Control-M is BMC Software’s workload automation solution that orchestrates application and data workflows across mainframe, cloud, and hybrid environments through a centralized interface.
The platform manages complex workflow dependencies, provides end-to-end visibility into production processes, and integrates with major cloud services, data platforms, and DevOps tools.
Discover Control-M architecture, its features, benefits, and shortcomings within the enterprise ecosystem.
Control-M overview
Control-M is BMC Software’s workload automation solution that manages workflows spanning mainframe systems to cloud infrastructure, providing centralized control over distributed processes.
The system provides end-to-end visibility into production workflows through a centralized interface. Control-M workload automation addresses workflow management across hybrid environments by offering a single point of control for diverse automation processes.
The platform handles complex workflow dependencies and maintains compliance requirements for business operations. Key functionality includes data workflow orchestration, file transfer management, and integration capabilities with existing enterprise technology stacks.
Integrations
Control-M workload automation integrates with major cloud services, including AWS, Azure, and Google Cloud, for workflow execution across cloud providers. Data platform integrations include Airflow, Snowflake, and Azure Data Factory for compatibility with existing data stack architectures. DevOps tool support covers Jenkins, GIT, and CI/CD platforms for development process integration.
Security integration includes CyberArk for access management and compliance requirements. The platform’s code-based configuration supports version control and testing within software development lifecycles. Integration capabilities extend automation across application and data environments while working with existing technology investments.
The system maintains compatibility with both legacy mainframe systems and modern cloud-native applications through standardized integration approaches.
Control-M architecture
Control-M employs a distributed architecture consisting of three primary components that manage workflow orchestration across enterprise environments. The system provides centralized control through Control-M/Enterprise Manager while distributing execution capabilities across multiple servers and agents.
Core components
- Control-M/Enterprise Manager (Control-M/EM) serves as the central control point for all Control-M/Servers, enabling users to view, monitor, manage, and intervene in batch workflow processing across the enterprise. The component includes client applications, server processes, and infrastructure elements that facilitate communication and data management.
- Control-M/Server functions as the scheduling engine responsible for job scheduling, workflow management, and processing coordination. Each server is platform-specific, maintaining its database that includes active jobs, performs load balancing, and handles requests from Control-M/EM. The architecture supports both distributed Control-M/Server installations and Control-M for z/OS mainframe implementations.
- Control-M/Agent and Remote Hosts execute jobs according to instructions from their associated Control-M/Server. Organizations can deploy dedicated agents on each controlled computer or use agentless Remote Hosts for job execution. Agents provide enhanced functionality, including counter support, multiple notification types, and application plug-in capabilities.
Control-M/EM sub-components
Control-M/EM clients include multiple interfaces for different user roles:
- Control-M for production definition and monitoring
- Configuration Manager for system management and security
- Self-service for web-based service analysis
- Workload Change Manager for workflow modification requests
- Automation API for developers and DevOps integration
Control-M/EM servers handle communication and specialized functions:
- GUI Server manages client-server communication with load-balancing capabilities
- Global Conditions Server distributes events for cross-server dependencies
- Gateway components facilitate Control-M/EM to Control-M/Server communication
- Web Server provides HTTP/S access for various applications
- SLA Manager, Forecast Server, and Self Service Server support add-on functionality
Services architecture
Control-M implements a microservices approach using independent services that perform specific tasks without requiring larger component dependencies. This architecture reduces resource consumption and improves operational efficiency across the environment.
- Control-M/EM Services include Apache Kafka for data streaming, Apache Zookeeper for distributed coordination, Services Health Monitor for status reporting, and specialized services for validation, reporting, and workflow insights. The Services Configuration Agent functions as a watchdog process monitoring all service operations.
- Control-M/Server Services provide dedicated functionality, including API Gateway for request routing, Job Info Service for logging and information handling, Job Order Service for order processing, and Scheduling Service for date calculation. The architecture maintains service independence while ensuring coordinated operation through Kafka messaging.
Figure 1: Control-M architecture design.1
User evaluations
| Platform | User ratings | Number of reviews |
|---|---|---|
| Trustradius | 9.3/10 | 237 |
| PeerSpot | 4.3/5 | 125 |
| G2 | 4.4/5 | 57 |
| Capterra | 4.3/5 | 3 |
Note: The table is sorted by the number of reviews.
We gathered Control-M user reviews from B2B review platforms such as G2,2 Capterra,3 and TrustRadius.4
Advantages
- Control-M provides secure, centralized job scheduling and monitoring with capabilities to define job dependencies and rerun failed jobs.
- User interface includes color-coded job status and an alert window for quick action on failed or late jobs.
- The software supports automation of various job types, including batch and API, with easy setup and scheduling features.
Shortcomings
- Users report that Control-M’s integration and upgrading processes need improvement due to complexity and time consumption.
- Job failure reasons need to be clearer, and bugs following updates or patches have negatively affected daily activities.
- Users find the licensing costs high for small and mid-sized businesses, and the process for moving workflows to higher environments difficult.
Control-M for big data
Control-M for big data manages data workflow orchestration across large-scale data processing environments. The solution addresses data pipeline challenges for organizations processing high-volume datasets through automated workflow management.
