Control-M Reviews

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Control-M serves as my primary solution for enterprise workload automation and job scheduling. I use Control-M for running batch jobs at specified times and frequencies, ensuring that jobs execute in the correct sequence while coordinating jobs across applications, databases, APIs, cloud, and platforms, including the movement of files between systems. Control-M provides monitoring capabilities for detecting failed, delayed, or stopped jobs and for alerting the operations team when workflows breach conditions. Furthermore, it helps restart failed jobs based on predefined rules, allowing me to track whether business workflows will complete within the required time timeline, which supports SLA management. On the cross-platform automation side, Control-M coordinates between Windows, Linux systems, mainframe, databases, cloud, and SaaS workloads.

Control-M offers exceptional features including centralized monitoring, workflow orchestration, cross-platform compatibility, advanced alerting, and automated recovery. I particularly appreciate the end-to-end workflow orchestration, which connects jobs across applications, databases, cloud, data platforms, and infrastructure, and it is also relevant for AI-first IT operations, giving AI agents control execution.

My primary feature is end-to-end workflow orchestration, but I also find the secondary feature of event-driven automation valuable, where jobs can be triggered by events, files, conditions, or external signals, not just schedules. This functionality is helpful for sequencing jobs and triggering them at the right point when the business is ready for the process to follow, allowing me observability in terms of events to initiate operational workflows. Other notable features include automated recovery remediation, real-time monitoring, and integration with ecosystems like SAP, databases, AWS, Azure, Snowflake, Databricks, and Informatica.

The AI-assisted workflow creation is fantastic, as Control-M capabilities include AI-assisted creation of workflows from natural language intent, which is useful for moving towards AI-first operations. Control-M has taken the right step in bridging the traditional world with the new AI-first approach. Additionally, the orchestration of complex business workflows is significant for my operations as it connects what is otherwise a collection of independent jobs. The dependency and impact intelligence feature knows what depends on what, which is extremely valuable when an upstream job fails or is delayed. This impact intelligence becomes handy for complex integrations or workflow processes needing connection.

Finally, the predictive SLA management feature can identify when a workflow is at risk of missing its business SLA, making my management predictive and not just preventive, which helps in rectifying issues proactively. Furthermore, the event-driven automation in the closed-loop automation helps me act as soon as I detect an anomaly in the system. Monitoring systems detect the issues, Control-M orchestrates it while I use my ITSM or any service management tools to govern all these steps.

Throughout my organization, Control-M has positively helped establish certain capabilities by providing centralized workflow orchestration that replaced the fragmented scheduling and manual coordination that was previously required. This shift has eliminated repetitive operations by implementing automation, significantly reducing manual intervention and operator dependency for routine batch activities. As a result, I manage dependencies much better, ensuring complex upstream and downstream processes execute in the correct sequence. This enhanced dependency management has led to improved reliability, with reduced missed schedules, reduced incomplete workflows, and fewer failures needing correction through human involvement.

Control-M has also contributed to faster recovery procedures by creating standardized recovery processes to eliminate knowledge dependency on individual operators. Beyond this, I have transitioned from merely monitoring jobs to managing business processes, ensuring operational personnel have a comprehensive view of the business processes' impacts, bolstering operational visibility. Cross-platform integration has connected legacy distributed databases, file transfers, and workloads through a common orchestration mechanism, minimizing the tool sprawl that previously required excessive investment. Operational standardization from Control-M has created repeatable ways of scheduling, monitoring, escalating, and recovering workloads, which has significantly enhanced the outlook on processes. Finally, operational visibility has provided a consolidated view of workflow execution and dependencies, expanding the understanding of processes without requiring extensive discussions with business teams, instilling confidence in IT operations.

The areas for improvement in Control-M involve four key dimensions: observability, intelligence, integration, and automation. I strive to shift from job monitoring to business service monitoring and integrate with enterprise observability tools like Dynatrace. I aim to incorporate AI-driven root cause analysis to avoid manual examinations of multiple jobs by allowing an AI agent to analyze job histories and dependencies. I envision improving recovery processes by making them more autonomous, where AI diagnoses failures and Control-M executes necessary actions with subsequent verification. Enhancing SLA management with predicted outcomes is essential to help me intervene proactively. I want to reduce operational noise by collecting intelligence around job failures and achieving a self-healing candidate factory.

