We use Control-M for ACS and Azure services as it has inbuilt cloud integration. We have a product that works on government databases where we use data scraping and then integrate it with Azure and OpenAI. This integration allows us to process data and get insights. We also use AWS services to save the processed data in the AS.

Control-M is a bit faster compared to other solutions. The job and coding are easier. Also, my DevOps and Ops teams work collaboratively with it, enhancing its efficiency. The workflow is much easier compared to the ACS services we were using. Automation is more advanced, deployment is fast, and version control has been simplified.

They should have a proper integration method that clearly defines the workflow. Additionally, there should be an automation system for developers to set it up more easily and quickly. My Ops team faces certain problems that need addressing.

I have been using Control-M for four to five months.

The downtime is higher compared to AWS. Indexing and databasing are more challenging, and the endpoint sometimes gets reset automatically. The accuracy rate is about 80% to 85%.

As we hire new interns and DevOps partners to scale our business, Control-M scales well with the enterprise's growth. As the workload on Control-M increases, its scalability is much higher. Its cost is very low.

I never had direct communication with technical support because solutions are available on the web. We didn't have a one-on-one conversation, but the support is adequate through online resources.

Neutral

We migrated from AWS to Control-M. It was more cost-effective and capable compared to AWS services. We were a startup with limited resources.

The setup was manageable with certain experienced DevOps staff, making it easy to deploy on the local server.

There was an built-in DevOps team that found Control-M more cost-effective and capable than AWS services.

New users should have a comprehensive understanding of how BMC and Control-M operate. Good coding skills are essential, as well as utilizing open-source codes. Monitoring should be done by someone knowledgeable about the system. I would rate Control-M a seven out of ten.

I am using Control-M for cloud infrastructure and automation-related tasks. As a cloud engineer, my work involves scheduling, deploying, managing, and monitoring processes for infrastructure and workflows. It is integrated with a CI/CD toolchain as part of our DevOps culture.

I am using the cloud version. I am using Helix Control-M.

Control-M has good integration capability. It integrates well with all the solutions. It also has good reporting capabilities.

Control-M has improved our organization's functions by supporting high availability and integrating with CI/CD workflows. It helps maintain high availability and manage workflows across the production environment, increasing our productivity.

Additionally, Control-M has offered broad-level exposure that has increased our efficiency. Our workflows run smoothly. Everything is easy. We have had very positive feedback.

Control-M is fine to integrate with our DevOps toolchain. It is neither difficult nor easy.

Control-M made it more simple to create, integrate, and automate data pipelines across on-premises and cloud technologies. It is very comprehensive.

Control-M provides workflow orchestration, including scheduling, deploying, managing, and monitoring workflows. It helps us meet our service-level agreements. It is integrated into our CI/CD pipeline. It enhances our operational productivity.

The UI can be challenging for new users due to its learning curve. Additionally, there are some errors during automation. More detailed logs would be helpful.

We would also like enhanced API support. The APIs should be more comprehensive.

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

Control-M is stable so far, with no issues regarding crashing or lagging.

Control-M is very scalable. It can absorb more workload wherever needed.

We have had occasional response issues with their customer service. They do not always provide timely support.

Neutral

We have used Redwood RunMyJobs and Apache Airflow. Control-M offers more features under one umbrella. It has cloud-native support, real-time analytics, and other features.

The initial setup was challenging due to network setup issues and a lack of timely support from the service team. Its implementation took about a month. We did not have any downtime.

We did the deployment in-house without using an integrator or consultant.

Pricing is generally affordable, though some features cost a bit more.

New users should familiarize themselves with the tools and undergo training. It is essential to understand the necessity of using Control-M in your organization. I would recommend starting with your workflows and gradually integrating it with all the tools.

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

The main use is for job scheduling. We are using Control-M to manage and schedule various jobs within our organization.

We are more comfortable with Control-M since we have people who know this tool well. It integrates seamlessly with other tools within our ecosystem.

The best aspects of the solution are the ecosystem and integration part. This makes Control-M particularly valuable for us.

Control-M could benefit from incorporating AI features for better job scheduling. For example, if a job fails, the system could automatically manage related failures and take remedial actions without manual intervention. This would make it more advanced.

I have been using Control-M in my current organization for the last six months.

We did not face any stability issues with Control-M. It has been very stable for our needs.

Scalability is very subjective to use cases. For our minimalistic use cases, Control-M is quite scalable. However, for larger use cases, such as those in banking where there are thousands of jobs, scaling might be different.

