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Why do Salesforce reports become slower as data volume increases?
Report performance is tightly coupled to data volume and selectivity. As tables grow, filters that were once efficient may no longer be selective enough. Formula fields, cross-object filters, and roll-ups further increase processing time. Joined reports are particularly expensive because each blockRead more
Report performance is tightly coupled to data volume and selectivity. As tables grow, filters that were once efficient may no longer be selective enough. Formula fields, cross-object filters, and roll-ups further increase processing time.
Joined reports are particularly expensive because each block is processed independently and then combined. If each block scans large datasets, performance degrades rapidly.
Improving performance usually involves tightening filters, reducing unnecessary fields, and sometimes redesigning report types or archiving historical data.
See lessTakeaway: Report slowness is usually a data growth problem, not a reporting bug.
Why does Salesforce automation slow down record saves over time?
This slowdown is almost always caused by automation stacking rather than a single inefficient component. Each record save can trigger record-triggered Flows, Apex triggers, validation rules, roll-ups, and even downstream automation on related objects. Individually these may be lightweight, but togetRead more
This slowdown is almost always caused by automation stacking rather than a single inefficient component. Each record save can trigger record-triggered Flows, Apex triggers, validation rules, roll-ups, and even downstream automation on related objects. Individually these may be lightweight, but together they add measurable execution time.
The issue often worsens because automation is added incrementally. New Flows or triggers are created to handle edge cases without considering existing logic, so the same record may be updated multiple times in one transaction. This leads to repeated evaluations, recalculations, and re-entry into automation chains.
See lessWhy do Salesforce reports become unreliable as business logic grows?
Reports depend on underlying data consistency. As more automation modifies records at different times and in different contexts, the same fields can mean different things across records. Formula fields, roll-ups, and timing of updates further amplify this. Teams usually stabilize reporting by definiRead more
Reports depend on underlying data consistency. As more automation modifies records at different times and in different contexts, the same fields can mean different things across records. Formula fields, roll-ups, and timing of updates further amplify this.
Teams usually stabilize reporting by defining a single source of truth, simplifying formulas, and documenting how key metrics are derived.
See lessTakeaway: Reports reflect system design quality, not just reporting configuration.
Why do SOQL queries perform well early on but slow down later?
SOQL performance is heavily influenced by data distribution, selectivity, and query patterns. As tables grow, queries that were once selective may no longer be, especially if filters rely on non-indexed fields or skewed data. Complex WHERE clauses and large result sets also add overhead. Improving pRead more
SOQL performance is heavily influenced by data distribution, selectivity, and query patterns. As tables grow, queries that were once selective may no longer be, especially if filters rely on non-indexed fields or skewed data. Complex WHERE clauses and large result sets also add overhead.
Improving performance usually involves rewriting queries to be more selective, using indexed fields, reducing returned fields, and sometimes redesigning data models.
See lessTakeaway: SOQL performance problems usually reflect data growth, not bad syntax.
Why does Apex code hit governor limits even after basic bulkification?
Bulkification solves only the most obvious limit issues. Once data volumes grow, limits are often hit due to large heap usage, expensive logic inside loops, trigger recursion, or automation chains triggered by DML. Even a single bulk-safe update can cascade into multiple Flows, triggers, and processRead more
Bulkification solves only the most obvious limit issues. Once data volumes grow, limits are often hit due to large heap usage, expensive logic inside loops, trigger recursion, or automation chains triggered by DML. Even a single bulk-safe update can cascade into multiple Flows, triggers, and processes.
The usual fix is to reduce the total work done per transaction—filter records aggressively, avoid unnecessary field queries, and break work into asynchronous jobs when possible.
See lessTakeaway: Governor limits are about total work, not just where SOQL and DML are placed.