- What is pragmarx/tracker used for in Laravel?
- Pragmarx Tracker is a Laravel-native package for recording page views and visitors. It captures unique visits, authenticated users, devices, browsers, operating systems, languages, countries, and referrers, and includes a dashboard for exploring traffic metrics. It fits a conventional Laravel monolith that needs request-level visitor tracking rather than a strategic product analytics platform.
- Which Laravel and PHP versions does pragmarx/tracker support?
- The last release was 2020-05-04, and the assessment does not list supported Laravel or PHP versions. Treat compatibility as unconfirmed and run a compatibility spike before committing. Pin Composer versions, audit dependencies, and verify PHP, Laravel, and database behavior. On a modern stack, expect that a fork or replacement may be required.
- How do I install and configure pragmarx/tracker?
- A compatible install follows the typical Laravel package flow: Composer install, publish configuration and migrations, register the middleware, and validate schema and route behavior. Confirm middleware ordering so it does not interfere with auth, sessions, CSRF, or route caching. Test migrations against a production-like schema first, especially if you plan to use a separate database connection.
- Is pragmarx/tracker safe to use in production?
- The assessment rates technical risk as medium to high because of stale framework and dependency constraints, limited upstream maintenance, database write amplification, PII and privacy exposure, bot traffic skew, and schema growth. It can be used in production only with explicit ownership, privacy review, retention jobs, monitoring, and a rollback plan. High star count does not equal active vendor support, and the package has zero dependents in the assessment.
- Does pragmarx/tracker track PII, and can I anonymize IP addresses?
- The package records visitor and request context, and the assessment flags PII and privacy exposure as a risk. It specifically asks whether IPs can be anonymized, so confirm that behavior in the code or a fork before production. Design a privacy and retention review up front, and avoid assuming default anonymization.
- Can pragmarx/tracker run on a separate database connection or queue writes?
- The assessment recommends isolating tracker tables on a separate database connection where possible. It also asks whether tracking is queueable or batchable, so validate write behavior rather than assuming asynchronous writes. Per-request database writes can become a bottleneck, so use sampling, indexes, retention, and batching or queueing if feasible.
- Does pragmarx/tracker work with API-only, SPA, or multi-tenant Laravel apps?
- The package is a poor fit for API-only, SPA-heavy, event-streaming, multi-service, or warehouse-centric analytics architectures. The assessment does not confirm built-in multi-tenant support, so validate that in a spike and consider isolating tracker tables per tenant or connection. It is intended for request-level tracking in a conventional Laravel monolith.
- What are the alternatives to pragmarx/tracker for Laravel analytics?
- The provided assessment does not name specific alternatives, but it frames adoption as a fork-or-replace decision on modern Laravel releases. Evaluate maintained Laravel analytics packages, first-party or hosted analytics, and internal event pipelines against your privacy, scaling, and retention needs. Run candidates in parallel and compare counts before cutover.
- How do I test pragmarx/tracker before rolling it out?
- Pilot in staging with representative traffic and run the tracker alongside any existing analytics tool in parallel before cutover. Test migrations against production-like schemas, verify MySQL and Postgres behavior, and confirm middleware ordering with auth, sessions, CSRF, and route caching. Roll out behind config flags and sampling, then validate against expected traffic patterns.
- Is pragmarx/tracker still maintained, and should I fork it?
- The last release was 2020-05-04, so expect internal ownership even though the MIT license allows an internal fork. Budget explicitly for tracking framework upgrades, dependency CVEs, schema changes, and rollback. Use community documentation as fallback support, and make a supported, forked, or rejected decision before production.