Customer support from BMC is good but not excellent. We always expect more from support, so I would rate it between three to nine on a scale of one to ten.

Positive

Before Control-M, there might have been an IBM scheduling tool in use. I am unsure why the switch happened as I have only seen Control-M being used since I joined.

The initial setup was straightforward. It did not require much effort as we had knowledgeable people in the team.

One person is generally enough for the installation and configuration parts. It typically takes around one day to complete the installation.

We found Control-M to be one of the best solutions available. I would recommend incorporating AI features for future improvements.

I'd rate the solution eight out of ten.

Control-M is used to schedule jobs and run them regularly. It helps to automate processes and reduce manual effort, minimizing the risk of errors and enhancing efficiency. Our clients use Control-M for various use cases, especially when there is a need for regular, automated job executions.

Control-M significantly reduces manual errors and enhances automation. It provides better scalability and more efficient data processing, making it a highly reliable solution for daily job operations.

Control-M can cross all platforms and offers integration for container and cloud solutions. This versatility is very helpful for my customers. The job scheduling capabilities are extremely convenient and easy to use, making Control-M a superior solution compared to others in the market.

I have no immediate ideas for improvements. I do not have any specific suggestions for additional features that should be included in the next release.

I have been using Control-M for about a year.

We do not encounter significant stability issues with Control-M. It runs jobs daily with stable performance.

Control-M is highly scalable. It offers complete functionality, making it an excellent choice for handling extensive operations.

Customer support is very responsive and efficient. If you open a case, it can usually be handled within one to two hours, especially for urgent issues. Their support is available in real-time and resolves issues promptly.

Positive

The initial setup of Control-M is easy and not difficult.

I always implement Control-M on-premises.

The pricing for Control-M is very expensive. It would be beneficial if the price could be reduced.

If your organization aims to reduce manual errors and enhance automation, Control-M is a suitable choice. It minimizes the risk of operational errors and missing processes, offering better scalability and automation.

I'd rate the solution nine out of ten.

Our organization works with the cloud and databases. Our primary use case for Control-M is automating orchestration and scheduling jobs across the cloud and on-prem. We use it to monitor and report on jobs. We also use the index to integrate with the cloud service. It leverages our ability to manage workloads across various cloud platforms like AWS and GCP. 

Implementing Control-M saved us time by reducing our manual intervention. We can divert more resources to meaningful work. It reduced the amount of manual intervention needed by 30 to 35 percent. 

In addition to improving efficiency, workflow orchestration enhances our integration with other tools. We can orchestrate across on-prem and cloud environments and reliably create and integrate data pipelines. Workflow orchestration is critical to our DevOps. Control-M is constantly surveying the network.

The most valuable features of Control-M are automation and orchestration. It allows a different schedule, and we can manage thousands of jobs. It ensures we can complete them on time accurately. This automation reduces our manual intervention, significantly reducing error.

Control-M should receive more notice when it releases new features. The user interface is also a bit complex, and the navigation should be streamlined. 

I have used Control-M for a year and a half. 

I rate Control-M eight out of 10 for stability. 

I rate Control-M nine out of 10 for scalability. 

I rate Control-M support eight out of 10. 

Positive

We used Broadcom before switching to Control-M. The migration was a little complex.

Deploying Control-M is somewhat complex. It's easier to convert to the other tool. We spent more than two weeks on the deployment and received some support from the Control-M side. We had almost five teams of people working on it. First, we set up the environment. Then, we ran the installation and reconfigured the database. After that, we did functional and integration testing. 

Switching to Control-M reduced our total ownership cost.

Control-M isn't cheap, but this is an enterprise model. 

I rate Control-M nine out of 10. I will recommend it. It's easy to integrate and has the flexibility we need. 

We predominantly use Control-M SAP R3 jobs. That's our primary batch job load with external vendors and internally on our AWS instance. That's our batch load alongside a few custom integrations. They are not public applications. It's all in-house applications. We have integrations and API integrations for the API hubs, which speak to multiple other applications within our next case.

It isn't the only point of failure, but Control-M handles our business-critical, priority-one applications. We have other options. Control-M runs the SAP side for all batches. The time needed to realize the benefits depends on the scale and complexity. 

One use case was in health care and involved shipment orders. With Control-M controlling the workflow, we could effectively monitor it and forecast any delays. This enabled us to deliver critical products in under four hours across hospitals in the network. 

