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To scale a Laravel application across VPS servers, make every application node disposable: store sessions, cache, and queues in shared Redis; store uploads in shared object storage; place multiple app nodes behind a load balancer; run queue workers separately; and put PgBouncer in front of PostgreSQL before adding replicas. Add a streaming read replica only when read traffic requires it, then route reads deliberately and keep consistency-sensitive reads on the primary.
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This order avoids the most common failure in a multi-server Laravel deployment: a request reaches a different VPS and cannot find state that was left on the previous node. It also prevents a database replica from being treated as a general performance cure. Replicas distribute read load, but they do not make one poorly performing query faster.
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What horizontal scaling changes in a Laravel deployment
Vertical scaling gives one VPS more CPU, memory, storage, or network capacity. Horizontal scaling adds more VPS instances and distributes work among them. Laravel can scale horizontally only when an individual application node does not own information that another node must read.
A user may submit a form on one node and load the next page from another. A queue job may be claimed by a worker on a different server. A deployment may remove one node while traffic continues through the others. These events are routine in a load-balanced system, so the application tier must be stateless.
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Stateless does not mean the whole system has no state. It means durable or shared state is kept in services designed for shared access rather than in a node’s local filesystem or process memory.
The target request and job flow
Client
|
Load balancer
|-- App node 1 (Laravel PHP workers)
|-- App node 2 (Laravel PHP workers)
|-- App node 3 (Laravel PHP workers)
|
|-- Shared Redis: sessions, cache, queue backend
|-- Shared object storage: uploaded files
|-- PgBouncer
|-- PostgreSQL primary (writes and consistency-sensitive reads)
|-- PostgreSQL streaming replica (eligible reads)
Separate queue-worker VPS nodes run Horizon against the same Redis backend.The load balancer distributes HTTP requests. Redis gives every app node the same session, cache, and queue view. Object storage makes uploaded files available regardless of which node handled the upload. PgBouncer limits and reuses database connections. PostgreSQL replication can then distribute suitable read traffic without moving writes away from the primary.
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Put sessions, cache, and queues in shared Redis
Configure all app nodes to use one shared Redis service for Laravel sessions, cache, and queues. Every node must use the same Redis endpoint and compatible application configuration. A local Redis instance on each VPS creates separate islands: a session written on node 1 may be absent on node 2, and a queued job may be invisible to workers connected elsewhere.
Shared Redis also gives Horizon a single queue backend. Each server can run Horizon against that backend, while Redis coordinates job claims so that two workers do not process the same queued job simultaneously under normal operation.
- Sessions: A request can move between app nodes without forcing a login again.
- Cache: Cached values are visible to every node and are not lost merely because the load balancer selects a different VPS.
- Queues: Web requests can enqueue work once, and dedicated workers on several servers can consume it from the same backend.
Plan Redis as a shared dependency rather than an incidental service on one app VPS. If it becomes unavailable, session access, cache operations, and queue dispatch or processing can all be affected, so monitor it separately and define a recovery plan before adding more app nodes.
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Move uploads to shared object storage
Do not treat an app node’s local disk as the authoritative home for user uploads. A file uploaded through node 1 may be requested later through node 2, which has no copy. Node replacement, autoscaling, or a deployment can also delete files that were stored only on an instance disk.
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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesUse shared object storage for uploads and configure every Laravel node to use the same storage location. Keep only temporary processing files on local disk, and make the application persist the resulting object before returning success. This separates durable media from the lifecycle of disposable web servers.
Control PostgreSQL connections with PgBouncer
Add a connection pooler such as PgBouncer in front of PostgreSQL before introducing read replicas. A horizontally scaled Laravel fleet can create a large number of database connections because every app node has its own PHP workers and deployment processes. PostgreSQL must still manage those connections even when the application is not actively running queries.
PgBouncer accepts connections from the Laravel nodes and reuses a controlled pool of PostgreSQL connections. This reduces connection overhead and helps prevent a burst of app nodes or workers from exhausting PostgreSQL’s connection capacity.
Where the pooler belongs
Laravel should connect to the pooler’s endpoint, while the pooler connects to the PostgreSQL primary and, where configured, replica endpoints. Keep write traffic on the primary. If a separate endpoint is used for replicas, route only reads that can tolerate replication delay.
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Pooling is not a substitute for query tuning, indexes, or adequate PostgreSQL resources. It addresses connection management; it does not accelerate a single slow SQL statement. Test transaction behavior and session-level database features with the selected PgBouncer mode before production rollout.
