Shows a purple '⚡ Alert' badge on findings that were discovered through
alert-triggered analysis rather than scheduled patrol runs. This gives
users visibility into how findings were discovered without cluttering
the patrol run history table.
Bug Fixes:
- Fix boolean fields with 'omitempty' not persisting false values
- AlertTriggeredAnalysis, PatrolAnalyzeNodes/Guests/Docker/Storage
- omitempty causes Go to skip false (zero value) when marshaling JSON
- On reload, NewDefaultAIConfig() sets true, and missing field stays true
- Fix model dropdown losing selection after save (SolidJS reactivity issue)
- Added explicit 'selected' attribute to option elements
- Ensures browser maintains selection with optgroups during re-renders
Improvements:
- Change patrol type label from 'Quick' to 'Patrol' in history table
- Add chat_model and patrol_model to AI settings update log
- Add alert_triggered_analysis to AI config load log for debugging
Instead of relying on pre-computed trend heuristics (which can be misleading
for edge cases like step changes vs continuous growth), we now pass downsampled
raw data points to the LLM so it can interpret patterns directly.
Changes:
- Add MetricSamples field to ResourceContext
- Add DownsampleMetrics() to reduce data points for LLM consumption
- Add formatMetricSamples() to format data compactly (e.g., 'Disk: 26→26→31%')
- Add computeGuestMetricSamples() to gather 7-day sampled history
- Populate MetricSamples for VMs and containers during context build
- Add History section to formatted context output
The LLM now sees actual patterns like 'stable for 6 days then jumped' rather
than just '45.8%/day growth rate' - allowing for much more nuanced interpretation.
This approach:
- Leverages LLM's pattern recognition instead of hard-coded heuristics
- Provides 7 days of data (~24 samples) for context on normal behavior
- Uses minimal tokens due to compact formatting with deduplication
- Is more future-proof as LLMs improve
Example output:
**History (7d sampled, oldest→newest)**: Disk: 26→26→26→26→26→31%
Refs: Frigate disk usage false positive investigation
- Remove unused correlations state and constants from AIOverviewTable
- Remove unused runbook-related imports, state, and functions from Alerts
- Add type annotation to Set() to fix type error
- Removes dead code left over from runbook UI removal
Fix Receipts was showing 'No fixes logged' most of the time since:
- Runbooks were removed
- Remediation logging was inconsistent
Just adds visual clutter without value. Removed ~100 lines of UI code.
The AI Intelligence Summary was adding noise rather than value:
- Predictions duplicated patrol findings
- Correlations were not actionable
- 'Fixed' items were vague diagnostics
- Status changes were startup noise
The real value is in the patrol findings section which shows:
- Actual issues found (critical/warning/watch/info)
- Actionable recommendations
- Suppression rules
Keeping the patrol findings, removing the redundant summary.
More aggressive noise filtering:
1. Anomaly threshold raised from 1.5x to 2x
- 1.5x is too borderline to be actionable
- Now requires genuinely significant deviation
2. Filter out 'Ran diagnostic' and 'Executed command' fallback items
- These are generic summaries that provide no value
- Only show remediations with specific, meaningful descriptions
Goal: If something shows in AI Intelligence, it should demand attention.
Critical changes to surface only actionable insights:
1. Anomalies now require at least 50% deviation from baseline
- '1.0x baseline' values filtered out (statistically significant but not actionable)
- Must be >1.5x above OR <0.5x below baseline to report
2. Status changes filter out startup noise
- 'unknown → running' is just system starting, not a real state change
- Backups removed from main list (they have dedicated section)
3. Only show genuinely interesting changes:
- Config changes, migrations, restarts, deletions
- Things that require operator attention
This massively reduces noise while keeping high-signal alerts.
Correlations currently show 'A and B alert together' which isn't useful:
- Bidirectional correlations (A→B AND B→A) are just coincidence
- 'experiences alert' is too vague to be actionable
- No root cause identification - just shows correlated things correlate
Hidden until we can properly identify:
- Root cause chains (A CAUSES B, not just 'A and B happen together')
- Specific trigger types (what kind of alert?)
