Manufacturers in recent years are seeing a great increase in the complexity of their operations, both as the result of shifts in our global economy and rapidly changing technologies like AI. Has your ERP kept up? In this resource, we show you 10 meaningful ways that Dynamics 365 Finance & Supply Chain Management can help…

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In many manufacturing organizations, there’s a quiet assumption that certain people will always be there. They’re the ones who know how things work inside and out. When something doesn’t look right, they know where to go and often how to fix the problem without much discussion.  That kind of experience is valuable. But it’s also extremely risky.  When operational know-how lives mostly in people’s heads…

The post The Real Cost of Tribal Knowledge & Legacy ERP Systems for Manufacturing  appeared first on Ellipse Solutions.

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Manufacturing leaders don’t usually complain that their business is “too complex.” But what they do say is that things that feel like they should be simple are harder than they should be. Decisions that used to feel straightforward now require time consuming side conversations and pulling data from spreadsheets… not their ERP system. At times…

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Preparing for a manufacturing ERP implementation involves far more than selecting software. This interactive checklist helps manufacturers assess their readiness across the areas that have the greatest impact on project success, including cross-functional alignment, production planning, inventory management, data governance, and user adoption. Use it to help identify your implementation team, clarify team responsibilities, and…

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Join us for a practical discussion on how organizations can evaluate Microsoft Dynamics partners more effectively, whether you are planning a new implementation, reassessing an existing relationship, or looking to improve long-term operational outcomes and support models. Key Learning Objectives

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Most manufacturers are not struggling to capture data. Orders are entered, production is recorded, inventory moves, and financials are updated. The system is doing its job. But the problem shows up when someone needs a clear answer.  Some examples of this include  Too often, the answer involves exporting data or building another spreadsheet. In other…

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Power Automate has become the backbone for many business processes, integrations, and automation scenarios across the Power Platform ecosystem. From approval processes to large-scale integrations, organisations increasingly rely on cloud flows to power mission-critical workloads.

Although Power Automate provides a comprehensive monitoring experience, one limitation quickly becomes apparent in production environments: cloud flow execution history is retained for only 28 days by default.

For many organisations, this introduces several operational challenges:

• Historical execution data is automatically removed after 28 days
• Troubleshooting failures that occurred months ago becomes difficult
• Long-term trend analysis is not possible
• SLA monitoring and compliance reporting become challenging
• Teams often resort to manual exports before execution history expires

Initially, organisations attempt to overcome these limitations through manual exports, Power BI snapshots, or custom logging implementations. While these approaches provide temporary visibility, they often increase maintenance overhead and introduce fragmented monitoring experiences.

To address this challenge, Microsoft introduced Cloud Flow Run Metadata in Dataverse, allowing organisations to persist cloud flow execution information beyond the default retention period.

In this article, we’ll explore how to extend the default flow run retention period using FlowRunTimeToLiveInSeconds, retrieve Cloud Flow Run Metadata from Dataverse, and build a lightweight dashboard for monitoring flow health and execution success rates.

Approach

Rather than relying solely on the Power Automate portal for short-term diagnostics, we can leverage Cloud Flow Run Metadata stored in Dataverse to build a historical monitoring solution.

Our approach consists of three steps:

1. Inspect the current retention period.
2. Update FlowRunTimeToLiveInSeconds to extend run history retention.
3. Retrieve flow execution metadata and surface it within a custom dashboard.

The dashboard presented in this article intentionally focuses on four key operational metrics:

While simple by design, this dashboard serves as a foundation that organisations can later enhance with trend analysis, SLA reporting, execution duration insights, and failure analytics.

Understanding FlowRunTimeToLiveInSeconds

Power Platform exposes an organization-level setting named FlowRunTimeToLiveInSeconds, which controls how long Cloud Flow Run Metadata is retained.

By default, this value is:

2419200 seconds

Which corresponds to:

28 days

Before modifying this setting, we can retrieve the current value from the Organization table.

const response = await fetch( "/api/data/v9.2/organizations?$select=organizationid,flowruntimetoliveinseconds"
); const data = await response.json(); console.log(data.value[0]);

Example response:

{ "organizationid":"0423e7e6-374c-f111-b31d-6045bdaacfdb", "flowruntimetoliveinseconds":2419200
}

Extending Cloud Flow Retention

Once the Organization Id is available, the retention period can be updated using a PATCH request.