Add app nodes behind a load balancer
Once shared state and database access are ready, run two or more identical Laravel app nodes behind a load balancer. Each node should contain the same application release, environment configuration, PHP runtime, web server configuration, and scheduled deployment state.
What the load balancer should do
- Send HTTP requests only to healthy app nodes.
- Stop sending traffic to a node during deployment or when its health check fails.
- Distribute requests without relying on a particular node’s local session or upload directory.
- Preserve the client information your application and logs require, using the proxy settings appropriate to your chosen load balancer.
HAProxy and Nginx are common choices for this role. The exact VPS configuration depends on the network layout, TLS termination point, health-check endpoint, and operating system, so treat those as deployment-specific decisions rather than copying a generic configuration unchanged.
Health checks should test useful dependencies
A process-level check proves only that the web server is listening. A useful readiness check should reflect whether the node can serve traffic with its required configuration. Decide explicitly how Redis and database failures should affect readiness: taking every node out of rotation during a shared dependency outage can make recovery harder, while keeping unhealthy nodes in rotation increases user-facing errors.
Run queues separately with Laravel Horizon
Web requests and background jobs compete for CPU, memory, and database connections if they run on the same VPS. Create separate queue-worker nodes and run Horizon against the shared Redis backend. The app nodes dispatch jobs; the worker nodes execute them.
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Why Horizon fits a multi-server queue
Horizon can run on each worker server while all instances use the same Redis connection. Redis coordinates queue access, preventing ordinary double processing when multiple workers claim jobs. You can therefore add worker VPS nodes without creating a separate queue for each machine.
Horizon also adjusts worker counts per queue between configured minimum and maximum values according to queue wait times, instead of relying only on fixed queue:work processes. Configure those limits per workload: a CPU-heavy video job, a short notification job, and a database-intensive import should not necessarily share identical concurrency.
Separate queues by workload
- Place latency-sensitive jobs on a queue that has reserved worker capacity.
- Put long-running or memory-heavy jobs on a separate queue so they cannot block short jobs.
- Set maximum worker counts with PostgreSQL and Redis capacity in mind; adding workers can increase database contention rather than throughput.
- Watch queue wait time, job runtime, failure count, and worker memory usage after every concurrency change.
Deploy worker code and app code as a compatible release. A worker that continues running old code while new requests enqueue a changed payload can fail even though both servers are individually healthy.
Use PostgreSQL replicas for reads, not as a second primary
PostgreSQL uses streaming replication to copy changes from a primary to one or more replicas. The primary remains the write authority. Replicas can serve eligible read traffic, spreading read load across servers, but they do not speed up one slow query and they cannot safely receive writes.
Choose the read path deliberately
A proxy such as HAProxy or Pgpool-II can route writes to the primary and reads to replicas. The proxy needs a clear policy for what happens when a replica is lagging or unavailable. Reads that must reflect the latest committed write should go to the primary.
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Replication lag is normal enough that application code must account for it. A user who creates an order and immediately loads its detail page can be sent to a replica that has not replayed the insert yet. For those read-after-write paths, use the primary or Laravel’s sticky read/write behavior.
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Laravel supports separate read and write host arrays in config/database.php, plus an optional sticky flag. A minimal structure is:
'pgsql' => [
'driver' => 'pgsql',
'read' => [
'host' => [env('DB_READ_HOST')],
],
'write' => [
'host' => [env('DB_WRITE_HOST')],
],
'sticky' => true,
// keep the remaining PostgreSQL settings shared by your deployment
],With sticky enabled, a request that performs a write uses the write connection for subsequent reads in that same request. This protects common read-after-write flows, but it does not make a later request automatically current. If the next request can land on a replica, route that particular operation to the primary when freshness matters.
Keep the read and write host definitions consistent across all app nodes. A node with a different environment variable or stale cached configuration can silently send traffic to the wrong database.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A deployment sequence that limits risk
- Inventory node-local state. Find session files, cache files, queue backends, uploaded media, generated exports, and any other data written outside PostgreSQL.
- Move sessions, cache, and queues to one shared Redis backend. Confirm that a value written through one app node can be read through another.
- Move uploads to shared object storage. Upload through one node and retrieve the object through another before exposing the load-balanced service.
- Introduce PgBouncer. Point Laravel at the pooler, verify connection limits and transaction behavior, and observe PostgreSQL connection counts under a representative worker load.
