odoo-performance-tuner
Expert guide for diagnosing and fixing Odoo performance issues: slow queries, worker configuration, memory limits, PostgreSQL tuning, and profiling tools.
Best use case
odoo-performance-tuner is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Expert guide for diagnosing and fixing Odoo performance issues: slow queries, worker configuration, memory limits, PostgreSQL tuning, and profiling tools.
Expert guide for diagnosing and fixing Odoo performance issues: slow queries, worker configuration, memory limits, PostgreSQL tuning, and profiling tools.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "odoo-performance-tuner" skill to help with this workflow task. Context: Expert guide for diagnosing and fixing Odoo performance issues: slow queries, worker configuration, memory limits, PostgreSQL tuning, and profiling tools.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/odoo-performance-tuner/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How odoo-performance-tuner Compares
| Feature / Agent | odoo-performance-tuner | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Expert guide for diagnosing and fixing Odoo performance issues: slow queries, worker configuration, memory limits, PostgreSQL tuning, and profiling tools.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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.Related Skills
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