# Enhanced Rollback Intelligence

## Overview

Enhanced Rollback Intelligence transforms rollback from a reactive recovery mechanism into a proactive, intelligent system. It provides metric-driven automatic rollback, partial rollback for multi-component releases, rollback impact analysis, and predictive failure detection.

This is a best-in-class implementation that minimizes downtime, reduces blast radius, and provides clear decision transparency through comprehensive impact analysis.

---

## Design Principles

1. **Proactive Detection**: Detect degradation before users report issues
2. **Minimal Blast Radius**: Rollback only what's necessary
3. **Predictive Analysis**: Anticipate rollback needs from early signals
4. **Full Transparency**: Every rollback decision is explainable
5. **Safe by Default**: Automatic rollback with human override capability
6. **Evidence-Backed**: All rollback decisions produce audit evidence

---

## Architecture

### Component Overview

```
┌────────────────────────────────────────────────────────────────────────┐
│                  Rollback Intelligence System                          │
├────────────────────────────────────────────────────────────────────────┤
│                                                                        │
│  ┌──────────────────┐    ┌───────────────────┐    ┌─────────────────┐ │
│  │ MetricsCollector │───▶│ HealthAnalyzer    │───▶│ RollbackDecider │ │
│  │                  │    │                   │    │                 │ │
│  └──────────────────┘    └───────────────────┘    └─────────────────┘ │
│           │                       │                        │          │
│           ▼                       ▼                        ▼          │
│  ┌──────────────────┐    ┌───────────────────┐    ┌─────────────────┐ │
│  │ BaselineManager  │    │ AnomalyDetector   │    │ ImpactAnalyzer  │ │
│  │                  │    │                   │    │                 │ │
│  └──────────────────┘    └───────────────────┘    └─────────────────┘ │
│           │                       │                        │          │
│           ▼                       ▼                        ▼          │
│  ┌──────────────────┐    ┌───────────────────┐    ┌─────────────────┐ │
│  │ PartialRollback  │    │ PredictiveEngine  │    │ RollbackExecutor│ │
│  │ Planner          │    │                   │    │                 │ │
│  └──────────────────┘    └───────────────────┘    └─────────────────┘ │
│                                                                        │
└────────────────────────────────────────────────────────────────────────┘
```

### Key Components

#### 1. MetricsCollector

Aggregates metrics from multiple sources for health analysis:

```csharp
public sealed class MetricsCollector
{
    private readonly ImmutableArray<IMetricsSource> _sources;

    public async Task<MetricsSnapshot> CollectAsync(
        Guid deploymentId,
        MetricsCollectionConfig config,
        CancellationToken ct)
    {
        var metrics = new ConcurrentDictionary<string, MetricSeries>();

        await Parallel.ForEachAsync(_sources, ct, async (source, ct) =>
        {
            var sourceMetrics = await source.CollectAsync(deploymentId, config.TimeRange, ct);
            foreach (var (name, series) in sourceMetrics)
            {
                metrics.TryAdd($"{source.Name}:{name}", series);
            }
        });

        return new MetricsSnapshot
        {
            DeploymentId = deploymentId,
            CollectedAt = _timeProvider.GetUtcNow(),
            TimeRange = config.TimeRange,
            Metrics = metrics.ToImmutableDictionary()
        };
    }
}

public interface IMetricsSource
{
    string Name { get; }
    Task<IReadOnlyDictionary<string, MetricSeries>> CollectAsync(
        Guid deploymentId, TimeRange range, CancellationToken ct);
}

// Implementations
public sealed class PrometheusMetricsSource : IMetricsSource { }
public sealed class DatadogMetricsSource : IMetricsSource { }
public sealed class CloudWatchMetricsSource : IMetricsSource { }
public sealed class ApplicationInsightsMetricsSource : IMetricsSource { }
public sealed class CustomWebhookMetricsSource : IMetricsSource { }
```

