Sf Governor Limits

Apex Governor Limits

When to use

• Writing or reviewing any trigger, trigger handler, batch, queueable, future or scheduled class.
• A run failed with System.LimitException, Apex CPU time limit exceeded, or Apex heap size too large.
• Sizing a bulk job: deciding batch scope, chunking a load, or choosing sync versus async.
• Wave 1 and wave 2 of the vibe-force workflow: sf-apex-engineer sizes the work against these numbers, sf-quality-gate reads the Code Analyzer findings that map to them.

All numbers below come from the Apex Developer Guide for Summer '26 / API version 67.0, the version pinned in config/vibe-force.defaults.json. Limits are per transaction unless the table says otherwise.

The numbers you must know by heart

Scheduled Apex is asynchronous but synchronous limits apply to it. For Bulk API and Bulk API 2.0 transactions the effective limit is the higher of the two columns.

The full tables - certified managed package and cross-namespace limits, platform limits, static limits, size-specific limits, miscellaneous limits, email limits - are in references/limit-tables.md.

What counts, and what does not

That "not CPU time" row is the one people get wrong. A slow query does not burn CPU time; a loop over its results does.

Core patterns

1. One DML per collection, never one per record

public with sharing class LineItemUpdater {
    public static void markHighVolume(List<Line_Item__c> items) {
        List<Line_Item__c> toUpdate = new List<Line_Item__c>();
        for (Line_Item__c li : items) {
            if (li.Units_Sold__c > 10) {
                li.Description__c = 'New description';
                toUpdate.add(li);
            }
        }
        if (!toUpdate.isEmpty()) {
            update as user toUpdate;
        }
    }
}

The if (!toUpdate.isEmpty()) guard is not decoration. An empty-list DML still consumes one of the 150 statements.

2. Query once, key by Id, look up in the loop

public with sharing class InvoiceRollup {
    public static void apply(List<Invoice_Statement__c> invoices) {
        Map<Id, Invoice_Statement__c> byId = new Map<Id, Invoice_Statement__c>(invoices);

        Map<Id, Decimal> totals = new Map<Id, Decimal>();
        for (AggregateResult ar : [
            SELECT Invoice_Statement__c inv, SUM(Value__c) total
            FROM Line_Item__c
            WHERE Invoice_Statement__c IN :byId.keySet()
            WITH USER_MODE
            GROUP BY Invoice_Statement__c
        ]) {
            totals.put((Id) ar.get('inv'), (Decimal) ar.get('total'));
        }

        for (Invoice_Statement__c inv : invoices) {
            inv.Total__c = totals.containsKey(inv.Id) ? totals.get(inv.Id) : 0;
        }
    }
}

One query, one map, no query inside the loop. GROUP BY moves the arithmetic into the database, where it costs no CPU time and no heap.

3. SOQL for loop when the result set is large

public with sharing class ContactSweeper {
    public static void touchAll(Id accountId) {
        List<Contact> batch = new List<Contact>();
        for (List<Contact> chunk : [
            SELECT Id, Description
            FROM Contact
            WHERE AccountId = :accountId
            WITH USER_MODE
        ]) {
            for (Contact c : chunk) {
                c.Description = 'swept';
                batch.add(c);
            }
            update as user batch;
            batch.clear();
        }
    }
}

The list form of the SOQL for loop hands you 200 records at a time and lets the previous chunk be garbage collected. That is the difference between 6 MB of heap and a LimitException. The single-sObject form (for (Contact c : [SELECT ...])) also chunks internally at 200.

4. Batch Apex when 50,000 rows is not enough

public with sharing class ExpireQuotesBatch implements Database.Batchable<SObject> {
    public Database.QueryLocator start(Database.BatchableContext ctx) {
        return Database.getQueryLocator([
            SELECT Id, Status__c FROM Quote__c WHERE Expires_On__c < TODAY AND Status__c != 'Expired'
        ]);
    }

    public void execute(Database.BatchableContext ctx, List<Quote__c> scope) {
        for (Quote__c q : scope) {
            q.Status__c = 'Expired';
        }
        update as system scope;
    }

    public void finish(Database.BatchableContext ctx) {}
}

Database.QueryLocator in start returns up to 50 million records, and the per-transaction limits reset for every execute call. That reset is the whole point of Batch Apex. Note that Database.getQueryLocator called as an ordinary method inside a transaction is capped at 10,000 records instead - the 50 million figure applies to the start method of a batch job.

Pick the scope size deliberately: Database.executeBatch(new ExpireQuotesBatch(), 100) when each record is expensive, the default 200 otherwise. Smaller scope means more executions, and executions count against the daily async limit.

5. Measure, do not guess

System.debug(LoggingLevel.INFO, 'SOQL ' + Limits.getQueries() + '/' + Limits.getLimitQueries());
System.debug(LoggingLevel.INFO, 'DML ' + Limits.getDmlStatements() + '/' + Limits.getLimitDmlStatements());
System.debug(LoggingLevel.INFO, 'Rows ' + Limits.getQueryRows() + '/' + Limits.getLimitQueryRows());
System.debug(LoggingLevel.INFO, 'Heap ' + Limits.getHeapSize() + '/' + Limits.getLimitHeapSize());
System.debug(LoggingLevel.INFO, 'CPU ' + Limits.getCpuTime() + '/' + Limits.getLimitCpuTime());

Every consumption method getX() has a ceiling twin getLimitX(). The full list is in references/limits-class-api.md.

