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The first request works. The second remembers more than it should. In a long-running PHP worker, that can happen when request-specific data is left in memory after one execution and becomes visible to another. Semitexa’s runtime addresses this by distinguishing the lifetime of a worker from the lifetime of each request, command, or asynchronous execution.
What a Semitexa worker keeps alive
Semitexa runs on Swoole workers that stay alive to handle multiple executions. The root service container is built once per worker, allowing stable services and discovered metadata—such as route information—to be reused. Individual HTTP requests, console commands, and asynchronous executions can resolve execution-scoped handlers as fresh clones rather than reusing one mutable handler instance.
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This is different from OPcache. OPcache caches compiled PHP bytecode; a persistent application can also keep its bootstrapped service graph and metadata available between executions. Neither mechanism eliminates database queries, remote calls, or business logic that must run for each execution.
As Taras Hanych (SyntaxWanderer) puts it, “The execution model shapes how dependencies are declared, how a handler is created, how state is carried, how a connection is returned and how HTML reaches the browser.”
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Give every piece of state an owner and a lifetime
The practical rule is to decide whether data belongs to one execution, one worker, or the application across workers and restarts. Semitexa’s lifecycle documentation, verified against Ultimate 2026.09.19.1020, describes four useful categories.
Per-execution state
The current request, authenticated principal, tenant, locale, and similar context must not linger as mutable worker-wide state. Semitexa documents coroutine-local context for concurrent Swoole requests, so one coroutine’s request or authorization data is not simply stored in a shared process variable. The framework registers cleanup callbacks for request and message processing, including exceptional paths.
Per-worker state
Data that is stable for the life of a worker can be kept in that process. Documented examples include immutable metadata caches, route discovery results, connection pools, and in-memory replay or idempotency sets. Such state can survive multiple executions handled by the same worker, but it is not automatically shared with another worker.
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Persistent or shared state
If information must survive worker replacement, deployment, or access from multiple workers, keep it in a suitable backing service such as a database, Redis, or a broker. The lifecycle documentation notes that in-memory replay and delivery fixtures are process-local; production systems that require cross-worker semantics need a MySQL- or Redis-backed implementation.
Test-only resettable state
Some worker-level state is intentionally retained in production but needs a clean baseline in tests. Semitexa documents explicit reset support for this purpose. Tests should use that reset rather than assume a persistent worker starts fresh for every case.
How cleanup works at the end of an execution
HTTP request cleanup
For HTTP handling, Semitexa documents a finally path that resets registered per-request stores, resets the request-scoped container and execution context, and then ends coroutine-local fallback state. Using a finalization path matters because cleanup must also run when request handling exits exceptionally.
Queued-message cleanup
Queue processing has a separate per-message cleanup path. It resets execution-specific state without relying on the HTTP request-scoped container, since a queued message is not an HTTP request.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesThese framework lifecycle guarantees are useful safeguards, not a reason to place request identity or tenant context in shared mutable services. Application code still needs to keep the ownership boundary clear.
Concurrency and the boundary of in-memory state
A Swoole worker can handle concurrent requests using coroutines. Context that is safe for a single execution may become unsafe if stored in an ordinary shared worker property: another coroutine could observe or overwrite it. Semitexa’s documented approach is coroutine-local context for request, auth, tenant, and RBAC information, with cleanup when execution ends.
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Process-local caches and fixtures have a different boundary. A value held by one worker is not a cross-worker coordination mechanism, and it disappears when that process is replaced. Use an external store when correctness depends on all workers seeing the same replay, delivery, or idempotency state.
Worker shutdown is bounded, not a durability guarantee
Semitexa’s startup and shutdown lifecycle includes a configured drain window. On worker exit, bootstrap raises a drain signal, clears timers, and attempts to cancel parked coroutines. That is a bounded shutdown procedure, not a promise that every in-flight operation finishes: some driver calls may not stop immediately, and Swoole can force termination after the configured wait.
Work that must outlive a worker needs durable handling: persist it appropriately, arrange retries, and make processing idempotent so a retry does not produce an unintended duplicate effect. Semitexa documents queue:work, webhook:work, and mail:work as explicit processes. Its scheduler surface separates inspection, plan materialization, and execution, making it possible to see and intervene in scheduled work rather than treating asynchronous activity as an invisible side effect of the HTTP server.
Long-lived SSE connections have their own resource costs
Semitexa’s SSE documentation, whose footer reports version 2026.10.03.1952, describes a long-lived text/event-stream response over plain HTTP. The documented defaults are authentication enabled, a cap of 5 connections per IP, a cap of 500 per worker, and a maximum connection age of 600 seconds. These are Semitexa defaults, not limits imposed by the SSE protocol.
An open stream consumes a coroutine, file descriptor, and response handle, so connection caps should be sized for the resources available to the deployment. The framework does not replay missed events after a client reconnects. If delivery guarantees matter, retain and replay events at the domain layer.
What the demonstration does—and does not—show
The article’s live handler demonstration shows an execution-scoped handler created fresh while its worker remains alive. It illustrates the lifecycle distinction; it is not a throughput or latency benchmark, and it does not establish concurrent tenant isolation. No named performance figure or benchmark is published in the article or runtime sources, so qualitative claims about speed should not be mistaken for measured results.
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Implementation references and command options can evolve. The lifecycle and worker documentation reports verification against Semitexa Ultimate 2026.09.19.1020, while the SSE page reports 2026.10.03.1952. Check the help output and source for the version installed in your environment before reproducing commands or relying on a specific option.
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