Handle Salesforce Apex governor limits proactively using Limits class checks and defensive coding patterns in bulk trigger contexts

In-depth guide

Steps

1. Call Limits.getQueries() and compare against Limits.getLimitQueries() (100) before issuing additional SOQL in a loop or utility method to detect limit approach
2. Use a LimitException try-catch pattern in non-critical callout paths so that a limit overflow degrades gracefully rather than rolling back the entire transaction
3. Pre-compute and cache SOQL results in static Map variables so repeated calls to the same utility method within a transaction reuse the cached data instead of issuing new queries
4. Replace heap-expensive operations (large string concatenations, nested lists) with streaming approaches or split processing into Queueable chains to stay under the 6 MB heap limit
5. For DML-heavy workflows, count pending DML rows before each operation with Limits.getDmlRows() versus Limits.getLimitDmlRows() (10 000) to avoid mid-batch failures
6. Log Limits consumption via a debug utility at the end of trigger execution during development so you see actual consumption trends across different batch sizes