I have not used Control-M's AI capabilities to the extent I would desire, as the accuracy was not very impressive. Insights for failure and performance analysis are not reliable. The AI workflow creator serves as a productivity accelerator, but generated workflows need thorough review and testing. AI monitoring is moderate in usefulness for summarizing logs, while root cause analysis should be treated as a hypothesis rather than a certainty. The AI pilot for planning is similarly moderate in that it assists in generating jobs but requires human validation for production changes. As for autonomous remediation, trust remains a concern as it necessitates deterministic policies and verification. While data-grounded AI capable of querying operational data is somewhat reliable, the interpretive nature of natural language queries leads to susceptibility to incomplete inferences, resulting in hallucinations. Therefore, I cannot consider Control-M AI a reliable root cause analysis engine at this stage.

I have been using Control-M on and off for about ten years.

Control-M is stable.

Control-M's scalability has met my business demands, supporting organic growth efficiently. I have not pinpointed any significant issues as my preparatory measures have allowed for both horizontal and vertical scaling.

I feel customer support could use improvements, not as a complaint but as an observation. Enterprise clients typically require more attention to hasten new feature implementations without acquisition barriers.

I have utilized Control-M for almost a decade now, and while alternative, non-enterprise solutions existed, their footprint has considerably diminished, with Control-M remaining my primary orchestration solution. When searching for a solution, I evaluated various competitors and believe I made a commendable choice selecting Control-M, which continues to expand in usage since.

My deployment of Control-M took about six to nine months, significantly influenced by my focus on standardization and numerous discussions regarding necessary amendments for partner integrations, which impacted SLA management and governance features requiring their own cycles of standardization and acclimatization.

I maintain a 360-degree relationship with the vendor, contributing certain features not necessarily related to the core product but within the ecosystems.

Regarding return on investment, I am witnessing a favorable trend toward realizing significant ROI through standardization where numerous inefficiencies have been addressed. My aim is to bring standardization across automation, which has curtailed tool sprawl considerably. Control-M's automation features are now treated as essential enterprise-grade solutions, driving alignment and significant cost reductions across various departments. In addition, centralized AI usage aids in managing token costs, which I find beneficial.

Pricing, setup costs, and licensing can be complex. The licensing has generally been acceptable in value, but it requires careful planning since costs can greatly vary based on deployment models and environmental scales, as well as the number and type of workload integrations being consumed.

When searching for a solution, I evaluated various competitors and believe I made a commendable choice selecting Control-M, which continues to expand in usage since.

Control-M is currently used significantly within my organization, largely due to my early adoption as legacy systems are centered on it. I have plans to increase its usage further as I experience more mergers and acquisitions, particularly in integrating smaller-scale entities into my main workflows. Thus, as I navigate diverse environments, enhancing integration remains a priority while minimizing the impact of security challenges and optimizing operational tasks. Control-M is highly effective when processes are somewhat homogeneous. Organizations should leverage its features to ensure full advantage of what Control-M offers, as my learning experiences have shown that a solid understanding of the solution supports effective business service management. I would rate Control-M as an eight out of ten. I choose an eight out of ten because I still have steps to cover in implementing broader intelligence from large language models into Control-M's features. Control-M is evolving toward an AI-native approach to IT operations, and I would like to see it embody that more fully. From a governance standpoint, I rate it as an eight, as there are areas needing evolution to become a very enterprise-grade application. Security-wise, I want to see a stronger AI-first methodology for operations, indicating there is ample opportunity for enhanced security features within Control-M.

Control-M is used for centralized monitoring and management of job scheduling across multiple platforms, and it serves day-to-day automation use cases, including file transfer and FTP and ERP jobs to be scheduled.

Multiple applications are supported, and with regard to file transfer, multiple files are received from the upstream and processed. When the file watcher successfully finds the files in the upstream, it transfers them to the downstream application, where multiple applications consume that file for their activities, including business warehouse management and day-to-day invoice processing, as well as file drive utilization.

Control-M is used for payroll, workflow management, ERP, supply chain, and file transfer, as well as HR portal management.

Control-M performs very well in building, scheduling, managing, and monitoring production workflows, and this workflow orchestration is important for DataOps and DevOps teams because it enables centralized scheduling activity and automation of complex workflows, thus improving operational efficiency and ensuring better governance and compliance.

