget constraints are not an issue.

I find it cost-effective, but I am not fully certain about the overall ROI.

The biggest lesson I learned from using Control-M is that it provides a single UI to monitor all jobs, making it much easier compared to my current project where I use Airflow, which involves managing multiple cron jobs across different tabs.

We do not have any direct contact with BMC software, so I would not describe the relationship as transformative.

I rate Control-M as nine because it simplifies complex data structures and pipelines.

I have used Control-M for database, SAP, web services, and file transfers. Additionally, I use it for normal scripts.

We had a customer who was using cron jobs to handle their workflows. With cron jobs, they faced problems related to SLA. When something failed, it took them time to identify issues, and sometimes they missed incidents which resulted in P1 situations in production environments. They transitioned to Control-M based on its features related to SLA and workflow visibility, which significantly helped them.

The GUI is the best feature, along with the file transfer capabilities. These are the two main components I use on a daily basis. Through GUI or CCM, we get control of all the components, which I really appreciate. 

While I cannot specify exact business impact numbers, frequent P1 incidents in the production environment typically indicate monetary losses.

While it can be used for DevOps purposes, we haven't used it for that purpose.

Support is one aspect that they really need to improve. Though we receive support for current versions, the challenge arises when working in large organizations with legacy workflows or applications, typically 10 to 20% of the total. 

When these legacy environments have outdated OS and face production issues from a Control-M perspective, BMC support states it's not supported anymore. Recently, we needed documentation for an old component during a production issue, and their response was that they couldn't help as it wasn't supported. Documentation should be maintained for all versions since they provided the application.

I have a total experience of around 19 years, with approximately 13 or 14 years specifically with Control-M. I started with 6.4.

Control-M is pretty stable. There are occasional issues, yet nothing major, and most issues are not caused by the software itself.

In on-premises environments, scalability features are limited. Planning and resource allocation must be done at the start. If workflows increase from 1,000 to 10,000, redeployment of the application becomes necessary. Database and application node planning must account for anticipated workflow volumes from the beginning.

We have approximately 1,000 users.

Support is an area that requires significant improvement.

Positive

I haven't migrated from other solutions.

I have limited experience with TWS. The TWS version we used was primarily command-line based, and its GUI capabilities were not comparable to Control-M.

The deployment process is straightforward. The environment's complexity affects deployment time rather than the software itself. Basic DB and Linux box installation takes approximately a week. The planning phase for system connectivity and task execution locations requires additional time.

The system requires maintenance with patches released once or twice yearly.

We are implementing this as a customer.

I can provide a general perspective on ROI. Manual tasks require human effort and are prone to errors, which Control-M helps eliminate. However, I cannot provide specific ROI figures.

Control-M is expensive and not cheap at all.

I have conducted technical assessments for several market solutions, though not in great depth. We explored alternative solutions due to Control-M's high cost rather than its technical limitations. My assumption is that all current enterprise-level scheduling or workload automation software provides similar technical functionalities and features.

We're a customer.

I would recommend Control-M for its performance capabilities. While cost-cutting is prevalent everywhere and Control-M's cost is on the higher side, from a technical perspective, it ranks among the top three solutions. 

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

I lead a team of Control-M schedulers and operators, and I also do some scheduling myself. A specific example of a task or workflow I manage with Control-M is that I have re-engineered a monolithic script. The process I re-engineered was designed for printing invoices, specifically the invoices of EDP clients, which amounts to about eight million invoices per month.

To handle that scale with Control-M, I made changes by decomposing the monolithic script, which was made in shell scripting, into Control-M jobs, getting the complete workflow, a PDF, and transforming it into a Control-M workload. I do a lot of transformation from monolithic scripts or jobs that can be transformed into workloads within Control-M.

The best features Control-M offers include cross-platform dependency management, which is interesting because a job on the mainframe depends on a file arriving from a Unix system that, in turn, depends on a Windows process completing, and Control-M handles that heterogeneous dependency chain natively.

A time when this feature really made a difference for my team was when we had several workloads that are dependent on each other, using different platforms, and that interconnection between those platforms is really relevant to the whole process. There are more features that add value to Control-M, such as the calendar and condition system, which is really powerful to schedule almost to perfection many workloads that are critical for the business, whether in energy, insurance, banking, etc., because it maintains the logic.

Using the conditions allows me to create the re-engineering process that I have mentioned, which depends not only on the conditions but allows everything to run smoothly and on time. Tasks that in the original monolithic script would take about two hours now take at least fifty percent less time because it is more efficiently designed. The time savings were enabled mostly by parallelization, but not only that; I can adjust several aspects.

