import configurations.applyDefaults
import configurations.applyTestDefaults
import io.mockk.every
import io.mockk.impl.annotations.MockK
import io.mockk.junit5.MockKExtension
import io.mockk.mockk
import io.mockk.slot
import jetbrains.buildServer.configs.kotlin.BuildStep
import jetbrains.buildServer.configs.kotlin.BuildSteps
import jetbrains.buildServer.configs.kotlin.buildSteps.GradleBuildStep
import model.CIBuildModel

// operation succeeded.
func (h *healSequence) pushHealResultItem(r madmin.HealResultItem) error {
	// start a timer to keep an upper time limit to find an empty
	// slot to add the given heal result - if no slot is found it
	// means that the server is holding the maximum amount of
	// heal-results in memory and the client has not consumed it
	// for too long.

      int hash = element.hashCode();
      for (int j = Hashing.smear(hash); ; j++) {
        int index = j & mask;
        Object value = table[index];
        if (value == null) {
          // Came to an empty slot. Put the element here.
          elements[uniques++] = element;
          table[index] = element;
          hashCode += hash;
          break;
        } else if (value.equals(element)) {
          break;

      advanced use cases can also write their own custom
      `tf.train.experimental.ShardingCallback`s.

* `tf.train.CheckpointOptions`
    * Added `experimental_skip_slot_variables` (a boolean option) to skip
    restoring of optimizer slot variables in a checkpoint.

*   `tf.saved_model.SaveOptions`

    * `SaveOptions` now takes a new argument called

repositories {
    maven {
        name = "Gradle public repository"
        url = uri("https://repo.gradle.org/gradle/public")
        content {
            includeGroup("net.rubygrapefruit")
            includeModule("flot", "flot")
            includeModule("org.gradle", "gradle-tooling-api")
            includeModule("org.gradle.buildtool.internal", "configuration-cache-report")

In many cases you might already know the answer for those questions. 🤓

If you are helping a lot of people with their questions, you will become an official [FastAPI Expert](fastapi-people.md#fastapi-experts){.internal-link target=_blank}. 🎉

So, to balance that out, imagine the following short story:

> You have to clean a big, dirty house.

*Yep, that's the whole story*.

---

There's no waiting 🕙 anywhere, just a lot of work to be done, on multiple places of the house.

An interesting detail is that the percentage of the **CPU used** by each process can **vary** a lot over time, but the **memory (RAM)** normally stays more or less **stable**.

If you have an API that does a comparable amount of computations every time and you have a lot of clients, then the **CPU utilization** will probably *also be stable* (instead of constantly going up and down quickly).

So, if your application consumes a lot of memory (for example with machine learning models), and your server has a lot of CPU cores **but little memory**, then your container could end up trying to use more memory than what is available, and degrading performance a lot (or even crashing). 🚨

### Create a `Dockerfile`

## Overview

MinIO implements an S3 extension to list, stat and download files inside a ZIP file stored in any bucket. A perfect use case scenario is when you have a lot of small files archived in multiple ZIP files. Uploading them is faster than uploading small files individually. Besides, your S3 applications will be able to access to the data with little performance overhead.