Introduction: Salesforce Well-Architected Returns
The Salesforce Well-Architected Framework is a set of best practices designed to help organizations build scalable, secure, and high-performing Salesforce implementations. As businesses increasingly rely on Salesforce for mission-critical operations, ensuring a well-architected system is crucial for long-term success.
In this blog, we’ll explore the latest Well-Architected Returns updates, key data modelling tips, and best practices to optimize your Salesforce org. Whether you’re an architect, admin, or developer, these insights will help you maximise efficiency and minimise technical debt.
Table of Contents
Introduction: Salesforce Well-Architected Returns1. Understanding the Salesforce Well-Architected Framework2. Latest News in Salesforce Well-Architected Returns3. Data Model Optimization Tips4. Security & Compliance Best Practices5. Performance Optimization Techniques6. Cost Optimization Strategies7. The Future and Trends for Salesforce ArchitectureConclusion
1. Understanding the Salesforce Well-Architected Framework
The Well-Architected Framework is built on six key pillars:
Operational Excellence: smooth deployments, monitoring, and incident response.
Security & Compliance – Protects data integrity and meets regulatory requirements.
Performance & Scalability – Optimises system speed and handles growth efficiently.
Reliability – Ensures high availability and disaster recovery.
Cost Optimization – Reduces unnecessary expenses in licensing and storage.
Sustainability – Minimises environmental impact through efficient resource usage.
Salesforce continuously updates this framework to align with evolving cloud architecture trends.
A. Health Check Tools
Salesforce has introduced improved health check dashboards that provide deeper insights into the following:
Security settings (e.g., password policies and session settings).
Performance bottlenecks (e.g., inefficient SOQL queries and workflow rules).
Compliance risks (e.g., GDPR and HIPAA alignment).
B. AI-Driven Recommendations
With Einstein AI, Salesforce now offers automated, well-architected recommendations, such as the following:
Unused custom fields that can be archived.
Duplicate processes that can be consolidated.
Optimised data storage to reduce costs.
C. New Integration Best Practices
Salesforce emphasises MuleSoft and Event-Driven Architectures (EDA) for seamless integrations. Key updates include:
Real-time event monitoring for better reliability.
API governance to prevent rate-limiting issues.
A well-designed data model is the backbone of a high-performing Salesforce org. Below are key strategies to optimize your data architecture.
A. Standard vs. Custom Objects
Leverage standard objects (accounts, contacts, and opportunities) whenever possible.
Use custom objects sparingly, only when business logic demands it.
B. Relationship Types: Master-Detail vs. Lookup
Master-Detail – Use when child records should cascade and delete with the parent.
Lookup – Use for optional relationships in which records should remain independent.
C. Indexing for Performance
Add custom indexes on frequently filtered fields (e.g., status, priority).
Avoid indexing fields with low selectivity (e.g., Boolean fields).
D. Archiving & Data Lifecycle Management
Use Big Objects for historical data (e.g., logs, audit trails).
Leverage Salesforce Data Archive to move stale records to cheaper storage.
E. Avoiding Data Skew
Account & user record skew can degrade performance.
Mitigation strategies:Use sharing rules instead of manual sharing.
Distribute workload across multiple owners.
A. Field-Level Security (FLS) & Object Permissions
Restrict access using profiles & permission sets.
Avoid “View All” and “Modify All” unless necessary.
B. Encryption & Data Masking
Use Shield Platform Encryption for sensitive data (PII, PCI).
Dynamic data masking hides sensitive information from unauthorised users.
C. Compliance Automation
Use the Compliance Center to track GDPR, CCPA, and other regulations.
Automate data retention policies to auto-delete expired records.
A. Query Optimization
Use selective SOQL queries (avoid SELECT *).
Leverage LIMIT and WHERE clauses to reduce data load.
B. Bulkification & Asynchronous Processing
Use Batch Apex for large data operations.
Queueable Apex is better for chained async jobs.
C. Caching Strategies
The platform cache reduces repeated calculations.
Lightning Data Service (LDS) minimises server calls in Lightning.
A. Storage Management
Archive unused files & records to reduce storage costs.
Monitor Data & File Storage in Setup > Company Information.
B. Licence Optimisation
Audit inactive users and downgrade licenses if possible.
Use permission sets instead of multiple profiles.
C. Automate Cost Tracking
Salesforce Optimiser identifies unused features.
Einstein Analytics predicts future storage needs.
A. Hyperforce & Multi-Cloud Deployments
Hyperforce enables flexible cloud deployments (AWS, Azure).
Multi-cloud strategies improve resilience.
B. AI & Predictive Analytics
Einstein GPT auto-generates well-architected recommendations.
Predictive scaling adjusts resources dynamically.
C. Low-Code & Pro-Code Balance
Use Flow for simple automations.
Apex for complex logic.
The return of Salesforce Well-Architected brings a renewed focus on building scalable, secure, and efficient solutions. With updated guidance and best practices, teams can better align architecture with business goals. Leveraging its data model validation tips ensures stronger governance and cleaner implementations.
Founder and CEO of iTechCloud Solution, a Salesforce consulting and product partner since 2017. He sets engagement strategy and stays the commercial owner of every account, working with clients across Salesforce, AI and data from the first call through to go-live.
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