Control-M has positively impacted my organization because if some condition fails or if a calendar is incorrectly defined, a simple error in a condition can stop a critical workload, stop invoicing, and stop files that should go to the banking system.

Control-M can be improved with better integration with modern DevOps toolchains, as while it has made strides with APIs and the automation API, integration with tools such as JIRA and ServiceNow could be more seamless out of the box.

There is also a knowledge barrier that BMC should be aware of; Control-M has a steep learning curve for deep operational mastery, where basic administration is fairly accessible, but truly understanding the platform takes months to years for a new person, and BMC could invest more in advanced training and certification paths beyond the basics.

I have been using Control-M for more than twenty years, since around 1996.

Control-M is stable in my experience. I have worked with Control-M environments processing tens of thousands of jobs, and currently, we have around six thousand jobs in the energy company.

Control-M is used quite extensively; we execute around six thousand jobs a day, serving around seventy to eighty applications, and it is always growing, also serving many DevOps teams.

BMC support is generally competent for standard issues.

Positive

Before choosing Control-M, I always worked with it and know alternatives such as TWS, Autosys, and other platforms similar to Control-M, but I have never worked with them.

The ROI of Control-M in critical infrastructure is less about percentage savings and more about what does not fail, such as when a national payment system opens every morning on time, or when millions of transactions are processed without a missed dependency.

Control-M has premium pricing, which is justified for enterprise-scale operations, as we are paying for a platform with decades of maturity, proven reliability, and the capacity to handle complex orchestration scenarios that simpler tools cannot manage.

I have always worked with Control-M, first on banking systems and then on energy systems, and though I worked with other systems, Control-M was always present. We have many users in many different roles; there are maybe four or five administration roles along with operation roles.

The biggest lesson I have learned from using Control-M is that it makes your life easier in dealing with batch processing, whether on mainframe or distributed servers, allowing you to define everything the way you want. I advise others looking into using Control-M to invest in people, not just the tool, emphasizing that a well-configured Control-M environment with experienced operators is essential for reliability.

Integrating Control-M with technologies for our data ops and DevOps processes can be difficult as technologies change. I would rate this review nine out of ten overall.

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.

Positive

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.

Control-M is our primary workload scheduling software, and we aim to utilize it for linking applications, hardware, and data transfers. Ideally, it should be the core component of our architecture. While we have started to expand its use over the past couple of years, we are not fully there yet.

A significant portion of our incoming files is handled through Managed File Transfer (MFT) Enterprise, which is an extension of Control-M. We have been utilizing this solution increasingly for both external and internal file transfers. Additionally, we rely on Control-M to schedule SAP jobs, which is one of its key functionalities. We also schedule a substantial portion of our data warehouse production using Control-M. 

As a health insurance company, we have a main internal application that heavily depends on Control-M. For instance, many incoming files need to be decoded and processed for our internal application, followed by a job that transfers the data into our databases. We have recently begun to use Control-M for the maintenance of various databases, such as SAP HANA, Oracle, and Postgres. This aspect of our usage is constantly growing.

Another significant aspect of our workflow involves creating customized job types for our clients. For example, some files we receive are encoded and zipped, for which there is no default Control-M job. To address this, we frequently use the Application Integrator to provide additional functionalities not currently available in Control-M. This allows us to automate tasks that would otherwise require manual intervention, such as extracting contents from ZIP files.

We are also standardizing processes with Control-M, providing standard job types for all our customers. This includes file renaming, combining files, or separating them based on specific application types. For instance, we receive files that contain multiple text files, which we may need to split or combine into a certain format when sending them out.

In summary, we are dedicated to making Control-M our primary workload automation and orchestration software. Recently, we've begun integrating Control-M with Ansible to manage patch routines for our Linux and Windows servers. The challenge has been linking these patch routines with our application jobs. We've started this integration so that whenever there is a patch, our applications automatically halt until we receive confirmation from Ansible. We frequently use the Control-M API for this purpose, enabling seamless coordination between Ansible and Control-M. Overall, these are the main use cases we are currently implementing with Control-M, and we continually seek to expand its applications across our operations.

The application integrator provides a toolbox that makes integration easy. We use it to mask Python scripts that handle various routines, such as ZIP solutions, while the application integrator manages drop-down menus. Sometimes the integrations that Control-M provides are not suitable for our specific use cases. For instance, with S3 storage from Amazon, Control-M's integration only uses a small percentage of available S3 functionalities, so we had to create our own solution. When using BMC tools such as the application integrator, Control-M provides an easy path to integrate many features.

One thing we have criticized is the MFTE capabilities, particularly regarding high availability. BMC hasn't provided a setup with multiple fallbacks for error situations. We've experienced main problems with MFTE where having one setup means when an error occurs, the entire service goes down. We have requested BMC to provide a high availability solution for MFTE. While there are other minor issues, this remains our main concern.