The platform integrates with big data technologies to orchestrate complex data processing workflows from ingestion through analysis. Organizations can leverage this functionality to ensure visibility across data pipeline execution while maintaining reliability for business-critical data processes.
The solution handles scheduling and dependency management for large-scale data operations, enabling organizations to achieve big data success through automated workflow orchestration.
Control-M managed file transfer
Control-M managed file transfer provides secure file movement capabilities integrated with workflow orchestration. The system supports multiple protocols, including SFTP, FTP over SSL, AS2, and PGP encryption for secure data transmission. Cloud storage integration includes Amazon S3, Azure Blob Storage, Azure Data Lake Storage Gen2, Google Cloud Storage, Oracle Cloud Storage, and Microsoft SharePoint.
The solution offers FIPS compliance and policy-driven processing rules for regulatory requirements. File transfer operations integrate with application workflows through a unified interface, providing consolidated visibility across both file movement and related workloads.
The system includes self-service capabilities enabling internal teams and external partners to manage file transfers independently. Advanced analytics and customizable dashboards provide monitoring capabilities for file transfer operations across cloud and on-premises infrastructure.
Figure 2: The graph showing the Control-M managed file transfer processes.5
Jobs-as-code
Jobs-as-code integrates workflow definitions into software development lifecycle processes using familiar development tools. The approach enables workflow automation through CI/CD pipelines using JSON, Python, Jenkins, and GIT for version control and testing. Developers can code jobs using standard text editors or IDEs within automated CI/CD frameworks.
The methodology supports existing build tools for automation development and automated testing using established testing frameworks. Deployment capabilities extend to downstream environments through standard software deployment practices.
Community solutions include operational tasks such as agent status monitoring, agentless scheduling, workload policy management, and user role modifications. CI/CD integration examples cover GitLab pipelines, folder cleanup utilities, and Control-M artifact management within development workflows.
Infrastructure-as-code capabilities include Control-M deployment in Kubernetes pods, AWS Lambda integration, and Terraform provisioning. IDE integration provides Control-M function access and code snippets within development environments. API gateway connections enable Control-M REST services access through enterprise API management platforms.
Check out the video below to see how the job-as-code approach works in real life.
Control-M for SAP
Control-M for SAP manages workflow orchestration across SAP environments, including SAP BTP, SAP ECC, SAP S/4HANA, SAP BW, and data archiving systems. The solution provides native integration with SAP systems while supporting RISE with SAP model compatibility. Job definitions can be imported using Control-M conversion tools for existing SAP workflows.
The platform manages processes including order-to-cash, procure-to-pay, payroll, year-end and month-end closing, and archiving operations. SAP event triggers activate with continuous monitoring and user-defined follow-up actions. The unified view eliminates the need for custom scripts while providing visibility across SAP and non-SAP systems.
Customer implementations include global SAP job scheduling across multiple production plants with tens of thousands of SAP jobs and managed file transfer operations. Teams, including support, job creation, and SAP specialists, can collaborate through the platform’s unified interface. Integration capabilities extend to products like Informatica alongside SAP systems.
Control-M for mainframe
Control-M for mainframe provides workflow orchestration for mainframe environments while enabling integration with multi-cloud systems. The solution manages mainframe business services delivery through native application workflow orchestration. Integration capabilities reduce manual processes required for orchestrating mainframe to cloud workflows and data pipelines.
The platform supports mainframe application migration to cloud environments while optimizing workflow execution to reduce processing costs and meet service level agreements.
Report management includes collection, retrieval, distribution, and archiving capabilities for reducing storage and distribution costs. JCL management ensures error-free job control language in application workflows while eliminating manual restart procedures.
Businesses can leverage Control-M to consolidate scheduling tools across mainframe, distributed systems, and cloud environments into a unified interface. Production job management includes mainframe jobs, Informatica jobs, and other enterprise software through the Control-M platform.
What’s new in Control-M
The latest Control-M release focuses on workflow orchestration enhancements across hybrid and multi-cloud environments with improved deployment flexibility and SaaS migration capabilities.
Hybrid and multi-cloud orchestration
Control-M provides enhanced deployment capabilities for cloud and hybrid environments with improved scalability features. The platform supports adaptable deployment models that accommodate varying infrastructure requirements across organizations. SaaS transition capabilities offer a simplified migration path while maintaining existing functionality and value propositions.
Key integrations strengthen Control-M capabilities through connections with specialized tools, including CyberArk for security management and application performance monitoring solutions like Datadog, AppDynamics, and Dynatrace.
These integrations extend the platform’s monitoring and security capabilities within existing enterprise technology stacks.
Jett generative AI advisor
Jett functions as a GenAI-powered advisor specifically designed for Control-M SaaS environments. The system provides instant workflow expertise through natural language query capabilities, enabling users to ask workflow-related questions and receive answers in simple, understandable language.
The AI advisor accelerates key workflow scenarios, including:
- Issue resolution through rapid problem identification
- Audit compliance verification with simplified data access
- Workflow optimization through pattern analysis
- Anomaly detection for proactive management
Figure 3: Control-M generative AI assistant Jett’s dashboard.6
Further reading
- Top IT Process Automation Tools
- Top IT Automation Trends, Predictions & Stats
- Top IT Automation Use Cases
- Benchmark Best IT Automation Software
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