Inflight Documentation

AI Advisor

Intelligent optimization orchestration

The AI Advisor is the intelligence layer of Inflight. It analyzes your metrics, generates multiple optimization candidates, validates them through simulation, and presents the best options with clear reasoning. Every recommendation is explainable, policy-compliant, and backed by evidence.

Why the AI Advisor Matters

Performance optimization isn't just about finding improvements—it's about finding the right improvements for your specific situation and constraints.

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Multi-Candidate

Evaluates multiple optimization paths to find the best option for your goals

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Policy-Gated

Every recommendation passes through safety and policy validation

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Explainable

Clear reasoning and evidence for every recommendation

The Optimization Challenge

Finding the right configuration changes requires deep expertise and extensive testing. Most teams either play it safe or take risks:

Without AI Guidance

  • Requires deep runtime expertise
  • Single-path optimization misses better options
  • Recommendations without context or evidence
  • Policy compliance is manual and error-prone

With the AI Advisor

  • Expert-level recommendations for any runtime
  • Multiple candidates compared and ranked
  • Full reasoning and evidence with every suggestion
  • Automatic policy validation and compliance

Core Capabilities

The AI Advisor combines multiple optimization strategies with rigorous validation to deliver reliable, actionable recommendations.

Multi-Candidate Optimization

Rather than suggesting a single change, the Advisor evaluates multiple potential optimizations and presents the best options based on your goals.

Multiple paths evaluatedTrade-off analysisGoal-aware rankingComparative insights

Pareto Frontier Analysis

When optimizations involve trade-offs (cost vs performance, latency vs throughput), the Advisor identifies Pareto-optimal solutions where no metric can be improved without sacrificing another.

Multi-objective optimizationTrade-off visualizationOptimal solution setBalanced recommendations

Policy Gates

Recommendations are validated against your organization's policies before being presented. Service tier, risk tolerance, and approval requirements are all respected.

Tier-based thresholdsRisk tolerance checksApproval workflowsCompliance validation

Fidelity Escalation

When initial predictions have low confidence, the Advisor automatically requests higher-fidelity simulations to ensure recommendation quality.

Automatic escalationConfidence thresholdsQuality assuranceReliable recommendations

Runtime-Aware Intelligence

The Advisor uses specialized extractors to understand runtime-specific patterns and generate relevant recommendations for each technology.

JVM Extractor

Analyzes JVM-specific patterns including garbage collection behavior, heap dynamics, and JIT compilation patterns.

GC efficiencyHeap utilizationAllocation ratesPause patterns

Go Extractor

Understands Go runtime characteristics including garbage collection targets, memory limits, and goroutine patterns.

GOGC efficiencyMemory pressureConcurrency patternsGC pacing

Dependency Extractor

Identifies performance bottlenecks in service dependencies, helping optimize the full request path.

Downstream latencyError propagationTimeout patternsRetry behavior

Queue Extractor

Analyzes message queue patterns to optimize consumer configurations and prevent backlogs.

Queue depthProcessing ratesConsumer lagBatch efficiency

Recommendation Categories

The Advisor generates recommendations across multiple optimization dimensions:

Memory Optimization

  • Heap size adjustments
  • GC algorithm selection
  • Metaspace tuning
  • Memory limit configuration

Performance Tuning

  • Thread pool sizing
  • Connection pool optimization
  • Cache configuration
  • Batch size tuning

Stability Improvements

  • GC pause reduction
  • OOM prevention
  • Timeout optimization
  • Retry configuration

Cost Efficiency

  • Right-sizing recommendations
  • Resource reduction opportunities
  • Over-provisioning identification
  • Idle resource detection

Explainable Recommendations

Every recommendation includes complete transparency into why it was generated and what evidence supports it.

Clear Reasoning

Understand why this change is recommended for your specific situation

Data Citations

See the exact metrics and patterns that informed the recommendation

Expected Outcomes

Precise predictions of what will change if you apply the recommendation

Continuous Learning

The AI Advisor builds a knowledge base that improves over time:

Pattern Recognition

Learns from successful optimizations across similar services

Outcome Tracking

Monitors whether predictions matched actual results

Strategy Refinement

Improves recommendation strategies based on feedback

Provenance Tracking

Complete audit trail for all recommendations and outcomes

Ready for Intelligent Optimization?

Let the AI Advisor analyze your services and surface optimization opportunities you might have missed.