- Direction of causality
Other improvements:
- Stopped VMs/containers filtered from anomaly detection
- Lower noise, more signal
Critical fixes to show only actionable insights:
1. Skip stopped VMs/containers from anomaly detection
- '0.0x baseline' for stopped resources is expected, not an anomaly
- Only check anomalies for status='running'
2. Filter correlations by confidence (>=70%)
- Low confidence correlations are likely coincidental
- Only show high-confidence, actionable dependencies
This reduces noise and surfaces genuinely useful intelligence.
Changed AIOverviewTable to use Promise.allSettled instead of
Promise.all so that one failing endpoint (e.g., anomalies 404)
doesn't break the entire component.
Each API result now has a fallback for failed requests, allowing
the table to gracefully degrade when endpoints are unavailable.
Separate anomalies API call from Promise.all so that a failure
in the anomalies endpoint doesn't break the entire AI Overview.
This fixes 'Failed to load AI overview data' error when the
anomalies endpoint isn't available (e.g., patrol not started).
Added collapsible sections to prevent overwhelming list:
- Dependencies limited to top 5 (sorted by confidence)
- Actions limited to top 5
- Changes limited to top 5
- 'Show more' buttons appear at bottom when items are hidden
- Clicking expands to show all items in that category
This addresses user feedback about excessive scrolling when
there are many dependency correlations or remediation actions.
Adds real-time anomaly detection results to the AI Overview Table:
- Anomalies appear at TOP of list (before predictions) since they're real-time
- Severity-based color coding (critical=red, high=orange, medium=amber, low=blue)
- Shows resource name, metric, and deviation ratio (e.g., 'CPU at 2.5x baseline')
- Subtitle shows current vs baseline values
- Timestamp shows 'Now' since anomalies are current state
This integrates the FREE anomaly detection feature directly alongside
the Pro patrol insights, providing immediate value to all users.
New useLearningStatus hook:
- Polls /api/ai/intelligence/learning every 60 seconds
- Provides resourceCount(), metricCount(), learningState()
- Convenience accessors: isActive(), isLearning(), isWaiting()
Enhanced AIStatusIndicator:
- Now shows when ANY baselines exist (not just when Patrol enabled)
- Tooltip shows 'X resources baselined' for transparency
- Healthy state 45 resources baselined'shows '
- Works even without Pro license since baselines are FREE
This makes the AI presence visible from the moment Pulse starts
learning, providing immediate value feedback to all users.
Free Features (no license required):
- Anomaly detection - removed license gating, purely statistical analysis
- Learning status endpoint - GET /api/ai/intelligence/learning
Learning Status Response:
- resources_baselined: count of resources with learned baselines
- total_metrics: total metric baselines (cpu + memory + disk)
- metric_breakdown: {cpu: X, memory: Y, disk: Z}
- status: 'waiting' | 'learning' | 'active'
- message: human-readable description
This makes the AI intelligence features visible to all users,
encouraging upgrades for the full LLM-powered patrol experience.
AIStatusIndicator:
- Now shows BOTH patrol findings AND baseline anomalies
- Displays even when only anomaly detection is active (no patrol)
- Badge count includes both findings + anomalies
- Tooltip provides detailed breakdown by severity
Trend Prediction (backend):
- Add TrendPrediction struct for resource exhaustion forecasting
- CalculateTrend() uses linear regression on sample history
- Predicts days until resource is full (or if declining/stable)
- Severity: critical (<7 days), warning (<30 days), info (>30 days)
- Human-readable descriptions like 'full in ~2 weeks (+0.5% per day)'
This creates a more cohesive intelligence experience where anomaly
detection works independently of the pro/patrol features, making
value visible immediately to all users.
Complete the anomaly indicator integration for all three metrics:
- CPU: EnhancedCPUBar (already done)
- Memory: StackedMemoryBar (new)
- Disk: StackedDiskBar (new)
All three metric bars now show a pulsing indicator (e.g., '2.5x↑')
when the current value is significantly above the learned baseline.