I started using the z/OS parts in 2007-2008 for one to two years. After switching companies, I have been using it in its current form since 2013, totaling twelve years of experience.

It is usually very stable, except for the MFT solution where an error leads to an outage. This has occurred several times in the last two to three years. We are in direct contact with their lab development regarding these issues. While the system is stable 99% of the time, when issues occur, they are significant.

The scalability is very good with numerous configuration options available. Though we sometimes use load balancers in front of Control-M, the available functions offer good options for configuration. Our license doesn't limit our ability to configure Control-M as needed, allowing us to easily create new agents or environments.

I don’t contact the BMC support every day, but we are in constant communication with them. They are currently migrating many features to their web interface, which means some functionalities that were available on their desktop solution are now missing. As a result, we are creating a lot of tickets regarding this issue. At least once a week, one of my colleagues reaches out to BMC support.

Regarding the quality and speed of their responses, it really depends on the representative and the topic at hand. There are certain areas where they have more experienced experts, while in other cases, the support staff tends to rely on standard procedures. Generally, their answers are acceptable; I would rate them around a seven out of ten. Many times, their assistance is more like a nine or ten, but there are occasions when a representative provides standard responses without understanding the specific issue. In these situations, I often have to clarify the problem multiple times because they start with standard solutions that don’t apply to my case. Overall, I would rate their support around a solid seven out of ten.

Neutral

I previously used OPC (now TWS) from IBM for z/OS software. We regularly evaluate the market, comparing different vendors with BMC, including Redwood, Stone Branch, and HLC. While we conduct proof of concepts and demonstrations from various vendors, we maintain only one product installation.

Control-M was previously used for both z/OS (mainframe) and distributed environments. However, we have since migrated from the mainframe to a distributed system two years ago, and now Control-M is only implemented on the distributed side. I was responsible for this migration due to my knowledge of mainframe systems. While Control-M was already in place, certain functionalities, like data transfer, were not integrated into Control-M. This integration has been accomplished in the last five years.

The learning curve for me was easy due to my background. It took about a year maximum to transition into an administration role. My experience with both mainframe and distributed systems was beneficial. For new colleagues without z/OS background, the learning curve was steeper. While becoming a scheduler is relatively easy in Control-M, mastering specific features requires more time and learning.

In terms of maintenance, we usually have one or two major releases each year, which is quite a significant process. If there’s one area where BMC could improve, it would be optimizing the maintenance process. The type of maintenance required depends on the range of components included. If we talk specifically about the core Control-M product or its basic components, then currently, there isn’t much maintenance involved. However, when we include the agents, the maintenance requirements increase. Overall, I would classify the maintenance needs as moderate. It could be less demanding, particularly during situations like a major version change, where we would prefer to minimize outages. We are in discussions with BMC about how to enhance this process. To summarize, I would say that the maintenance requirements are not low, but they don’t necessitate weekly attention either. So, I would characterize it as being in the middle range.

Control-M is among the highest-priced solutions in the market. When comparing with other vendors, BMC consistently maintains premium pricing. We hope for more creative pricing solutions from BMC in the future, as currently, the price often remains constant regardless of package customization or feature selection. We would appreciate more pricing flexibility from BMC.

Our relationship with BMC is more in the direction of transformative. We’ve built a solid relationship with BMC over the years. It was a process, but I would classify it as transformative. They support us well. While there are certain functions we wish were available, overall, I think our relationship is transformative.

We have a good relationship with BMC, and that required effort on both sides. Sometimes, there’s a gap between what we need as customers and the direction BMC is heading. However, overall, we’re satisfied with how BMC provides us with solutions. Of course, there are things we feel are missing at times, but I also must say that the experience can vary depending on who you’re speaking with at BMC. The experience with sales representatives can differ from discussions with technical staff. In general, though, I would say the relationship is positive.

 I would overall rate Control-M an eight out of ten.

My main use case for Control-M is scheduling jobs and maintaining the EM server and the Control-M server, along with giving support to the asset team on troubleshooting of job failures.

We typically schedule OS jobs and AFT jobs in Control-M, and we also have SAP jobs and Informatica jobs running on Control-M.

Regarding my main use cases with Control-M, we are scheduling jobs for the asset team and maintaining the architecture of Control-M.

Control-M offers several great features, with scheduling jobs being a very good feature, while the GUI feature is user-friendly and makes scheduling jobs very easy, saving a lot of time compared to other scheduling tools.

