I started using Claude code (CC) a couple weeks back and have some very positive outcomes. For clarity, I have been in the IT field since 1990, and my background is mainly infrastructure engineering (now DevOps). I don't write code professionally; I write tools as needed to accomplish tasks. That said, I understand end-to-end systems and the parts in the middle pretty well.
Here are some projects Claude has helped create:
1. Apache Airflow "DAG" (cron jobs) to automate dumping data from an on-prem PGSQL server to a cloud bucket. I have limited Python skills, but CC helped me focus on what I wanted to get done instead of worrying about code. It was an iterative process over a couple of days, but the net result is we now have a working model to easily perform on-prem to cloud data migrations. The Python code is complex with lots of edge conditions, but it is very readable and makes perfect sense.
2. Custom dashboard to correlate HAProxy server stats with run-time container (LXC) hooks. In this case, we needed to make sure some system services were running properly even if HAProxy said the container was running. To my surprise, CC immediately knew how to parse the HAProxy status output and match that with internal container processes. The net for this project is a very nice dashboard that tells us exactly if the container is up/down or some services inside the container are up/down. And, it even gives us detailed metrics to tell us if PGSQL replication is lagging too far behind the production server.
3. Billing summary for cloud provider. For this use case, we wanted to get a complete billing summary from our cloud provider - each VM, storage bucket, network connection, etc. And, for each object, we needed a full breakdown (VM with storage, network, compute pricing). It took a few days to get it done, but the result is a very, very nice tool that gives us a complete breakdown of what each resource costs. The first time I got it working 100%, we were able to easily save a few thousand $$ from our bill due to unused resources allocated long ago. And, to be clear, I knew nothing about API calls to the cloud provider to get this data much less the complexities of creating a web page to display the data.
4. Custom "DB Rebuild" web app. We run a number of DBs in in our dev/test network that need to get refreshed for testing. The DB guys don't know much about servers, containers, or specific commands to rebuild the DBs, so this tool is perfect. It provides a simple "rebuild db" button with status messages, etc. I wrote this with CC in a day or so, and the DB guys really like the workflow (easy for them). No need to Github tickets to do DB rebuilds; they can easily do it themselves.
Again, the key is focusing my energy on solving problems, not becoming a python/go/javascript expert. And, CC really helps me here. The productivity our team has achieved over the past few weeks is nothing short of amazing. We are creating tools that would require hiring expert coders to write, and giving us the ability to quickly iterate on new business ideas.
Here are some projects Claude has helped create:
1. Apache Airflow "DAG" (cron jobs) to automate dumping data from an on-prem PGSQL server to a cloud bucket. I have limited Python skills, but CC helped me focus on what I wanted to get done instead of worrying about code. It was an iterative process over a couple of days, but the net result is we now have a working model to easily perform on-prem to cloud data migrations. The Python code is complex with lots of edge conditions, but it is very readable and makes perfect sense.
2. Custom dashboard to correlate HAProxy server stats with run-time container (LXC) hooks. In this case, we needed to make sure some system services were running properly even if HAProxy said the container was running. To my surprise, CC immediately knew how to parse the HAProxy status output and match that with internal container processes. The net for this project is a very nice dashboard that tells us exactly if the container is up/down or some services inside the container are up/down. And, it even gives us detailed metrics to tell us if PGSQL replication is lagging too far behind the production server.
3. Billing summary for cloud provider. For this use case, we wanted to get a complete billing summary from our cloud provider - each VM, storage bucket, network connection, etc. And, for each object, we needed a full breakdown (VM with storage, network, compute pricing). It took a few days to get it done, but the result is a very, very nice tool that gives us a complete breakdown of what each resource costs. The first time I got it working 100%, we were able to easily save a few thousand $$ from our bill due to unused resources allocated long ago. And, to be clear, I knew nothing about API calls to the cloud provider to get this data much less the complexities of creating a web page to display the data.
4. Custom "DB Rebuild" web app. We run a number of DBs in in our dev/test network that need to get refreshed for testing. The DB guys don't know much about servers, containers, or specific commands to rebuild the DBs, so this tool is perfect. It provides a simple "rebuild db" button with status messages, etc. I wrote this with CC in a day or so, and the DB guys really like the workflow (easy for them). No need to Github tickets to do DB rebuilds; they can easily do it themselves.
Again, the key is focusing my energy on solving problems, not becoming a python/go/javascript expert. And, CC really helps me here. The productivity our team has achieved over the past few weeks is nothing short of amazing. We are creating tools that would require hiring expert coders to write, and giving us the ability to quickly iterate on new business ideas.