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Understanding message consumption at the integration level can help you identify which integrations are driving usage and monitor your Oracle Integration billing more effectively.
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This guide shows how to view the number of billed messages consumed by each integration using the **Consumed Messages for Integration** metric.
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---
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## Prerequisites
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- Access to the Oracle Cloud Console
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- Permissions to view Oracle Integration metrics in OIC Monitoring
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<small><i>Check References section.</i></small>
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---
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## Step 1: Open the "Consumed Messages for Integration" Metric
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Navigate to your Oracle Integration Monitoring tab and locate the **Consumed Messages for Integration** metric.
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From the chart menu (โฎ), select **View query in Metrics Explorer**.
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### Why?
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This opens the metric query in Metrics Explorer, where you can customize how the data is displayed.
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---
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## Step 2: Edit the Metric Query
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In Metrics Explorer, click the query menu (โฎ) and select **Edit Query**.
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---
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## Step 3: Configure the Query
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On the **Edit Query** page:
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- Set **Statistic** to **Sum**
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- Ensure **Aggregate metric streams** is **unchecked**
> **Important:** Disabling aggregation allows Oracle Integration to display metrics separately for each integration instead of combining all integrations into a single value.
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---
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## Step 4: Apply the Desired Time Range
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Select the date range you want to analyze.
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Examples:
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- Last 24 Hours
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- Last 7 Days
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- Last 30 Days
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- Custom Date Range
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After applying the filter, the chart will display billed message activity for individual integrations.
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---
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## Step 5: View the Data in Table Format
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From the chart options (โฎ), select **View in Table**.
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---
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## Step 6: Review Billed Messages Per Integration
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The table displays message consumption grouped by integration.
This provides a detailed breakdown of consumption for each integration during the selected time period.
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---
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## Summary
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To view billed message consumption per integration:
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1. Open **Consumed Messages for Integration**.
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2. Select **View query in Metrics Explorer**.
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3. Edit the query.
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4. Set **Statistic = Sum**.
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5. Uncheck **Aggregate metric streams**.
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6. Apply the desired date range.
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7. Select **View in Table**.
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8. Review the billed message counts for each integration.
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Using this approach provides a clear view of Oracle Integration message consumption at the integration level, making it easier to monitor usage and understand billing trends.
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@@ -46,10 +46,8 @@ This section contains various examples related to Application Integration: demo
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โ OCI Language for real-time sentiment analysis of customer interactions
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โ OCI Speech for converting speech to text in automated workflows
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โ Human-in-the-loop escalation
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โ OCI Generative AI for dynamic AI-powered content generation
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โ Native Actions in OIC to orchestrate end-to-end intelligent automation
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โ Exposing Integrations as AI-callable tools with MCP Server in OIC
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The focus is on practical implementation patterns for AI-driven customer support scenarios, showing how quickly developers can bring AI capabilities directly into enterprise workflows.
@@ -59,7 +57,6 @@ This section contains various examples related to Application Integration: demo
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This session covers following key topic
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โ ๐๐ด๐ฒ๐ป๐๐ถ๐ฐ ๐๐ ๐๐ถ๐๐ต ๐ข๐ฟ๐ฎ๐ฐ๐น๐ฒ ๐๐ป๐๐ฒ๐ด๐ฟ๐ฎ๐๐ถ๐ผ๐ป โ How OIC fits into agentic architectures where AI agents reason, select tools, and invoke OIC flows to orchestrate real business processes.
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โ ๐๐ ๐ฝ๐ผ๐๐ฒ ๐๐ป๐๐ฒ๐ด๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐ ๐ฎ๐ ๐ ๐๐ฃ ๐ง๐ผ๐ผ๐น๐ โ Publishing OIC integrations as Model Context Protocol (MCP) endpoints โ discoverable, callable, and OAuth-secured for AI agents.
โ ๐ข๐๐ ๐๐ ๐๐ด๐ฒ๐ป๐ โ Building workflows where AI agents invoke multiple integrations to trigger, orchestrate, and enrich enterprise processes.
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โ ๐ฅ๐ฒ๐ฎ๐น-๐๐ผ๐ฟ๐น๐ฑ ๐๐ฒ๐บ๐ผ๐ โ Invoice automation using OCI Document Understanding & ERP Cloud, and Expense Report approval with human-in-the-loop workflows.
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If you're building new integrations or modernising existing ones, this session offers practical skills to design intelligent, scalable, and secure agentic solutions.
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## Blogs
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-[6 Hard Lessons From 3 Years of Shipping AI Workflows](https://www.linkedin.com/pulse/6-hard-lessons-from-3-years-shipping-ai-workflows-harris-qureshi-pzrlf/)
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Over the last 3 years, I've shipped AI workflows into production across multiple organizations and noticed a consistent pattern:
Organizations still need systems to connect, data to move, processes to orchestrate, and governance to ensure everything works reliably at scale.
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Whether the conversation is about APIs, microservices, SaaS integration, AI agents, the underlying challenge remains the same: making things work together.
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That recurring customer question inspired us to write this article
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-[How We Built an AI Agent on Top of Enterprise Systems](https://www.linkedin.com/pulse/how-we-built-ai-agent-top-enterprise-systems-harris-qureshi-ask2f/)
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