* **Starlette**:
    * Will have the next best performance, after Uvicorn. In fact, Starlette uses Uvicorn to run. So, it probably can only get "slower" than Uvicorn by having to execute more code.
    * But it provides you the tools to build simple web applications, with routing based on paths, etc.

  }

  public void testCountOverflow_doesNotThrow() {
    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.add(ONE_VALUE);
    for (int power = 1; power < Long.SIZE - 1; power++) {
      accumulator.addAll(accumulator.snapshot());
    }
    // Should overflow without throwing.
    accumulator.addAll(accumulator.snapshot());
    assertThat(accumulator.count()).isLessThan(0L);

   * because underutilization = free resources for the taking. If we are primarily interested to
   * deal with overflow, then stored permits could be given out /slower/ than fresh ones. Thus, we
   * require a (different in each case) function that translates storedPermits to throttling time.
   *
   * This role is played by storedPermitsToWaitTime(double storedPermits, double permitsToTake). The

* **PGAdmin** для СУБД PostgreSQL, которые легко можно заменить на PHPMyAdmin и MySQL.
* **Flower** для отслеживания работы Celery.
* Балансировка нагрузки между фронтендом и бэкендом с помощью **Traefik**, а значит, Вы можете расположить их на одном домене, разделив url-пути, так как они обслуживаются разными контейнерами.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

///

## Dataclasses in `response_model`

You can also use `dataclasses` in the `response_model` parameter:

{* ../../docs_src/dataclasses/tutorial002.py hl[1,7:13,19] *}

  This change added the following metrics:
    - `apiserver_flowcontrol_nominal_limit_seats`: Nominal number of execution seats configured for each priority level
    - `apiserver_flowcontrol_lower_limit_seats`: Configured lower bound on number of execution seats available to each priority level
    - `apiserver_flowcontrol_upper_limit_seats`: Configured upper bound on number of execution seats available to each priority level

  }

  public void testCountOverflow_doesNotThrow() {
    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.add(ONE_VALUE);
    for (int power = 1; power < Long.SIZE - 1; power++) {
      accumulator.addAll(accumulator.snapshot());
    }
    // Should overflow without throwing.
    accumulator.addAll(accumulator.snapshot());
    assertThat(accumulator.count()).isLessThan(0L);

* **PGAdmin** PostgreSQL database admin tool'u, PHPMyAdmin ve MySQL ile kolayca değiştirilebilir.
* **Flower** ile Celery job'larını monitörleme.
* **Traefik** ile backend ve frontend arasında yük dengeleme, böylece her ikisini de aynı domain altında, path ile ayrılmış, ancak farklı kapsayıcılar tarafından sunulabilirsiniz.

        a full-time Guava team member. [Feedback](https://stackoverflow.com/a/4543114) from our
        users indicates that they really appreciate Guava's high power-to-weight ratio. It's
        important to us to keep Guava as easy to use and understand as we can. That means boiling
        features down to compact but powerful abstractions, and controlling feature bloat carefully.

- When scheduling a mix of pods using `ResourceClaims` and others that don't, scheduling a pod with `ResourceClaims` has a lower impact on scheduling latency. ([#121876](https://github.com/kubernetes/kubernetes/pull/121876), [@pohly](https://github.com/pohly))