Process Control includes seven workflow patterns: Sequential Chaining for dependent steps, Parallel Execution for independent tasks, Fan-Out/Fan-In for distributed work, Loops for repetition, Checkpointing for resumable processes, Rollback for reversible changes, and Wait States for timing synchronization. The right pattern depends on whether your steps depend on each other, need speed or reliability, and whether you can recover from failures. Most workflows combine multiple patterns. Start with Sequential Chaining, then add Parallel Execution for independent branches.
Your automation runs a 12-step process. Step 4 fails. The entire thing stops. You have no idea what completed and what did not.
Someone re-runs it from the beginning. Steps 1-3 execute again. Now you have duplicates in your database and customers who received the same email twice.
Three hours to untangle a mess that happened in three seconds.
How your steps execute matters as much as what they do.
Part of Layer 4: Orchestration - Controlling how workflows execute.
Process Control determines how your automated steps run: one after another, simultaneously, in loops, with save points, or with the ability to undo. The wrong choice means fragile automation that breaks under real conditions. The right choice means workflows that handle failures gracefully and complete reliably.
Most workflows need multiple patterns. Sequential chaining for dependent steps. Parallel execution for independent ones. Checkpointing for long-running jobs. Rollback for multi-system changes. The question is which patterns you need and where.
Each pattern solves a different execution problem. Using the wrong one means workflows that are slow, fragile, or impossible to recover.
Sequential | Parallel | Fan-Out | Loops | Checkpoints | Rollback | Wait States | |
|---|---|---|---|---|---|---|---|
| Primary Purpose | |||||||
| When to Use | |||||||
| Speed Impact | |||||||
| Failure Behavior |
The right choice depends on your step dependencies, speed requirements, and how you need to handle failures.
“Each step needs the output of the previous step”
Sequential chaining enforces dependencies and prevents downstream steps from running on garbage.
“I have 5 data sources to query and they do not depend on each other”
Parallel execution runs all 5 queries at once. Total time is the slowest query, not the sum.
“I need to process 500 records as fast as possible”
Fan-out/fan-in distributes records across workers and merges results.
“I need to keep retrying until something succeeds”
Loops handle retry logic and exit conditions cleanly.
“My job runs for 3 hours and I cannot afford to restart from scratch”
Checkpointing saves state so you resume from where you stopped, not the beginning.
“If step 5 fails, I need to undo steps 1-4”
Rollback executes compensating actions in reverse order.
“I need to wait for an external API or human approval”
Wait states pause execution until conditions are met without burning resources.
Answer a few questions to get a recommendation.
Process control is not about automation technology. It is about coordinating work so that dependencies are respected, resources are used efficiently, and failures do not cause catastrophic data loss.
Work needs to happen in multiple steps with coordination
Choose execution patterns that match step dependencies and failure requirements
Workflows complete reliably even when individual steps fail
When pulling a monthly report requires 5 data sources that do not depend on each other...
That's a parallel execution opportunity - query all 5 simultaneously instead of sequentially.
When a 3-hour data migration fails at hour 2 and has to restart from scratch...
That's a checkpointing problem - save state so failures resume instead of restart.
When 47 invoices were created with wrong pricing and need to be reversed...
That's a rollback need - compensating transactions to undo each change in reverse order.
When automation hits API rate limits and everything fails at once...
That's a wait states problem - add delays between requests to respect external constraints.
Which of these sounds most like your current automation challenges?
These patterns seem simple until they fail. Then the cost becomes obvious.
Move fast. Structure data “good enough.” Scale up. Data becomes messy. Painful migration later. The fix is simple: think about access patterns upfront. It takes an hour now. It saves weeks later.
Process control determines how steps in an automated workflow execute: in sequence, in parallel, in loops, or with pauses. It includes patterns for recovery when things fail, like checkpointing to resume from where you stopped and rollback to undo completed steps. Good process control makes automation reliable instead of fragile.
Use sequential execution when each step depends on the result of the previous step. The output of step 1 becomes the input of step 2. Use parallel execution when steps are independent and do not need to wait for each other. Processing 5 data sources at once instead of one after another cuts time from 25 minutes to 5 minutes.
Fan-out/fan-in splits a single task into multiple parallel subtasks, executes them simultaneously, then merges the results back together. Instead of processing 100 items one by one, you process all 100 at once and wait only for the slowest one. Total time becomes the slowest task, not the sum of all tasks.
Use checkpointing to save workflow state at key points. If a 3-hour job fails at hour 2, it can resume from that checkpoint instead of starting over. Track which items have been processed, save intermediate results, and persist state to durable storage. On restart, read the last checkpoint and continue forward.
You need rollback when your workflow makes changes across multiple systems that must stay consistent. If step 5 of 7 fails, you may need to undo steps 1-4 that already completed. Rollback uses compensating transactions that reverse each change. Not all actions are reversible, so identify irreversible steps upfront.
Wait states pause workflow execution until a condition is met or time passes. They align your workflow with external constraints: rate limits on APIs, dependent processes that need time to complete, or human approvals that take hours. Without wait states, workflows race ahead and break on external timing requirements.
Loops process items one at a time with state tracking between iterations. Fan-out/fan-in processes all items simultaneously. Use loops when you need to process items in order, track cumulative state, or when parallelism would overwhelm downstream systems. Use fan-out/fan-in when items are independent and speed matters.
Most workflows combine multiple patterns. A sequential chain might include a parallel step for independent data fetches, with checkpointing after each major phase and rollback capability for the entire sequence. Wait states synchronize with external systems. Loops handle collections. The patterns compose to match your specific reliability and performance requirements.
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