container based compute environment. A cloud-native application is portable and resilient by design, and can scale horizontally by simply replicating. Modern orchestration platforms like Kubernetes, DC/OS make replicating and managing containers in huge clusters easier than ever.

While containers provide isolated application execution environment, orchestration platforms allow seamless scaling by helping replicate and manage containers. MinIO extends this by adding isolated storage environment...

* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.
* **Deep Learning**: this is a sub-field of Machine Learning, so, the same applies. It's just that there is not a single spreadsheet of numbers to multiply, but a huge set of them, and in many cases, you use a special processor to build and / or use those models.

    @ValueSource(ints = { 0, 1, 10, 100, 1000, 4096 })
    void testDecodeWithVariousAceCounts(int aceCount) throws SMBProtocolDecodingException {
        // This test is theoretical as we can't create huge buffers
        // but tests the boundary conditions
        if (aceCount <= 10) { // Only test small counts practically
            byte[] buffer = new byte[2048];

It used custom types in its declarations instead of standard Python types, but it was still a huge step forward.

It also was one of the first frameworks to generate a custom schema declaring the whole API in JSON.

* Machen Sie sich auch keine Sorgen über Stilregeln, es gibt bereits automatisierte Tools, die das überprüfen.

Und wenn es irgendeinen anderen Stil- oder Konsistenz-Bedarf gibt, bitte ich direkt darum oder füge zusätzliche Commits mit den erforderlichen Änderungen hinzu.

### Den Code überprüfen