#### 2. BaselineManager

Maintains and compares deployment baselines:

```csharp
public sealed class BaselineManager
{
    public async Task<Baseline> CreateBaselineAsync(
        Guid releaseId,
        Guid environmentId,
        TimeRange stableWindow,
        CancellationToken ct)
    {
        var metrics = await _metricsCollector.CollectAsync(
            releaseId, new MetricsCollectionConfig { TimeRange = stableWindow }, ct);

        return new Baseline
        {
            Id = Guid.NewGuid(),
            ReleaseId = releaseId,
            EnvironmentId = environmentId,
            CreatedAt = _timeProvider.GetUtcNow(),
            StableWindow = stableWindow,
            Metrics = CalculateBaselineMetrics(metrics)
        };
    }

    private BaselineMetrics CalculateBaselineMetrics(MetricsSnapshot snapshot)
    {
        return new BaselineMetrics
        {
            // Error rate baseline (P50, P95, P99)
            ErrorRateP50 = CalculatePercentile(snapshot.GetMetric("error_rate"), 50),
            ErrorRateP95 = CalculatePercentile(snapshot.GetMetric("error_rate"), 95),
            ErrorRateP99 = CalculatePercentile(snapshot.GetMetric("error_rate"), 99),

            // Latency baseline
            LatencyP50 = CalculatePercentile(snapshot.GetMetric("latency_ms"), 50),
            LatencyP95 = CalculatePercentile(snapshot.GetMetric("latency_ms"), 95),
            LatencyP99 = CalculatePercentile(snapshot.GetMetric("latency_ms"), 99),

            // Throughput baseline
            ThroughputMean = CalculateMean(snapshot.GetMetric("requests_per_second")),
            ThroughputStdDev = CalculateStdDev(snapshot.GetMetric("requests_per_second")),

            // Resource baseline
            CpuMean = CalculateMean(snapshot.GetMetric("cpu_percent")),
            MemoryMean = CalculateMean(snapshot.GetMetric("memory_percent")),

            // Custom metrics
            CustomMetrics = snapshot.Metrics
                .Where(m => m.Key.StartsWith("custom:"))
                .ToDictionary(m => m.Key, m => CalculateMetricBaseline(m.Value))
                .ToImmutableDictionary()
        };
    }
}

public sealed record Baseline
{
    public Guid Id { get; init; }
    public Guid ReleaseId { get; init; }
    public Guid EnvironmentId { get; init; }
    public DateTimeOffset CreatedAt { get; init; }
    public TimeRange StableWindow { get; init; }
    public BaselineMetrics Metrics { get; init; }
}
```

#### 3. HealthAnalyzer

Analyzes current health against baseline:

```csharp
public sealed class HealthAnalyzer
{
    public async Task<HealthAnalysis> AnalyzeAsync(
        Guid deploymentId,
        Baseline baseline,
        HealthAnalysisConfig config,
        CancellationToken ct)
    {
        var currentMetrics = await _metricsCollector.CollectAsync(
            deploymentId,
            new MetricsCollectionConfig { TimeRange = config.AnalysisWindow },
            ct);

        var analysis = new HealthAnalysis
        {
            DeploymentId = deploymentId,
            BaselineId = baseline.Id,
            AnalyzedAt = _timeProvider.GetUtcNow(),
            OverallHealth = HealthStatus.Healthy,
            Signals = new List<HealthSignal>()
        };

        // Error rate analysis
        var errorSignal = AnalyzeErrorRate(currentMetrics, baseline, config);
        analysis.Signals.Add(errorSignal);

        // Latency analysis
        var latencySignal = AnalyzeLatency(currentMetrics, baseline, config);
        analysis.Signals.Add(latencySignal);

        // Throughput analysis
        var throughputSignal = AnalyzeThroughput(currentMetrics, baseline, config);
        analysis.Signals.Add(throughputSignal);

        // Resource analysis
        var resourceSignal = AnalyzeResources(currentMetrics, baseline, config);
        analysis.Signals.Add(resourceSignal);

        // Custom metrics analysis
        foreach (var (name, baselineMetric) in baseline.Metrics.CustomMetrics)
        {
            var customSignal = AnalyzeCustomMetric(name, currentMetrics, baselineMetric, config);
            analysis.Signals.Add(customSignal);
        }

        // Calculate overall health
        analysis.OverallHealth = CalculateOverallHealth(analysis.Signals);
        analysis.RollbackRecommended = ShouldRecommendRollback(analysis);
        analysis.Confidence = CalculateConfidence(analysis);

        return analysis;
    }

    private HealthSignal AnalyzeErrorRate(
        MetricsSnapshot current,
        Baseline baseline,
        HealthAnalysisConfig config)
    {
        var currentP95 = CalculatePercentile(current.GetMetric("error_rate"), 95);
        var baselineP95 = baseline.Metrics.ErrorRateP95;

        var deviation = (currentP95 - baselineP95) / Math.Max(baselineP95, 0.001);
        var status = deviation switch
        {
            > 2.0 => SignalStatus.Critical,   // 200% above baseline
            > 1.0 => SignalStatus.Warning,    // 100% above baseline
            > 0.5 => SignalStatus.Degraded,   // 50% above baseline
            _ => SignalStatus.Healthy
        };

        return new HealthSignal
        {
            Name = "error_rate",
            Status = status,
            CurrentValue = currentP95,
            BaselineValue = baselineP95,
            DeviationPercent = deviation * 100,
            Threshold = config.ErrorRateThreshold,
            Message = status switch
            {
                SignalStatus.Critical => $"Error rate {currentP95:P2} is {deviation:P0} above baseline",
                SignalStatus.Warning => $"Error rate elevated: {currentP95:P2} vs {baselineP95:P2} baseline",
                _ => $"Error rate normal: {currentP95:P2}"
            }
        };
    }
}

public sealed record HealthAnalysis
{
    public Guid DeploymentId { get; init; }
    public Guid BaselineId { get; init; }
    public DateTimeOffset AnalyzedAt { get; init; }
    public HealthStatus OverallHealth { get; init; }
    public ImmutableArray<HealthSignal> Signals { get; init; }
    public bool RollbackRecommended { get; init; }
    public double Confidence { get; init; }  // 0.0 - 1.0
    public string? RecommendationReason { get; init; }
}

public enum HealthStatus
{
    Healthy,
    Degraded,
    Warning,
    Critical,
    Unknown
}
```

