Migrating Automation Workflows to Cut Costs by 60%

A founder reduced automation expenses from $49/month to $0 by migrating 23 workflows from Make.com to a self-hosted n8n instance, eliminating operation limits.

A founder reduced their automation expenses from $49/month on Make.com to $0 by migrating 23 existing scenarios to a self-hosted n8n instance. This strategic shift eliminated the recurring operation limits that previously forced quarterly plan upgrades. The migration, completed within two weeks, provides a direct playbook for founders seeking to optimize costs in their workflow automation stack.

The Cost of Operation-Based Pricing

The previous automation setup on Make.com incurred a $49/month charge, primarily due to an operation-based pricing model. Make.com counts every module execution within a scenario as an "operation." For instance, a scenario comprising six modules, running 200 times monthly, would consume 1,200 operations. With 23 such scenarios handling critical functions like lead captures, Slack notifications, email sequences, and weekly reports, the founder consistently approached and exceeded operation limits. This necessitated frequent plan upgrades, driving up the monthly expenditure and creating an unpredictable cost structure. The system's design meant that increased usage directly translated to higher costs, regardless of the complexity of the individual workflow execution.

n8n's Execution-Based Model

The migration to n8n fundamentally altered the cost structure by shifting from operation-based billing to workflow execution-based billing. n8n charges once per workflow execution, irrespective of the number of nodes (modules) within that workflow. The founder opted for a self-hosted n8n instance, which reduced the automation bill to $0. This self-hosted model provides unlimited workflows and unlimited executions, removing the scaling constraints inherent in Make.com's pricing.

A direct comparison highlights the difference:

Beyond cost, n8n offers enhanced capabilities such as a full Node.js/Python runtime for custom code, compared to Make.com's basic formula functions. It also provides native integrations for advanced AI/LLM models like Claude, GPT-4o, and Gemini, which are limited on Make.com. The self-hosting option, available via Docker, npm, or Railway, provides greater control and flexibility over the automation environment.

Translating Automation Concepts

A key step in the migration involved understanding the conceptual differences between Make.com and n8n. While both platforms offer visual workflow builders, their terminology and underlying mechanics vary. The founder compiled a translation dictionary to bridge this gap, which proved critical for converting existing scenarios efficiently.

The most significant conceptual difference is the "Operation" versus "Execution." Make.com's granular counting of every module execution directly impacts cost, whereas n8n's single count per workflow run decouples cost from workflow complexity. This distinction underpins the entire cost savings strategy. Understanding these equivalences allowed for a systematic conversion of each of the 23 scenarios.

Migrating a Core Workflow Example

The migration process can be illustrated with a common workflow: a lead capture form that writes to a Google Sheet and sends a confirmation email. On Make.com, this workflow consisted of three modules: Webhooks → Google Sheets (Add Row) → Gmail. Each run of this scenario consumed three operations. With 200 leads per month, this single workflow alone accounted for 600 operations monthly.

The n8n equivalent achieves the same functionality using a Webhook node, a Google Sheets node, and an Email node. However, regardless of the number of nodes, n8n counts this as a single workflow execution per run. For a self-hosted instance, this translates to zero cost per execution. The founder provided three import-ready workflow JSONs, including this lead capture example, demonstrating the direct translation and implementation. This specific example highlights how the shift in billing model directly impacts recurring costs for even basic, high-volume workflows.

WHAT WE'D CHANGE

The strategy of migrating to a self-hosted n8n instance for zero direct cost is effective for specific use cases, but it introduces new operational considerations. The "free" aspect of self-hosting omits the cost of time and expertise required for setup, ongoing maintenance, security patching, and ensuring high availability. For a solo founder, this overhead can be substantial, potentially diverting critical focus from core product development and customer acquisition.

The founder's 23 scenarios, handling lead captures, notifications, and reports, suggest a relatively contained and non-mission-critical automation footprint. Larger organizations or those with more complex, high-availability automation needs might find the self-hosting burden prohibitive. Such environments often demand a managed cloud solution for n8n, which carries a $24/month cost for the "Pro" tier. This negates some of the direct savings and reintroduces a recurring expense, albeit potentially lower than Make.com for high-volume users. Furthermore, relying on self-managed infrastructure introduces single points of failure and necessitates robust backup and disaster recovery strategies that are typically handled by managed service providers. The specific context of a solo founder with a defined set of workflows makes this migration feasible, but it may not directly translate to teams with complex, high-availability automation requirements or those lacking dedicated DevOps expertise.

LANDING

The shift from operation-based pricing to execution-based models, particularly through self-hosting, offers a clear path to significant cost reduction for founders. This specific migration demonstrates that substantial savings are achievable, provided the operational overhead of self-management is fully understood and accounted for. The decision to self-host ultimately hinges on a founder's technical capacity, the criticality of their automation workflows, and their willingness to trade direct financial cost for increased operational responsibility.

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