Unified Workflow Orchestration with Bluemetrix and BMC Helix Control-M
- The Bluemetrix Team
- Jul 1
- 3 min read
Organisations are looking for products that allow them to spend less time managing data infrastructure and more time focusing on core business functions. For developers, job scheduling is a critical part of managing repetitive, data-driven tasks across environments. With the Bluemetrix Workflow Manager integration with Control-M from BMC, developers and data teams now have a unified interface to simplify how jobs are created, scheduled, tested, and migrated across platforms such as Airflow, BMC Control-M, and Oozie.
Most importantly, developers no longer need to be Control-M experts. Bluemetrix Workflow Manager provides an intuitive and efficient way to manage jobs, whether teams are working in development or migrating to production, empowering greater autonomy while reducing complexity for data operations.
Scenario 1: Independent Scheduling for Spark Pipelines
Traditionally, Spark developers often work in environments where test and production systems rely on different schedulers. As a result, managing these workflows require platform-specific expertise in both systems, which adds operational overhead and deployment errors during migration or testing phases. In this scenario, Spark developers can build, schedule and test data pipelines independent of workflow management platforms.
Developers create data workflows consisting of multiple inter-dependent Spark jobs.
Using the CLI or RESTful (via cURL) API, the Spark workflows are submitted to the Bluemetrix Workflow Manager.
If the test environment uses Airflow, testing the scheduled jobs on Airflow can be done using the Airflow client connection.
And if the production environment uses Control-M, operations can integrate the newly released Spark workflow into production via the CTM client.
Benefits of this system:
Developers only have to submit workflows and scheduling details once to the Bluemetrix Workflow Manager.
Developers, testers and data operators do not need to worry about having expertise in multiple workflow management platforms.
Different scheduling platforms can be used by different teams in different environments.
Scheduling workflows and data pipelines becomes platform independent.
Scenario 2: Scheduler Platforms Migration
Organisations still running legacy platforms like Oozie can modernize without rewriting workflows from scratch. In this scenario, developers can easily enable the lift-and-shift of job definitions across platforms, allowing migration of workflows between scheduling platforms.
Oozie is currently managing many data pipelines, but the user wants to migrate these jobs to Control-M or Airflow.
Oozie jobs can be imported into the Bluemetrix Workflow Manager using the Oozie client connection
The jobs and scheduling information for each are converted to a platform independent structure within the Bluemetrix Workflow Manager.
Now these jobs can be exported and scheduled to run on Control-M and Airflow.
Benefits of this system:
Easy lift and shift from one scheduling platform to another without the need to manually migrate scheduling jobs.
Workflow definition and structure is platform independent. Meaning, build or import once and deploy to multiple platforms.
Allows testing of new scheduling platforms while keeping existing systems running.
Can run multiple scheduling platforms in parallel.
Scenario 3: Hybrid Workflow Orchestration Support
When an organisation runs Airfklow for development but relies on Control-M in production. Monitoring job across both platforms is difficult and lacks a unified reporting view. In this scenario, Bluemetrix workflow manager enables Control-M to monitor and report on Airflow jobs.
User schedules and runs Jobs in Airflow
User creates rules for Bluemetrix Workflow Manager Airflow client to identify jobs to be monitored on Airflow
Bluemetrix Workflow Manager Airflow client reports to CM on activity of Jobs that pass the rule sets
Bluemetrix Workflow Manager CTM client incorporates Airflow jobs into reports and SLAs
Benefits
Client customers can run multiple schedulers across the organization
Customers can set rules to monitor and capture activity on Jobs of interest on non-production schedulers
These job details can be exported to CM for final report and SLA enforcement
Control-M is a single pane of glass for all critical pipeline activity across the organization
Next Steps for Implementing Cross-Platform Scheduling at Scale
For organisations orchestrating data workflows across hybrid environments, platform-agnostic scheduling capability is essential to ensuring the data teams can build, test, and deploy pipelines efficiently, without being locked into a single tool or burdened by operational overhead.
Bluemetrix Workflow Manager integrates natively with Control-M to eliminate the burdens of static, siloed scheduling, such as enabling developers to work in their preferred environments without needing deep expertise in production systems, and ensuring operations are maintained in a centralised control and observability. This saves substantial time in testing and deployment, simplifies migration between platforms, vastly reduces risk, and empowers teams to focus on delivering reliable, production-ready data workflows. For organisation using Bluemetrix, these capabilities have resulted in 70% of data processing time reduction and millions of customer protected.
Read our customer sucess stories or speak to our expert here.