#### 4. AnomalyDetector

Detects anomalies in real-time metrics:

```csharp
public sealed class AnomalyDetector
{
    private readonly ImmutableArray<IAnomalyAlgorithm> _algorithms;

    public async Task<AnomalyReport> DetectAsync(
        MetricSeries series,
        AnomalyDetectionConfig config,
        CancellationToken ct)
    {
        var anomalies = new List<Anomaly>();

        foreach (var algorithm in _algorithms)
        {
            var detected = await algorithm.DetectAsync(series, config, ct);
            anomalies.AddRange(detected);
        }

        // Deduplicate and rank
        var ranked = anomalies
            .GroupBy(a => a.Timestamp.Ticks / TimeSpan.FromMinutes(1).Ticks)
            .Select(g => g.OrderByDescending(a => a.Severity).First())
            .OrderByDescending(a => a.Severity)
            .ToImmutableArray();

        return new AnomalyReport
        {
            Series = series.Name,
            DetectedAt = _timeProvider.GetUtcNow(),
            Anomalies = ranked,
            OverallSeverity = ranked.Any() ? ranked.Max(a => a.Severity) : AnomalySeverity.None
        };
    }
}

// Anomaly detection algorithms
public interface IAnomalyAlgorithm
{
    Task<IReadOnlyList<Anomaly>> DetectAsync(
        MetricSeries series, AnomalyDetectionConfig config, CancellationToken ct);
}

public sealed class ZScoreAlgorithm : IAnomalyAlgorithm
{
    // Detects values > N standard deviations from mean
    public async Task<IReadOnlyList<Anomaly>> DetectAsync(
        MetricSeries series, AnomalyDetectionConfig config, CancellationToken ct)
    {
        var mean = series.Values.Average();
        var stdDev = CalculateStdDev(series.Values, mean);
        var threshold = config.ZScoreThreshold;

        return series.DataPoints
            .Where(dp => Math.Abs((dp.Value - mean) / stdDev) > threshold)
            .Select(dp => new Anomaly
            {
                Timestamp = dp.Timestamp,
                Value = dp.Value,
                ExpectedValue = mean,
                Deviation = (dp.Value - mean) / stdDev,
                Algorithm = "z_score",
                Severity = CalculateSeverity((dp.Value - mean) / stdDev, threshold)
            })
            .ToList();
    }
}

public sealed class SlidingWindowAlgorithm : IAnomalyAlgorithm
{
    // Detects sudden changes in moving average
}

public sealed class SeasonalDecompositionAlgorithm : IAnomalyAlgorithm
{
    // Detects anomalies accounting for daily/weekly patterns
}

public sealed class IsolationForestAlgorithm : IAnomalyAlgorithm
{
    // ML-based multivariate anomaly detection
}
```

