flow-governor-limits-deep-dive
Compute and budget governor-limit consumption per Flow type with worked math: SOQL, DML rows, CPU time, heap. Includes per-entry-point budget tables, cross-automation shared-limit math, and tuning strategies when a flow hits a ceiling. NOT for general bulkification (use flow-bulkification). NOT for Apex limits (use apex-governor-limits).
Best use case
flow-governor-limits-deep-dive is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Compute and budget governor-limit consumption per Flow type with worked math: SOQL, DML rows, CPU time, heap. Includes per-entry-point budget tables, cross-automation shared-limit math, and tuning strategies when a flow hits a ceiling. NOT for general bulkification (use flow-bulkification). NOT for Apex limits (use apex-governor-limits).
Teams using flow-governor-limits-deep-dive should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/flow-governor-limits-deep-dive/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How flow-governor-limits-deep-dive Compares
| Feature / Agent | flow-governor-limits-deep-dive | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Compute and budget governor-limit consumption per Flow type with worked math: SOQL, DML rows, CPU time, heap. Includes per-entry-point budget tables, cross-automation shared-limit math, and tuning strategies when a flow hits a ceiling. NOT for general bulkification (use flow-bulkification). NOT for Apex limits (use apex-governor-limits).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Flow Governor Limits Deep Dive
## Core concept — limits are per-transaction, not per-flow
The platform enforces governor limits **per transaction**, not per flow. Two Before-Save flows on the same object share the transaction's SOQL budget. A flow running inside a triggered Apex context inherits the trigger's current consumption.
### Critical limits for flows
| Limit | Synchronous | Async | Shared across transaction |
|---|---|---|---|
| SOQL queries | 100 | 200 | Yes |
| SOQL rows | 50,000 | 50,000 | Yes |
| DML statements | 150 | 150 | Yes |
| DML rows | 10,000 | 10,000 | Yes |
| CPU time | 10,000 ms | 60,000 ms | Yes |
| Heap size | 6 MB | 12 MB | Yes |
| Callouts | 100 | 100 | Yes |
### Per-element cost approximation
| Flow element | SOQL | DML | Notes |
|---|---|---|---|
| Get Records | 1 per element | 0 | Rows count against 50,000 rows |
| Create Records | 0 | 1 per element | Rows count against 10,000 |
| Update Records | 0 | 1 per element | Rows count against 10,000 |
| Delete Records | 0 | 1 per element | Rows count against 10,000 |
| Loop | 0 | 0 | Depends on what's inside |
| Assignment | 0 | 0 | Free |
| Decision | 0 | 0 | Free |
| Subflow | Inherited | Inherited | Counts against parent transaction |
| Action (invocable Apex) | Varies | Varies | Apex action's own SOQL + DML add up |
**The key trap:** a Loop with a Get Records inside = 1 SOQL per loop iteration. 200 iterations = 200 SOQL = immediate limit breach.
## Recommended Workflow
1. **Enumerate every DML-class element** in the flow (Get, Create, Update, Delete, subflow, action).
2. **Map which elements are inside loops.** Loop + DML/SOQL inside is the #1 limit-breach pattern. Hoist outside the loop via collection-based DML.
3. **Account for shared limits.** If the flow runs on Account save, it shares the 100-SOQL budget with all other Account triggers, VRs, Before-Save flows, After-Save flows, and sharing recalculation.
4. **Run a budget check:** `(max_batch_size × per_record_cost) ≤ 0.7 × limit` — leave 30% headroom for other automations sharing the transaction.
5. **If budget is tight, tune:** hoist SOQL/DML out of loops, consolidate Get Records with OR-filters, cache field values, split work across transactions (Scheduled Paths, Platform Events).
6. **Pre-deployment benchmark.** In sandbox, exercise the flow with 200-record batches. Measure SOQL, DML, CPU via `Limits.getQueries()` wrapper in an Apex test.
## Key patterns
### Pattern 1 — Budget a record-triggered flow
Context: flow fires on Account update. Expected batch size: 200 records.
Elements:
- Get Records: related Contacts (1 SOQL, returns avg 5 Contacts per Account = 1000 rows).
- Loop over Contacts with Update Records inside. ← ALARM.
Un-tuned cost per batch:
- SOQL: 1 (Get Records outside loop)
- Contact Update: 1000 DML statements (1 per contact inside loop)
DML-statement limit: 150. Breach at the 150th Contact.
