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Product analytics isn't about accumulating data, but about asking better questions. Google Analytics gives you a good foundation for acquisition and traffic, but tools like PostHog are specifically designed to understand what happens within the product: where users drop off, what they find valuable, and why they return (or don't). This article is your minimum viable starting point for measuring what matters from day one.

Your Django application works locally, passes tests, and the team wants to deploy it to production. But between "it works on my machine" and "it runs stably on a server" lies a territory full of decisions that are rarely well explained. Kamal fits right into that in-between space: when manual scripts no longer scale, but Kubernetes is still more than you need.

Production security isn't just a list of enabled tools. It's a set of safeguards your team can verify. If you can't explain who has access, what's exposed, and what happens when something goes wrong, your system isn't ready.

Deployment is just the beginning. If your app isn't monitored, your users will discover every problem before you do. What you need isn't pretty dashboards or alerts for everything. You need to know what to watch, what to ignore, and when to take action.

There are teams that don't test anything and pray before every deployment. And there are teams that aim for 100% coverage and don't deliver on time. Both have a testing problem. The question isn't whether to test, but how much, where, and why.

Most CI/CD guides are written for teams of 50 people with a dedicated platform team. But if you're three, five, or ten developers, those guides don't apply. What you need is a working pipeline that can be set up in days (not months) and that your team can maintain without a full-time DevOps engineer.