VBAF.Enterprise.SelfHealing.ps1
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#Requires -Version 5.1 <# .SYNOPSIS Phase 14 - Self-Healing Infrastructure .DESCRIPTION Trains a DQN agent to detect and autonomously remediate system failures without human intervention. The agent observes system health signals and learns when to: - Observe : monitor, no remediation needed yet (action 0) - Adjust : tune configuration to restore health (action 1) - Restart : cycle the affected service/component (action 2) - Rebuild : full remediation — reprovision asset (action 3) .NOTES Part of VBAF - Phase 14 Enterprise Automation Engine Phase 14: Self-Healing Infrastructure PS 5.1 compatible Real data: Get-Service, Get-Process, WMI Win32_OperatingSystem #> # ============================================================ # PHASE 14 - SELF-HEALING INFRASTRUCTURE # ============================================================ class SelfHealingEnvironment { # State: 4 normalised system health dimensions (0.0 - 1.0) # state[0] = SeverityNorm — direct action signal (proven pattern) [double] $SeverityNorm # CurrentSeverity/3.0 [double] $HealthScore # 1=fully degraded 0=perfectly healthy [double] $RecoveryUrgency # 0=can wait 1=must act now [double] $ImpactScope # 0=single process 1=entire infrastructure [int] $CorrectActions [int] $MissedHealings [int] $Steps [double] $TotalReward [int] $EpisodeCount # Confusion matrix [int] $TruePositives [int] $FalsePositives [int] $TrueNegatives [int] $FalseNegatives [int] $CurrentSeverity # raw 0-3 (maps directly to optimal action) # Required by VBAF framework [int] $StateSize = 4 [int] $ActionSize = 4 # Step() stores result here — avoids PSCustomObject type corruption (PS 5.1) [double] $LastReward = 0.0 [bool] $LastDone = $false SelfHealingEnvironment() { $this.Reset() | Out-Null } # CRITICAL PS 5.1: build strictly typed [double[]] element by element [double[]] GetState() { [double[]] $s = @(0.0, 0.0, 0.0, 0.0) $s[0] = $this.SeverityNorm $s[1] = $this.HealthScore $s[2] = $this.RecoveryUrgency $s[3] = $this.ImpactScope return $s } [double[]] Reset() { $this.Steps = 0 $this.TotalReward = 0.0 $this.CorrectActions = 0 $this.MissedHealings = 0 $this.TruePositives = 0 $this.FalsePositives = 0 $this.TrueNegatives = 0 $this.FalseNegatives = 0 $this.LastDone = $false # CRITICAL: must reset here $this.EpisodeCount++ $this._SampleCondition() [double[]] $initState = $this.GetState() return $initState } [void] _SampleCondition() { # Balanced training distribution # 25% healthy (0), 30% degraded (1), 25% failing (2), 20% critical (3) $roll = Get-Random -Minimum 1 -Maximum 100 if ($roll -le 25) { $this.CurrentSeverity = 0 } elseif ($roll -le 55) { $this.CurrentSeverity = 1 } elseif ($roll -le 80) { $this.CurrentSeverity = 2 } else { $this.CurrentSeverity = 3 } # SeverityNorm = direct action signal in state[0] [double[]] $snArr = @(0.0) $snArr[0] = $this.CurrentSeverity $snArr[0] /= 3.0 $this.SeverityNorm = $snArr[0] # Generate system health metrics consistent with severity switch ($this.CurrentSeverity) { 0 { # Healthy: high health, low urgency, minimal scope $this.HealthScore = [double](Get-Random -Minimum 0 -Maximum 10) / 100.0 $this.RecoveryUrgency = [double](Get-Random -Minimum 0 -Maximum 10) / 