Optimizing Salesforce Performance: Practical Steps for Faster, More Reliable Orgs
Salesforce is a powerful platform, but as organizations grow, performance and maintainability can suffer. Focusing on data architecture, automation design, and release practices delivers the biggest gains. Below are practical steps that reduce latency, improve scalability, and keep admin and developer work sustainable.
Streamline your data model
– Archive or purge stale records to reduce table size and improve query performance. Implement retention policies for objects with rapid growth.
– Use skinny tables or custom indexes for frequently queried fields in very large tables. Test changes in a sandbox before deploying.
– Favor lookup relationships over master-detail where appropriate to avoid unnecessary cascades and sharing recalculations.
Make queries selective and efficient
– Ensure SOQL queries use indexed fields and selective filters. Avoid leading wildcards in LIKE clauses and expensive cross-object filters.
– Use LIMIT and selective WHERE clauses in list views, Apex, and integrations. For large data operations, rely on Bulk API or batch processing to prevent timeouts and governor limits.
– Monitor slow queries with the Query Plan Tool and Event Monitoring to identify bottlenecks.
Rethink automation and triggers
– Consolidate multiple triggers on the same object into a single handler framework to control execution order and reduce redundant queries.
– Prefer declarative automation (Flows) for straightforward use cases, but review runtime behavior regularly. Complex logic may still need optimized Apex with careful bulkification.
– Replace synchronous operations that run on critical user actions with asynchronous processing where acceptable — use queueable jobs, batch processing, or platform events to offload heavy work.
Reduce UI and page load times
– Minimize the number of related lists and formula fields shown on record pages; heavy page layouts cause more queries and rendering work.
– Use Lightning Component best practices: lazy loading for data, pagination for large lists, and client-side caching when possible.
– Review console components and record pages for embedded reports or charts that may trigger extra queries.
Governance, permissions, and sharing
– Simplify sharing models where feasible. Complex sharing rules and excessive manual shares increase recalculation times during bulk operations.
– Use permission set groups to reduce profile sprawl and keep security configuration easier to audit.
– Regularly run Health Check and Permission Analyzer to surface over-permissive access and potential security risks.
CI/CD and release management
– Adopt a source-driven development workflow with version control and automated testing to reduce regressions and deployment headaches.
– Automate deployments with Salesforce CLI and use scratch orgs or sandboxes for realistic testing of data volumes and integrations.
– Maintain a release calendar and change log so admins and integrators can coordinate schema changes and minimize downstream breakage.
Monitor proactively
– Use Salesforce Optimizer, Debug Logs, and event logs to identify inefficient customizations, unused fields, or excessive automation.
– Set up alerts for API usage spikes, long-running transactions, and storage thresholds to catch escalation early.
– Track key performance indicators like average page load time, batch job runtimes, and error rates after each release.
Small changes compound into major improvements.
Regular housekeeping, intentional automation design, and a mature release process reduce costs, speed up user workflows, and make growth predictable. Implement these steps iteratively: prioritize based on impact and measure results after each change to build a faster, more resilient Salesforce org.