feat(ultraplan-local): v1.6.0 — /ultraresearch-local deep research command

Add /ultraresearch-local for structured research combining local codebase analysis with external knowledge via parallel agent swarms. Produces research briefs with triangulation, confidence ratings, and source quality assessment. New command: /ultraresearch-local with modes --quick, --local, --external, --fg. New agents: research-orchestrator (opus), docs-researcher, community-researcher, security-researcher, contrarian-researcher, gemini-bridge (all sonnet). New template: research-brief-template.md. Integration: --research flag in /ultraplan-local accepts pre-built research briefs (up to 3), enriches the interview and exploration phases. Planning orchestrator cross-references brief findings during synthesis. Design principle: Context Engineering — right information to right agent at right time. Research briefs are structured artifacts in the pipeline: ultraresearch → brief → ultraplan --research → plan → ultraexecute. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-08 08:58:35 +02:00 · 2026-04-08 08:58:35 +02:00 · baa2d0220b
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+# Real-Time Streaming and Live Monitoring Dashboards
+
+**Last updated:** 2026-02
+**Status:** GA
+**Category:** Monitoring & Observability
+
+---
+
+## Introduksjon
+
+Real-time streaming og live monitoring er kritiske kapabiliteter for operasjonell overvåking av AI-applikasjoner i produksjon. Mens tradisjonell logging og metrics aggregeres over tid (typisk 1-5 minutter), tilbyr real-time løsninger innsikt med under ett sekunds latency, noe som er essensielt for debugging, incident response og operasjonell overvåking av AI-tjenester.
+
+Microsoft-stakken tilbyr to primære løsninger: **Application Insights Live Metrics** for sanntidsovervåking av applikasjonsytelse med 1-sekunds latency, og **Fabric Real-Time Intelligence** med Real-Time Dashboards for streaming analytics på tvers av multiple datakilder. Live Metrics er optimalisert for utviklere som trenger umiddelbar tilbakemelding under deployment og debugging, mens Real-Time Intelligence er bygget for operasjonelle scenarier som krever kontinuerlig overvåking av store datavolumer.
+
+Begge løsningene har ulike arkitekturer: Live Metrics bruker en dedikert push-basert control channel som streamer data direkte fra applikasjonen til portalen uten persistering, mens Real-Time Dashboards benytter Kusto Query Language (KQL) mot eventhouses eller Azure Data Explorer med refresh-intervaller ned til 10 sekunder.
+
+---
+
+## Kjernekomponenter
+
+### Application Insights Live Metrics
+
+| Komponent | Beskrivelse | Latency |
+|-----------|-------------|---------|
+| **Live Metrics Stream** | Push-basert streaming av telemetri fra app til portal | < 1 sekund |
+| **Custom Filters** | Real-time filtering på URL, duration, telemetry type | Real-time |
+| **Server Instance Filtering** | Isoler spesifikke server-instanser for debugging | Real-time |
+| **Performance Counters** | Windows performance counters (CPU, memory, requests) | < 1 sekund |
+| **Exception Stack Traces** | Full stack traces for exceptions når de skjer | Real-time |
+| **Control Channel** | Secure channel for filter-signaler (krever Entra ID auth) | N/A |
+
+**Støttede plattformer:**
+
+```csharp
+// ASP.NET Core - OpenTelemetry (anbefalt, enabled by default)
+builder.Services.AddOpenTelemetry().UseAzureMonitor(options => {
+    options.EnableLiveMetrics = true; // Default: true
+});
+
+// ASP.NET Core - Classic API (manual config)
+using Microsoft.ApplicationInsights.Extensibility.PerfCounterCollector.QuickPulse;
+
+var quickPulseProcessor = null;
+config.DefaultTelemetrySink.TelemetryProcessorChainBuilder
+    .Use((next) => {
+        quickPulseProcessor = new QuickPulseTelemetryProcessor(next);
+        return quickPulseProcessor;
+    })
+    .Build();
+
+var quickPulseModule = new QuickPulseTelemetryModule();
+quickPulseModule.Initialize(config);
+quickPulseModule.RegisterTelemetryProcessor(quickPulseProcessor);
+```
+
+**Nøkkelegenskaper:**
+
+- **On-demand streaming:** Data sendes KUN når Live Metrics-panen er åpen (spart kostnader)
+- **Ingen persistering:** Data vises kun i real-time, ikke lagret for historisk analyse
+- **Sampling:** Stack traces og exceptions samples, men alle metrics og counters sendes
+- **Gratis:** Ingen ekstra kostnad for Live Metrics data (kun standard ingestion)
+
+### Fabric Real-Time Intelligence & Real-Time Dashboards
+
+| Komponent | Beskrivelse | Refresh Rate |
+|-----------|-------------|--------------|
+| **Real-Time Dashboard** | No-code dashboard med KQL queries | 10 sekunder - manuell |
+| **Eventhouse** | Time-series optimalisert database for streaming data | Subsecond ingestion |
+| **Eventstream** | No-code streaming pipelines med transformasjoner | Near real-time |
+| **Data Activator** | Event detection med subsecond latency, trigger actions | < 1 sekund |
+| **Copilot for Dashboards** | AI-generert dashboard fra natural language prompts | N/A |
+
+**Støttede datakilder:**
+
+| Datakilde | Use Case | Latency |
+|-----------|----------|---------|
+| Eventhouse | Fabric-native streaming events | Subsecond |
+| Azure Data Explorer | Log og telemetry analytics | < 5 sekunder |
+| Application Insights | App performance metrics | 1-5 minutter* |
+| Log Analytics | Azure resource logs | 1-5 minutter* |
+
+*Application Insights og Log Analytics har inherent ingestion latency (1-5 min), men kan queries via Real-Time Dashboard.
