Real-Time Org Limit Analyzer

• API limits, email allocations, and async job ceilings are silently approached with no advance warning to the admin team.
• Native Setup limit pages require manual checking — there is no built-in mechanism to alert admins before a limit is reached.
• When a limit is breached, integrations stop firing, automations fail, and end users are impacted without any visibility into why.
• Storage and platform event limits grow gradually — teams discover them too late to take preventive action.
• There is no built-in record of historical limit consumption, making it impossible to identify trends or forecast when limits will be reached.

Step 1 — Snapshot captured for every monitored limit

OrgLimitsService reads every available System.OrgLimit on each scheduled run, maps each to a business category (API, Email, Storage, or Org), calculates remaining value, percentage used, and health status, then writes a Limit_Snapshot__c record for every limit on every run — powering historical trend charts on the dashboard.

Step 2 — Thresholds evaluated and alerts opened or updated

LimitAlertService compares current utilization against four threshold tiers. For each breached limit, existing alerts are refreshed in place if severity is unchanged, stale alerts are auto-resolved and replaced when severity escalates, and alerts are automatically resolved when usage returns to healthy levels — ensuring only one active alert exists per limit at any time.

Step 3 — AI recommendation generated for every new alert

Every new alert triggers an immediate callout via Named Credential to OpenAI GPT-4o through OpenAILimitRecommendationService. A structured prompt — containing the limit name, category, percentage used, and status — returns four sections: root cause, business impact, recommended action, and prevention steps. If the AI callout fails, a fallback recommendation is applied automatically so alert creation is never blocked.

Step 4 — Alerts auto-resolved when usage returns to healthy levels

When utilization drops below the CAUTION threshold, Is_Resolved__c is set and Resolved_At__c is populated automatically. Only one active alert per limit exists at any time — resolved alerts are never reopened; a new one is created if the limit rises again.

Every available System.OrgLimit is read on each run and mapped to one of four business categories. Any limit not explicitly mapped defaults to the Org category — ensuring no limit goes unmonitored as Salesforce adds new platform limits over time.

Functional flow: from scheduled snapshot capture through threshold evaluation, AI recommendation generation, and auto-resolution of alerts.

The Real-Time Org Limit Analyzer is an AI-powered solution built natively on Salesforce. The system autonomously runs end-to-end — continuously monitoring every governor limit across the org, evaluating consumption against tiered thresholds, generating AI-powered remediation guidance, and surfacing live health status to administrators — rather than waiting for manual checks or reacting after a limit has already been breached.

Each capability is delivered through Salesforce technologies as follows:

• Automated Limit Snapshot Capture: On every scheduled run, OrgLimitsService reads every available System.OrgLimit, maps it to a business category (API, Email, Storage, or Org), and calculates remaining value, percentage used, and health status. A Limit_Snapshot__c record is written for every limit on every run, powering historical trend charts on the dashboard.
• Threshold Evaluation & Alert Lifecycle Management: LimitAlertService compares current utilization against four threshold tiers (CRITICAL ≥ 90%, WARNING ≥ 75%, CAUTION ≥ 50%, OK < 50%). For each breached limit, existing alerts are refreshed in place if severity is unchanged, stale alerts are auto-resolved and replaced when severity escalates, and alerts are automatically resolved when usage returns to healthy levels — ensuring only one active alert exists per limit at any time.
• AI Remediation Generation: Every new alert triggers an immediate callout via Named Credential to OpenAI GPT-4o through OpenAILimitRecommendationService. A structured prompt — containing the limit name, category, percentage used, and status — returns four sections: root cause, business impact, recommended action, and prevention steps. If the AI callout fails, a fallback recommendation is applied automatically so alert creation is never blocked.
• Live Lightning Dashboard: A custom Lightning Web Component surfaces current limit status, historical trend charts, and all active alerts in a single embeddable screen. Summary cards show CRITICAL, WARNING, and CAUTION counts at a glance; category tabs allow drill-down by API, Email, Storage, and Org; a utilization table with progress bars provides per-limit detail; and a Manual Refresh Now action supports on-demand checks between scheduled runs.
• Scheduled Orchestration & Data Housekeeping: The full pipeline runs automatically on a configured schedule (up to four times per hour) without any administrator trigger. Conflicting scheduled jobs are auto-aborted before re-registration to prevent duplicate runs, and Limit_Snapshot__c records are purged after 30 days to control storage growth.