We can apply the same standards and run the same set of jobs across environments. Once they are tested in the non-production environment, we can move them seamlessly to the production environment. 

We have a nightly process of batch reports. Before Control-M, we spent around 12 hours manually scheduling reports in SAP. After streamlining the process, we reduced manual work to nine and a half hours. The business could update all the processes before midnight.

While it doesn't totally free up IT personnel, it provides visibility into self-service tools where business users can see their pipelines or job streams. It would be read-only access for the business side, but to take action on the job, they still need to contact the IT team. 

Control-M doesn't facilitate collaboration between business and IT users, but It provides a better user experience. Both parties can see what they are talking about, so there's no black zone for any of the parties. Before Control-M, the functional team had a particular nomenclature to relate what they had seen on Control-M. With the self-service tool, they can simply relay the job name. The collaboration starts there, and it builds over with a lot of other parameters.

Control-M provides a centralized view of our enterprise workload. As the owner, I can access my dashboard and see the status of jobs across the enterprise. It is strong at integrating with different applications and creating a pipeline of dependencies across applications on different operating systems. 

When it comes to developments where we have to move across regions or environments, it seamlessly integrates and adapts to different regions. Regarding integration with the DevOps pipeline, it allows us to use a JSON file and promote it across environments easily. 

We use Control-M to deploy workflows for DataOps and DevOps initiatives. It allows us to quickly test workflows or configuration changes without much manual effort. We add the JSON file for the conversation parameters and let the system handle the schedule. Integrating other DevOps tools within the journey gives us the management perspective and approval of multiple pipelines.

I'm currently working on the SaaS version, but I've also worked on the on-prem versions before. There is a handful of features that haven't been added to the SaaS version, and the BMC knows that. It's a matter of time before they prioritize the missing pieces and bring them into the SaaS version. 

I started using Control-M back in 2018.

Control-M has the best stability in the market. They claim 99.99 percent availability. It's hardly four hours of downtime throughout the year.

Control-M is infinitely scalable. We only need to add agents. BMC will take care of it if you need anything on the SaaS side, but we can handle the rest using our agent architecture.

I rate BMC support 10 out of 10. They are stringent about their SLA timelines. They respond on time, and if it's a priority one, they will call immediately. 

Positive

We previously used the SAP Scheduler and adopted Dollar Universe. All our local manual efforts ran in  Windows Scheduler.

It was a greenfield approach, and I was there from day one as a consultant. Deploying Control-M can be easy or difficult, depending on what the business needs. It takes a while to understand the infrastructure setup our business needs and the number of jobs we need to run through this application. 

It took a while to understand the infrastructure setup we require. We had to understand the number of jobs running through this application and how business-critical they are. The documentation BMC provides is top-notch and covers every step we must follow. 

Migrating to Control-M is a bit tricky in terms of preparing the data and having the right tool to convert required parameters into a Control-M-ready job. Control-M has a feature called AMIGO that helps us migrate from the existing source.  Converting a job and loading it into our Control-M format isn't straightforward. We must do some prerecorded checks and setups before. 

There is some maintenance in the form of updating agents and deploying patches on the SAP application. Since it's a SaaS application, BMC handles most of the maintenance on the server side. 

The license model is based on the number of jobs we run on the SaaS application or the number of executions, unlike the on-premise model options. If we have a handful of jobs, it's always good to consider Control-M, but if it's a large number of jobs, Control-M might not be a great option. 

Control-M enables us to consolidate our jobs, and it helps us have a uniform approach and schedule. It helps to have the audit logs available. The scheduler space is nice in terms of control. 

We attempted to leverage ActiveBatch by Redwood and a few other options, but Control-M had all the features we needed. It gives us a 360-degree view of our implementation across silos. The architectural requirements also vary depending on the criticality of the applications. 

Control-M allows us to customize the job templates for any application we need, which covers all our future plans. Its integration speed is excellent because it has templates for every application. 

I rate Control-M 10 out of 10. New users will be fine if they follow the Control-M documentation. There's also a book you can buy on Amazon called "Batch Scheduling" that comprehensively covers batch operations and how BMC has evolved over time. 

We use Control-M for batch automation. Previously, all of our batch work was manual, but now Control-M has significantly reduced the need for manual intervention. As a result, our batch processes are now 99% automated.