+
+**KQL Query Eksempel (streaming dashboard):**
+
+```kusto
+// Real-time monitoring av AI request latency
+AIRequests
+| where timestamp > ago(5m)
+| summarize
+    AvgDuration = avg(duration),
+    P95Duration = percentile(duration, 95),
+    RequestCount = count()
+    by bin(timestamp, 10s), operation_Name
+| render timechart
+```
+
+**Auto-refresh konfigurasjon:**
+
+- Minimum refresh interval: **10 sekunder**
+- Anbefalt for high-volume scenarier: **30-60 sekunder** (reduserer compute cost)
+- Manual refresh: Alltid tilgjengelig for ad-hoc analyse
+
+---
+
+## Arkitekturmønstre
+
+### Mønster 1: Live Metrics for CI/CD Validation
+
+**Scenario:** Validere deployment i sanntid under release pipeline.
+
+**Arkitektur:**
+
+```
+Developer → Deploy til Azure → App starter → Live Metrics åpnes i portal
+                                             ↓
+                                    Monitor exceptions, latency, dependencies
+                                             ↓
+                                    Validate fix → Close Live Metrics (stop streaming)
+```
+
+**Fordeler:**
+- Umiddelbar feedback (< 1 sekund latency)
+- Ingen setup utover Application Insights instrumentation
+- Gratis (no-cost streaming)
+- Filter på spesifikk server instance under rolling deployment
+
+**Ulemper:**
+- Krever manuell observasjon (ingen alerting)
+- Data persisteres ikke (kun for live debugging)
+- Control channel må sikres med Entra ID for production (API keys deprecated Sept 2025)
+
+**Når bruke:**
+- Debugging av nye deployments
+- Load testing validation
+- Exception tracking under release
+- Server-specific performance issues
+
+### Mønster 2: Real-Time Dashboard for Operations
+
+**Scenario:** Kontinuerlig overvåking av AI-tjenester i produksjon med alerting.
+
+**Arkitektur:**
+
+```
+AI App → Application Insights → Eventhouse (via Eventstream)
+                                      ↓
+                              Real-Time Dashboard (10s refresh)
+                                      ↓
+                              Data Activator → Teams/Email Alert
+```
+
+**Fordeler:**
+- Persistent storage i Eventhouse (long-term analytics)
+- Proactive alerting via Data Activator
+- Multi-source dashboards (combine App Insights + Azure Monitor)
+- No-code dashboard creation med Copilot
+
+**Ulemper:**
+- Higher latency enn Live Metrics (10s min refresh)
+- Krever Fabric capacity (kostnader)
+- Mer kompleks setup (Eventstream pipeline)
+
+**Når bruke:**
+- Production operations med SLA requirements
+- Multi-service monitoring (microservices)
+- Compliance requirements (data retention)
+- Business stakeholder visibility (shareable dashboards)
+
+### Mønster 3: Hybrid - Live Metrics + Real-Time Dashboard
+
+**Scenario:** Kombinere ad-hoc debugging (Live Metrics) med persistent monitoring (Real-Time Dashboard).
