If you’ve ever had a critical batch job silently fail overnight only to discover the fallout during morning standup you already know the problem. ERP systems are no longer simple record-keeping tools. They are the operational backbone of your organization, running financial postings, supply chain updates, inventory syncs, and automated workflows around the clock. And when something goes wrong in that backbone, the ripple effects reach every corner of the business.

The question is no longer whether you need visibility into your ERP operations. The question is how deep that visibility needs to go.

The Gap Between Monitoring and Observability

There’s an important distinction that often gets lost in technical conversations: monitoring tells you that something happened. Observability tells you why.

For years, ERP teams have relied on basic monitoring dashboards showing job statuses, email alerts when something fails, and manual log reviews when things go sideways. That approach worked reasonably well when business processes were simpler and slower. But in today’s environment, where automated workflows run continuously and AI-driven agents are increasingly involved in operational decisions, basic monitoring just doesn’t cut it anymore.

Modern businesses need operational context. They need to understand not just that a job failed, but what the system looked like when it failed, what was running in parallel, whether resources were constrained, and how this failure connects to downstream business outcomes like delayed reports, inaccurate financials, or missed order deadlines.

That’s observability and it’s becoming a foundational requirement for any enterprise running Dynamics 365 ERP.

What’s Changed: Batch Telemetry Gets a Major Upgrade

Microsoft has significantly expanded the telemetry capabilities available within Dynamics 365 Finance and Supply Chain Management two of the most widely used enterprise modules in the ecosystem. These improvements bring a new level of insight into batch workload behavior that was simply not possible before.

For organizations working with us at Vaden Consultancy, this is a development worth paying close attention to.

The expanded telemetry now captures behavioral signals across the full lifecycle of batch job execution. This includes:

Job start and stop events not just a binary pass/fail record, but actual execution duration data. Now you can understand how long a job should take versus how long it actually took, and spot trends over time.

Failure details with execution context when a job fails, the telemetry captures information about the conditions surrounding that failure, including correlated log entries. This dramatically reduces the time engineers spend reconstructing what happened.

Throttling indicators these signals reveal when system load is creating contention between jobs, something that was previously very difficult to identify without deep manual investigation.

Thread availability data one of the most common and frustrating ERP problems is jobs that appear to be queued but never start. Thread starvation where available threads are fully consumed by competing workloads is now visible, letting teams address capacity issues before they cascade.

Queue depth metrics for organizations using Priority-Based Scheduling, this shows exactly how many tasks are waiting across queues at any point in time, providing a real-time window into scheduling pressure.

All of this telemetry flows into Azure Application Insights, a platform most IT teams are already familiar with. That means you can apply your existing dashboards, alerting rules, and KQL queries to this new data without rebuilding your monitoring stack from scratch.

Real Problems This Solves

To understand why this matters in practice, consider two scenarios we see frequently when working with enterprise clients.

Scenario One: High-priority jobs completing late

A manufacturing company runs overnight priority jobs for inventory costing and financial consolidation. These jobs are supposed to finish before the morning shift starts reviewing numbers. But increasingly, they’re finishing late or not at all by the time the finance team logs in.

With the expanded queue telemetry, the root cause becomes clear: lower-priority batch tasks are consuming thread capacity during the overnight window, causing the critical jobs to sit in queue long past their expected run time. Without this telemetry, diagnosing this required hours of manual log analysis. With it, the pattern surfaces in a dashboard query within minutes.

Scenario Two: Bank reconciliation jobs stuck in “Waiting” state

A finance team notices that their daily bank reconciliation jobs are sitting in a “Waiting” status for unusually long periods. Everything looks fine on the surface the jobs are queued, no errors are being thrown  but the work isn’t getting done.

Thread telemetry reveals the answer: threads are fully saturated by parallel workloads running at the same time. The reconciliation jobs are waiting for execution capacity that simply isn’t available. Armed with this insight, the team can properly right-size their AOS batch configuration and stagger workloads to prevent the bottleneck from recurring.

These aren’t edge cases. They’re the kinds of operational puzzles that cost enterprise teams enormous amounts of time every week and they’re now solvable with the right telemetry in place.

The Connection to AI-Assisted Operations

Here’s where this gets especially interesting for businesses thinking about where ERP operations are headed.

AI agents are beginning to play a real role in enterprise IT operations. Whether it’s automated anomaly detection, intelligent alerting, or AI-assisted root cause analysis, these capabilities all have one thing in common: they are only as good as the data they receive.

Low-quality signals produce low-quality insights. If your AI tools are working from incomplete or delayed telemetry, they’ll miss patterns, fire false alerts, and fail to surface the issues that actually matter. High-fidelity batch telemetry changes that equation.

With rich execution data flowing into Application Insights, organizations can establish performance baselines for their critical workloads — and then configure intelligent alerts that fire when behavior deviates from those baselines in meaningful ways. Instead of reacting to failures after they’ve already impacted business outcomes, teams can catch early warning signs and address them proactively.

For companies exploring agentic ERP capabilities  where AI agents increasingly handle monitoring, diagnosis, and even some remediation tasks  this observability foundation is not optional. It’s the prerequisite.

Getting Started: What You Actually Need to Do

If your organization is running Dynamics 365 Finance or Supply Chain Management and you haven’t yet integrated with Azure Application Insights, that’s the starting point. Microsoft provides comprehensive documentation on their monitoring and telemetry framework through Microsoft Learn, covering everything from initial configuration to advanced querying.

Once your environment is connected to Application Insights, enabling the expanded batch telemetry signals is straightforward it can be toggled on from within system administration settings. From there, the signals begin flowing into your Application Insights resource automatically.

For organizations that have already configured the integration, the expanded batch telemetry is an additive enhancement. You don’t need to rebuild your existing setup — you simply enable the new signals and extend your existing dashboards and alerts to incorporate the new data.

At Vaden Consultancy, we help organizations move through this process efficiently, from initial configuration through building out the monitoring dashboards and alerting logic that make the telemetry genuinely actionable.

Smarter Operations Start with Better Visibility

There’s a broader shift happening in how enterprise IT teams operate their ERP environments. The days of reactive troubleshooting — where problems are discovered only after they’ve already impacted the business are giving way to a proactive model built on continuous observability and intelligent automation.

Dynamics 365 Business Central and the broader Dynamics 365 product family are being built to support this shift. The expanded batch telemetry capabilities are a concrete example of that direction  giving IT professionals and system administrators the data they need to run their environments with greater confidence and less firefighting.

For businesses that depend on their ERP to deliver accurate, timely results, this isn’t just a technical improvement. It’s a competitive advantage. The organizations that build strong observability practices now will be the ones best positioned to benefit from AI-assisted operations as those capabilities mature.

If you’d like to understand how these capabilities apply to your specific Dynamics 365 environment, our team at Vaden Consultancy is ready to help you assess where you are and map out the right path forward.

Ready to take your ERP operations to the next level? Get in touch with our team today.