{"id":59252,"date":"2026-10-20T06:54:25","date_gmt":"2026-10-19T20:54:25","guid":{"rendered":"https:\/\/www.cloudproinc.com.au\/index.php\/2026\/10\/20\/building-a-tenant-wide-microsoft-foundry-model-operations-dashboard\/"},"modified":"2026-10-20T06:55:36","modified_gmt":"2026-10-19T20:55:36","slug":"building-a-tenant-wide-microsoft-foundry-model-operations-dashboard","status":"publish","type":"post","link":"https:\/\/www.cloudproinc.com.au\/index.php\/2026\/10\/20\/building-a-tenant-wide-microsoft-foundry-model-operations-dashboard\/","title":{"rendered":"Building a Tenant-Wide Microsoft Foundry Model Operations Dashboard"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">In this blog post Building a Tenant-Wide Microsoft Foundry Model Operations Dashboard we will show how to give technology leaders one clear view of AI cost, capacity, ownership and risk across Azure.<\/p>\n\n\n\n<!--more-->\n\n\n\n<p class=\"wp-block-paragraph\">The problem usually appears after the first few AI projects succeed. Different teams create Microsoft Foundry resources, deploy several models and run pilots across multiple Azure subscriptions. Before long, nobody can confidently explain what is running, who owns it, what it costs or whether it has enough capacity for Monday morning.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Microsoft Foundry is Microsoft\u2019s platform for building and operating AI applications, models and agents. It brings together services such as Azure OpenAI models, third-party models, agent tools, security controls and operational monitoring.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A tenant-wide dashboard sits above individual projects. It collects information from every Azure subscription the dashboard is authorised to read, then presents it through a shared Azure Workbook or Azure Managed Grafana dashboard.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Why the standard project view is not enough<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Foundry provides useful monitoring inside individual resources and projects. Azure also offers a consolidated view covering costs, usage, quota and alerts.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">However, CIOs often need a broader business view. They need to compare departments, identify unowned deployments, see which applications are approaching capacity and separate production spending from experiments.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Quota is particularly easy to misunderstand. It is the processing capacity available to a model, often measured in tokens per minute. Tokens are small pieces of text processed by the model. Quota is not a spending limit, and having more quota does not mean the business has approved more spending.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Quota scope can also differ by model and deployment type. Your dashboard should therefore record whether capacity is shared by subscription, region, model or deployment type rather than treating every model the same way.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">The technology behind the dashboard<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A practical dashboard normally combines five Microsoft services:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Azure Resource Graph<\/strong> creates an inventory of Foundry resources and model deployments across subscriptions.<\/li>\n<li><strong>Azure Monitor<\/strong> collects request volumes, token usage, response times, errors and other operational measurements.<\/li>\n<li><strong>Log Analytics<\/strong> stores detailed monitoring records so teams can investigate trends and incidents.<\/li>\n<li><strong>Microsoft Cost Management<\/strong> supplies actual charges, budgets and cost allocation data.<\/li>\n<li><strong>Azure Workbooks<\/strong> combines these sources into an interactive dashboard with filters for subscription, owner, environment, model and region.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">For larger environments, Cost Management exports can place detailed daily cost records into an Azure Storage account. This is generally more reliable than repeatedly requesting large volumes of billing data through an application interface.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Cost information is not immediate and may arrive several hours after usage occurs. The dashboard should clearly distinguish near-real-time operational usage from delayed billing figures.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What technology leaders should see first<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">1. Total cost and cost movement<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The first row should show month-to-date cost, forecast cost, budget variance and the largest increases. A CIO should be able to identify an unexpected spending change in seconds.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Break costs down by business unit, application, environment and owner. This requires consistent resource tags such as <code>CostCentre<\/code>, <code>Application<\/code>, <code>Environment<\/code> and <code>BusinessOwner<\/code>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2. Quota pressure and capacity risk<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Show the models approaching their capacity limits, recent throttling events and unused quota assigned to dormant deployments. Throttling means Azure temporarily rejects or slows requests because an application is sending more work than its allocated capacity supports.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This allows teams to move capacity, request an increase or optimise an application before users experience failures. Production workloads should use dedicated capacity planning rather than relying on temporary shared quota intended for testing.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">3. Usage and reliability<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Track requests, input and output tokens, errors, response times and model availability. These measurements reveal whether increased spending reflects genuine adoption, inefficient prompts or an application repeatedly retrying failed requests.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Model operations monitoring should not be confused with AI quality evaluation. The dashboard tells you whether a service is available, busy and expensive. The evaluation process covered in How to Monitor and Evaluate Microsoft Foundry Agents Safely determines whether its answers remain accurate, safe and useful.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">4. Ownership and governance gaps<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Every production deployment should have a named technical owner, business owner, cost centre, approved purpose and data classification. The dashboard should flag missing information rather than leaving someone to discover it during an audit or incident.