Architecture principle: Deterministic Apex guarantees accurate limit reading, threshold evaluation, and alert record management for anything that directly reflects org health data; the AI layer via OpenAI GPT-4o handles contextual remediation language and actionable guidance per alert; and the scheduled orchestration layer makes the system truly proactive — running continuously on its own and surfacing risk before limits are breached, rather than waiting for an outage to prompt investigation.

Automated Scheduled Monitoring — No Manual Initiation

The monitoring cycle runs automatically on a configured schedule. There is no report to trigger, no dashboard to refresh manually, and no process to initiate. Each run captures, evaluates, and alerts without any administrator action.

• Scheduled at configured intervals — four times per hour or daily, configurable without code changes
• Every monitored limit captured and evaluated on every run
• Old jobs auto-aborted before re-registration — no duplicate or conflicting schedules
• Snapshot records purged after 30 days to control data storage growth

Intelligent Alert Lifecycle — Open, Update, and Auto-Resolve

Alert records are managed automatically through their full lifecycle. A limit can only have one active alert open at any time — the system resolves stale alerts, refreshes existing ones, and never creates duplicate noise.

• One active alert per limit at any time — no duplicate or stale records
• Alert refreshed in place when severity stays the same — no unnecessary record churn
• Old alert auto-resolved and new alert opened when severity level changes
• Alerts auto-resolved when usage returns below the CAUTION threshold

AI Remediation Per Alert — Root Cause and Action in Every Record

Every new alert record is enriched with an AI-generated recommendation covering root cause, business impact, the recommended action to take, and prevention steps. Admins receive actionable guidance immediately — no manual investigation required.

• Root cause: why this limit is being approached, specific to the limit category
• Impact: what will fail or be affected if the limit is breached
• Recommended action: the single most important step to take right now
• Prevention steps: changes to avoid the same situation in future cycles
• AI outage fallback: a generic recommendation is used if the callout fails — alert creation is never blocked

Live Lightning Dashboard — Full Org Health in One Screen

A custom Lightning Web Component dashboard surfaces current limit status, historical trends, and active alerts in a single screen — embeddable on any Lightning page or app home page.

• Summary cards: total limits monitored, CRITICAL/WARNING/CAUTION counts at a glance
• Category tabs: API, Email, Storage, and Org limits browsable separately
• Drill-down table with progress bars showing utilization percentage per limit
• Active alerts panel: all open alerts with severity, current usage, and AI recommendation
• Manual Refresh Now action for on-demand status checks between scheduled runs

The Real-Time Org Limit Analyzer shifts org limit management from a reactive, manual activity to a proactive, automated process — giving admins, architects, and leaders the visibility they need before limits affect users.

For Salesforce Administrators

• Receive proactive alerts at CAUTION, WARNING, and CRITICAL — not after a limit has already caused an outage
• Every alert includes an AI-generated root cause and recommended action — no manual investigation needed
• Active alerts auto-resolve when usage returns to healthy levels — no manual record cleanup
• Live dashboard gives an instant full-org health read from a single Lightning page

For Architects & Technical Leads

• Historical trend data shows how limit consumption is evolving — forecast capacity issues before they become incidents
• Four-category classification (API, Email, Storage, Org) makes triage faster and more targeted
• All limit snapshots and alerts stored as native Salesforce records — queryable, reportable, and dashboardable
• Named Credential authentication keeps OpenAI credentials secure — no API keys in code

For Operations & Business Leaders

• Integrations, automations, and email sends stay within limits — with enough warning to act before users are impacted
• No manual monitoring, no Setup page checks, and no reactive firefighting when limits are silently breached
• Scales automatically as the org grows — every new limit Salesforce introduces is monitored without configuration
• No additional Salesforce licensing required — runs on native platform capabilities