#### 5. PredictiveEngine

Predicts potential failures from early warning signals:

```csharp
public sealed class PredictiveEngine
{
    public async Task<FailurePrediction> PredictAsync(
        Guid deploymentId,
        HealthAnalysis currentAnalysis,
        IReadOnlyList<HealthAnalysis> historicalAnalyses,
        CancellationToken ct)
    {
        var prediction = new FailurePrediction
        {
            DeploymentId = deploymentId,
            PredictedAt = _timeProvider.GetUtcNow()
        };

        // Trend analysis
        var errorTrend = AnalyzeTrend(
            historicalAnalyses.Select(a => a.GetSignal("error_rate")));
        var latencyTrend = AnalyzeTrend(
            historicalAnalyses.Select(a => a.GetSignal("latency")));

        // Pattern matching against known failure patterns
        var patterns = await _patternStore.GetKnownFailurePatternsAsync(ct);
        var matchedPatterns = patterns
            .Where(p => MatchesPattern(currentAnalysis, historicalAnalyses, p))
            .ToList();

        if (matchedPatterns.Any())
        {
            var bestMatch = matchedPatterns.OrderByDescending(p => p.Confidence).First();
            prediction.FailureLikelihood = bestMatch.Confidence;
            prediction.PredictedFailureType = bestMatch.FailureType;
            prediction.EstimatedTimeToFailure = bestMatch.TypicalTimeToFailure;
            prediction.EarlyWarningSignals = bestMatch.MatchedSignals;
            prediction.RecommendedAction = bestMatch.RecommendedAction;
        }
        else
        {
            // Extrapolation-based prediction
            if (errorTrend.Slope > 0 && errorTrend.Confidence > 0.8)
            {
                var timeToThreshold = EstimateTimeToThreshold(
                    errorTrend, currentAnalysis.GetSignal("error_rate").Threshold);

                prediction.FailureLikelihood = errorTrend.Confidence * 0.7;
                prediction.PredictedFailureType = FailureType.ErrorRateExceeded;
                prediction.EstimatedTimeToFailure = timeToThreshold;
                prediction.EarlyWarningSignals = new[] { "error_rate_trending_up" }.ToImmutableArray();
            }
        }

        return prediction;
    }

    private TrendAnalysis AnalyzeTrend(IEnumerable<HealthSignal> signals)
    {
        var values = signals.Select(s => (s.Timestamp, s.CurrentValue)).ToList();
        if (values.Count < 3)
            return TrendAnalysis.Insufficient;

        // Linear regression
        var (slope, intercept, rSquared) = LinearRegression(values);

        return new TrendAnalysis
        {
            Slope = slope,
            Intercept = intercept,
            Confidence = rSquared,
            Direction = slope > 0.01 ? TrendDirection.Increasing :
                       slope < -0.01 ? TrendDirection.Decreasing :
                       TrendDirection.Stable
        };
    }
}

public sealed record FailurePrediction
{
    public Guid DeploymentId { get; init; }
    public DateTimeOffset PredictedAt { get; init; }
    public double FailureLikelihood { get; init; }  // 0.0 - 1.0
    public FailureType? PredictedFailureType { get; init; }
    public TimeSpan? EstimatedTimeToFailure { get; init; }
    public ImmutableArray<string> EarlyWarningSignals { get; init; }
    public RecommendedAction? RecommendedAction { get; init; }
}

public enum FailureType
{
    ErrorRateExceeded,
    LatencyDegraded,
    ThroughputDrop,
    ResourceExhaustion,
    MemoryLeak,
    ConnectionPoolExhaustion,
    CascadingFailure
}
```