Control-M has multiple benefits; it has improved ROI, and all KPIs have been met by implementing Control-M, resulting in a large reduction in the number of incidents. Before using Control-M, approximately 100 to 150 incidents occurred daily; now it has reduced to 10, and ROI and KPI targets are now met, indicating performance is in the green, whereas before it used to be in amber or red.

Control-M offers best features such as reducing manual effort for SLA compliance through its visual monitoring tool, minimizing operational error, and providing end-to-end workflow visibility; incident resolution can also be faster thanks to its GUI.

Control-M licensing is somewhat expensive for smaller organizations, and companies are hesitant to adopt BMC Control-M; the initial setup and implementation require a lot of admin work, so reducing that requirement would be greatly helpful.

The accuracy and reliability of Control-M's AI capabilities need improvement; AI in Control-M is not used much, so detailed commentary on this aspect is limited.

I have more than 10 years of experience in this field.

Control-M is very stable.

Control-M can be rated nine out of ten when it comes to scalability; it is very scalable and allows adding jobs and processes easily.

Control-M pricing is on the higher side; the cost should be reduced to onboard multiple customers, especially since open-source options are emerging. However, BMC customer support is very helpful and assists with licensing and everything.

Autosys was previously used before switching to Control-M because it offers a better visual experience, customer support, and more features.

Control-M takes one week to deploy, including setting up the environment, the agent, and the EM server.

A return on investment has been observed.

Before choosing Control-M, options like Apache Airflow and some of the processes in BizTalk were evaluated, but Control-M was found to be superior.

Control-M's governance and security are being worked on, and governance and audit capabilities exist, with all EM servers and Control-M servers being able to be hosted locally, so there are not many issues on the governance part.

Integrating Control-M with technologies for DataOps and DevOps processes has been a moderate experience; while a few CI/CD pipelines have been included in Control-M, deploying DevOps has not been easy, but a few features have been added, including using Control-M stats.

Control-M should be considered by those looking to use it because it offers enterprise-grade reliability, strong module integration with tools like Informatica and AWS, better support, and scalability compared to other schedulers. I would give this review an overall rating of 9.

Private Cloud

Microsoft Azure

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

On-premises

Other

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

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

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

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

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

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

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

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

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

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

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

Positive

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

The client is a big enterprise client.

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

Around 15 members are using Control-M.

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

On-premises

Control-M manages pretty much everything in our hemisphere, helping us meet our financial regulatory obligations, file transfers, running scripts, PowerShell, and SQL, making it critical to our day-to-day operations.

Control-M supports our DataOps and DevOps initiatives by providing an avenue for our DevOps teams to problem-solve in an easy way, giving them a platform to build on rather than having to start from scratch.

The measurable benefits or improvements we've achieved with Control-M are critical in the finance industry, as it keeps us on target with all regulatory requirements. Without Control-M, I don't know where we'd be, and if we shut it off, the business would probably run for about six hours before we faced serious issues, highlighting its role as a key component to our success.

Control-M has definitely enabled new capabilities and business processes that weren't possible before, allowing us to go to other departments and problem-solve for them, eliminating manual tasks that have been done for years. Departments now benefit from not even needing to look back at whether a task is being done since the information is readily available, providing them more time in their day for productivity and enhancing life for our customers.

Control-M is a great product already, but everything can do with a bit of improvement. Personally, I'd like to see a little bit more color in the web interface, and in terms of its technical ability, the one thing I would be critical about is a bit more user-friendliness with the reports and the way we input information into it.

I've been working with Control-M for three years.

Once we have tested things and gotten them into play, during the three years that I've been working with Control-M, I've encountered only one problem, and BMC's support has been quite good, allowing us to solve that issue quickly and easily.

Once we have tested things and gotten them into play, during the three years that I've been working with Control-M, I've encountered only one problem, and BMC's support has been quite good, allowing us to solve that issue quickly and easily.

Neutral

The biggest return on investment from using Control-M, from my point of view, is the ease of use and the time it gives our employees back in their day to be more productive.