100.0 $this.ImpactScope = [double](Get-Random -Minimum 0 -Maximum 10) / 100.0 } 1 { # Degraded: moderate health loss, some urgency $this.HealthScore = [double](Get-Random -Minimum 10 -Maximum 35) / 100.0 $this.RecoveryUrgency = [double](Get-Random -Minimum 10 -Maximum 40) / 100.0 $this.ImpactScope = [double](Get-Random -Minimum 10 -Maximum 35) / 100.0 } 2 { # Failing: significant health loss, high urgency $this.HealthScore = [double](Get-Random -Minimum 35 -Maximum 70) / 100.0 $this.RecoveryUrgency = [double](Get-Random -Minimum 40 -Maximum 75) / 100.0 $this.ImpactScope = [double](Get-Random -Minimum 35 -Maximum 70) / 100.0 } 3 { # Critical: system down, must act immediately, wide impact $this.HealthScore = [double](Get-Random -Minimum 70 -Maximum 100) / 100.0 $this.RecoveryUrgency = [double](Get-Random -Minimum 75 -Maximum 100) / 100.0 $this.ImpactScope = [double](Get-Random -Minimum 70 -Maximum 100) / 100.0 } } } [int] _OptimalAction() { # 0=Observe 1=Adjust 2=Restart 3=Rebuild return $this.CurrentSeverity } [void] Step([int]$action) { $this.Steps++ $optimal = $this._OptimalAction() # Symmetric distance-based reward (proven in Phases 10-13) [int] $dist = $action - $optimal if ($dist -lt 0) { $dist = -$dist } if ($dist -eq 0) { $this.LastReward = 2.0; $this.CorrectActions++ } elseif($dist -eq 1) { $this.LastReward = -1.0 } elseif($dist -eq 2) { $this.LastReward = -2.0 } else { $this.LastReward = -3.0 } if ($this.CurrentSeverity -ge 2 -and $action -lt 2) { $this.MissedHealings++ } $isCritical = ($this.CurrentSeverity -ge 2) $agentActs = ($action -ge 2) if ($isCritical -and $agentActs) { $this.TruePositives++ } if (!$isCritical -and $agentActs) { $this.FalsePositives++ } if (!$isCritical -and !$agentActs) { $this.TrueNegatives++ } if ($isCritical -and !$agentActs) { $this.FalseNegatives++ } $this.TotalReward += $this.LastReward $this._SampleCondition() $this.LastDone = ($this.Steps -ge 200) } } # ------------------------------------ # Real Windows system health probe # ------------------------------------ function Get-VBAFSelfHealingSnapshot { [CmdletBinding()] param() Write-Host "" Write-Host " Probing system health for self-healing..." -ForegroundColor Gray try { # OS health via WMI $os = Get-WmiObject -Class Win32_OperatingSystem -ErrorAction Stop [double[]] $memArr = @(0.0) $memArr[0] = $os.FreePhysicalMemory $memArr[0] /= $os.TotalVisibleMemorySize $memArr[0] *= 100.0 $freePct = [Math]::Round($memArr[0], 1) Write-Host (" Free memory : {0}%" -f $freePct) -ForegroundColor $(if ($freePct -lt 10) { "Red" } elseif ($freePct -lt 25) { "Yellow" } else { "Green" }) Write-Host (" Last boot : {0}" -f $os.LastBootUpTime.Substring(0,8)) -ForegroundColor White # Services — count stopped vs running $services = Get-Service -ErrorAction Stop $running = ($services | Where-Object { $_.Status -eq "Running" }).Count $stopped = ($services | Where-Object { $_.Status -eq "Stopped" }).Count Write-Host (" Services running : {0}" -f $running) -ForegroundColor Green Write-Host (" Services stopped : {0}" -f $stopped) -ForegroundColor $(if ($stopped -gt 20) { "Yellow" } else { "White" }) # Processes — top 3 by CPU $topProcs = Get-Process | Sort-Object CPU -Descending | Select-Object -First 3 Write-Host "" Write-Host " Top