#### 6. ImpactAnalyzer

Analyzes rollback impact before execution:

```csharp
public sealed class ImpactAnalyzer
{
    public async Task<RollbackImpactAnalysis> AnalyzeAsync(
        RollbackRequest request,
        CancellationToken ct)
    {
        var analysis = new RollbackImpactAnalysis
        {
            RequestId = request.Id,
            AnalyzedAt = _timeProvider.GetUtcNow()
        };

        // 1. Identify affected components
        var currentRelease = await _releaseStore.GetAsync(request.CurrentReleaseId, ct);
        var targetRelease = await _releaseStore.GetAsync(request.TargetReleaseId, ct);

        analysis.AffectedComponents = currentRelease.Components
            .Where(c => targetRelease.Components.Any(tc =>
                tc.Name == c.Name && tc.Digest != c.Digest))
            .Select(c => new AffectedComponent
            {
                Name = c.Name,
                CurrentDigest = c.Digest,
                TargetDigest = targetRelease.Components.First(tc => tc.Name == c.Name).Digest,
                ChangeType = DetermineChangeType(c, targetRelease)
            })
            .ToImmutableArray();

        // 2. Analyze downstream dependencies
        var dependencyGraph = await _dependencyStore.GetGraphAsync(
            request.EnvironmentId, ct);

        foreach (var component in analysis.AffectedComponents)
        {
            var dependents = dependencyGraph.GetDependents(component.Name);
            analysis.DownstreamImpact.Add(component.Name, new DependencyImpact
            {
                DirectDependents = dependents.Direct.Count,
                TransitiveDependents = dependents.Transitive.Count,
                CriticalPathComponents = dependents.OnCriticalPath.ToImmutableArray()
            });
        }

        // 3. Estimate downtime
        analysis.EstimatedDowntime = EstimateDowntime(analysis.AffectedComponents, request.Strategy);

        // 4. Risk assessment
        analysis.RiskLevel = AssessRisk(analysis);
        analysis.RiskFactors = IdentifyRiskFactors(analysis);

        // 5. Data migration considerations
        analysis.DataMigrationRequired = await CheckDataMigrationAsync(
            currentRelease, targetRelease, ct);

        // 6. Feature flag impact
        analysis.FeatureFlagImpact = await AnalyzeFeatureFlagImpactAsync(
            currentRelease, targetRelease, ct);

        // 7. Generate recommendation
        analysis.Recommendation = GenerateRecommendation(analysis);

        return analysis;
    }

    private RollbackRisk AssessRisk(RollbackImpactAnalysis analysis)
    {
        var riskScore = 0;

        // Component count
        riskScore += analysis.AffectedComponents.Length * 10;

        // Downstream impact
        var totalDependents = analysis.DownstreamImpact.Values.Sum(d => d.TransitiveDependents);
        riskScore += totalDependents * 5;

        // Data migration
        if (analysis.DataMigrationRequired)
            riskScore += 50;

        // Critical path
        var criticalPathCount = analysis.DownstreamImpact.Values
            .Sum(d => d.CriticalPathComponents.Length);
        riskScore += criticalPathCount * 20;

        return riskScore switch
        {
            < 20 => RollbackRisk.Low,
            < 50 => RollbackRisk.Medium,
            < 100 => RollbackRisk.High,
            _ => RollbackRisk.Critical
        };
    }
}

public sealed record RollbackImpactAnalysis
{
    public Guid RequestId { get; init; }
    public DateTimeOffset AnalyzedAt { get; init; }

    // What's changing
    public ImmutableArray<AffectedComponent> AffectedComponents { get; init; }

    // Who's affected
    public ImmutableDictionary<string, DependencyImpact> DownstreamImpact { get; init; }

    // How long
    public TimeSpan EstimatedDowntime { get; init; }

    // How risky
    public RollbackRisk RiskLevel { get; init; }
    public ImmutableArray<RiskFactor> RiskFactors { get; init; }

    // Special considerations
    public bool DataMigrationRequired { get; init; }
    public DataMigrationAnalysis? DataMigration { get; init; }
    public FeatureFlagImpact? FeatureFlagImpact { get; init; }

    // Recommendation
    public RollbackRecommendation Recommendation { get; init; }
}

public sealed record RollbackRecommendation
{
    public RollbackDecision Decision { get; init; }
    public string Rationale { get; init; }
    public ImmutableArray<string> Warnings { get; init; }
    public ImmutableArray<string> Prerequisites { get; init; }
    public RollbackStrategy SuggestedStrategy { get; init; }
}
```