I would give Control-M a very good rating in building, scheduling, managing, and monitoring workflows. It is pretty easy to use, and we have taken people without any type of formal training and been able to get them into using Control-M fully as a scheduler within weeks, proving its ease of use. In terms of its use for scheduling and building, it provides options, and it comes back to having flexibility, which is appreciated by anyone who has worked in the build area. With all the plug-in options and various job types that you can create, it increases the flexibility and the avenues available for using Control-M as a solution.

I've not had much interaction with licensing. In terms of costs, I think in life you have to pay for what you want, and generally, if you want quality, you've got to pay for it, but in my limited knowledge of pricing outside of Control-M and BMC, I think it is competitive, recognizing there's not a lot out there like Control-M, making it difficult to determine what the price should be as it is a critical piece of work worth its value. I would rate this product an 8.5 out of 10.

On-premises

Other

My main use case for Control-M involves managing the banking financial data that we receive from different sources and types of files, which we integrate into our data warehouse. Then we extract this data through various use cases and store it in global GCS buckets. From there, we integrate it in Apache Airflow DAGs, run data, and create multiple pipelines based on the use case, ultimately producing the financial engines that generate AI outputs for our Looker dashboards, which serve predictive analytical purposes, including aggregations and drill-down reports.

A specific example of a workflow where Control-M is critical involves managing the banking processes such as account openings, updates, and credit card applications, where the orchestration of different financial services, credit cards, and insurance products are integrated into predictive analytical frameworks using Control-M for those workflows. For instance, when someone applies for a loan, our engine checks the credit score to assess eligibility, fraud risk, and delivery capabilities for various loan types. Control-M orchestrates these daily activities effectively.

Control-M nowadays has capabilities to integrate AI agents for enhanced orchestration, allowing us to embed workflows within Apache Airflow, which has over 70,000 customers. This seamless capture of data into buckets supports our analytical perspectives, providing valuable insights such as fail statuses and troubleshooting needs with an intuitive drag-and-drop dashboard. The insights are vital for understanding failure points and success statuses, which improves our operations. Control-M continuously offers many features and enhancements that are user-friendly and beneficial to companies like ours.

We manage integration and sequencing across diverse data platforms and cloud environments through Control-M, incorporating it with Juniper networks and using unique transaction IDs for seamless data handling. The data stored in GCS buckets is then processed through our platforms and utilized in Looker dashboards for predictive analytics.

Currently, we have not implemented Control-M for AI or ML workloads; however, with future updates, I foresee the potential for integrating these capabilities as part of managing larger data volumes effectively.

Control-M integrates with our Google Kubernetes Engine (GKE), facilitating the orchestration of both batch and online processes in our financial services. This integration ensures efficient data handling and processing within the Google Cloud environment, meeting our daily operational needs.

Control-M aids our organization in compliance with requirements such as SOX and audit trails by overseeing batch processing data sourced from Cloud SQL, where transactions are validated and processed efficiently, reflecting correctly in our dashboards.

Control-M positively impacts our organization by saving time and costs, securing and optimizing our data processes, particularly with large volumes of varied file types crucial to our banking strategies. When we implement Control-M, we see significant time and cost savings, which are essential for our product and operations.

The best features Control-M offers include the ability to predict failures and easily identify issues through its AI agent, which provides inbuilt solutions, significantly reducing troubleshooting time. The root cause analysis that previously took long now finds failures quickly, which I find essential in today's IT environment where time is money. This capability eliminates much wasted time spent fixing issues, making Control-M one of the best tools for such needs.

In the context of our daily activities with Control-M, using Airflow DAGs is quite extensive as we manage hundreds of them with various tasks. When a specific task fails, Control-M's AI agent notifies us about the error through a red alert, allowing us to quickly identify the failed task and resolve it without wasting time. This efficiency helps our organization deliver features faster to the market, which is crucial for business success.

The current AI trend is about automation in day-to-day activities, and Control-M stands out as a strong player among tools that provide these solutions. Previously, we relied on cron jobs for scheduling and managing workflows, but now Control-M's AI agent automates 70% to 80% of our tasks, allowing more resources for developing new enhancements and features swiftly to market.

Regarding governance and security, data governance is crucial as it ensures data lineage and secure handling of sensitive financial and healthcare information, with features that allow for data masking to protect critical data points.

I find the accuracy of Control-M's AI capabilities to be around 85%, with its reliability output also at 85%, based on our product's performance.