The GUI helps my team day-to-day by making job scheduling very easy, as we can use planning tabs or the back-end of the job through drag and drop, and after adding a few job details, we are ready to proceed. The monitoring tab is also very useful for monitoring daily or scheduled jobs, and the forecast feature is excellent for predicting how jobs will execute in the future.

The reporting feature serves us well for extracting reports on job executions and past executions.

Control-M has positively impacted our organization as we have saved a lot of time and money by utilizing its features, which we found to be very convenient compared to other workload automation tools.

We are saving a lot of time as earlier we had numerous manual activities that usually took four to five hours to perform, and since automating those tasks in Control-M, we now execute them within two hours, effectively saving two hours per batch execution.

The reporting feature has limitations with job execution, and I believe there should be integration with Power BI or any visualization tool to provide a detailed summary of each job instance on a single dashboard.

Control-M could have more types of jobs that could be integrated with it, but for now, the features are adequate.

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

Control-M is stable in both production and non-production environments.

Control-M's scalability is convenient, easy to use, and flexible with various integrations.

The customer support for Control-M is convenient, providing us with 24/7 assistance for architecture and job execution issues.

Previously, we were using AutoSys, but we found AutoSys not user-friendly based on feedback from the asset team, prompting us to switch to Control-M, which is better suited for our organization.

Control-M is deployed in my organization on a private cloud.

We use AWS as our cloud provider.

We require around five to six staff for the deployment and maintenance of Control-M, all of whom are Control-M admins assisting in deploying Control-M for various asset teams and maintaining their services.

We have seen a return on investment due to money and time saved as we automate tasks in Control-M, allowing us to reduce staff numbers as well.

The pricing for Control-M is genuinely fair compared to other workload automation tools in the market, and its features add value, making us satisfied with its pricing structure.

We evaluated AutoSys before choosing Control-M as our solution.

The biggest lesson I have learned from using Control-M is that automation is very convenient, with workload automation and job scheduling being easy and maintaining jobs in Control-M being very manageable.

My advice for others considering Control-M is that it is definitely a reliable option since it is convenient, flexible, and stable.

Control-M is extensively used as we have deployed it for many asset teams, and we plan to increase its usage as we are in discussions with different teams to migrate their manual activities into Control-M.

I would rate this review as a nine out of ten.

My use case with Control-M is for job automation and job scheduling. Instead of making 10 different technologies where we need to run jobs, automation allows us to reduce the number of people needed. Cost-cutting is significant; instead of 10 people, we can handle the work with only one or two people.

The best features in Control-M that I like the most are job scheduling and monitoring.

Earlier, I worked for many clients, and currently I am working for Zurich, Japan. There, we used different vendors such as Infosys, Cognizant, DXC Technologies, and two others. The project operates 24/7 as an insurance project where transactions happen during daytime, so we need to run jobs during nighttime as well to upload data, take backups, and complete other necessary tasks. Instead of managing this manually, I have automated everything related to job scheduling and job configuration.

The areas that have room for improvement are the GUI to make it more user-friendly. The interface is very easy, very good, and secure. Currently, I have not found any significant improvements needed. Every year the versions improve, and everything is progressing well.

I have been working with Control-M for almost 16 years.

Control-M is a stable product, and I would rate it 10 as a stable product.

The scalability is an eight out of 10. It is easy to upscale or downscale.

I can give the technical support a nine out of 10.

Positive

With Control-M, I compare the solution with other solutions I have worked on such as TWS (Tivoli Workload Scheduler), CA7, AutoSys, Tivoli DC (Tivoli Workload Dynamic Schedule), and Job Scheduling Console. I find that Control-M is more secure compared with the firewall system.

Deployment is very easy with no issues.

For the clients, they have to buy licenses, which are reasonable.

With Control-M, I would recommend implementing this product. It is a more secure solution.

The solution requires easy maintenance because most of the time we take care of it on weekends like Saturday and Sunday, or during public holidays.

There is nothing difficult about integration. It is very easy to integrate technologies for data ops and DevOps processes.

Currently, I am taking care of almost 10,000 jobs in an insurance company.

I would assess the BMC service team for helping map out migration as effective. For migrations, we perform them in development first. We configure the jobs in development, then move to SAT testing, UAT testing, and ST testing, and then to pre-production and production. If there are more jobs, we do migrations on weekends, on Saturday and Sunday, or at midnight one day before.

Deployment takes approximately one or two days and depends on the job types. Installing Control-M can take up to one or two days maximum. For scheduling, we need to configure different agents in different vendor systems such as UNIX systems, Informatica systems, or Tandem systems. For these configurations, we need to install the agents and define them in Control-M.

To make the solution a 10, there could be more automation. I would rate this review overall as a 9.