+
+**Arkitektur:**
+
+```
+AI App → Application Insights ─┬→ Live Metrics (on-demand)
+                               └→ Eventhouse → Real-Time Dashboard
+                                                      ↓
+                                               Data Activator Alerts
+```
+
+**Fordeler:**
+- Best of both worlds: Live debugging + persistent monitoring
+- Cost-efficient (Live Metrics kun når åpen, dashboard alltid tilgjengelig)
+- Enkel escalation fra dashboard til Live Metrics for deep-dive
+
+**Ulemper:**
+- Dobbel ingestion (App Insights + Eventhouse) hvis begge brukes samtidig
+- Mer kompleks setup
+
+**Når bruke:**
+- Enterprise AI-løsninger med både dev og ops teams
+- Critical workloads som krever både proactive alerting og reactive debugging
+
+---
+
+## Beslutningsveiledning
+
+### Når bruke Live Metrics
+
+| Kriterium | Anbefaling |
+|-----------|------------|
+| **Use Case** | Debugging, deployment validation, load testing |
+| **Latency krav** | < 1 sekund |
+| **Data retention** | Ikke nødvendig (kun live view) |
+| **Alerting** | Ikke påkrevd (manuell observasjon OK) |
+| **Cost sensitivity** | Høy (gratis streaming) |
+| **Team** | Developers, DevOps |
+
+### Når bruke Real-Time Dashboard
+
+| Kriterium | Anbefaling |
+|-----------|------------|
+| **Use Case** | Operations monitoring, SLA tracking, compliance |
+| **Latency krav** | 10 sekunder - 1 minutt OK |
+| **Data retention** | Påkrevd (historisk analyse) |
+| **Alerting** | Kritisk (proactive incident response) |
+| **Multi-source** | Ja (combine App Insights + Azure Monitor + custom events) |
+| **Team** | Operations, business stakeholders |
+
+### Vanlige feil
+
+❌ **Bruke Live Metrics for production alerting**
+Live Metrics har ingen alerting-kapabilitet. Bruk Real-Time Dashboard med Data Activator.
+
+❌ **Åpne Live Metrics kontinuerlig i produksjon**
+Live Metrics streamer data kun når panen er åpen, men slutter ikke automatisk. Lukk etter debugging for å stoppe streaming overhead på app.
+
+❌ **Forvente persistering i Live Metrics**
+Data i Live Metrics discarderes når du lukker panen. Bruk Logs eller Metrics Explorer for historiske queries.
+
+❌ **Sette Real-Time Dashboard refresh til 10s for alle scenarier**
+Høyere refresh rate = høyere compute cost. Bruk 30-60s for most production dashboards, 10s kun for critical metrics.
+
+❌ **Bruke usecured control channel i production**
+API keys for Live Metrics retired Sept 2025. Migrer til Entra ID authentication.
+
+### Røde flagg
+
+🚩 **Live Metrics viser ingen data**
+- Sjekk firewall: Live Metrics bruker **separate endpoints** (`live.applicationinsights.azure.com`) enn vanlig telemetri
+- Verifiser TLS 1.2 support (Live Metrics krever TLS 1.2+)
+- Bekreftet at OpenTelemetry Distro er nyeste versjon (live metrics enabled by default)
+
+🚩 **Real-Time Dashboard viser gammel data (> 1 min latency)**
+- Application Insights har inherent ingestion latency (1-5 min). For true real-time, stream direkt til Eventhouse via Eventstream.
+
+🚩 **Data Activator trigger for ofte (false positives)**
+- Bruk anomaly detection functions i KQL (series_decompose_anomalies) for å detektere avvik fra baseline istedenfor statiske thresholds.
+
+---
+
+## Integrasjon med Microsoft-stakken
+
+### Azure OpenAI + Live Metrics
+
+```csharp
+// Track Azure OpenAI calls i Live Metrics
+var activity = new Activity("AzureOpenAI.ChatCompletion");
+activity.Start();
+
+try {
+    var response = await openAIClient.GetChatCompletionsAsync(deploymentName, options);
+
+    telemetryClient.TrackDependency(
+        "AzureOpenAI",
+        "ChatCompletion",
+        deploymentName,
+        activity.StartTimeUtc,
+        activity.Duration,
+        success: true);
+} catch (Exception ex) {
+    telemetryClient.TrackException(ex);
+    throw;
+} finally {
+    activity.Stop();
+}
+```
+
+Live Metrics vil vise:
+- Dependency latency i real-time
+- Exception stack traces hvis Azure OpenAI API feiler
+- CPU/memory impact av token processing
+
+### Copilot Studio + Real-Time Dashboard
+
+**Scenario:** Monitor Copilot Studio agent performance med Real-Time Dashboard.
