AWS Free Instance Issues

User
Aws free instance yarn run Dev pm command cause server unreachable some time
Assistant
Running resource-intensive commands like `yarn run dev` on an AWS free-tier instance can cause performance issues or even make the server temporarily unreachable. This typically happens because the free-tier instances, such as `t2.micro` or `t4g.micro`, have limited CPU, memory, and I/O resources, which are insufficient for heavy tasks.

### Possible Causes:
1. **Resource Overload**:
– `yarn run dev` involves building and serving assets, which consumes significant CPU and memory.
– If the instance is already running a web server, database, and other services, resource contention can cause it to become unresponsive.

2. **Network Throttling**:
– The free-tier instances have limited bandwidth, which might be strained during development.

3. **Swap Space Not Configured**:
– Without swap space, high memory usage leads to the system killing processes or becoming unresponsive.

### Solutions

#### 1. **Optimize Development Setup**
– **Run Dev Commands Locally**: Use a local development environment instead of the AWS instance for running `yarn run dev`. Sync your changes to the instance only when necessary.
– **Use Build Tools Only When Needed**: Run `yarn build` for production-ready assets instead of keeping `yarn dev` running.

#### 2. **Increase Instance Capacity**
– Upgrade to an instance with more resources, such as `t3.medium` or `t3a.medium`. These instances offer better performance but incur additional costs.

#### 3. **Add Swap Space**
– Create swap space to prevent the system from crashing due to high memory usage:

sudo fallocate -l 2G /swapfile
  sudo chmod 600 /swapfile
  sudo mkswap /swapfile
  sudo swapon /swapfile

Add it to `/etc/fstab` to make it persistent:

echo '/swapfile swap swap defaults 0 0' | sudo tee -a /etc/fstab

#### 4. **Use Docker for Resource Isolation**
– Run `yarn dev` inside a Docker container. This isolates resource usage and may prevent the host from becoming unresponsive.

#### 5. **Monitor Server Resources**
– Use tools like `htop` or `top` to monitor resource usage:

sudo apt install htop
  htop

Identify processes consuming excessive CPU or memory and optimize accordingly.

#### 6. **Offload Static Asset Serving**
– Configure a CDN like Cloudflare to serve static assets, reducing the load on your instance.

Let me know if you'd like detailed guidance on any of these steps!

User
Yarn run build take lot of time I'm aws ssh
Assistant
If `yarn run build` takes a long time on your AWS instance, it’s likely due to the resource constraints of the instance, particularly on AWS free-tier instances like `t2.micro` or `t4g.micro`. Here are some strategies to optimize and improve the performance:

### 1. **Optimize the Build Process**
#### a. **Enable Production Mode**
Ensure the build process is optimized for production to reduce unnecessary work. Run:

NODE_ENV=production yarn run build

#### b. **Reduce Dependencies**
– **Tree Shaking**: Ensure your build process removes unused code.
– **Bundle Analyzer**: Use a tool like `webpack-bundle-analyzer` to identify large dependencies:

yarn add webpack-bundle-analyzer
  yarn run analyze

### 2. **Upgrade Your AWS Instance**
The default free-tier instances are underpowered for build tasks. Consider upgrading to a more powerful instance temporarily:
– Use a `t3.medium` or higher, which has more vCPUs and memory.
– After the build, you can downgrade back to a free-tier instance to save costs.

### 3. **Run Builds Locally**
Instead of building on the AWS instance, build assets on your local machine and upload them:
#### Steps:
1. Build on your local machine:

yarn run build

2. Upload the build folder to the AWS instance:

scp -i /path/to/your-key.pem -r ./dist ubuntu@<your-aws-ip>:/var/www/share/public

### 4. **Use a Remote Build Service**
#### a. **GitHub Actions/CI Pipelines**
Set up a CI/CD pipeline to build your application remotely and deploy it directly to the instance. Tools like GitHub Actions, GitLab CI, or CircleCI can do this.

#### b. **Third-Party Build Tools**
Use cloud build services like [Vercel](https://vercel.com) or [Netlify](https://www.netlify.com/) for the build process. You can sync the built assets to AWS.

### 5. **Optimize Docker (If Using Docker)**
If you’re building inside a Docker container:
– **Limit Resources**: Add resource constraints in `docker-compose.yml` to prevent the build from hogging all available resources.
– **Increase Swap Memory**: Ensure enough memory is available by adding swap space inside the container.

### 6. **Monitor Build Process**
Install tools like `htop` to monitor CPU and memory usage during the build:

sudo apt install htop
htop

Identify any bottlenecks and optimize them.

### 7. **Add Temporary Swap Space**
If the instance runs out of memory during the build:

sudo fallocate -l 2G /swapfile
sudo chmod 600 /swapfile
sudo mkswap /swapfile
sudo swapon /swapfile

This prevents memory crashes and improves performance.

### 8. **Alternative: Build in a Dedicated Environment**
– Use a dedicated build server with higher specs.
– Sync the built assets to AWS using `rsync` or `scp`.

Let me know which option suits your needs best, and I can provide more details on implementation!

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