Improvement for Control-M is a continuous process since challenges arise regularly; we strive to fix problems and enhance the system consistently. Control-M offers extensive connectivity to resources, facilitating integrations with platforms such as Apache Airflow, which is beneficial. Everything seems fine based on my use case.

I have been using Control-M for the last two years, as it was integrated into our product.

Control-M demonstrates good scalability, offering a supportive community that provides effective solutions.

On a scale of one to ten, I rate customer support as nine.

Before Control-M, we used workflow automation solutions that were less robust. We switched to Control-M to replace fragile scripts and manual scheduling with a centralized orchestration that optimizes management costs and SLA tracking for preventing costly job failures.

Since implementing Control-M, I estimate we save about 50% to 60% of our troubleshooting time and around 30% of costs, which we've measured quarter to quarter based on our product performance.

In terms of pricing and setup costs, the experience has been manageable, though specifics were not detailed.

I rate Control-M an eight overall. I rate Control-M an eight because most of the sources are integrated, the system works seamlessly with orchestration and scheduling, and it provides a user-friendly experience that yields time, cost savings, reliability, and security. I advise those considering Control-M to view it as user-friendly, open-source, and backed by excellent customer support, making integration and dashboard creation easy while benefiting from continuous feature improvements.

Private Cloud

Google

I primarily use Control-M for scheduling jobs for scripts, batch scripts, and Linux scripts. Most of the writing involves service restarts on servers.

For data ops and DevOps processes, the requirement involves integration processes that need to be scheduled in Control-M, allowing management of cyclic processes for integration and continuous execution.

For building, scheduling, and managing production workflows, access is available through the URL or from the client software, Control-M Configuration Manager.

Control-M has made it easier to create workflows for both cloud and on-premises environments with features such as drag and drop functionality. This makes it simpler for users to create jobs and integrate them with dependent jobs.

Control-M has helped consolidate job scheduler tools with features such as SMS and mail capabilities, which other scheduler tools do not provide.

The best features of Control-M are particularly effective for Windows scripts and Windows servers, mainly for service restarts.

What is most appreciated about Control-M is that it is easy and reliable. Jobs that have been created can be accessed through the front end URL, where operations such as hold, release, and execution can be managed entirely from the user GUI front end.

Workflow orchestration is important for data ops and DevOps tasks as it makes scheduling scripts and managing various aspects of operations much easier through a single screen.

There are areas for improvement in Control-M as it carries some vulnerability points that could be fixed in any version, or it could be made easier for organizations to repeatedly install or update new patches with more stable versions.

I have been using Control-M for four years.

On a scale from one to ten, with ten being the best, Control-M's stability is assessed as a solid product at approximately eight or nine. BMC support provides robust backing, with new patches arriving daily and being integrated with previous versions to replace outdated updates and fix bugs while unlocking more features. No stability issues have been noticed during the four years of use.

Regarding scalability, based on the features and how they help with day-to-day tasks, Control-M can be considered scalable.

In terms of technical support, the focus involves creating scripts for service restarts on particular servers with the main target of providing support for automation services, automation management, job failure management, and managing the agent package and Control-M package.

The deployment of Control-M is easier than other tools. There are no critical tasks or activities required to deploy on the server; it simply involves setup and installation on the server with the tool ready to use immediately.

Regarding pricing, Control-M is not the cheaper option. License renewal is based on active jobs in a year, but it is cost effective. More features are provided compared to other tools at the same price.

When comparing Control-M with other solutions such as ActiveBatch, JAMS, and IBM, Control-M offers easier manageable operations for hold, release, and execution, which can be managed directly from its front-end URL. In its configuration tools where jobs are created, there are no difficulties encountered. Unlike other tools where dependency tools and jobs must be mentioned separately, Control-M provides direct drag and drop functionality with arrows. This is much easier than other tools such as IBM Task Scheduler or Jenkins.

Approximately 2,000 to 3,000 people use Control-M, including users from Axis Bank where all employees are using Control-M.

Control-M is recommended to other users by providing them a demo and showing them the uses, which helps them understand the benefits and features that Control-M provides that cannot be obtained from other tools. This allows them to rely on Control-M for their day-to-day tasks.