+
+1. **Enable Application Insights** for Copilot Studio (via Power Platform admin)
+2. **Create Eventstream** som subscriber til App Insights metrics
+3. **Build Real-Time Dashboard** med KQL queries:
+
+```kusto
+// Copilot Studio conversation success rate (10s buckets)
+customEvents
+| where name == "ConversationCompleted"
+| extend success = tostring(customDimensions.Success)
+| summarize
+    SuccessRate = countif(success == "true") * 100.0 / count()
+    by bin(timestamp, 10s)
+| render timechart
+```
+
+4. **Setup Data Activator** til å trigger alert hvis SuccessRate < 95% i 1 minutt.
+
+### Azure AI Foundry + Eventhouse
+
+Azure AI Foundry Observability dashboard støtter **native integration med Application Insights**, som kan streams til Eventhouse for real-time dashboards:
+
+1. **Enable Application Insights** for AI Foundry project
+2. **Use Eventstream** til å route App Insights logs til Eventhouse
+3. **Create Real-Time Dashboard** med queries for:
+   - Token usage per minute
+   - Model latency (P50, P95, P99)
+   - Content safety violations
+   - Groundedness scores
+
+---
+
+## Offentlig sektor (Norge)
+
+### GDPR og datasuverenitet
+
+**Live Metrics:**
+- **Ingen persistering:** Data i Live Metrics lagres ikke, kun streames til browser. GDPR Article 6(1)(f) "legitimate interests" for debugging.
+- **PII i custom filters:** Bruk IKKE custom filters med potensielt sensitive data (customer ID, email) før Entra ID authentication er aktivert (påkrevd fra Sept 2025).
+
+**Real-Time Dashboard:**
+- **Eventhouse data residency:** Velg Fabric capacity i Norway East/West for datasuverenitet.
+- **Data retention policies:** Eventhouse støtter granular retention policies per table (påkrevd for Forvaltningsloven § 10 journalføring).
+
+### Schrems II og dataoverføring
+
+- **Live Metrics endpoints:** `live.applicationinsights.azure.com` er hosted i Azure public cloud. For Schrems II compliance, bruk Azure Government (ingen Live Metrics) eller on-prem Azure Stack HCI med Azure Arc-enabled Application Insights.
+- **Real-Time Dashboard:** Fabric eventhouses kan deployes til Norway regions med Microsoft EU Data Boundary compliance.
+
+### AI Act Article 72 - Logging
+
+Real-Time Dashboards dekker **AI Act Article 72** krav for "automatic recording of events (logs)":
+
+- **High-risk AI systems** (Article 6): Real-Time Dashboard + Eventhouse retention ≥ 6 måneder.
+- **Audit trail:** KQL queries mot Eventhouse gir immutable audit log for AI decisions.
+- **Incident response:** Data Activator alerts sikrer rask respons på AI failures (Article 9 risk management).
+
+### Forvaltningsloven § 11 - Begrunnelse
+
+Real-Time Dashboards kan kombineres med AI Foundry tracing til å bygge "begrunnelse for vedtak":
+
+```kusto
+// Retrieve AI decision trace for specific case
+AITraces
+| where timestamp between (datetime(2026-02-05T10:00) .. datetime(2026-02-05T10:05))
+| where customDimensions.caseId == "CASE-12345"
+| project timestamp, operation_Name, promptTokens, completionTokens, groundednessScore
+| order by timestamp asc
+```
+
+Dette gir sporbarhet for AI-baserte vedtak (påkrevd av Forvaltningsloven § 11).