Severity colors:
- Critical (>4σ): red
- High (3-4σ): orange
- Medium (2.5-3σ): yellow
- Low (2-2.5σ): blue
This is 100% deterministic - no LLM involved. The indicators appear
automatically based on statistical deviation from learned baselines.
Connect anomaly data to the EnhancedCPUBar component in GuestRow.
When a VM/container's CPU is significantly above its learned baseline,
a pulsing indicator (e.g., '2.5x') appears directly on the CPU bar.
This provides real-time baseline deviation feedback without any LLM
involvement - purely deterministic statistical analysis.
Memory and disk anomaly hooks are prepared but not yet wired to their
respective bar components (TODO for follow-up).
Add frontend infrastructure for displaying baseline anomalies:
- useAnomalies hook for fetching and caching anomaly data
- AnomalyCell component for displaying multiple anomalies
- AnomalyIndicator/AnomalyBadge components for inline display
- Update EnhancedCPUBar to accept optional anomaly prop
The anomaly endpoint is polled every 30 seconds and cached.
Anomaly badges show severity (color) and deviation ratio (e.g., '2.5x').
This prepares the UI for displaying real-time baseline deviations
without requiring LLM interaction.
Add /api/ai/intelligence/anomalies endpoint that compares live metrics
against learned baselines to surface deviations - all deterministic
(no LLM required).
Backend:
- Add AnomalyReport struct with severity classification
- Add CheckResourceAnomalies method to baseline store
- Add HandleGetAnomalies API handler
- Add GetStateProvider getter to AI service
Frontend:
- Add AnomalyReport and AnomaliesResponse types
- Add getAnomalies API function
- Add AnomalySeverity type
This is the first step toward surfacing deterministic intelligence
directly in the UI without requiring LLM interaction.
- Create Intelligence struct that aggregates all AI subsystems
- Add /api/ai/intelligence endpoint for system-wide and per-resource insights
- Wire Intelligence into PatrolService as a facade (not replacement)
- Add TypeScript types and API client for frontend
- Add unit tests for Intelligence orchestrator
- Fix pre-existing test failures using diagnostic commands instead of actionable ones
The Intelligence orchestrator provides:
- System-wide health scoring (A-F grades)
- Aggregated findings, predictions, correlations
- Per-resource context generation for AI prompts
- Learning progress tracking
This unifies access to AI subsystems without replacing existing code paths.
- KubernetesClusters.tsx: Escape -> as → in JSX text to fix parsing error
- Settings.tsx: Remove unused HostProxySummary interface (deprecated in v5)
- AIOverviewTable.tsx: Prefix unused summarizeAction with underscore
The pulse-sensor-proxy feature was deprecated in v5 and disabled by default.
The frontend was still calling /api/temperature-proxy/host-status which
returned 410 Gone, causing console errors.
Removed:
- HostProxyStatusResponse interface
- _hostProxyStatus signal (was never read)
- refreshHostProxyStatus function
- Polling interval that called the deprecated endpoint
The temperature monitoring now uses pulse-agent instead.
Backend:
- Enhanced buildEnrichedResourceContext to ALWAYS show learned baselines with
status indicators (normal/elevated/anomaly) instead of only when anomalous
- This makes Pulse Pro's 'moat' visible - users can see the AI understands
their infrastructure's normal behavior patterns
- Added baseline import to service.go
Frontend (user changes):
- Added incident event type filtering with toggle buttons
- Added resource incident panel to view all incidents for a resource
- Added timeline expand/collapse functionality in alert history
- Added incident note saving with proper incidentId tracking
- Added startedAt parameter for proper incident timeline loading
Multiple frontend components were using - as a fallback
when guest.id was falsy. This format drops the node component, which is
critical for clustered setups where the same VMID can exist on different
nodes.
