> ## Documentation Index
> Fetch the complete documentation index at: https://enterprise-docs.dify.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Performance Tuning

## Display Helm Chart Values

```bash theme={null}
helm show values dify/dify
```

## 1. Improve Resource Allocation

* You can improve the performance of Dify by adjusting the resource allocation for services in the Helm chart values file.
* You can increase these values based on your environment and available resources.
* Recommended configuration for each component:

| Category         | Component            | Replicas | Request CPU | Request Mem | Limit CPU | Limit Mem | Notes     |
| ---------------- | -------------------- | -------- | ----------- | ----------- | --------- | --------- | --------- |
| Core Application | API                  | 6        | 1           | 1 GB        | 1         | 2 GB      | ①         |
|                  | Worker               | 2        | 4           | 4 GB        | 4         | 8 GB      | ②         |
|                  | Worker Beat          | 1        | 1           | 2 GB        | 2         | 4 GB      |           |
|                  | Web                  | 1        | 0.5         | 1 GB        | 1         | 2 GB      |           |
|                  | Sandbox              | 1        | 2           | 2 GB        | 2         | 4 GB      | ③         |
| Enterprise       | Enterprise           | 1        | 2           | 2 GB        | 2         | 2 GB      |           |
|                  | Enterprise\_Audit    | 1        | 1           | 2 GB        | 2         | 4 GB      |           |
|                  | Enterprise\_Frontend | 1        | 1           | 2 GB        | 1         | 2 GB      |           |
| Plugin           | Plugin Daemon        | 1        | 1           | 2 GB        | 2         | 4 GB      |           |
|                  | Plugin Controller    | 1        | 0.5         | 1 GB        | 1         | 2 GB      |           |
|                  | Plugin Connector     | 1        | 1           | 2 GB        | 1         | 2 GB      |           |
|                  | Plugin Manager       | 1        | 1           | 2 GB        | 2         | 4 GB      |           |
| Infrastructure   | SSRF Proxy           | 1        | 0.5         | 0.5 GB      | 1         | 1 GB      |           |
|                  | Gateway              | 1        | 1           | 2 GB        | 2         | 4 GB      |           |
|                  | Unstructured         | -        | -           | -           | -         | -         | As needed |
|                  | MinIO                | -        | -           | -           | -         | -         | As needed |

**Notes:**

* ① **API**: Scale replicas horizontally as needed
* ② **Worker**: Scale replicas horizontally as needed (if there are many files to upload)
* ③ **Sandbox**: Scale replicas horizontally as needed (if there are many compute tasks)
  * `maxWorkers`: 4 (number of worker processes)
  * `workerTimeout`: 15 (call timeout)

**Configuration Example:**

```yaml theme={null}
api:
  replicas: 6
  resources:
    requests:
      cpu: 1
      memory: 1Gi
    limits:
      cpu: 1
      memory: 2Gi

worker:
  replicas: 2
  resources:
    requests:
      cpu: 4
      memory: 4Gi
    limits:
      cpu: 4
      memory: 8Gi

sandbox:
  replicas: 1
  maxWorkers: 4
  workerTimeout: 15
  resources:
    requests:
      cpu: 2
      memory: 2Gi
    limits:
      cpu: 2
      memory: 4Gi
```

## 2. Improve External PostgreSQL Performance

### 2.1 Calculate Database Maximum Connections

When configuring the database, you need to calculate the required maximum connections using the following formula:

```
Max Connections = (SQLALCHEMY_POOL_SIZE + SQLALCHEMY_MAX_OVERFLOW) × API Workers × API Replicas
                + (SQLALCHEMY_POOL_SIZE + SQLALCHEMY_MAX_OVERFLOW) × Worker Workers × Worker Replicas
```

**Parameters:**

* `SQLALCHEMY_POOL_SIZE`: Database connection pool size per worker
* `SQLALCHEMY_MAX_OVERFLOW`: Maximum additional connections when pool overflows
* `API Workers`: API service's `serverWorkerAmount`
* `Worker Workers`: Worker service's `celeryWorkerAmount`

**Calculation Example:**

Assuming the following configuration:

* API: replicas=6, serverWorkerAmount=1
* Worker: replicas=2, celeryWorkerAmount=1
* SQLALCHEMY\_POOL\_SIZE=100
* SQLALCHEMY\_MAX\_OVERFLOW=150

The maximum connections would be:

```
(100 + 150) × 1 × 6 + (100 + 150) × 1 × 2 = 1500 + 500 = 2000
```

<Warning>
  It is recommended to reserve 20-30% headroom based on the calculation result to handle traffic spikes. In the above example, set `max_connections` to 2400-2600.
</Warning>

### 2.2 Complete Configuration Example

```yaml theme={null}
api:
  replicas: 6
  serverWorkerAmount: 1
  extraEnv:
    - name: SQLALCHEMY_POOL_SIZE
      value: "100"
    - name: SQLALCHEMY_MAX_OVERFLOW
      value: "150"
  resources:
    requests:
      cpu: 1
      memory: 1Gi
    limits:
      cpu: 1
      memory: 2Gi
```

## 3. Performance Monitoring Recommendations

### 3.1 Key Metrics

Monitor the following metrics to ensure the system is running well:

**Database Connections:**

* Current active connections
* Connection pool utilization
* Requests waiting for connections

**Resource Usage:**

* CPU utilization (recommended to keep below 70%)
* Memory utilization (recommended to keep below 80%)
* Disk I/O

**Application Performance:**

* API response time
* Worker task queue length
* Task execution time

### 3.2 Common Performance Bottlenecks

| Symptom                        | Possible Cause               | Solution                                              |
| ------------------------------ | ---------------------------- | ----------------------------------------------------- |
| Slow API response              | Insufficient API replicas    | Increase API replicas                                 |
| Task backlog                   | Insufficient Worker capacity | Increase Worker replicas or celeryWorkerAmount        |
| Database connection exhaustion | Insufficient connections     | Increase max\_connections or optimize connection pool |
| Out of memory                  | Memory limit too low         | Increase memory limits                                |
| CPU throttling                 | CPU limit too low            | Increase CPU limits                                   |