6. Assert the budget in a test

@IsTest
private class InvoiceRollupTest {
    @IsTest
    static void rollupIsBulkSafe() {
        List<Invoice_Statement__c> invoices = TestDataFactory.invoices(200);
        insert invoices;

        Test.startTest();
        Integer queriesBefore = Limits.getQueries();
        InvoiceRollup.apply(invoices);
        Integer used = Limits.getQueries() - queriesBefore;
        Test.stopTest();

        Assert.isTrue(used <= 2, 'Rollup must stay at 2 queries for any volume, used ' + used);
    }
}

Test.startTest() resets the governor limits once per test method and gives the code under test a fresh budget; Test.stopTest() restores the test context and forces queued async work to run. Limits apply individually to each test method. A test that asserts a constant query count for a 200-record input is the only reliable proof that code is bulk safe - coverage percentage proves nothing about limits.

7. Check org-level capacity before starting a big job

Map<String, System.OrgLimit> limits = OrgLimits.getMap();
System.OrgLimit async = limits.get('DailyAsyncApexExecutions');
System.debug(async.getValue() + ' of ' + async.getLimit() + ' async executions used today');

Batch Apex pre-checks the required async capacity when Database.executeBatch is called. If the job needs more executions than remain in the rolling 24-hour window, it throws before it starts and the remaining allowance is left unchanged.

Anti-patterns

DML inside a loop

// wrong - 151st record throws
for (Line_Item__c li : liList) {
    li.Description__c = 'New description';
    update li;
}

Fix: collect into a list, one update after the loop (pattern 1).

SOQL inside a loop

// wrong - one query per iteration
for (Invoice_Statement__c inv : Trigger.new) {
    List<Line_Item__c> items = [SELECT Id FROM Line_Item__c WHERE Invoice_Statement__c = :inv.Id];
}

Fix: one query with IN :ids, results keyed into a Map (pattern 2). Code Analyzer reports this as DbInLoop (Flow) and as the SOQL-in-loop Apex rules; vf-check analyzer fails on it.

Holding every record in one list

// wrong - 50,000 fat records will not fit in 6 MB
List<Contact> all = [SELECT Id, Description, Big_Text__c FROM Contact];
for (Contact c : all) { ... }

Fix: a SOQL for loop (pattern 3), fewer fields in the SELECT, or Batch Apex (pattern 4). Querying only the fields you use is the cheapest heap fix there is.

Nested loops over two collections

// wrong - 200 x 200 = 40,000 iterations of body, CPU time dies
for (Account a : accounts) {
    for (Contact c : contacts) {
        if (c.AccountId == a.Id) { ... }
    }
}

Fix: build a Map<Id, List<Contact>> once, then a single loop. CPU time is the limit that bulkification alone does not fix - algorithmic shape does.

Calling Limits.getHeapSize() inside a loop

Code Analyzer flags this as its own rule. The call itself is cheap but doing it per iteration is noise; sample it once before and once after the loop.

Recursive trigger without a guard

Stack depth for recursive trigger-firing DML is 16, and a trigger that updates its own object can re-enter. Use a static Set<Id> of processed ids, or the bypass mechanism in skill sf-fflib-operations.

Assuming a certified managed package shares your budget

Certified managed packages get their own copy of most per-transaction limits. Non-certified packages do not - their usage counts against your org's limits. When a limit blows up in a transaction that touches managed code, find out which kind of package it is before you refactor your own code.

Verification

# Static detection of loop-bound SOQL/DML before anything runs
node "${CLAUDE_PLUGIN_ROOT}/scripts/checks/vf-check.mjs" analyzer --changed

# Run the Apex tests, including the bulk-safety assertions
node "${CLAUDE_PLUGIN_ROOT}/scripts/checks/vf-check.mjs" apex --target-org <alias>

# Limit consumption of a single operation, from the log
sf apex run --file scripts/apex/probe.apex --target-org <alias>
sf apex get log --number 1 --target-org <alias> | grep -E "LIMIT_USAGE_FOR_NS|CUMULATIVE_LIMIT_USAGE" -A 20

# Current org-level capacity
sf org list limits --target-org <alias>

The LIMIT_USAGE_FOR_NS block at the end of a debug log is the authoritative per-namespace consumption report for a transaction. Set the APEX_CODE category to FINEST and the SYSTEM category to at least FINE to get it - see skill sf-debugging-logs.

References

• references/limit-tables.md - every official limit table for API 67.0
• references/limits-class-api.md - Limits and OrgLimits methods
• references/remediation-playbook.md - symptom to fix, per limit

Sibling skills: sf-soql-sosl-optimization (selectivity, indexes, large data volumes), sf-async-apex-patterns (batch, queueable, future, platform events), sf-apex-development (trigger shape and order of execution), sf-apex-testing (test mechanics and coverage gates), sf-code-analyzer-quality (the rules that detect these statically), sf-debugging-logs (reading LIMIT_USAGE_FOR_NS), sf-data-management (loading volume without a transaction at all).

Source: Apex Developer Guide, "Execution Governors and Limits", Summer '26 / API 67.0 (atlas.en-us.262.0.apexcode.meta); Apex Reference Guide, Limits and OrgLimits classes.