The review board evaluates whether candidates can identify risks in a scenario, assess their probability and impact, and propose concrete mitigation strategies. Candidates who only address risks when prompted score lower than those who weave risk awareness throughout their architecture.
Risk Description Likelihood Impact Governor limit exceedance Automation or integration hits platform limits Medium High Performance degradation Slow queries, page load times with data growth High High Integration failure External system downtime, API changes Medium High Data migration errors Incomplete, duplicated, or corrupted data Medium High Security vulnerability FLS bypass, sharing model gaps, injection Low Critical Technical debt accumulation Shortcuts that compound over time High Medium Platform upgrade impact Salesforce releases breaking existing functionality Low Medium
Risk Description Likelihood Impact Key person dependency Single expert with no backup Medium High Stakeholder misalignment Business units with conflicting requirements Medium High Change resistance Users refusing to adopt new system Medium High Scope creep Requirements expanding beyond original scope High Medium Resource availability Team members pulled to other projects Medium Medium Vendor dependency AppExchange vendor acquired or sunset Low High Knowledge gaps Team lacks skills for chosen technology Medium Medium
Risk Description Likelihood Impact Data quality issues Dirty data causing automation failures High Medium Data volume growth Unexpected data growth exceeding storage Medium High Data loss Accidental deletion, failed migration Low Critical PII exposure Sensitive data visible to unauthorized users Low Critical Data silos Duplicate data across systems with no sync Medium Medium
Risk Description Likelihood Impact API version deprecation External system deprecates API version Medium High Message ordering Events processed out of order Medium Medium Data inconsistency Sync failures creating divergent data Medium High Rate limiting External system throttles API calls Medium Medium Authentication expiry Tokens, certificates, or credentials expire Medium High
This matrix helps prioritize risks and determine which require active mitigation vs monitoring.
Figure 1. Performance degradation sits in the top-right quadrant (high probability and high impact), making it the single risk most deserving of proactive architectural investment. Security vulnerabilities land in the contingency quadrant: catastrophic if they occur, but low probability with proper controls in place.
Quadrant Strategy Action High Probability, High Impact Mitigate Actively Invest in prevention. Design architecture to avoid this risk. Budget time and resources. Low Probability, High Impact Contingency Plan Have a documented response plan. Do not invest in prevention, but be prepared to respond. High Probability, Low Impact Monitor Closely Accept the risk but track it. Set thresholds for escalation. Low Probability, Low Impact Accept and Monitor Log the risk but do not invest resources. Review periodically.
Once a risk is identified, assess it, classify it, and assign a response strategy. This flow ensures consistent handling across the project.
Figure 2. Risks with changing probability must re-enter the scoring step rather than being reassigned a response directly. A risk that was medium last sprint may now be critical. CAB escalation on materialization ensures deployment decisions account for the active incident.
A risk register tracks risks throughout the project. In a CTA scenario, reference the risk register as part of governance.
Field Description Example Risk ID Unique identifier RISK-001 Category Technical, Organizational, Data, Integration Technical Description What could go wrong ”SOQL queries on Account may degrade with 10M+ records” Probability High, Medium, Low High Impact Critical, High, Medium, Low High Risk Score Probability x Impact (numeric) 9 (3 x 3) Mitigation Strategy What you will do to reduce probability or impact ”Implement skinny tables, selective indexes, archive records >5 years” Contingency Plan What you will do if the risk materializes ”Implement async processing, increase timeout, add caching layer” Owner Who is responsible for monitoring this risk Technical Architect Status Open, Mitigating, Closed, Materialized Mitigating Review Date When to next review this risk Every sprint retrospective
Risk Mitigation Contingency Query performance degradation Skinny tables, custom indexes, selective filters Implement caching, async processing Storage limit exceedance Data archival strategy, Big Objects Purchase additional storage, aggressive archival Data migration timeout Batch processing, parallel loads, off-hours Phased migration over multiple weekends Report performance Summary reporting objects, async reports CRM Analytics for complex reporting
Risk Mitigation Contingency Cross-cloud data inconsistency Event-driven sync, conflict resolution rules Manual reconciliation process, data steward role License cost overrun License optimization analysis, feature mapping Renegotiate license mix, consolidate users Integration complexity Middleware layer, standardized patterns Simplify to point-to-point for critical paths User adoption challenges Role-specific training, change champions Phased rollout, parallel running
Risk Mitigation Contingency Vendor acquisition/sunset Exit strategy for each package, data portability Build replacement with custom code Governor limit conflicts Limit budget allocation per package, monitoring Remove lowest-value package, optimize custom code Upgrade breaking changes Regression test suite, staging validation Version lock, coordinate with vendor Total cost escalation TCO model with annual review triggers Renegotiate or replace with custom build
Risk Mitigation Contingency Regulatory non-compliance Per-region compliance mapping, Shield encryption Region-specific org isolation Data residency violation Hyperforce region selection, data masking Separate orgs per jurisdiction Timezone/language issues Locale-aware development, i18n testing Region-specific customization layer Coordinated deployment complexity Release train model, feature flags Staggered regional releases
Present risks as a structured, proactive analysis, not as an afterthought.
Structure the discussion as:
Identify the top 3-5 risks specific to the scenario (not generic risks)
For each risk, state:
What the risk is and why it exists in this specific scenario
How likely it is and how severe the impact would be
What the architecture does to prevent it
What the fallback plan is if prevention fails
Connect risks to architecture decisions: “I chose middleware over point-to-point integration partly because it reduces the integration failure risk by providing retry logic and monitoring.”
CTA Risk Presentation Pattern
“The top risk I see in this scenario is [risk]. It’s likely because [reason specific to scenario]. If it materializes, the impact is [consequence]. My architecture mitigates this by [architectural decision]. As a contingency, [fallback plan].”
Audience Detail Level Format Frequency Steering Committee High-level, top 5 risks Dashboard, RAG status Monthly Project Team Detailed, all active risks Risk register Sprint review Technical Team Technical risks with actions Technical risk log Weekly standup CAB Deployment-specific risks Change request form Per deployment
Risk Area What to Monitor Alert Threshold Governor limits Apex CPU time, SOQL count per transaction >70% of limit Performance Page load time, query execution time >3 second page load Storage Data storage usage, file storage usage >80% capacity Integration Error rate, response time, queue depth >5% error rate API limits Daily API call consumption >70% of daily limit User adoption Login frequency, feature usage <50% expected adoption
Personal study notes for the Salesforce CTA exam. Content compiled from VJ's study notes, official Salesforce documentation, community sources, and online publicly available content, then organized and presented with AI assistance. Not affiliated with Salesforce. © 2025–2026 VJ Srivastava.