#### 7. PartialRollbackPlanner

Plans rollback of specific components:

```csharp
public sealed class PartialRollbackPlanner
{
    public async Task<PartialRollbackPlan> PlanAsync(
        PartialRollbackRequest request,
        CancellationToken ct)
    {
        var currentRelease = await _releaseStore.GetAsync(request.CurrentReleaseId, ct);
        var dependencyGraph = await _dependencyStore.GetGraphAsync(request.EnvironmentId, ct);

        var plan = new PartialRollbackPlan
        {
            Id = Guid.NewGuid(),
            CreatedAt = _timeProvider.GetUtcNow(),
            RequestedComponents = request.ComponentsToRollback,
            TargetDigests = new Dictionary<string, string>()
        };

        // 1. Determine which components to actually rollback
        var componentsToRollback = new HashSet<string>(request.ComponentsToRollback);

        // 2. Check for required co-rollbacks (tight coupling)
        foreach (var component in request.ComponentsToRollback)
        {
            var requiredCoRollbacks = dependencyGraph.GetRequiredCoRollbacks(component);
            foreach (var required in requiredCoRollbacks)
            {
                if (!componentsToRollback.Contains(required))
                {
                    componentsToRollback.Add(required);
                    plan.AutoIncludedComponents.Add(required, $"Required by {component}");
                }
            }
        }

        // 3. Find target digests for each component
        foreach (var component in componentsToRollback)
        {
            var history = await _deploymentHistoryStore.GetComponentHistoryAsync(
                request.EnvironmentId, component, ct);

            // Find last known good version
            var targetVersion = history
                .Where(h => h.Status == DeploymentStatus.Succeeded)
                .Where(h => !request.ExcludeDigests.Contains(h.Digest))
                .OrderByDescending(h => h.DeployedAt)
                .Skip(request.VersionsBack - 1)  // Default: 1 (previous)
                .FirstOrDefault();

            if (targetVersion == null)
            {
                plan.CannotRollback.Add(component, "No previous good version found");
                continue;
            }

            plan.TargetDigests[component] = targetVersion.Digest;
            plan.RollbackDetails.Add(new ComponentRollbackDetail
            {
                ComponentName = component,
                CurrentDigest = currentRelease.Components.First(c => c.Name == component).Digest,
                TargetDigest = targetVersion.Digest,
                TargetDeployedAt = targetVersion.DeployedAt,
                VersionsBack = request.VersionsBack
            });
        }

        // 4. Validate compatibility
        var compatibility = await ValidateCompatibilityAsync(plan, ct);
        plan.CompatibilityValidation = compatibility;

        // 5. Determine execution order
        plan.ExecutionOrder = DetermineExecutionOrder(plan, dependencyGraph);

        return plan;
    }

    private ImmutableArray<string> DetermineExecutionOrder(
        PartialRollbackPlan plan,
        DependencyGraph graph)
    {
        // Topological sort based on dependencies
        // Rollback dependents before dependencies
        var sorted = new List<string>();
        var visited = new HashSet<string>();

        void Visit(string component)
        {
            if (visited.Contains(component))
                return;

            visited.Add(component);

            var dependents = graph.GetDependents(component).Direct;
            foreach (var dependent in dependents.Where(d => plan.TargetDigests.ContainsKey(d)))
            {
                Visit(dependent);
            }

            sorted.Add(component);
        }

        foreach (var component in plan.TargetDigests.Keys)
        {
            Visit(component);
        }

        return sorted.ToImmutableArray();
    }
}

public sealed record PartialRollbackPlan
{
    public Guid Id { get; init; }
    public DateTimeOffset CreatedAt { get; init; }

    // Input
    public ImmutableArray<string> RequestedComponents { get; init; }

    // Analysis
    public ImmutableDictionary<string, string> AutoIncludedComponents { get; init; }
    public ImmutableDictionary<string, string> CannotRollback { get; init; }

    // Plan
    public ImmutableDictionary<string, string> TargetDigests { get; init; }
    public ImmutableArray<ComponentRollbackDetail> RollbackDetails { get; init; }
    public ImmutableArray<string> ExecutionOrder { get; init; }

    // Validation
    public CompatibilityValidation CompatibilityValidation { get; init; }
}
```

