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Salesforce governor limits, checked before they bite
Governor limits are Salesforce's way of protecting a multi-tenant platform: caps on SOQL queries per transaction, DML rows, CPU time, heap size, callouts, and dozens more. They're well documented — and still one of the most common causes of production incidents, because designs that work perfectly with test data collapse at real-world volume.
The pattern is familiar to anyone who has run a Salesforce org at scale: a trigger that behaves with 10 records hits the 'Too many SOQL queries: 101' wall during a data load; a nightly integration works for months and then fails when the business doubles; a Flow built by a well-meaning admin loops into CPU timeout. By the time these surface, they're production emergencies instead of design decisions.
This tool reviews your use case before you build it. Describe the scenario, transaction volume, integration count, and user count, and it returns an overall risk level, the specific governor limits your design is most likely to hit, mitigation patterns for each, and monitoring recommendations — so limit-awareness happens in the design review, not the incident retro.
Governance & Limits Checker
Identify Salesforce governor limit risks in your design before they become production incidents.
🔒 Describe scenarios in general terms — please don't include confidential client names or personal data.
The limits that cause the most incidents
- →SOQL queries per transaction (100 sync / 200 async) — almost always a query inside a loop.
- →DML rows per transaction (10,000) — bulk loads and cascading automation.
- →CPU time (10s sync / 60s async) — heavy Flow and Apex logic on high-volume objects.
- →Heap size (6MB / 12MB) — processing large files or query results in memory.
- →API requests per 24 hours — chatty integrations polling instead of using events.
How it works
Describe what you're building and the volumes involved. The tool maps your scenario against the current limits, rates the overall risk, and — most usefully — recommends the design patterns that avoid each risk: bulkification, asynchronous processing, Platform Events instead of polling, batch Apex for volume, and selective queries with proper indexing.
When to run a limits check
At design time for any high-volume object or integration, before promising a customer that an architecture will scale, and when reviewing an existing org that's showing symptoms — slow triggers, intermittent flow errors, or integration retries. Ten minutes here routinely saves a rearchitecture later.
Frequently asked questions
What are governor limits in Salesforce?
Runtime caps Salesforce enforces per transaction and per org — on SOQL queries, DML operations, CPU time, heap size, callouts, and API requests — to keep the multi-tenant platform stable. Exceeding one throws an uncatchable exception that rolls back the transaction.
How do I avoid hitting governor limits?
The core patterns: bulkify all triggers and Flows, never query or perform DML inside loops, move heavy processing to asynchronous contexts (Batch, Queueable, Platform Events), and design integrations around events rather than polling. This tool tells you which patterns matter for your specific scenario.
Does this replace a technical architecture review?
No — it's a fast first pass that catches the common risks and gives your review a structured starting point. Validate the output against your org's specifics before finalizing a design.
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