Infinity Cache Laravel Package

Technical Evaluation

Architecture fit. morilog/infinity-cache is a model-layer, transparent query-cache: it sits between the Eloquent builder and the cache store, keyed presumably on generated SQL plus bindings, with invalidation wired to model lifecycle events (saved, deleted, restored). Architecturally that is the right shape for a read-heavy Laravel app — no controller-level Cache::remember sprawl, and invalidation lives next to the write path. The problem is vintage, not design. The last release is February 2016, which places it squarely in the Laravel 5.1/5.2 era: manual service-provider registration in config/app.php (package auto-discovery did not exist until 5.5), PHP 5.5/5.6 syntax, and pre-Illuminate\Support\Str-v2 helper conventions. On Laravel 9/10/11 the code is likely readable but not installable as-is. Treat it as an architecture reference, not a dependency.

Integration feasibility. Composer is the first gate and it fails hard. A 2016 composer.json will pin illuminate/support and illuminate/database to 5.*, so composer require morilog/infinity-cache against a modern app errors out before any code loads. Circumventing that with --ignore-platform-reqs or a forked constraint set only buys you a runtime failure surface: Illuminate\Database\Eloquent\Builder internals, global scope registration, and cache repository contracts have all shifted. The realistic paths are (a) fork into app/Packages/ or a private VCS repo with updated constraints and tests, or (b) reimplement the 150–300 line pattern natively. Given 31 stars, zero dependents, and no maintainer activity in roughly a decade, (b) is the defensible default.

Technical risk.

• Silent staleness is the dominant risk. This class of package fails by returning wrong data, not by throwing. A missed invalidation on a Model::where(...)->update() mass update (events bypassed), a raw DB::statement, or a write from a queue worker or sibling service produces stale reads with no signal.
• Abandonment. No releases since 2016, no dependents, no evidence of CI or a test suite. There is no upstream to patch a correctness bug or a PHP 8 deprecation.
• Unbounded key growth. "Infinity" implies no TTL; without disciplined tagging, Redis memory grows monotonically and eviction policy becomes your accidental invalidation strategy.
• Low blast radius, high subtlety. The code footprint is small, so audit cost is low — but the invalidation semantics are subtle enough that an audit is mandatory, not optional.

Key questions.

1. Does invalidation use cache tags, and if so, what happens on file/database stores where tags are unsupported?
2. How are query keys derived — does binding order and connection name participate in the hash?
3. How are eager-loaded relations and withCount subqueries attributed to models for busting?
4. Does it handle mass updates, upsert, raw statements, and soft-delete restore()?
5. Is there any test suite, and does it cover cross-model invalidation (e.g. a Post write invalidating a User->posts query)?
6. What is the per-request overhead of key construction versus the hit rate actually observed?

Integration Approach

Stack fit. The package assumes Laravel 5.x, PHP 5.5–7.0, and a cache store that either supports tags (Redis/Memcached) or tolerates a tag-emulation fallback. It has no place in a Laravel 10/11 codebase without modification, and no place at all in a multi-service architecture where other writers touch the same tables.

Migration path. Two viable routes, in preference order:

If the goal is purely to learn the invalidation model, read the source and port it. If the goal is production caching on a schedule, take a maintained package with a tag-based invalidation story you can reason about, or build the thin native version and own it.

Compatibility. Verify explicitly before committing to any route: PHP version and strict-types behavior, Laravel's Builder/Model event surface, cache store capabilities (tags require Redis or Memcached — file and database do not support them), and whether the app runs under Octane or Horizon where long-lived workers change the invalidation timing assumptions.

Sequencing.

1. Week 1 — spike: read source, write a failing test matrix for invalidation (create/update/mass-update/delete/restore/relation).
2. Week 1–2 — decide build vs. fork vs. buy based on whether the maintained alternative passes the same matrix.
3. Week 2–3 — implement behind an interface (QueryCache contract) so the store and strategy are swappable.
4. Week 3 — instrument hit rate and stale-read detection in staging before any production enablement.
5. Week 4 — enable per-endpoint behind a feature flag, not globally.

Operational Impact

Maintenance. Adopting the package means adopting a fork. That is a permanent, low-volume but non-zero tax: every Laravel major upgrade requires re-validating the fork against new builder internals, and there is no upstream to lean on. Owning ~200 lines of native code is cheaper over a three-year horizon than owning a vendored 2016 fork.

Support. Effectively none. No maintainer activity since 2016, no issue triage, no security response channel, MIT with no warranty. Any production incident traces back to your team. Budget for that explicitly — it is the single strongest argument against adoption.

Scaling. Cache effectiveness is entirely store-dependent. Redis with tags scales well but requires memory planning; a no-TTL "infinity" policy without eviction discipline turns Redis into an OOM risk under key cardinality growth (every distinct binding combination is a key). Plan: bounded TTL as a backstop even if invalidation is event-driven, hit-rate dashboards, and a per-model key-count alarm.

Failure modes, ranked by severity:

1. Stale reads from missed invalidation — mass updates, raw SQL, queue workers, other services. Silent, hard to detect, erodes trust in the cache layer permanently.
2. Thundering herd — popular keys expiring or being busted simultaneously, driving a write-path-triggered read storm against the primary.
3. Unbounded memory growth — no TTL plus high-cardinality bindings.
4. Cross-tenant leakage — if the key hash omits tenant scope, one tenant can read another's cached rows. Catastrophic and must be tested explicitly.
5. Cache-store outage — confirm the package degrades to pass-through rather than throwing; verify by killing Redis in staging.

Ramp-up. The code is small enough that a mid-level engineer can read it in a day; the conceptual ramp-up is the real cost. Invalidation semantics — which queries a given write must bust, and which it silently cannot — must be documented and understood by everyone who writes a query. Without that, the cache becomes a correctness liability that surfaces months later as an unexplainable data discrepancy.

Recommendation. Score 0.435 is fair. Do not take this as a production dependency. Mine it for the invalidation pattern, implement a thin owned version or adopt a maintained alternative, and gate rollout on a proven invalidation test matrix with tenant isolation and store-failure degradation both verified.