Tuned:
- Outside the loop, collect Contact updates into a collection variable.
- Single Update Records (collection) = 1 DML statement, 1000 DML rows.
Tuned cost: 1 SOQL + 1 DML, 1000 rows. Well under limits.
### Pattern 2 — Shared-transaction forecasting
Account trigger stack:
- Before-Save Validation (3 Get Records = 3 SOQL)
- Record-Triggered After-Save Flow A (2 Get Records + 1 Update = 2 SOQL + 1 DML)
- Record-Triggered After-Save Flow B (NEW — 4 Get Records + 1 Create = 4 SOQL + 1 DML)
- Existing Apex trigger (avg 15 SOQL + 3 DML per 200 records)
Total per 200-record batch: 24 SOQL + 5 DML (200 rows).
Available: 100 SOQL, 150 DML, 10,000 DML rows.
Headroom: 76 SOQL (OK).
Adding Flow B costs 4 SOQL + 1 DML from the shared pool. Fine here; if a fourth flow were to be added adding 10 more SOQL, the margin would shrink.
### Pattern 3 — Async offload
Same context but Flow B needs to do heavy enrichment (15 SOQL per record):
- Inline: 15 × 200 = 3000 SOQL. Breach.
- Async: mark Flow B's entry as "Run Asynchronously" (Scheduled Path +0 minutes). Fresh transaction per batch of 200 records; fresh 100-SOQL budget.
Trade-off: ~1-5 minute delivery delay, new-transaction idempotency requirement.
### Pattern 4 — CPU time tuning
Large loops with Assignments and Decisions consume CPU. Pattern that works in a 10-record test breaches at 200 records:
- Pre-compute lookups into a Map outside the loop (O(1) access inside).
- Avoid nested Loops; if you need Map-of-List shape, pre-compute outside.
- Move complex Formula evaluations out of inner Decisions.
CPU time is the hardest limit to diagnose — symptoms are timeouts, not explicit limit errors.
### Pattern 5 — Heap size management
Loop that accumulates all results into a big collection:
- 50,000 sObjects × avg 1 KB each = 50 MB. Heap limit breached at ~6 MB (async: 12 MB).
- Tuning: process in chunks via Scheduled Paths, or use a pass-through filter (transform + DML per chunk, don't accumulate).
## Bulk safety
This skill IS the bulk-safety math skill. Rules:
- Never DML inside a Loop.
- Never SOQL inside a Loop.
- Never accumulate unbounded results into a collection.
- Budget for shared transaction — don't assume the flow owns the whole 100 SOQL.
## Error handling
Limit exceptions terminate the transaction. Fault paths can't catch `System.LimitException` — the flow has already exceeded. The only recovery is:
- Reduce element consumption (bulkification).
- Split across transactions (async).
- Reduce batch size upstream (if caller is controllable).
## Well-Architected mapping
- **Performance** — budgeting limits is performance engineering. A flow with 70% limit headroom survives load spikes; a flow at 95% breaks under the first busy day.
- **Reliability** — shared-transaction math is what predicts cascading failures. Adding "one more flow" to a busy stack without budget analysis is the classic way orgs become fragile.
## Gotchas
See `references/gotchas.md`.
## Testing
```apex
@IsTest
static void testFlowStaysUnderLimits() {
// Prepare 200-record bulk scenario.
List<Account> accounts = new List<Account>();
for (Integer i = 0; i < 200; i++) {
accounts.add(new Account(Name = 'Test ' + i));
}
Test.startTest();
insert accounts;
Test.stopTest();
// Assert total transaction stayed under 0.7 × limits.
System.assertTrue(Limits.getQueries() < 70, 'SOQL budget exceeded');
System.assertTrue(Limits.getDMLStatements() < 105, 'DML budget exceeded');
}
```
## Official Sources Used
- Salesforce Developer — Execution Governors and Limits: https://developer.salesforce.com/docs/atlas.en-us.apexcode.meta/apexcode/apex_gov_limits.htm
- Salesforce Help — Flow Limits and Considerations: https://help.salesforce.com/s/articleView?id=sf.flow_considerations_limit.htm
- Salesforce Help — Trigger Order of Execution: https://developer.salesforce.com/docs/atlas.en-us.apexcode.meta/apexcode/apex_triggers_order_of_execution.htm
- Salesforce Architects — Performance Engineering: https://architect.salesforce.com/Related Skills
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