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AI Performance Analyzer

The AI Performance Analyzer automatically analyses your application's query patterns, detects performance issues, and recommends improvements — all without modifying any code.

Quick Start

from aksara.ai.performance_analyzer import run_performance_analysis

report = run_performance_analysis()
print(f"Score: {report.score} ({report.grade})")
print(f"Issues: {report.issue_count}")
print(f"Recommendations: {report.recommendation_count}")

CLI

aksara ai flows performance           # Text summary
aksara ai flows performance --json    # JSON output
aksara ai flows performance --summary # Summary only
aksara ai flows performance --metrics # Include metrics
aksara ai flows performance --issues  # Include issues list

Studio UI

Open Aksara Studio and navigate to the Performance panel in the sidebar. Click Run Analysis to execute the full pipeline.

Pipeline Steps

Step Description
1 Load the Project Context Graph
2 Collect query data from graph queries, events, and diagnostics
3 Detect slow queries (execution time > 200 ms)
4 Detect N+1 patterns (repeated param-only queries > 5)
5 Detect query explosions (routes with > 10 queries)
6 Detect missing indexes (table-scan / seq-scan diagnostics)
7 Detect heavy joins (JOIN count > 3)
8 Detect route hotspots (routes with ≥ 2 slow queries)
9 Compute metrics (totals, averages, max queries per route)
10 Score and grade (penalty-based scoring, A–F grading)

Scoring

Starting from 100, each detected issue applies a penalty:

Category Penalty
Slow query −10
N+1 pattern −15
Missing index −10
Query explosion −10
Heavy join −5
Large payload −5
Route hotspot −10

Grades: A (90–100), B (80–89), C (70–79), D (60–69), F (< 60)

Data Models

  • PerformanceReport — Top-level report with score, grade, issues, recommendations, metrics, ok, elapsed_ms, generated_at.
  • PerformanceIssue — A detected issue with issue_id, severity, title, description, route, model, query, category.
  • PerformanceRecommendation — An improvement suggestion with recommendation_id, title, description, impact, related_issue_ids.
  • PerformanceMetrics — Computed metrics: total_routes, total_queries, slow_queries, n_plus_one_candidates, missing_indexes, avg_queries_per_route, max_queries_route.

Console Integration

Ask the AI console about performance:

  • "analyze performance"
  • "why is my app slow"
  • "find slow queries"
  • "n+1 query patterns"
  • "missing indexes"

Safety

The Performance Analyzer never modifies code, database, or files. It only returns analysis, issues, and recommendations.