BMC is doubling down on cloud—and on Amazon. The enterprise software veteran has signed a five-year strategic collaboration agreement (SCA) with Amazon Web Services to expand how enterprises orchestrate application workflows and data pipelines at scale.

At the center of the deal is BMC’s Control-M SaaS platform, which will now run on AWS as its preferred cloud provider. The move formalizes a long-standing relationship and positions Control-M as a cloud-native orchestration layer for hybrid, data, and AI-driven enterprises.

For CIOs and data leaders grappling with sprawling multi-cloud environments and AI initiatives, the message is clear: BMC wants to be the automation backbone that connects it all—now with deeper AWS integration and generative AI baked in.

What’s New: GenAI and Agentic AI Meet Enterprise Orchestration

The headline innovation isn’t just infrastructure. It’s intelligence.

Through the partnership, BMC is embedding its generative AI capabilities—most notably Jett, its AI-powered advisor—into Control-M running on AWS. Jett delivers intelligent guidance, automated insights, and context-aware recommendations designed to help teams modernize faster across AWS environments.

BMC is also pushing into agentic AI, positioning Control-M as more than a job scheduler. The company aims to deliver native AWS-based automation that can autonomously manage data pipelines and workflows across hybrid and cloud systems.

For organizations building machine learning pipelines in services like Amazon SageMaker, the integration promises out-of-the-box orchestration that ties together data prep, model training, deployment, and monitoring. That’s a practical win for enterprises trying to move AI projects from pilot to production without creating new silos.

Why It Matters: Orchestration Is the New Control Plane

As enterprises scale AI and data initiatives, orchestration has quietly become mission-critical. Modern architectures often span on-prem infrastructure, multiple clouds, containers, and managed AI services. Without a unified layer to coordinate workflows, complexity spirals fast.

That’s where Control-M fits in.

Already available in AWS Marketplace, the platform enables end-to-end orchestration of data pipelines across hybrid environments. With this expanded collaboration, BMC is betting that AWS customers want a single control plane to manage everything from legacy workloads to containerized microservices to AI jobs.

The timing aligns with broader industry shifts. Enterprises are accelerating cloud modernization while contending with governance, data residency, and compliance demands. BMC recently expanded Control-M SaaS availability to the AWS Sydney Region, alongside deployments in Ireland, Canada, and the U.S.—a nod to rising demand for localized data processing and resiliency.

Deep AWS Integration Across Services

The collaboration extends beyond hosting. BMC continues to roll out monthly integrations with AWS services, including:

• Amazon Athena

• Amazon Bedrock

• Amazon Elastic Container Service (ECS)

• AWS CloudFormation

• AWS Mainframe Modernization

• Amazon SageMaker

This expanding ecosystem suggests a deliberate strategy: make Control-M the connective tissue between AWS-native services and legacy enterprise systems.

For customers like Air Europa, the appeal is immediate integration with tools such as Amazon SageMaker to support data, machine learning, and AI roadmaps. The orchestration layer becomes the operational glue that ties data strategy to execution.

Competitive Context: The Automation Arms Race

BMC’s move comes amid intensifying competition in automation and workload orchestration. Vendors across the IT operations, DevOps, and data engineering spectrum are racing to embed AI into workflow management. Meanwhile, hyperscalers like AWS are expanding their own native orchestration capabilities.

By aligning closely with AWS rather than competing head-on, BMC is taking a pragmatic route. It strengthens its relevance inside the AWS ecosystem while differentiating through enterprise-grade automation depth and hybrid support—areas where many cloud-native tools still lag.

The five-year term also signals commitment. Strategic collaboration agreements with AWS typically involve joint go-to-market efforts, co-innovation, and tighter technical alignment. For BMC, that means greater visibility inside one of the world’s largest cloud marketplaces.

The Bigger Picture: Modernization Without Disruption

For enterprises, modernization isn’t just about moving to the cloud. It’s about orchestrating legacy systems, data platforms, AI workloads, and emerging services without breaking what already works.

By making AWS its preferred cloud for Control-M SaaS, BMC is betting that customers want flexibility without fragmentation. The promise: unified orchestration across hybrid, cloud, data, and AI workloads—paired with AI-driven insights to reduce operational drag.

If BMC delivers, Control-M could evolve from a trusted scheduling platform into a strategic AI-era control layer for enterprise operations.

In a market obsessed with generative AI headlines, this deal is less about flashy demos and more about plumbing—the kind that determines whether digital transformation efforts actually scale.

And in enterprise IT, the plumbing is where the real battles are won.

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