Expert guide for diagnosing and fixing Odoo performance issues: slow queries, worker configuration, memory limits, PostgreSQL tuning, and profiling tools.
Install with the open skills CLI (global, non-interactive — available in every Claude Code session):
npx skills add sickn33/agentic-awesome-skills --skill "odoo-performance-tuner" -g -a claude-code -yOr manually — copy the SKILL.md below into:
~/.claude/skills/odoo-performance-tuner-sickn33/SKILL.md---
name: odoo-performance-tuner
description: "Expert guide for diagnosing and fixing Odoo performance issues: slow queries, worker configuration, memory limits, PostgreSQL tuning, and profiling tools."
risk: safe
source: "self"
---
# Odoo Performance Tuner
## Overview
This skill helps diagnose and resolve Odoo performance problems — from slow page loads and database bottlenecks to worker misconfiguration and memory bloat. It covers PostgreSQL query tuning, Odoo worker settings, and built-in profiling tools.
## When to Use This Skill
- Odoo is slow in production (slow page loads, timeouts).
- Getting `MemoryError` or `Worker timeout` errors in logs.
- Diagnosing a slow database query using Odoo's profiler.
- Tuning `odoo.conf` for a specific server spec.
## How It Works
1. **Activate**: Mention `@odoo-performance-tuner` and describe your performance issue.
2. **Diagnose**: Share relevant log lines or config and receive a root cause analysis.
3. **Fix**: Get exact configuration changes with explanations.
## Examples
### Example 1: Recommended Worker Configuration
```ini
# odoo.conf — tuned for a 4-core, 8GB RAM server
workers = 9 # (CPU_cores × 2) + 1 — never set to 0 in production
max_cron_threads = 2 # background cron jobs; keep ≤ 2 to preserve user-facing capacity
limit_memory_soft = 1610612736 # 1.5 GB — worker is recycled gracefully after this
limit_memory_hard = 2147483648 # 2.0 GB — worker is killed immediately; prevents OOM crashes
limit_time_cpu = 600 # max CPU seconds per request
limit_time_real = 1200 # max wall-clock seconds per request
limit_request = 8192 # max requests before worker recycles (prevents memory leaks)
```
### Example 2: Find Slow Queries with PostgreSQL
```sql
-- Step 1: Enable pg_stat_statements extension (run once as postgres superuser)
CREATE EXTENSION IF NOT EXISTS pg_stat_statements;
-- Step 2: Also add to postgresql.conf and reload:
-- shared_preload_libraries = 'pg_stat_statements'
-- log_min_duration_statement = 1000 -- log queries taking > 1 second
-- Step 3: Find the top 10 slowest average queries
SELECT
LEFT(query, 100) AS query_snippet,
round(mean_exec_time::numeric, 2) AS avg_ms,
calls,
round(total_exec_time::numeric, 2) AS total_ms
FROM pg_stat_statements
ORDER BY mean_exec_time DESC
LIMIT 10;
-- Step 4: Check for missing indexes causing full table scans
SELECT schemaname, tablename, attname, n_distinct, correlation
FROM pg_stats
WHERE tablename = 'sale_order_line'
AND correlation < 0.5 -- low correlation = poor index efficiency
ORDER BY n_distinct DESC;
```
### Example 3: Use Odoo's Built-In Profiler
```text
Prerequisites: Run Odoo with ?debug=1 in the URL to enable debug mode.
Menu: Settings → Technical → Profiling
Steps:
1. Click "Enable Profiling" — set a duration (e.g., 60 seconds)
2. Navigate to and reproduce the slow action
3. Return to Settings → Technical → Profiling → View Results
What to look for:
- Total SQL queries > 100 on a single page → N+1 query problem
- Single queries taking > 100ms → missing DB index
- Same query repeated many times → missing cache, use @ormcache
- Python time high but SQL low → compute field inefficiency
```
## Best Practices
- ✅ **Do:** Use `mapped()`, `filtered()`, and `sorted()` on in-memory recordsets — they don't trigger additional SQL.
- ✅ **Do:** Add PostgreSQL B-tree indexes on columns frequently used in domain filters (`partner_id`, `state`, `date_order`).
- ✅ **Do:** Enable Odoo's HTTP caching for static assets and put a CDN (Cloudflare, AWS CloudFront) in front of the website.
- ✅ **Do:** Use `@tools.ormcache` decorator on methods pulled repeatedly with the same arguments.
- ❌ **Don't:** Set `workers = 0` in production — single-threaded mode serializes all requests and blocks all users on any slow operation.
- ❌ **Don't:** Ignore `limit_memory_soft` — workers exceeding it are recycled between requests; without the limit they grow unbounded and crash.
- ❌ **Don't:** Directly manipulate `prefetch_ids` on recordsets — rely on Odoo's automatic batch prefetching, which activates by default.
## Limitations
- PostgreSQL tuning (`shared_buffers`, `work_mem`, `effective_cache_size`) is highly server-specific and not covered in depth here — use [PGTune](https://pgtune.leopard.in.ua/) as a starting baseline.
- The built-in Odoo profiler only captures **Python + SQL** traces; JavaScript rendering performance requires browser DevTools.
- **Odoo.sh** managed hosting restricts direct PostgreSQL and `odoo.conf` access — some tuning options are unavailable.
- Does not cover **Redis-based session store** or **Celery task queue** optimizations, which are advanced patterns for very high-traffic instances.
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when implementing any feature or bugfix, before writing implementation code