+
+---
+
+## Kostnad og lisensiering
+
+### Application Insights Live Metrics
+
+| Komponent | Kostnad | Merknad |
+|-----------|---------|---------|
+| **Live Metrics streaming** | **Gratis** | Ingen ekstra ingestion cost |
+| **Underlying telemetry** | Standard App Insights pricing | $2.88/GB (pay-as-you-go) |
+| **Entra ID authentication** | Inkludert i Entra ID P1/P2 | Påkrevd fra Sept 2025 |
+
+**Optimaliseringstips:**
+- Lukk Live Metrics etter debugging (stopper streaming overhead på app)
+- Bruk sampling for underlying telemetry (påvirker ikke Live Metrics, men reduserer ingestion cost)
+
+### Fabric Real-Time Intelligence
+
+| Komponent | Kostnad (estimat) | Merknad |
+|-----------|-------------------|---------|
+| **Real-Time Dashboard** | Inkludert i Fabric capacity | Ingen ekstra kostnad |
+| **Eventhouse storage** | ~$0.10/GB/måned | Time-series compressed |
+| **Eventstream compute** | Inkludert i Fabric capacity | Avhenger av throughput |
+| **Data Activator** | Separate SKU (preview pricing TBA) | Per reflex/trigger |
+| **Minimum Fabric capacity** | F2 SKU (~$262/måned) | Kan skales opp/ned |
+
+**Kostnadsmodell for eventhouse:**
+- **Ingestion:** Ingen ekstra kostnad (dekket av capacity)
+- **Storage:** Compressed time-series (~10:1 compression ratio for telemetry)
+- **Query compute:** CU usage avhenger av dashboard refresh rate og query complexity
+
+**Optimaliseringstips:**
+- Bruk **table update policies** for pre-aggregation (reduserer query compute)
+- Set dashboard refresh til **30-60s** for non-critical metrics (reduserer CU usage)
+- Enable **caching** for ofte-brukte queries (cache retention 5 min - 1 time)
+- Bruk **materialized views** for expensive aggregations (calculate once, query mange)
+
+### Total Cost of Ownership (TCO) Eksempel
+
+**Scenario:** AI-tjeneste med 1M requests/dag, 5 GB telemetry/dag.
+
+**Option 1: Live Metrics only**
+- App Insights ingestion: 5 GB/dag × 30 dager × $2.88/GB = **$432/måned**
+- Live Metrics: **$0/måned**
+- **Total: $432/måned**
+
+**Option 2: Real-Time Dashboard + Eventhouse**
+- App Insights ingestion: **$432/måned**
+- Eventhouse storage: 150 GB × $0.10 = **$15/måned**
+- Fabric F2 capacity: **$262/måned**
+- **Total: $709/måned**
+
+**Trade-off:**
+- **+65% cost** for Real-Time Dashboard, MEN får persistent storage, alerting, multi-source dashboards.
+- For enterprise workloads med SLA requirements: Real-Time Dashboard ROI gjennom redusert downtime.
+
+---
+
+## For arkitekten (Cosmo)
+
+### Spørsmål å stille
+
+1. **Hva er primary use case for real-time monitoring?**
+   - Debugging/deployment validation → Live Metrics
+   - Production operations med SLA → Real-Time Dashboard
+   - Begge → Hybrid approach
+
+2. **Hva er akseptabel latency for monitoring?**
+   - < 1 sekund → Live Metrics
+   - 10 sekunder - 1 minutt → Real-Time Dashboard
+   - Varierer per metric → Kombiner begge
+
+3. **Er data retention påkrevd (compliance, audit)?**
+   - Nei → Live Metrics sufficient
+   - Ja → Real-Time Dashboard med Eventhouse
+
+4. **Har dere eksisterende Fabric capacity?**
+   - Ja → Legg til Real-Time Dashboard (no extra infra cost)
+   - Nei → Vurder cost/benefit mot managed App Insights only
+
+5. **Trenger dere alerting basert på real-time metrics?**
+   - Ja → Data Activator (krever Real-Time Dashboard)
+   - Nei → Live Metrics eller standard Azure Monitor alerts (1-5 min latency)
+
+6. **Hvor mange datakilder skal monitors?**
+   - Kun én app → Live Metrics
+   - Multiple apps/services → Real-Time Dashboard (unified view)
+
+7. **Hvem er primary audience for dashboards?**
+   - Developers → Live Metrics (ad-hoc debugging)
+   - Operations/business → Real-Time Dashboard (shareable, no-code)
+
+8. **Er Schrems II compliance påkrevd?**
+   - Ja → Fabric eventhouse i Norway regions
+   - Nei → Standard Application Insights OK
+
+### Fallgruver
+
+⚠️ **Over-reliance på Live Metrics for production**
+Live Metrics er designet for debugging, ikke production monitoring. Mangler alerting og persistering.
+
+⚠️ **Underestimere Fabric capacity krav**
+Real-Time Dashboard krever minimum F2 SKU. Start med F2, skaler opp hvis CU throttling.
+
+⚠️ **Ignorere API key deprecation (Sept 2025)**
+Migrer til Entra ID authentication for Live Metrics control channel NÅ, ikke vent til deadline.
+
+⚠️ **Sette for aggressive refresh rates**
+10s refresh på alle dashboards gir høy CU cost. Bruk 30-60s for de fleste metrics.
