Performance Bottleneck Identifier

Identify performance bottlenecks through code-level profiling analysis, hot path detection, resource constraint mapping, and throughput limiter identification.

Guiding Principle

"Optimize the bottleneck. Everything else is noise until the constraint moves."

Procedure

Step 1 — Hot Path Detection

1. Trace the critical request path from entry point to response.
2. Identify synchronous blocking points in async codebases.
3. Map I/O operations: database queries, HTTP calls, file system access on the critical path.
4. Detect serialized operations that could be parallelized.
5. Flag computational hotspots: large data transformations, sorting, serialization [HECHO].

Step 2 — Resource Constraint Analysis

1. Identify CPU-bound operations: heavy computation, encryption, compression.
2. Find memory-bound operations: large object allocation, buffer copying, cache size.
3. Detect I/O-bound operations: disk reads, network calls, database round-trips.
4. Check for thread/connection pool exhaustion patterns.
5. Map resource contention: locks, mutexes, shared state between request handlers [HECHO].

Step 3 — Throughput Limiter Identification

1. Calculate theoretical throughput based on resource constraints.
2. Identify the single biggest constraint (Theory of Constraints).
3. Check for backpressure mechanisms: what happens when the system is overloaded?
4. Assess queue depths and processing rates for async workloads.
5. Detect cascading failures: when one bottleneck causes others to degrade.

Step 4 — Bottleneck Report

1. Rank bottlenecks by impact on user-facing latency.
2. Provide specific optimization recommendations per bottleneck.
3. Estimate improvement potential for each fix.
4. Produce a latency breakdown diagram showing time spent in each component.

Quality Criteria

• Bottlenecks identified on actual critical paths, not theoretical [HECHO]
• Resource constraints specified with type (CPU/memory/I/O/network)
• Optimization estimates include reasoning [INFERENCIA]
• Theory of Constraints applied to identify the single biggest limiter

Anti-Patterns

• Optimizing non-bottleneck code (no improvement until the constraint moves)
• Profiling only in development without production-like data volumes
• Treating all slow queries equally without checking if they're on the hot path
• Adding caching without understanding invalidation requirements