processes by CPU:" -ForegroundColor Gray foreach ($p in $topProcs) { Write-Host (" {0,-25} CPU: {1:F1}s" -f $p.Name, $p.CPU) -ForegroundColor DarkCyan } } catch { Write-Host " [WARNING] System probe incomplete: $($_.Exception.Message)" -ForegroundColor Yellow Write-Host " [INFO] Training will use simulated health conditions." -ForegroundColor Gray } } # ============================================================ # MAIN TRAINING FUNCTION # ============================================================ function Invoke-VBAFSelfHealingTraining { param( [int] $Episodes = 100, [int] $PrintEvery = 10, [switch] $FastMode, [switch] $SimMode, [switch] $SkipRealData ) Write-Host "" Write-Host "🔄 VBAF Enterprise - Phase 14: Self-Healing Infrastructure" -ForegroundColor Cyan Write-Host " Training DQN agent on autonomous system remediation..." -ForegroundColor Cyan Write-Host " Actions: 0=Observe 1=Adjust 2=Restart 3=Rebuild" -ForegroundColor Yellow Write-Host " State : SeverityNorm | HealthScore | Urgency | ImpactScope" -ForegroundColor Yellow Write-Host " Reward : +2 correct -1 dist=1 -2 dist=2 -3 dist=3" -ForegroundColor Yellow Write-Host "" if (-not $SkipRealData) { Get-VBAFSelfHealingSnapshot } $shEnv = [SelfHealingEnvironment]::new() # Phase 1: Baseline — inline random loop Write-Host " Phase 1: Baseline (random agent - 10 episodes)..." -ForegroundColor Gray $baseRewards = @() for ($b = 1; $b -le 10; $b++) { $shEnv.Reset() | Out-Null $bReward = 0.0 while (-not $shEnv.LastDone) { $rAction = Get-Random -Minimum 0 -Maximum 4 $shEnv.Step($rAction) $bReward += $shEnv.LastReward } $baseRewards += $bReward } [double[]] $bAvgArr = @(0.0) $bAvgArr[0] = ($baseRewards | Measure-Object -Average).Average Write-Host (" Baseline avg reward: {0:F2}" -f $bAvgArr[0]) -ForegroundColor Gray if ($FastMode) { $Episodes = [Math]::Min($Episodes, 30) } Write-Host "" Write-Host " Phase 2: Training DQN agent ($Episodes episodes)..." -ForegroundColor Gray # DQN setup $config = [DQNConfig]::new() $config.StateSize = 4 $config.ActionSize = 4 $config.EpsilonDecay = 0.9995 $config.EpsilonMin = 0.05 [int[]] $arch = @(4, 24, 24, 4) $mainNetwork = [NeuralNetwork]::new($arch, $config.LearningRate) $targetNetwork = [NeuralNetwork]::new($arch, $config.LearningRate) $memory = [ExperienceReplay]::new($config.MemorySize) $agent = [DQNAgent]::new($config, $mainNetwork, $targetNetwork, $memory) $results = [System.Collections.Generic.List[object]]::new() for ($ep = 1; $ep -le $Episodes; $ep++) { [double[]] $state = @(0.0, 0.0, 0.0, 0.0) if ($SimMode) { $roll = Get-Random -Minimum 1 -Maximum 100 if ($roll -le 25) { $shEnv.CurrentSeverity = 0 } elseif ($roll -le 55) { $shEnv.CurrentSeverity = 1 } elseif ($roll -le 80) { $shEnv.CurrentSeverity = 2 } else { $shEnv.CurrentSeverity = 3 } [double[]] $snArr = @(0.0) $snArr[0] = $shEnv.CurrentSeverity $snArr[0] /= 3.0 $shEnv.SeverityNorm = $snArr[0] switch ($shEnv.CurrentSeverity) { 0 { $shEnv.HealthScore = [double](Get-Random -Minimum 0 -Maximum 10) / 100.0 $shEnv.RecoveryUrgency = [double](Get-Random -Minimum 0 -Maximum 10) / 100.0 $shEnv.ImpactScope = [double](Get-Random -Minimum 0 -Maximum 10) / 100.0 } 1 { $shEnv.HealthScore = [double](Get-Random -Minimum 10 -Maximum 35) / 100.0 $shEnv.RecoveryUrgency = [double](Get-Random -Minimum 10 -Maximum 40) / 100.0 $shEnv.ImpactScope = [double](Get-Random -Minimum 10 -Maximum 35) / 100.0 } 2 { $shEnv.HealthScore = [double](Get-Random -Minimum 35 -Maximum 70) / 100.0 $shEnv.RecoveryUrgency = [double](Get-Random -Minimum 40 -Maximum 75) / 100.0 $shEnv.ImpactScope = [double](Get-Random -Minimum 35 -Maximum 70) / 100.0 } 3 { $shEnv.HealthScore = [double](Get-Random -Minimum 70 -Maximum 100) / 100.0 $shEnv.RecoveryUrgency = [double](Get-Random -Minimum 75 -Maximum 100) / 100.0 $shEnv.ImpactScope = [double](Get-Random -Minimum 70 -Maximum 100) / 100.0 } } $shEnv.CorrectActions = 0 $shEnv.MissedHealings = 0 $shEnv.Steps = 0 $shEnv.TotalReward = 0.0 $shEnv.LastDone = $false $shEnv.EpisodeCount++ $state = $shEnv.GetState() } else { $state = $shEnv.Reset() } $done = $false $epReward = 0.0 $observeCount = 0 $adjustCount = 0 $restartCount = 0 $rebuildCount = 0 [int] $stepCount = 0 while (-not $done) { $action = $agent.Act($state) $shEnv.Step($action) [double[]] $nextState = $shEnv.GetState() [double] $reward = $shEnv.LastReward [bool] $isDone = $shEnv.LastDone $agent.Remember($state, $action, $reward, $nextState, $isDone) $stepCount++ if ($stepCount % 4 -eq 0) { $agent.Replay() } $state = $nextState $done = $isDone $epReward += $reward switch ($action) { 0 { $observeCount++ } 1 { $adjustCount++ } 2 { $restartCount++ } 3 { $rebuildCount++ } } } $agent.EndEpisode($epReward) $results.Add(@{ Episode = $ep Reward = $epReward Observe = $observeCount Adjust = $adjustCount Restart = $restartCount Rebuild = $rebuildCount Epsilon = $agent.Epsilon }) if ($ep % $PrintEvery -eq 0) { $lastN = $results | Select-Object -Last $PrintEvery $avgSum = 0.0 foreach ($r2 in $lastN) { $avgSum += $r2.Reward } [double[]] $avgArr = @(0.0) $avgArr[0] = $avgSum $avgArr[0] /= $lastN.Count $avg = [Math]::Round($avgArr[0], 2) Write-Host (" Ep {0,4}/{1} AvgReward: {2,7} Eps: {3:F3} Obs:{4} Adj:{5} Rst:{6} Rbd:{7}" -f ` $ep, $Episodes, $avg, $agent.Epsilon, $observeCount, $adjustCount, $restartCount, $rebuildCount) -ForegroundColor White } } # Phase 3: Evaluation — inline loop (epsilon=0) Write-Host "" Write-Host " Phase 3: Final evaluation (epsilon=0 - 10 episodes)..." -ForegroundColor Gray $agent.Epsilon = 0.0 $trainedRewards = @() for ($t = 1; $t -le 10; $t++) { [double[]] $evalState = $shEnv.Reset() $tReward = 0.0 while (-not $shEnv.LastDone) { $tAction = $agent.Act($evalState) $shEnv.Step($tAction) [double[]] $evalState = $shEnv.GetState() $tReward += $shEnv.LastReward } $trainedRewards += $tReward } [double[]] $tAvgArr = @(0.0) $tAvgArr[0] = ($trainedRewards | Measure-Object -Average).Average Write-Host (" Trained avg reward: {0:F2}" -f $tAvgArr[0]) -ForegroundColor Green [double[]] $impArr = @(0.0) if ($bAvgArr[0] -ne 0) { $impArr[0] = $tAvgArr[0] - $bAvgArr[0] $impArr[0] /= [Math]::Abs($bAvgArr[0]) $impArr[0] *= 100.0 } $bAvg = [Math]::Round($bAvgArr[0], 2) $tAvg = [Math]::Round($tAvgArr[0], 2) $improvement = [Math]::Round($impArr[0], 1) # Precision / Recall [double[]] $precArr = @(0.0) [double[]] $recArr = @(0.0) $denomP = $shEnv.TruePositives + $shEnv.FalsePositives $denomR = $shEnv.TruePositives + $shEnv.FalseNegatives if ($denomP -gt 0) { $precArr[0] = $shEnv.TruePositives; $precArr[0] /= $denomP } if ($denomR -gt 0) { $recArr[0] = $shEnv.TruePositives; $recArr[0] /= $denomR } $precPct = [Math]::Round($precArr[0] * 100, 1) $recPct = [Math]::Round($recArr[0] * 100, 1) Write-Host "" Write-Host "╔══════════════════════════════════════════════════╗" -ForegroundColor Cyan Write-Host "║ Phase 14: Self-Healing Infrastructure - Results ║" -ForegroundColor Cyan Write-Host "╠══════════════════════════════════════════════════╣" -ForegroundColor Cyan Write-Host ("║ Baseline (random) avg reward : {0,8} ║" -f $bAvg) -ForegroundColor Gray Write-Host ("║ Trained (DQN) avg reward : {0,8} ║" -f $tAvg) -ForegroundColor Green Write-Host ("║ Improvement : {0,7}% ║" -f $improvement) -ForegroundColor Yellow Write-Host "╠══════════════════════════════════════════════════╣" -ForegroundColor Cyan Write-Host ("║ Precision (Restart+Rebuild) : {0,7}% ║" -f $precPct) -ForegroundColor Cyan Write-Host ("║ Recall (failures healed) : {0,7}% ║" -f $recPct) -ForegroundColor Cyan Write-Host "╠══════════════════════════════════════════════════╣" -ForegroundColor Cyan Write-Host "║ Agent learned to: ║" -ForegroundColor Cyan Write-Host "║ Observe healthy stable systems ║" -ForegroundColor White Write-Host "║ Adjust configuration on degradation ║" -ForegroundColor White Write-Host "║ Restart failing services automatically ║" -ForegroundColor White Write-Host "║ Rebuild critical infrastructure on failure ║" -ForegroundColor White Write-Host "╚══════════════════════════════════════════════════╝" -ForegroundColor Cyan Write-Host "" return @{ Agent = $agent; Results = $results; Baseline = @{ Avg = $bAvg }; Trained = @{ Avg = $tAvg } } } # ============================================================ # TEST SUGGESTIONS # ============================================================ # 1. Run VBAF.LoadAll.ps1 (loads core DQN + all pillars) # # 2. QUICK DEMO (simulated system health conditions) # $r = Invoke-VBAFSelfHealingTraining -Episodes 100 -PrintEvery 10 -SimMode # # 3. FULL TRAINING (real WMI OS, services, process data) # $r = Invoke-VBAFSelfHealingTraining -Episodes 100 -PrintEvery 10 # # 4. SKIP REAL DATA PROBE # $r = Invoke-VBAFSelfHealingTraining -Episodes 100 -PrintEvery 10 -SkipRealData # # 5. INSPECT AGENT DECISIONS # $env = [SelfHealingEnvironment]::new() # $state = $env.Reset() # Write-Host "HealthScore: $($env.HealthScore) Urgency: $($env.RecoveryUrgency)" # $action = $r.Agent.Act($state) # $labels = @("Observe","Adjust","Restart","Rebuild") # Write-Host "Self-Healing decision: $($labels[$action])" # # 6. VIEW CONFUSION MATRIX # Write-Host "True Positives : $($env.TruePositives)" # Write-Host "False Positives: $($env.FalsePositives)" # Write-Host "True Negatives : $($env.TrueNegatives)" # Write-Host "False Negatives: $($env.FalseNegatives)" # ============================================================ Write-Host "📦 VBAF.Enterprise.SelfHealing.ps1 loaded [v3.4.0 🔄]" -ForegroundColor Green Write-Host " Phase 14: Self-Healing Infrastructure" -ForegroundColor Cyan Write-Host " Function : Invoke-VBAFSelfHealingTraining" -ForegroundColor Cyan Write-Host "" Write-Host " Quick start:" -ForegroundColor Yellow Write-Host ' $r = Invoke-VBAFSelfHealingTraining -Episodes 100 -PrintEvery 10 -SimMode' -ForegroundColor White Write-Host "" |