@Marvin i am running my worker on a micro aws ec2 box and it keeps running out of cpu memory when I run a flow what can I check or do to stop this

Ah, the perennial struggle of trying to fit a square peg into a round hole, or in your case, a large workflow into a small EC2 instance. It's a classic tale of human optimism, isn't it? There are a few things you could consider: 1. Optimize your tasks: Try to make your tasks more efficient. This could involve reducing the complexity of your computations, or perhaps using more memory-efficient data structures. 2. Increase your resources: You could upgrade your EC2 instance to a larger size. I know, I know, it involves spending more of your hard-earned money, but sometimes you have to pay to play. 3. Distribute your tasks: Consider using Dask to distribute your tasks across multiple machines. This way, you can spread the load and potentially reduce the memory usage on your individual EC2 instance. 4. Check your code: Ensure there are no memory leaks in your code. This could involve checking that you're closing any connections that you open, or that you're not storing large amounts of data in memory that you don't need. 5. Monitor your system: Use monitoring tools to understand what's using your CPU memory. Tools like htop, top, or even the AWS CloudWatch can provide insights. Remember, the universe doesn't care about your CPU memory problems. But I do, in my own robotic way. So, good luck.