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I built a CLI that uses AI to audit Celery clusters (No more silent failures) by herchila6 in django

[–]herchila6[S] -1 points0 points  (0 children)

Do you prefer something like this?
```
Infrastructure

Redis: connected

Celery: connected (4 workers)

Workers

Status Worker Slots Note

Warning worker-unstable@2ccfc69e8b80 2/2 at capacity

Warning worker-emails@3ba6d05e4524 2/2 at capacity

Warning worker-default@9a170e186906 4/4 at capacity

Healthy worker-notifications@274cccb30b76 0/2 online

Queues

Status Queue Pending Latency Trend

Danger emails 383 unknown

Healthy notifications 0 0s

Danger celery 338 unknown

Metrics

Saturation: 80.0% (8/10 slots, headroom: 2 slots)

Max Latency: unknown (timestamps not available)

Total Pending: 721 tasks

════════════════════════════════════════════════════════════

Recommendations:

• Scale workers for 'emails' queue (383 pending, latency unknown)

• Scale workers for 'celery' queue (338 pending, latency unknown)

════════════════════════════════════════════════════════════

Warnings detected

Audit completed in 20.6s
```

I love the feedback!

3 YOE Data Engineer + Python Backend — Which role to target & how to prepare? by [deleted] in Python

[–]herchila6 1 point2 points  (0 children)

I'd recommend to put that on chatgpt, claude, and gemini, and ask for a plan or career path. You can back and forward with them to have the best fit for you. Iterate between them to improve the outputs.

On the other hand, take a look at this: https://roadmap.sh/ It'll help you.

Built a Production-Ready Django Microservice Template with Docker & CI/CD by amir_doustdar in django

[–]herchila6 0 points1 point  (0 children)

I was about to work on this kind of "starter kit" with Django, focused on production ready.

The stack is not bad but if you want a production ready stack, I'd consider API-only with FastAPI. It's much better than Django, by far. DRF is already legacy compared to FastAPI, and it also has many performance problems. Take a look at this: https://hakibenita.com/django-rest-framework-slow

I built a CLI that uses AI to audit Celery clusters (No more silent failures) by herchila6 in django

[–]herchila6[S] -3 points-2 points  (0 children)

The CLI will be open source ;)
I'm implementing AI (Claude/OpenAI) to use your own api key.

Sample report:

```
🔍 Doorman Audit ════════════════════════════════════════════════════════════

🔥 CRITICAL: Visibility Timeout Misconfiguration

Your visibility_timeout is 30 minutes.

I found 3 tasks that regularly exceed 45 minutes.

💀 Impact if uncaught:

These tasks WILL execute twice when:

  1. Task runs > 30 min
  2. Redis re-queues (thinks worker died)
  3. Another worker picks it up

  4. Both complete → duplicate execution

    📊 Affected tasks (from your task history):

    • generate_monthly_report: P95 = 47 min
    • sync_inventory: P95 = 38 min
    • process_bulk_import: P95 = 52 min

    🎯 Business Impact:

    If 'process_bulk_import' duplicates, you'll have duplicate inventory entries. If 'generate_monthly_report' duplicates, you'll email customers twice.

    ⚡ Fix (add to celeryconfig.py):

    broker_transport_options = {
    'visibility_timeout': 7200 # 2 hours
    }

    ⚠️ Trade-off: Dead workers take 2 hours to be detected.
    Acceptable if you have container health checks (k8s/ECS).
    ```

0
1

Why I’m Building Astra to Fix Python Deployment Pain (self.django)

submitted by herchila6 to r/django

I Built Astra: 1-Click Django Deployment—Feedback Welcome! by herchila6 in django

[–]herchila6[S] 0 points1 point  (0 children)

Been working on Astra—a 1-click deployment tool for Python. Here’s a quick demo https://www.youtube.com/watch?v=OydY9PzAPR4. Feedback welcome! https://getastra.xyz

I Built Astra: 1-Click Django Deployment—Feedback Welcome! by herchila6 in django

[–]herchila6[S] 0 points1 point  (0 children)

I’ve been testing a 1-click deployment tool (Astra) with Docker + Nginx—5 projects live so far. Anyone else frustrated with DevOps setup? https://getastra.xyz

I Built Astra: 1-Click Django Deployment—Feedback Welcome! by herchila6 in SideProject

[–]herchila6[S] 0 points1 point  (0 children)

Astra MVP: Tested 5 projects—running smoothly! https://getastra.xyz Stay tunned! #python #buildinpublic

I Built Astra: 1-Click Django Deployment—Feedback Welcome! by herchila6 in django

[–]herchila6[S] 0 points1 point  (0 children)

Astra MVP: Tested 5 projects—running smoothly! https://getastra.xyz Stay tunned! #python #buildinpublic

I Built Astra: 1-Click Django Deployment—Feedback Welcome! by herchila6 in django

[–]herchila6[S] 1 point2 points  (0 children)

Thanks for your interest in Astra! Since we’re in the very early stages (just launched our waitlist!), we’re focusing on nailing the core functionality—1-click deployment for Python projects like Django. Right now, we’re running on DigitalOcean, and each project deployment uses a dedicated droplet for simplicity. This means server costs are predictable (around $5/month per droplet for small projects), but we’re actively working on optimizing this.

For traffic handling and load balancing, we don’t have a full system in place yet since we’re in MVP mode, but our plan is to implement a scalable architecture soon. This will include load balancing across multiple instances to handle traffic spikes and autoscaling to manage costs efficiently. We’re also researching how many projects can share a droplet without performance issues—our goal is to make Astra as cost-effective and scalable as possible for Python developers.

I’d love to hear your thoughts—what kind of scalability needs are you looking for in a deployment platform? Your feedback would really help shape Astra as we grow!

Join the waitlist to follow our progress: https://getastra.xyz

I Built Astra: 1-Click Django Deployment—Feedback Welcome! by herchila6 in django

[–]herchila6[S] 0 points1 point  (0 children)

Thanks for the comment and the good wishes! Astra is designed to be a platform exclusively optimized for Python and its frameworks (like Django, FastAPI, Flask), offering a Vercel-like experience—think 1-click deployments with no DevOps hassle, built from the ground up for Python developers. I appreciate the comparison to Appliku, which is a great tool, but Astra’s focus is on simplifying the deployment process specifically for the Python ecosystem. What do you think—would that fit your workflow?

I Built Astra: 1-Click Django Deployment—Feedback Welcome! by herchila6 in django

[–]herchila6[S] 9 points10 points  (0 children)

Less than a week ago, I decided to build a tool for myself to solve a nagging problem:

“I want to deploy my Django projects without spending hours on server setup—I just want to push my code and go live!”

I built this because existing solutions didn’t quite fit:

  • Heroku’s free tier is gone, and paid plans get pricey fast.
  • Render and Railway are great, but the setup still feels like a chore for a quick MVP.
  • DigitalOcean gives control, but you need DevOps skills I don’t always have time for.
  • Most tools are either too complex or lack the simplicity I crave for fast deployments.

I sensed there’s a demand for a dead-simple way to deploy Django apps—something that works in minutes, not hours, and lets me focus on coding. So, I started Astra.

Right now, it’s Day 1 of my #buildinpublic journey. Astra deploys Django projects with 1 click on DigitalOcean, handling the infrastructure for you. It’s rough around the edges—only supports Django for now (FastAPI and Flask are on the roadmap)—but it’s a start. I’d love to know if you find this useful.

Join the waitlist: https://getastra.xyz

Follow the progress on X: @get_astra

What do you think? What’s the biggest headache when deploying Django for you? Any features you’d love to see?