On-premises nasazení: Mějte svá projektová data plně pod kontrolou

Yes, "on-premises" indeed refers to IT infrastructure, systems, software, and data that are deployed on an organization's own servers or within its facilities. This means that the organization owns and manages the hardware and software locally, as opposed to utilizing cloud services provided by third-party vendors.

Yes! With Easy AI for Easy8, you have the unique flexibility to choose between cloud hosting or on-premises deployment for your project management AI.

Docker is an open-source platform that enables developers to create, deploy, and manage applications using containerization technology. Docker allows developers to package applications along with all their dependencies into containers. These containers are lightweight, portable, and can run consistently across various computing environments. A Docker container includes everything needed to run the application, such as code, libraries, and configuration files, ensuring that it operates the same way regardless of where it is deployed.

Docker is popular thanks to its ability to simplify software development and deployment while offering robust features that address scalability, portability, flexibility, and security needs effectively. Its ease of use, combined with a strong community ecosystem and continuous improvements, has made it an essential tool in modern DevOps workflows.

The choice between cloud AI and on-premises AI largely depends on an organization’s specific needs regarding cost management, performance requirements, data security concerns, and customization capabilities. Each approach has its advantages and challenges that must be carefully evaluated before making a decision.

When considering Cloud AI, it operates on a pay-as-you-go model, resulting in variable costs that can scale with usage. Performance-wise, it offers high scalability, making it ideal for handling growing workloads, though it may be subject to potential latency issues. Scalability is a strong suit, as cloud AI can easily adjust to demand without significant infrastructure changes. However, users have limited control over the infrastructure, as much of it is managed by third-party providers. In terms of security, cloud AI offers advanced features, but it requires placing trust in external providers to maintain data security and privacy.

On the other hand, On-Premises AI requires a significant upfront investment but offers predictable ongoing expenses, which can be beneficial for long-term budgeting. It generally provides better performance in terms of low latency, as all processes occur within the local infrastructure. However, scalability is limited by the existing hardware, which may require additional investments to expand. The key advantage of on-premises AI is the level of control it offers—users have full control over the system, from hardware to software. This also extends to security, where organizations can implement custom security measures tailored to their specific needs, without relying on third-party trust.

The correct term is "on-premises." This term refers to something located on a site or property, typically in the context of IT infrastructure, such as software or hardware that is hosted locally rather than in the cloud.  Additionally, some professionals prefer the abbreviation "on-prem" for casual contexts, which is widely accepted.

In contrast, "on-premise" is considered incorrect in this context. The word "premise" refers to a proposition or statement used as a basis for argument, which does not apply to physical locations. Therefore, using "on-premise" in place of "on-premises" is a common grammatical error that is often seen in marketing and tech discussions.

The minimum hardware requirements for server solution, suitable for 25 users, include an Intel Xeon E5440 @ 2.83GHz processor, 4 GB of memory, 20 GB of disk space, and a network card. For more details find out more about larger implementation.

The software requirements for an on-premises setup include Docker Engine version 24.0.5 (recommended), support for all major operating systems, and a database such as Percona 8.x. A full list of compatible software is available in the documentation. 

Docker tools are emphasised because they are the only true necessities when opting for a Docker-based solution. With Docker, there’s no need to configure additional dependencies such as operating systems or other components, simplifying the setup process. This is why we strongly recommend Docker for a hassle-free installation experience.

For direct (legacy) installations, server administrators must pre-install the specified requirements to successfully implement, update, or upgrade Easy8. The choice of deployment determines the ease of installation and ongoing management, making Docker a practical and efficient choice.

Read more about software requirements to receive all detailed information.