One point is deducted from the overall rating because Control-M carries some vulnerability points. The overall rating for Control-M is nine out of ten.

I predominantly use Control-M for file transfers through the SaaS version. BMC has recently added an enterprise feature for the SaaS version, and we are now using it mostly for the file transfer part and also the APIs, which has been our latest addition.

With my current project, the File Transfer Enterprise is the best use case for us in terms of secured transfers and how we can track the transfers and manage significantly more with the transfers we are doing. This is the best feature, considering the ROI as to what my current scenario was and what we have achieved with the enterprise feature.

File Transfer Enterprise is the most valuable feature for our current project in terms of secured transfers and how we can track the transfers and manage significantly more with the transfers we are doing. This feature provides the best value, considering the ROI that we have achieved with the enterprise feature.

The integrator feature is not being supported by the BMC support team, which leaves it to us to customize and integrate it. Of course, the use cases differ and that is when they have decided not to have it under the support cluster. However, having basic support on the integration integrator would help us considerably. We do a lot of research and development to achieve what we need to accomplish, but BMC has the experts and eventually they have the answers. If they include the integrator feature under the support structure, it would be greatly beneficial.

The integrator feature is handy, but it can be tricky when we are trying to integrate in terms of achieving the connection profile. Setting up the connection profile initially to get any integrator working for us is somewhat tricky with different use cases we want to achieve. It is not straightforward.

I have been using Control-M since 2008 when I got into IT and started my career.

The SaaS version is excellent in terms of stability. For the price, it is very stable. We have not had any downtime. It has been more than two and a half years, approaching three years now since we got SaaS onto our system with no downtime at all. It is quite stable.

The scalability aspect is simply a matter of getting more agents in place and since it is a SaaS version, it gets scaled up on their end. We do not have to worry much about it. Of course, the licensing comes into play if the number of jobs are increasing, but it is dynamic.

I have recently contacted the BMC Control-M technical support team.

They are top-notch in terms of speed and quality. Most of the time, any question starts with extracting the logs and providing them to the support team, and they go through that. If they are not able to resolve the issue, they take time and put it to the research and development team. Of course, it takes a while if it goes to research and development, but they make sure that the issue is resolved. That is something great about them.

I would give the support a score of nine. I would still like to rate them ten, but some cases do take a while to get the resolution.

Autosys has been used and is the closest alternative to BMC Control-M. There are other features and other products, but Autosys is the most used alternative. However, it is nowhere near what BMC Control-M has to offer.

The initial deployment of Control-M was straightforward. With the current SaaS version, there is a support window of 14 days or specific hours. It is straightforward and depends on who is going to drive the deployment. For my case, I was experienced with the on-premise version as well, so that seemed straightforward for me. However, for those coming in with lesser experience, it may take some time. The documentation is excellent, so it is straightforward.

The deployment of Control-M requires two administrators. Basically, one administrator is the minimum need, but one can do the deployment. Since we have two admins, we share the workload. One is sufficient for the task.

Pricing for Control-M is on the costlier side when it comes to SaaS pricing. However, it does take off all the hassles of maintaining the Control-M server itself. This leaves us with only managing the agent part of it. It has pros and cons to that pricing feature, but it is on a higher side. Mostly in terms of ROI, the companies and stakeholders have that complaint.

Control-M does require maintenance on our end. There are two different windows of maintenance. One is when the core technology, in our case SAP, is getting under maintenance window, so we have to pause our jobs and resume it later on. This is a critical window that prevents our jobs from being pushed into SAP. We have to pause it and resume it depending on the schedules and make sure that we resume it and do not miss any jobs. The other window is when our agent maintenance or agent infrastructure maintenance occurs, when switching from a primary to a secondary agent, routing it, and making sure nothing is lost in the transit. Those are the two maintenance activities we perform.

We have a team of seven today, with two of us as admins. We have three schedulers and two monitoring agents.

Our engagement is with BMC. I have been involved with getting the contract rolled in for my current client and getting into the core of the technicalities in achieving the job requirements. It has been both.

We achieved the project in a month's time with Control-M. We had a project of converting and migrating our jobs from SAP workload onto the Control-M scheduler. End to end, we took less than a month to get the agents installed on the SAP infrastructure and get these jobs migrated from the SAP workload. Overall, I give this product a review rating of ten.

