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Control-M + Boomi AtomSphere
Your Boomi workflow starts before a process ever executes — and it can fail when something upstream breaks. An SFTP V2 delivery arrives late or incomplete. A Salesforce REST extraction finishes after the downstream processing window. Control-M orchestrates the full chain: SFTP file arrival, data transformation, Boomi process execution, and downstream warehouse delivery.
common workflow issues
Does this sound like your week?
These aren’t edge cases. They’re the normal operating conditions for teams running Boomi processes across multiple tools. Here’s how Control-M handles each one.
UPSTREAM DATA
The SFTP delivery is late. Your Boomi process must not start.
Control-M waits for the required file or upstream job condition before releasing the Boomi process. Dependencies replace disconnected schedules, preventing premature execution and keeping incomplete data from propagating into downstream applications.
PROCESS FAILURE
The Boomi process errors at 2:14 a.m. Downstream jobs are waiting.
Control-M tracks Boomi execution status and detects unsuccessful completion before downstream jobs are released. Dependency logic prevents the failure from cascading, while centralized monitoring gives operations teams the context needed to respond quickly.
API THROTTLING
Status checks hit Boomi’s API limit. Monitoring starts returning errors.
Control-M provides configurable status polling and tolerance settings for Boomi jobs, accounting for Boomi’s five-API-calls-per-second limitation. Failed status checks can be retried according to the configured tolerance before the job ends Not OK.
CROSS-TOOL DEPENDENCY
Boomi finished successfully. The Snowflake load still cannot run.
Control-M evaluates the Boomi job’s completion alongside the downstream workflow dependencies and releases the next job when its conditions are satisfied. Boomi and downstream data-platform jobs become one coordinated production flow instead of separate schedules.
SLA RISK
The process is still running. Your 7:00 a.m. delivery is at risk.
Control-M connects Boomi execution to the SLA of the broader workflow, giving teams visibility beyond an individual process run. SLA monitoring and predictive delay detection help operators intervene before a late upstream process becomes a missed business deadline.
Control‑M + Boomi AtomSphere
Control‑M + Boomi AtomSphere
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workload.types |
Boomi process execution · Atom-based execution · process-name execution · process-ID execution · Advanced JSON execution requests · cloud integration processes |
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trigger.type |
upstream job completion · file arrival · time schedule · Control-M event · API-driven scheduling · cross-application dependency |
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cross_tool.deps |
SFTP/file transfer · Salesforce · Snowflake · Databricks · AWS Glue · Apache Airflow · REST API |
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cloud.platforms |
Boomi cloud endpoints · Control-M SaaS · Control-M on-premises · hybrid application environments |
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error_handling |
status polling frequency · configurable tolerance · Not OK status detection · downstream cascade prevention · SLA monitoring · centralized alerting |
|
throughput |
up to 50 Boomi jobs simultaneously per Control-M/Agent · configurable status polling frequency · Boomi five-API-calls-per-second status-check limit |
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observability |
Boomi job status · job results · job output · end-to-end dependency visibility · SLA tracking · centralized Control-M monitoring |
end-to-end orchestration
One production workflow. Every tool in the stack.
Control-M orchestrates workflows across Boomi, SFTP, Salesforce, Snowflake, Databricks, Airflow, and cloud services in a single job flow — with dependency tracking, SLA visibility, and automated recovery across all of them.
- Cross-tool dependency: SFTP → Boomi process → Snowflake load → analytics handoff
- Data-aware triggers: file arrival, API event, upstream completion, process status
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Boomi AtomSphere |
execute process · select Atom · select process · process-ID execution · monitor status/results/output |
|
SFTP / file transfer |
file arrival · secure transfer · upstream dependency · delivery confirmation |
|
Salesforce |
coordinate extraction · sequence dependencies · schedule processing · downstream handoff |
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Snowflake |
coordinate data loads · downstream dependencies · SLA alignment · execution monitoring |
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Databricks |
trigger jobs · sequence processing · monitor completion · coordinate downstream delivery |
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Apache Airflow |
trigger DAGs · track completion · connect upstream/downstream dependencies · SLA coordination |
|
Cloud services / REST APIs |
API execution · event coordination · cross-platform dependencies · centralized scheduling |
MONITOR PROCESSES
Monitor Boomi execution across the complete data pipeline.
Boomi reports individual process execution, but production delivery often depends on jobs outside that process. Control-M provides centralized visibility across Boomi and surrounding workflow steps so data teams can see execution health and dependency state together:
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Boomi process execution status
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Job results and output
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Upstream and downstream dependencies
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End-to-end workflow monitoring
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Failure and wait visibility
SLA ASSURANCE
Manage Boomi processes against the business deadline.
A successful Boomi process is not enough when the complete pipeline finishes late. Control-M connects Boomi execution to end-to-end service delivery, helping teams identify delays and manage dependencies before they threaten the workflow SLA:
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End-to-end SLA tracking
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Predictive delay detection
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Cross-platform dependency visibility
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Centralized workflow alerts
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Downstream cascade prevention
Documentation
Bring order to complex workflows
Learn how Control-M helps teams orchestrate complex processes with greater visibility, coordination, and control.