Changes:
- GuestDrawer.tsx: Updated guestId() and handleAskAI() to use canonical format
- GuestRow.tsx: Updated buildGuestId() to use canonical format
- Dashboard.tsx: Updated handleGuestRowClick() and guest rendering loop,
also fixed legacy metadata fallback to use consistent keying
- ThresholdsTable.tsx: Updated guestsGroupedByNode() to use canonical format
Backend changes:
- Removed temporary debug logging added during investigation
- Added alert history section to AI buildEnrichedResourceContext() function
The backend generates VM/Container IDs in instance:node:vmid format (e.g.,
delly:delly:101) via makeGuestID(). This format is now consistently used
across all frontend fallbacks to prevent AI context, metadata, overrides,
and metrics from colliding or desyncing in clustered environments.
- Fixed normalizeStorageDefaults to allow Trigger=0
- Fixed normalizeNodeDefaults (Temperature) to allow Trigger=0
- Added comprehensive tests for all threshold normalization patterns
- Updated existing test that expected old behavior
Related to #864
- Login.tsx: Use apiClient.fetch with skipAuth to avoid auth loops
- router.go: Skip CSRF validation for /api/login endpoint
- hot-dev.sh: Detect encrypted files before generating new key to prevent data loss
Header and action buttons now stack vertically on narrow screens
instead of overflowing. Button labels are shortened on mobile.
Related to discussion #845 (feedback from @MDE186)
When the user logged out, the code would immediately set needsAuth=true
and return WITHOUT first fetching /api/security/status. This meant the
securityStatus signal was null, causing shouldShowLocalLogin() in Login.tsx
to return true (since !undefined === true).
Now we always fetch security status before showing the login form, even
in the just_logged_out path. This ensures hideLocalLogin, oidcEnabled,
and other OIDC settings are properly available to the Login component.
- Add HandleLicenseFeatures handler that was missing from license_handlers.go
- Add /api/license/features route to router
- Update AI service and metadata provider
- Update frontend license API and components
- Fix CI build failure caused by tests referencing unimplemented method
The 'Removed Docker Hosts' section was not appearing in Settings -> Agents
even when hosts were blocked from re-enrolling. This prevented users from
using the 'Allow re-enroll' button to unblock their Docker agents.
Root cause: The WebSocket store was missing:
1. The 'removedDockerHosts' property in its initial state
2. A handler to process removedDockerHosts data from WebSocket messages
This meant the backend was correctly sending the data, but the frontend
was completely ignoring it.
Changes:
- Add removedDockerHosts to WebSocket store initial state and message handler
- Add removedDockerHosts to App.tsx fallback state for consistency
- Add missing BroadcastState call after AllowDockerHostReenroll succeeds
Also includes previous fixes from this session:
- Add PULSE_AGENT_URL as alias for PULSE_AGENT_CONNECT_URL (config.go)
- Add runtime Docker/Podman auto-detection in pulse-agent (main.go)
Fixes issue reported by darthrater78 in discussion #845
- Create reusable UrlEditPopover component with fixed positioning
- Add createUrlEditState hook for managing editing state
- Update DockerHostSummaryTable to use new popover
- Update DockerUnifiedTable (containers & services) to use new popover
- Update GuestRow (Proxmox VMs/containers) to use new popover
- Update HostsOverview (Proxmox hosts) to use new popover
- Add Docker host metadata API for custom URLs
- Consistent styling with save, delete, cancel buttons and keyboard shortcuts
Previously, each DockerContainerRow component made 2 API calls on mount:
- AIAPI.getSettings() for AI enabled status
- DockerMetadataAPI.getMetadata() for annotations
With 100+ containers, this resulted in 200+ API calls firing simultaneously,
exceeding the 500 requests/minute rate limit and causing 429 errors.
Fix:
- Lift AI settings check to DockerUnifiedTable parent component (1 call)
- Use pre-fetched dockerMetadata prop for annotations (already batch-fetched)
- Pass aiEnabled and initialNotes as props to child rows
This reduces API calls from O(n*2) to O(1) when loading the Docker overview.
Fixes#859
Adds IncludeAllDeployments option to show all deployments, not just
problem ones (where replicas don't match desired). This provides parity
with the existing --kube-include-all-pods flag.