+
+⚠️ **Blande real-time streaming med batch ETL**
+Real-Time Dashboard er IKKE erstatning for data warehouse. Bruk for operational monitoring, ikke business analytics.
+
+### Anbefalinger per modenhetsnivå
+
+**Nivå 1 - Proof of Concept:**
+- Start med **Live Metrics** (gratis, zero-config)
+- Enable for ASP.NET Core/Java/Python apps (enabled by default med OpenTelemetry)
+- Bruk under deployment validation
+
+**Nivå 2 - Pilot (produksjon med begrenset scope):**
+- Introduser **Real-Time Dashboard** for critical services
+- Deploy Eventhouse i Norway region (GDPR compliance)
+- Setup Data Activator for 2-3 critical alerts (error rate, latency)
+- Start med F2 capacity, monitor CU usage
+
+**Nivå 3 - Production (enterprise-scale):**
+- Hybrid approach: Live Metrics for developers + Real-Time Dashboard for ops
+- Multi-source dashboards (App Insights + Azure Monitor + custom events)
+- Materialized views for expensive aggregations
+- Entra ID authentication for Live Metrics control channel
+- KQL alert queries med anomaly detection (series_decompose_anomalies)
+
+**Nivå 4 - Optimalisert:**
+- Custom Eventstream pipelines med pre-aggregation
+- Dedicated Fabric capacity (F8+) for high-throughput
+- Automated dashboard generation med Copilot
+- Integration med Power BI for business stakeholder reporting
+- Cross-region replication av Eventhouse (disaster recovery)
+
+---
+
+## Kilder og verifisering
+
+### Microsoft Learn (Verified via MCP)
+
+1. **Live Metrics: Monitor and diagnose with 1-second latency**
+   https://learn.microsoft.com/en-us/azure/azure-monitor/app/live-stream
+   **Confidence:** Verified (Feb 2026) - Authoritative doc for Live Metrics
+
+2. **What is Real-Time Dashboard?**
+   https://learn.microsoft.com/en-us/fabric/real-time-intelligence/real-time-dashboards-overview
+   **Confidence:** Verified (Feb 2026) - Fabric Real-Time Intelligence GA features
+
+3. **Configure Azure Monitor OpenTelemetry**
+   https://learn.microsoft.com/en-us/azure/azure-monitor/app/opentelemetry-configuration#live-metrics
+   **Confidence:** Verified (Feb 2026) - OpenTelemetry Live Metrics config
+
+4. **Troubleshoot Live Metrics issues**
+   https://learn.microsoft.com/en-us/troubleshoot/azure/azure-monitor/app-insights/troubleshoot-live-metrics
+   **Confidence:** Verified (Feb 2026) - Firewall, TLS requirements
+
+5. **Monitor .NET and Node.js applications with Application Insights (Classic API)**
+   https://learn.microsoft.com/en-us/azure/azure-monitor/app/classic-api#collecting-telemetry-data
+   **Confidence:** Verified (Feb 2026) - Manual Live Metrics setup (legacy)
+
+6. **Build real-time monitoring and observable systems for media**
+   https://learn.microsoft.com/en-us/azure/architecture/example-scenario/monitoring/monitoring-observable-systems-media
+   **Confidence:** Verified (Feb 2026) - Real-time architecture patterns
+
+7. **Observability in generative AI**
+   https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/observability
+   **Confidence:** Verified (Feb 2026) - AI Foundry monitoring integration
+
+8. **Implement advanced monitoring for Azure OpenAI through a gateway**
+   https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/azure-openai-gateway-monitoring#near-real-time-monitoring
+   **Confidence:** Verified (Feb 2026) - Near real-time vs batch monitoring trade-offs
+
+### Confidence per seksjon
+
+| Seksjon | Confidence | Kilde |
+|---------|-----------|-------|
+| Application Insights Live Metrics | Verified | MCP fetch: live-stream doc |
+| Fabric Real-Time Dashboard | Verified | MCP fetch: real-time-dashboards-overview |
+| Arkitekturmønstre | Baseline | Synthesized fra multiple MCP sources |
+| Code samples | Verified | MCP code search: C# Live Metrics setup |
+| Kostnad og lisensiering | Baseline | Pricing calculated fra public Azure pricing (Feb 2026) |
+| Offentlig sektor compliance | Baseline | Applied GDPR/AI Act principles til verified features |
+
+**MCP calls:** 6 (3 × search, 2 × fetch, 1 × code search)
+**Unique sources:** 8 Microsoft Learn URLs
+**Last verified:** 2026-02-05