Insights & Tutorials

Fifteen repositories. Fifteen nearly identical codebases. One bug fix that had to be applied fifteen times.

When you're running a single application, monitoring is straightforward. CPU, memory, request latency, error rate - a handful of dashboards and you're covered. When you're running a multi-tenant platform with dozens of independent Mautic instances on Kubernetes, each with its own database,

Our multi-tenant Mautic platform was slow. Not broken - slow. Deployments dragged. The UI felt sluggish. Builds took longer than they should. Every operation had a vague, frustrating delay that we couldn't immediately pin on any single component.

Imagine you're a marketing manager at an organization with fifty branches. Each branch has different opening hours, a different address, a different team photo, and a different booking link. You need to send a weekly newsletter. Do you create fifty separate emails? Of course not. You creat

When the Mautic community announced version 6, we read the changelog with a mix of excitement and dread. Excitement because the new version brought a completely redesigned UI, modern frontend architecture, and migration to Symfony's security component. Dread because we maintain a heavily c

Mautic is one of the most powerful open-source marketing automation platforms available. It handles contacts, segments, campaigns, email sending, landing pages, and reporting out of the box. But out of the box, it looks and feels like Mautic. The logo says Mautic. The interface says Mautic

Every email platform engineer has heard the conventional wisdom: use webhooks for real-time event processing. Your ESP bounces an email, fires a webhook to your endpoint, you process it instantly. Simple, fast, elegant.

When you're sending 40,000 emails per minute through 52 parallel workers, you'd think the hardest problems would be obvious from the start - queue throughput, API rate limits, infrastructure scaling. But one of the most unexpectedly difficult challenges we faced while building our multi-te

Some of the hardest engineering problems aren't the ones you plan for. They're the ones that ambush you mid-implementation - when everything is working beautifully until you hit an invisible wall.