Debugging in Salesforce

 Debugging in Salesforce is not just reading logs — it’s understanding how the platform behaves behind the scenes.

Most performance issues, Flow faults, and trigger failures can be diagnosed quickly when you know what to look for.

Here’s a clean technical workflow for debugging Salesforce issues effectively:

1️⃣ Start With the Right Debug Log Levels

Set log levels for:

Apex Code → FINE

Workflow → FINER

Validation → FINER

System → INFO

This gives a complete view without overwhelming noise.

2️⃣ Identify Where the Transaction Broke

Look for:

FLOW_ELEMENT_ERROR

SOQL_EXECUTE spikes

FATAL_ERROR exceptions

DML_BEGIN followed by failure

EXCEPTION_THROWN

Most failures occur around a specific element or a DML boundary.

3️⃣ Trace CPU Time Consumption

The CPU line should be checked first, not last.

Watch for:

Nested loops

Too many Flow Decisions

Large collections

Repetitive queries

Subflow chaining

Anything causing CPU > 10,000ms will break the transaction.

4️⃣ Check for Unselective Queries

If you see high execution time at SOQL_EXECUTE_BEGIN, your query might not be selective.

Fix options:

Add indexed fields

Filter on Low-Cardinality fields

Reduce OR conditions

Limit returned fields

5️⃣ Analyze Automation Chain Conflicts

Most debugging problems come from multiple automations firing at once:

Record-Triggered Flows

Apex Triggers

Validation Rules

Process Builders

Workflow Rules

Consolidate logic → simplify debugging → reduce execution time.

6️⃣ Use Debug Mode for Flow

In Flow Debug mode:

Watch element-by-element execution

Check variable values

Identify which path misbehaves

Validate your loop logic in real time

7️⃣ Check Integration Logs

When APIs are involved:

Validate Named Credentials

Inspect request/response payload

Check callout order

Look for retries or timeouts

Confirm authentication headers

This avoids misdiagnosing integration failures as Apex or Flow issues.

8️⃣ Reproduce With Bulk Data

A solution that passes with one record may fail with 500.
Always test with:

Bulk inserts

Mass updates

Data Loader samples

Full/partial sandbox datasets

Bulk testing reveals real production behavior.

Final Thought:

Debugging isn’t just about finding errors — it’s about understanding how Salesforce processes data, automation, and limits in one unified transaction.

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Salesforce Debugging: A Platform-Level Strategy

Debugging in Salesforce is not just reading log lines — it’s interpreting how the platform allocates CPU, memory, automation context, and transaction state.

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1️⃣ Use Smart Log Level Configuration

Set focused visibility without noise:

Component	Level
Apex Code	FINE
Workflow/Flow	FINER
Validation	FINER
System	INFO

This produces actionable logs while avoiding heap-filling debug spam.

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2️⃣ Locate the Breakpoint in the Transaction

Look specifically for:

• FLOW_ELEMENT_ERROR

• SOQL_EXECUTE_BEGIN / SOQL_EXECUTE_END spikes

• EXCEPTION_THROWN

• FATAL_ERROR

• DML_BEGIN immediately followed by rollback

Errors almost always cluster around DML or Flow decision junctions.

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3️⃣ CPU Profiling Comes First, Not Last

Common CPU killers:

• Recursion (Trigger → Flow → Trigger)

• Subflow chaining

• Loops with SOQL/DML

• 10,000+ record collection operations

• Flows configured like procedural code

• Excessive invocable calls in orchestrations

Rule: If CPU ~ 8,000–10,000ms → solution redesign required, not patching.

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4️⃣ Detect Query Selectivity Failures

Long SOQL runtime usually means:

• Missing index usage

• OR-based filters

• Text fields instead of Id/Lookup filters

• Too broad data scope (e.g., CreatedDate > LAST_N_YEARS:20)

Fix with:

• Custom index

• Skinny tables (rare case)

• Deterministic WHERE filters

• Avoiding != and NOT IN conditions

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5️⃣ Break Down the Automation Collision

Most failures = automation stacking:

Layer	Impact
Record-Triggered Flows	recursion & CPU
Triggers	hidden loops
Process Builder	legacy slowdown
Workflow	duplicated DML

Merge logic to a single controller (usually Flow + Apex invocables).

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6️⃣ Debug Flows Visually

Flow Debugger lets you:

• Inspect path routing

• Validate loop counts

• Track variable mutation

• Check paused/wait events

• Confirm entry vs scheduled execution divergence

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7️⃣ Integration Checkpoints

If logs show callouts:

• Validate Named Credential trust

• Inspect HTTP payload instead of Apex variables

• Verify retry logic and remote timeout settings

• Track callout order (callouts block DML)

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8️⃣ Simulate Real Production Load

Never approve a fix until tested in bulk:

• 200–2000 record batch runs

• Async queue + scheduled flow combinations

• API batch inserts

• Full sandbox datasets

If your solution passes 1 record but fails bulk → it’s not a solution.

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💡 Summary

Debugging means recognizing where in the transaction the platform pushes back:

• CPU ceiling

• SOQL selectivity

• Flow orchestration loops

• Multi-automation collisions

• Integration timing

Master the platform behaviors, not just error messages.