#### 8. RollbackDecider

Makes automated rollback decisions:

```csharp
public sealed class RollbackDecider
{
    public async Task<RollbackDecision> DecideAsync(
        Guid deploymentId,
        HealthAnalysis healthAnalysis,
        FailurePrediction? prediction,
        AutoRollbackPolicy policy,
        CancellationToken ct)
    {
        var decision = new RollbackDecision
        {
            DeploymentId = deploymentId,
            DecidedAt = _timeProvider.GetUtcNow(),
            HealthAnalysis = healthAnalysis,
            Prediction = prediction,
            Policy = policy
        };

        // Check if auto-rollback is enabled
        if (!policy.Enabled)
        {
            decision.Action = RollbackAction.NotifyOnly;
            decision.Reason = "Auto-rollback disabled by policy";
            return decision;
        }

        // Check maintenance window
        if (!IsWithinRollbackWindow(policy))
        {
            decision.Action = RollbackAction.DeferToWindow;
            decision.Reason = "Outside auto-rollback window";
            decision.DeferredUntil = GetNextRollbackWindowStart(policy);
            return decision;
        }

        // Evaluate health signals against policy thresholds
        var criticalSignals = healthAnalysis.Signals
            .Where(s => s.Status == SignalStatus.Critical)
            .ToList();

        var warningSignals = healthAnalysis.Signals
            .Where(s => s.Status == SignalStatus.Warning)
            .ToList();

        // Critical signals: immediate rollback
        if (criticalSignals.Any())
        {
            decision.Action = RollbackAction.ImmediateRollback;
            decision.Reason = $"Critical health signals: {string.Join(", ", criticalSignals.Select(s => s.Name))}";
            decision.TriggeringSignals = criticalSignals.ToImmutableArray();
            decision.SuggestedStrategy = RollbackStrategy.AllAtOnce;
            return decision;
        }

        // Predictive rollback
        if (prediction != null &&
            prediction.FailureLikelihood >= policy.PredictiveThreshold &&
            prediction.EstimatedTimeToFailure < policy.PredictiveWindow)
        {
            decision.Action = RollbackAction.PreemptiveRollback;
            decision.Reason = $"Predicted failure ({prediction.FailureLikelihood:P0} confidence) " +
                            $"within {prediction.EstimatedTimeToFailure}";
            decision.SuggestedStrategy = RollbackStrategy.Rolling;
            return decision;
        }

        // Warning signals: check duration
        if (warningSignals.Any())
        {
            var oldestWarning = warningSignals.Min(s => s.Timestamp);
            var warningDuration = _timeProvider.GetUtcNow() - oldestWarning;

            if (warningDuration >= policy.WarningGracePeriod)
            {
                decision.Action = RollbackAction.GracefulRollback;
                decision.Reason = $"Warning signals persisted for {warningDuration}";
                decision.TriggeringSignals = warningSignals.ToImmutableArray();
                decision.SuggestedStrategy = RollbackStrategy.Rolling;
                return decision;
            }
            else
            {
                decision.Action = RollbackAction.Monitor;
                decision.Reason = $"Warning signals detected, monitoring for {policy.WarningGracePeriod - warningDuration}";
                return decision;
            }
        }

        // All healthy
        decision.Action = RollbackAction.None;
        decision.Reason = "All health signals within acceptable thresholds";
        return decision;
    }
}

public sealed record RollbackDecision
{
    public Guid DeploymentId { get; init; }
    public DateTimeOffset DecidedAt { get; init; }
    public RollbackAction Action { get; init; }
    public string Reason { get; init; }
    public HealthAnalysis HealthAnalysis { get; init; }
    public FailurePrediction? Prediction { get; init; }
    public ImmutableArray<HealthSignal>? TriggeringSignals { get; init; }
    public RollbackStrategy? SuggestedStrategy { get; init; }
    public DateTimeOffset? DeferredUntil { get; init; }
    public AutoRollbackPolicy Policy { get; init; }
}

public enum RollbackAction
{
    None,               // No action needed
    Monitor,            // Continue monitoring
    NotifyOnly,         // Alert but don't rollback
    DeferToWindow,      // Wait for rollback window
    GracefulRollback,   // Rolling rollback
    PreemptiveRollback, // Rollback before predicted failure
    ImmediateRollback   // Emergency rollback
}
```

---

## Auto-Rollback Policy

```csharp
public sealed record AutoRollbackPolicy
{
    public Guid Id { get; init; }
    public string Name { get; init; }
    public Guid EnvironmentId { get; init; }

    // Enable/disable
    public bool Enabled { get; init; }

    // Thresholds
    public double ErrorRateCriticalThreshold { get; init; }   // e.g., 0.10 (10%)
    public double ErrorRateWarningThreshold { get; init; }    // e.g., 0.05 (5%)
    public double LatencyP95CriticalThreshold { get; init; }  // e.g., 5000ms
    public double LatencyP95WarningThreshold { get; init; }   // e.g., 2000ms

    // Grace periods
    public TimeSpan WarningGracePeriod { get; init; }         // e.g., 5 minutes

    // Predictive settings
    public double PredictiveThreshold { get; init; }          // e.g., 0.80 (80% confidence)
    public TimeSpan PredictiveWindow { get; init; }           // e.g., 10 minutes

    // Rollback window
    public TimeOnly RollbackWindowStart { get; init; }        // e.g., 00:00
    public TimeOnly RollbackWindowEnd { get; init; }          // e.g., 23:59
    public ImmutableArray<DayOfWeek> RollbackDays { get; init; }

    // Notifications
    public NotificationConfig Notifications { get; init; }

    // Manual override
    public bool RequireApprovalForProduction { get; init; }
}
```

---

## API Design

### REST Endpoints

```
# Health Analysis
GET    /api/v1/deployments/{id}/health                    # Get current health
GET    /api/v1/deployments/{id}/health/history            # Health history
GET    /api/v1/deployments/{id}/baselines                 # List baselines
POST   /api/v1/deployments/{id}/baselines                 # Create baseline

# Predictions
GET    /api/v1/deployments/{id}/predictions               # Get failure predictions

# Impact Analysis
POST   /api/v1/rollback/analyze                           # Analyze rollback impact
POST   /api/v1/rollback/partial/analyze                   # Analyze partial rollback

# Auto-Rollback Policies
POST   /api/v1/rollback/policies                          # Create policy
GET    /api/v1/rollback/policies                          # List policies
PUT    /api/v1/rollback/policies/{id}                     # Update policy
DELETE /api/v1/rollback/policies/{id}                     # Delete policy

# Rollback Execution
POST   /api/v1/rollback/execute                           # Execute full rollback
POST   /api/v1/rollback/partial/execute                   # Execute partial rollback
POST   /api/v1/rollback/{id}/approve                      # Approve pending rollback
POST   /api/v1/rollback/{id}/cancel                       # Cancel rollback

# History
GET    /api/v1/rollback/history                           # Rollback history
GET    /api/v1/rollback/history/{id}                      # Rollback details
GET    /api/v1/rollback/history/{id}/evidence             # Rollback evidence
```