It's so easy to navigate, and especially for new hires, it's very straightforward to show them around the client because it is user-friendly. It's very easy to use. Compared to other softwares, Control-M has significantly simplified our monthly release process, making it easier to move things forward.

We're upgrading Control-M, and the process is very long. There are numerous boxes to tick and things to check to ensure everything is in order before the upgrade happens. We run three instances of Control-M, and making various changes for each is challenging.

I have been using Control-M for five years.

You might experience a brief connection issue, but it usually resolves within a few minutes. The problem is related to the web server.

Scalability is excellent. We utilize only about 20% of Control-M's capabilities. 

Support is helpful, and the online community is very good. There's the community forum, which I use regularly to find answers to questions. BMC has been very helpful in that space. They were extremely fast and solved a difficult problem our in-house team couldn't solve in a matter of minutes. 

Positive

The initial setup is straightforward. We used to use in-house software.

We have three different environments where people can work. People can use our development instance of Control-M to work on their batch processes before they go live, allowing them to experiment and refine until they get it right.

It's much simpler now. Everything was a manual batch job. Using the features of Control-M every day makes our batch processing so much easier.

It makes our lives so much easier. For our operations team, which runs our daily batch overnight, viewing everything as it happens has been an absolute lifesaver, especially if things go wrong overnight. It's great to have that visibility. It has also sped up our process, reducing overhead and weekend overtime. Batch processing is much quicker now, resulting in fewer manual errors.

Control-M has so much functionality that even if you initially purchase it to handle a specific part of your batch work, it can offer much more. We've progressed beyond traditional batch processing to include MFT, which has been incredibly useful. Our file watchers and other automation features have significantly simplified our workflows and made our lives much easier.

Overall, I rate the solution a ten out of ten.

We use the product as our primary application tool for workload automation. It helps monitor and manage client domains in terms of configuration daily.

The product has enhanced the interface with a clear visual display of data and process batches, showing the completion status of workflows. It makes it easier to understand our organization's progress at a glance.

The platform integrates with Jenkins, Ansible, Docker, and Kubernetes. It can schedule and manage container workflows.

Integrating new solutions into the DevOps toolchain with the right approach and resources is straightforward. However, sometimes it can be complex.

It offers excellent visibility and management capabilities. It provides a centralized platform for monitoring and managing workflows and job scheduling. It supports various scheduling options, including time-based, event-based, and condition-based scheduling, allowing users to automate complex workflows efficiently.

It has simplified the process by streamlining the data workflow. It facilitates data extraction from sources, transforms it as needed, and loads it into the destination database. This comprehensive support for data extraction, transformation, and loading (ETL).

It is highly effective for building, scheduling, managing, and monitoring production workflows. For instance, it allows us to set up ETL processes to run at specific times, such as daily at midnight or in the morning. This precise scheduling ensures that all dependencies are met and tasks are executed in the correct sequence. For example, the transformation job is scheduled to start after the extraction job has been completed.

Operational efficiency is crucial as it reduces processing time. Faster data flow means job workflows are completed more quickly, reducing processing time. It is essential for meeting tight deadlines and maintaining smooth operations.

While numerous scheduling solutions are available, BMC's Control-M is highly effective for managing and orchestrating workflows across an enterprise.

The platform's best features are the monitoring capabilities. It is essential for tracking activities and ensuring jobs run smoothly. Additionally, the scheduling capability excels in building, scheduling, managing, and monitoring production workflows. These features are critical to our organization's operations and efficiency.

They could enhance the product's data flow, job processing speed, and efficiency.

Additionally, improvements are needed in real-time monitoring and alerts. Developing more robust real-time analytics capabilities to monitor and report the performance status of DevOps workflows would be beneficial.

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

It is a stable product. I rate the stability a nine.

Our organization has a team of 50 executives who use the product.

It is scalable. I rate the scalability a nine.

BMC's service team significantly supported the development of our migration plan for the Standard AutoCorrelation Controller (SGP). Their assistance involved several key steps. First, they helped us identify and map out the different requirements and dependencies, including how SGP jobs interact with one another and their integration within Control-M. The migration plan included phases for testing, fallback strategies, and execution. Post-migration validation was crucial to ensure that all SGP jobs were successfully migrated and were functioning correctly in the new environment.

Positive

The initial setup is easy. The deployment takes two months and involves a team of 50 executives.

The platform has helped us save 30% of operations time.

The product price is reasonable. I rate the pricing an eight.

I rate the product a nine out of ten.