For example, the following updates the retention period to 14 days.

await fetch(`/api/data/v9.2/organizations(${orgId})`, { method: "PATCH", body: JSON.stringify({ flowruntimetoliveinseconds: 7776000 }) });

Organisations can select a retention period that aligns with their monitoring and reporting requirements.

Retrieving Cloud Flow Run Metadata

Once retention has been configured, we can go ahead and retrieve Cloud Flow Run Metadata available through the flowruns table.

For this dashboard, we only retrieve the fields required for reporting purposes.

const query = "flowruns?$select=workflowid,status,createdon,duration"; const response = await odata(query);

These columns provide enough information to calculate the dashboard metrics.

 Aggregating Flow Metrics

Rather than querying aggregate values individually, the dashboard computes metrics client-side after retrieving flow runs.

For example:

flowMap[wfId].total++; if (r.status === "Succeeded")
{
flowMap[wfId].success++;
}

Success percentage can then be derived using:

const rate = (success / total) * 100;

Failures are calculated as:

const failures = total - success;

This provides enough information to surface the four dashboard KPIs.

• Total Runs
• Successful Runs
• Failed Runs
• Success Rate

Building the Dashboard

To visualise Cloud Flow Run Metadata, we created a lightweight HTML web resource.

The dashboard displays Total Runs, Successful Runs, Failed Runs and Success Rates

along with a simple breakdown of individual cloud flows, including:

• Success percentage
• Average execution duration
• Number of failures
• Last execution date

Dashboard Output

Figure 1: Power Automate Flow Dashboard

Conclusion

Although Power Automate provides excellent short-term monitoring capabilities, the default 28-day retention period can become a limitation for organisations operating business-critical automations.

By leveraging FlowRunTimeToLiveInSeconds together with Cloud Flow Run Metadata stored in Dataverse, organisations can retain execution history for longer periods, simplify troubleshooting, and build monitoring experiences tailored to their operational requirements.

The dashboard presented in this article focuses on four essential metrics, but the same metadata can easily be extended to support:

• SLA monitoring
• Historical trend analysis
• Capacity planning
• Failure analytics
• Operational insights
• Enterprise-scale Power Platform governance

For organisations seeking deeper visibility into their automation landscape, Cloud Flow Run Metadata provides a practical foundation for long-term monitoring beyond the limitations of the Power Automate portal.

FAQs

What is the default run history retention period in Power Automate?
Power Automate retains cloud flow run history for 28 days by default. This is controlled by an organization-level setting called FlowRunTimeToLiveInSeconds, which is set to 2,419,200 seconds (28 days) out of the box.

Where is Cloud Flow Run Metadata stored?
Cloud Flow Run Metadata is stored in Dataverse, in a table called flowruns. Key columns include workflowid (the associated flow), status (Succeeded/Failed), createdon (execution timestamp), and duration (runtime).

Can I build a custom dashboard for Power Automate flow monitoring?
Yes. By querying the flowruns table in Dataverse, you can build a lightweight HTML web resource or Power BI dashboard that surfaces metrics like Total Runs, Successful Runs, Failed Runs, and Success Rate, calculated client-side from the retrieved run data.

What can Cloud Flow Run Metadata be used for beyond basic monitoring?
Beyond the four core KPIs, the same metadata can support SLA monitoring, historical trend analysis, capacity planning, failure analytics, and enterprise-scale Power Platform governance.

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ERP projects in manufacturing are often treated as a defining moment. A system is selected, a timeline is set, and the expectation is that the new platform will support everything from financials to production in one coordinated launch. That approach can introduce unnecessary strain across the organization and increase the likelihood of disruption during an…

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When manufacturers evaluate ERP systems, the conversation usually starts with functionality. Can the system manage production planning? Does it support inventory control, quality management, supply chain visibility, and shop floor operations? Can it scale across multiple plants or facilities?  Those are all important questions. But there is another factor that often receives far less attention, despite having a…

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Most ERP evaluations in manufacturing start the same way. Leadership teams focus on functionality, reporting, implementation timelines, and whether the system can support production, inventory, supply chain, and financial operations. They compare features, review demos, and evaluate whether the platform can meet today’s operational requirements. What often receives far less attention is a much quieter question…  What Happens…

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