- Clone the app node. Build a second node from the same release and environment configuration. Check that both nodes use identical Redis, storage, and database endpoints.
- Put the nodes behind the load balancer. Test health checks, node removal, deployment draining, and a request sequence that crosses nodes.
- Move Horizon to worker VPS nodes. Connect every worker to the same Redis backend, then test dispatch, completion, retries, and failure handling.
- Measure before adding a replica. Establish whether the bottleneck is database reads, writes, connections, CPU, memory, storage latency, or a slow query. A replica is useful only when read demand is the limiting factor.
- Add a PostgreSQL streaming replica. Keep writes on the primary, expose the replica through a deliberate routing layer, and monitor replay delay.
- Route selected reads. Send only replica-safe reads to the read path. Keep read-after-write and freshness-critical queries on the primary, using Laravel’s sticky behavior where it fits the request lifecycle.
Failure modes to plan for
| Symptom | Likely design problem | Corrective action |
|---|---|---|
| Users lose sessions when requests switch VPS nodes | Sessions remain on node-local storage | Use one shared Redis session backend on every app node |
| Uploaded files appear on one node but return 404 on another | Files are stored on local disk | Persist uploads in shared object storage |
| PostgreSQL rejects connections during traffic or worker bursts | Every process opens an unmanaged database connection | Place PgBouncer before PostgreSQL and size the pool deliberately |
| Jobs are invisible to some workers | Workers use different Redis backends or queue settings | Point all Horizon instances at the same Redis queue backend |
| A newly created record is missing immediately afterward | The read went to a lagging replica | Use the primary for freshness-sensitive reads and enable Laravel sticky routing where appropriate |
| Adding workers increases database latency | Concurrency exceeded database capacity | Reduce worker limits, separate queues, and measure query and connection pressure |
| Reads remain slow after adding replicas | The workload is dominated by one slow query | Investigate the query and database plan; replicas distribute load but do not accelerate one query |
Operational checks after each scaling change
Application checks
- Log the app node identifier so a request can be traced across load-balancer hops.
- Verify session continuity by authenticating through one node and making subsequent requests through another.
- Upload and retrieve a file through different nodes.
- Confirm that cache invalidation is visible from every node.
Queue checks
- Dispatch a known test job and confirm that any worker can claim it.
- Measure queue wait time separately from job runtime.
- Check retries and failed-job handling after stopping one worker node.
- Watch Redis memory and worker memory as Horizon changes process counts.
Database checks
- Track active PostgreSQL connections before and after PgBouncer.
- Measure replica replay delay and define the maximum lag acceptable for each read class.
- Verify that writes never reach a read replica.
- Test a read-after-write request and confirm that it remains consistent.
When horizontal scaling is the wrong next step
Adding VPS nodes increases operational overhead. The team must maintain shared Redis, object storage credentials, a load balancer, worker processes, database pooling, deployment coordination, monitoring, and failure procedures. For a small or lightly loaded application, that complexity can cost more in maintenance than it returns in capacity.
First identify the limiting resource. If one slow query, an undersized primary, inefficient application code, or an unbounded queue is responsible, adding app nodes may simply multiply the pressure. PgBouncer is the earlier database scaling step because connection exhaustion can occur before PostgreSQL needs replicas. Add replicas when measured read demand justifies them, not because a multi-server diagram looks complete.
Designing for failover
A read replica is not automatically a failover system. Decide how the application behaves when the primary, pooler, Redis service, or load balancer fails. Database promotion, DNS or proxy changes, Laravel configuration, and queue recovery all need an explicit runbook.
Patroni is sometimes proposed for PostgreSQL failover, but its suitability depends on the surrounding topology and operational expertise; validate its behavior in a staging failure test rather than assuming it provides a complete solution by itself. Likewise, a proxy can route traffic, but it does not replace backup, restore, replication monitoring, or a tested promotion procedure.
Quick Recap
Final implementation checklist
- All app nodes use shared Redis for sessions, cache, and queues.
- Uploads live in shared object storage, not node-local disk.
- App nodes are identical and sit behind health-checked load balancing.
- Horizon runs on separate worker nodes against the same Redis backend.
- Laravel connects through PgBouncer with a tested connection policy.
- PostgreSQL writes stay on the primary.
- Read replicas are added only for measured read-load needs.
- Replica lag is monitored, and freshness-critical reads use the primary.
- Laravel’s
stickyread/write setting is enabled where same-request read-after-write consistency is required. - Failure, node removal, deployment draining, and recovery have been tested rather than assumed.
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