---

## Metrics & Observability

### Prometheus Metrics

```
# Health Analysis
stella_deployment_health_status{deployment_id, environment, status}
stella_deployment_health_signal{deployment_id, signal_name, status}
stella_deployment_health_analysis_duration_seconds

# Predictions
stella_failure_prediction_likelihood{deployment_id, failure_type}
stella_failure_prediction_time_to_failure_seconds{deployment_id}
stella_failure_predictions_total{outcome}  # correct, false_positive, missed

# Rollback Decisions
stella_rollback_decisions_total{action, environment}
stella_rollback_decision_confidence{deployment_id}

# Rollback Execution
stella_rollback_executions_total{type, strategy, status}
stella_rollback_duration_seconds{type, strategy}
stella_rollback_components_total{type, status}

# Impact
stella_rollback_impact_components{deployment_id}
stella_rollback_impact_dependents{deployment_id}
stella_rollback_impact_risk_level{deployment_id, level}
```

---

## Evidence Generation

Every rollback decision and execution produces evidence:

```csharp
public sealed record RollbackEvidence
{
    // Decision context
    public HealthAnalysis HealthAnalysis { get; init; }
    public FailurePrediction? Prediction { get; init; }
    public RollbackDecision Decision { get; init; }

    // Impact analysis
    public RollbackImpactAnalysis ImpactAnalysis { get; init; }

    // Execution
    public RollbackPlan Plan { get; init; }
    public RollbackResult Result { get; init; }

    // Audit
    public string InitiatedBy { get; init; }  // "system:auto" or user ID
    public string? ApprovedBy { get; init; }
    public DateTimeOffset InitiatedAt { get; init; }
    public DateTimeOffset CompletedAt { get; init; }
}
```

---

## Configuration Example

```yaml
auto_rollback_policy:
  name: "production-auto-rollback"
  environment_id: "prod-001"
  enabled: true

  thresholds:
    error_rate:
      critical: 0.10    # 10% error rate
      warning: 0.05     # 5% error rate
    latency_p95:
      critical: 5000    # 5 seconds
      warning: 2000     # 2 seconds
    throughput_drop:
      critical: 0.50    # 50% drop
      warning: 0.25     # 25% drop

  grace_periods:
    warning: "00:05:00"  # 5 minutes

  predictive:
    enabled: true
    threshold: 0.80      # 80% confidence
    window: "00:10:00"   # 10 minute lookahead

  rollback_window:
    enabled: false       # Allow 24/7 for production
    days: [monday, tuesday, wednesday, thursday, friday, saturday, sunday]

  notifications:
    on_warning: true
    on_rollback_initiated: true
    on_rollback_completed: true
    channels:
      - type: slack
        channel: "#prod-alerts"
      - type: pagerduty
        severity: critical

  approval:
    require_for_production: false  # Auto-rollback without approval
```

---

## Test Strategy

### Unit Tests
- Severity calculation for various health signals
- Baseline comparison logic
- Anomaly detection algorithms
- Impact analysis calculations

### Integration Tests
- Full health analysis pipeline
- Predictive engine with historical data
- Partial rollback planning
- Auto-rollback decision flow

### Chaos Tests
- Metrics source failures during analysis
- Database unavailability
- Concurrent rollback requests

### Golden Tests
- Deterministic health scoring
- Deterministic impact analysis
- Evidence packet structure

---

## Migration Path

### Phase 1: Metrics Collection (Week 1-2)
- Metrics collector implementation
- Prometheus/Datadog sources
- Baseline manager

### Phase 2: Health Analysis (Week 3-4)
- Health analyzer
- Signal evaluation
- Anomaly detection

### Phase 3: Impact Analysis (Week 5-6)
- Impact analyzer
- Dependency graph integration
- Risk assessment

### Phase 4: Partial Rollback (Week 7-8)
- Partial rollback planner
- Compatibility validation
- Execution order

### Phase 5: Predictive Engine (Week 9-10)
- Trend analysis
- Pattern matching
- Failure prediction

### Phase 6: Auto-Rollback (Week 11-12)
- Rollback decider
- Policy management
- Automated execution