- Add IncludeAllDeployments to kubernetesagent.Config
- Add --kube-include-all-deployments flag and PULSE_KUBE_INCLUDE_ALL_DEPLOYMENTS env var
- Update collectDeployments to respect the new flag
- Add test for IncludeAllDeployments functionality
- Update UNIFIED_AGENT.md documentation
Addresses feedback from PR #855
When 'Hide local login form' was enabled in Settings -> Authentication,
the local login form was still displayed instead of showing only the
SSO login. This regression occurred in Pulse 5.x.
Root cause: When App.tsx passed hasAuth to Login.tsx, the Login component
created a minimal SecurityStatus object with only hasAuthentication set,
missing the hideLocalLogin and other OIDC settings.
Changes:
- App.tsx: Store and pass full securityStatus to Login component
- Login.tsx: Accept securityStatus prop and initialize state from it
- Login.tsx: Initialize authStatus directly from props to respect
hideLocalLogin on first render
- Added tests for hideLocalLogin behavior
Fixes#857
- Remove unused type imports: SnapshotAlertConfig, PMGThresholdDefaults, RawOverrideConfig, BackupAlertConfig
- Remove unused imports: Settings, Power, JSX, onMount, createEffect
- Remove unused function _getUnitSuffix
- Fix GuestDefaults type to avoid index signature conflict
- Prefix unused catch variables with underscore
- Fix StickyNote title prop by wrapping in span element
- Add CollapsibleSection component with animated expand/collapse
- Wrap all 6 resource sections (Nodes, VMs, PBS, Storage, Backups, Snapshots) with accordion UI
- Add section icons and resource counts in headers
- Add expand all / collapse all buttons for quick navigation
- Make help banner dismissible with localStorage persistence
- Add Ctrl/Cmd+F keyboard shortcut to focus search
- Add keyboard shortcut hint badge on search input
- Add icons to tab navigation for quick identification
- Improve mobile tab labels with shorter text on small screens
- Create reusable components: ThresholdBadge, ResourceCard, GlobalDefaultsRow
- Create useCollapsedSections hook with localStorage persistence
- Default less-used sections (Storage, Backups, Snapshots, PBS) to collapsed
The issue was a SolidJS reactivity problem in the Dashboard component.
When guestMetadata signal was accessed inside a For loop callback and
assigned to a plain variable, SolidJS lost reactive tracking.
Changed from:
const metadata = guestMetadata()[guestId] || ...
customUrl={metadata?.customUrl}
To:
const getMetadata = () => guestMetadata()[guestId] || ...
customUrl={getMetadata()?.customUrl}
This ensures SolidJS properly tracks the signal dependency when the
getter function is called directly in JSX props.
The previous fix (3b4c77de) only addressed PVE/PBS nodes but missed
guest rows. Now VMs and LXC containers also show CPU details tooltip
on hover using EnhancedCPUBar.
Backend:
- Add smart provider fallback when selected model's provider isn't configured
- Automatically switch to a model from a configured provider instead of failing
- Log warning when fallback occurs for visibility
Frontend (AISettings.tsx):
- Add helper functions to check if model's provider is configured
- Group model dropdown: configured providers first, unconfigured marked with ⚠️
- Add inline warning when selecting model from unconfigured provider
- Validate on save that model's provider is configured (or being added)
- Warn before clearing last configured provider (would disable AI)
- Warn before clearing provider that current model uses
- Add patrol interval validation (must be 0 or >= 10 minutes)
- Show red border + inline error for invalid patrol intervals 1-9
- Update patrol interval hint: '(0=off, 10+ to enable)'
These changes prevent confusing '500 Internal Server Error' and
'AI is not enabled or configured' errors when model/provider mismatch.
- Remove confusing Force Docker, Force Kubernetes, Force Proxmox checkboxes
- Auto-detection handles these platforms; checkboxes were redundant
- Keep Skip TLS verification checkbox (commonly needed for self-signed certs)
- Add Troubleshooting section with --enable-* and --disable-* flags for edge cases
- Update tests to reflect simplified UI