I work with Control-M from a commercial aspect and engage with IT and operation teams across different industries, which gives me direct exposure to how Control-M is used in real production environments. My role is to deliver tangible value to these teams.

The valuable features of Control-M depend on the specific customer needs. Some customers have business-critical processes, strict SLAs, and hybrid or multi-cloud environments where Control-M provides end-to-end visibility of all these processes. Control-M also offers different modules, such as MFT, which allows users to transfer files with the tool. As a commercial professional, I cannot personally attest to specific features since I do not typically use the tool directly, but I can share what customers have told me they value about the product.

As a commercial professional, I think one of the downsides of Control-M is that not all people know they can use a tool such as Control-M, and they think that Control-M is going to be very expensive, which is the reason why they don't want to use it or seek more information about it. However, when they are accustomed to using this type of tool or Control-M as a scheduler, they feel better with it and with their role inside their enterprise. For example, if they don't have any scheduler, they don't know that they can use a scheduler to automate different business processes. When they recognize that they can use this type of tool, one of the objectives is to reduce costs. They may spend money in the short term, but in the medium or long term, they will probably have more benefits than risk.

Control-M has everything that a person needs because the problem is not high cost. Control-M is available on-premises and in the cloud, and they are having more apps every week with the app integrator. I don't have anything that I dislike about Control-M. Possible areas for improvement could include documentation, configuration, and pricing. Being more flexible and having out-of-the-box reporting for business stakeholders would be beneficial. Continuing to simplify licensing and packaging for smaller customers would also help improve customer conversations. Reporting is often mentioned as an area where Control-M could continue to evolve. Many customers would appreciate more out-of-the-box business-friendly reports. Control-M has operability with SLA-focused reports, but developing something with less customization would be better.

I have been using Control-M for more or less two years.

I think that some instability is normal because everything is in the cloud, and I can remember a few months when the AWS cloud crashed. If you see the SLA reports or responses from different customers, they are very happy with the tool. Control-M achieves more or less 98% or 99% uptime in the cloud, which is a fantastic rate. I think 100% is impossible to achieve, and 99.8% is a good number.

Control-M, developed by BMC, which was previously part of BMC Helix and is now BMC Software, is focusing on Digital Business Automation processes. They are developing many different modules in Control-M, and the scalability is fantastic. Probably in a couple of years, Control-M is going to be the best scheduler. Currently, they are competing with other schedulers such as Redwood, Broadcom, and Stonebranch, but in a couple of years, maybe one or two years, Control-M is not going to have any competitors.

I have used technical support from BMC when we need to do demos for instances in the BMC tool. The technical support team are very good professionals and they do their jobs excellently. Since I don't use Control-M directly, if I have a problem with Control-M, the technical team from my enterprise would need to talk with the technical team from BMC. I usually talk with the commercial team from BMC rather than the technical team. I talk with the technical team when I need to make a demo, proof of concept, or proof of value, and we need to customize the future instance for the client. If I need to rate the technical support from BMC, I would give them a 10 because whenever I want to do something with them, they answer me, and I am very happy with them.

Positive

I don't use any alternative schedulers. I know that you can talk about Redwood, Broadcom, or Stonebranch, but I don't use any one of these schedulers.

I don't have a lot of contact with deployment. Probably if I think about some customers, they tell me that there is also interest in simplifying upgrades and environment standardization, particularly for organizations with multiple Control-M instances. If you talk with a small customer, they are going to be happy with deployment, upgrades, or the environment.

Control-M has an upgrade more or less every year or every two years. If you want to use the latest upgrade, you need to upgrade your tool.

The implementation team depends on the person doing the deployment.

The current pricing is good. Other vendors such as Broadcom are increasing their prices, so right now, Control-M is not one of the highest-cost schedulers. My customers have never told me anything negative about the pricing or licensing. BMC can be very amenable with the pricing of the tool. I have small customers, and I think that is a good point of view because they think they can't have the budget for a tool such as Control-M, but they do have the budget. Control-M is a tool for every kind of customer. You can sell Control-M for 15K on-premises and you can sell it for 7 million or 11 million. I think that people need to change their thinking because Control-M is not just an expensive tool. It is a tool for everyone, for every enterprise.

I would rate Control-M at nine.

Amazon Web Services (AWS)