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Useful governance warnings include public network access, missing diagnostic logging, old model versions, deployments without budgets and production resources using non-standard regions. Regional choices can affect privacy, availability and cost, as explained in Global Regional and Data Zone Deployments in Microsoft Foundry.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">5. Security posture<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The dashboard can also show critical Microsoft Defender for Cloud or Wiz findings associated with Foundry resources. Examples include overly broad access, exposed endpoints and missing network restrictions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This does not automatically make an organisation compliant with Essential Eight, the Australian Government\u2019s baseline cybersecurity framework. It does provide evidence for access control, logging, accountability and regular security review.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Start by building a reliable inventory<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Azure Resource Graph can find model deployments across every subscription available to the person or managed identity running the query. The following simplified query provides a useful starting point:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>resources\n| where type =~ &#39;microsoft.cognitiveservices\/accounts\/deployments&#39;\n| extend AccountName = tostring(split(name, &#39;\/&#39;))\n| extend DeploymentName = tostring(split(name, &#39;\/&#39;))\n| extend ModelName = tostring\n| extend ModelVersion = tostring\n| extend ModelFormat = tostring\n| extend SkuName = tostring\n| extend Capacity = todouble\n| project subscriptionId, resourceGroup, location,\n AccountName, DeploymentName, ModelName,\n ModelVersion, ModelFormat, SkuName, Capacity, tags\n| order by subscriptionId asc, AccountName asc<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\">Resource naming and properties can vary between model types, so test the query against your own environment. Add joins to subscription and resource group information so the dashboard can display friendly business names instead of Azure identifiers.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Standardise data collection before designing charts<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A polished dashboard cannot repair inconsistent source data. Before building charts, establish a minimum operational standard for every Foundry resource.<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Apply mandatory ownership, cost and environment tags.<\/li>\n<li>Send diagnostic logs to approved Log Analytics workspaces.<\/li>\n<li>Enable operational alerts for errors, latency and capacity pressure.<\/li>\n<li>Create budgets for subscriptions, resource groups or AI cost centres.<\/li>\n<li>Assign read-only dashboard access using role-based access control, which determines who can view or change Azure resources.<\/li>\n<li>Document approved models, versions, deployment types and regions.<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">Be careful with centralised logs containing prompts or responses. These may include personal, confidential or commercially sensitive information. Collect only what is required, restrict access and align retention with Australian privacy obligations.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">A common 200-person business scenario<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Consider a 200-person professional services company with three AI pilots. Finance sees one growing Azure bill, while IT sees seven model deployments spread across development and production subscriptions.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A tenant-wide dashboard reveals that two unused test deployments are still active, one production application is close to its quota ceiling and several resources have no business owner. It also shows that a large share of token usage comes from repeated prompts containing unnecessary document content.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The business can remove unused resources, shorten prompts and address the capacity problem before an outage. More importantly, management can connect AI spending to specific applications and business owners rather than treating it as an unexplained infrastructure charge.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Turn the dashboard into a management process<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A dashboard only creates value when someone acts on it. Assign owners for cost, capacity, security and model lifecycle decisions, then schedule a short monthly review.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Use agreed thresholds such as 80 per cent quota utilisation, 20 per cent monthly cost growth or missing ownership tags. Alerts should create a clear action for a named person rather than sending another email to a shared mailbox.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The dashboard should also connect with your broader production governance model. Our guide to moving AI agents into production safely explains the approval and accountability controls that sit around this operational view.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">One dashboard creates one version of the truth<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A tenant-wide Microsoft Foundry operations dashboard gives CIOs a practical answer to four questions: what is running, what does it cost, will it cope with demand and who is accountable?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">CloudProInc brings more than 20 years of enterprise IT experience to this work. As a Melbourne-based Microsoft Partner and Wiz Security Integrator, we build hands-on Azure, Foundry, Defender and Wiz reporting that technology teams can operate after the engagement ends.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If your AI deployments are growing faster than your ability to track them, we are happy to review your current cost, quota and governance visibility and identify the gaps \u2014 no strings attached.<\/p>\n\n\n","protected":false},"excerpt":{"rendered":"<p>Combine cost, quota, usage and governance data in one Microsoft Foundry dashboard to prevent budget surprises, capacity problems and uncontrolled AI deployments.<\/p>\n","protected":false},"author":1,"featured_media":59254,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":true,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[21,13,124,115],"tags":[],"class_list":["post-59252","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-azure-monitor","category-blog","category-cloud-cost-finops","category-microsoft-ai-foundry"],"jetpack-related-posts":[{"id":57294,"url":"https:\/\/www.cloudproinc.com.au\/index.php\/2026\/10\/12\/microsoft-ai-foundry-hq-closes-the-gap-between-ai-experimentation-and-enterprise-grade-deployment\/","url_meta":{"origin":59252,"position":0},"title":"Microsoft AI Foundry HQ Closes the Gap Between AI Experimentation and Enterprise-Grade Deployment","author":"CPI Staff","date":"October 12, 2026","format":false,"excerpt":"Most Australian organisations have the same AI problem right now. 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