As with other support business processes, there are two approaches to organizing IT infrastructure: either consolidate computing resources on their own technological platform, managed by an in-house IT department, or outsource the computing resources to cloud providers. While it may be easier to entrust IT infrastructure management to third-party professionals, developing in-house competencies by implementing modern automation tools for data center (DC) management is often more reliable and secure.
However, regardless of the choice, it is clear that both companies managing their own DCs and cloud service operators need to focus on optimizing computing resource costs. The primary objectives of DC management are to maximize the computing power of existing equipment and smooth out spikes in resource consumption. In some cases, users of high-performance servers may need to conserve electricity or computing power when there is low demand.
DC management solutions are designed to automate IT infrastructure management, optimizing resources in line with the company's or operator's strategy. In this article, we will review the requirements for products to manage the heart of digitalization-the DC.
However, regardless of the choice, it is clear that both companies managing their own DCs and cloud service operators need to focus on optimizing computing resource costs. The primary objectives of DC management are to maximize the computing power of existing equipment and smooth out spikes in resource consumption. In some cases, users of high-performance servers may need to conserve electricity or computing power when there is low demand.
DC management solutions are designed to automate IT infrastructure management, optimizing resources in line with the company's or operator's strategy. In this article, we will review the requirements for products to manage the heart of digitalization-the DC.
The Mega-Mind of DC
Solutions for optimizing the operational costs of IT infrastructure must meet the following requirements:
Load Management for Any Environment
Currently, nearly all server infrastructures are virtual, making tools for automatic IT resource management and load balancing essential. Similarly, tools for load distribution in a microservices environment are equally important.
Adaptability to Any Infrastructure
The solution should maximize the use of existing technologies, making its compatibility with various hypervisors, storage systems, networks, and increasingly popular converged systems that unify all resources into a single solution.
Ensuring Uninterrupted Operation
The solution should unify virtualization elements-containers, virtual machines, and networks-with physical computing devices-servers, routers, and storage systems. Management must be provided at different levels: for DCs, private, public, or hybrid clouds, as well as in multi-cloud configurations. Distributing computing resources on such a global scale helps to use resources more efficiently and to select the most cost-effective configurations.
Dynamic Adaptation to Operating Conditions
In a climate of shifting trends and staff shortages, it's crucial for the solution to automatically and promptly make decisions about reallocating computing resources between various configurations and, in some cases, to propose solutions, using AI to analyze accumulated data.
Load Management for Any Environment
Currently, nearly all server infrastructures are virtual, making tools for automatic IT resource management and load balancing essential. Similarly, tools for load distribution in a microservices environment are equally important.
Adaptability to Any Infrastructure
The solution should maximize the use of existing technologies, making its compatibility with various hypervisors, storage systems, networks, and increasingly popular converged systems that unify all resources into a single solution.
Ensuring Uninterrupted Operation
The solution should unify virtualization elements-containers, virtual machines, and networks-with physical computing devices-servers, routers, and storage systems. Management must be provided at different levels: for DCs, private, public, or hybrid clouds, as well as in multi-cloud configurations. Distributing computing resources on such a global scale helps to use resources more efficiently and to select the most cost-effective configurations.
Dynamic Adaptation to Operating Conditions
In a climate of shifting trends and staff shortages, it's crucial for the solution to automatically and promptly make decisions about reallocating computing resources between various configurations and, in some cases, to propose solutions, using AI to analyze accumulated data.
Data Center under Control
We gathered a list of key tasks that must be solved using modern digital products for seamless IT infrastructure management.
- Authorization of IT resources: the solution must regularly search for and authorize all connected IT resources.
- Identification of objects and parameter rules: the product must identify interrelated elements, their parameters, actions, and locations to create a complete overview of IT resources.
- Settings and functionality tailored to needs: the solution must allow customization of parameters and functionality according to unique business needs. Authorized objects can be manually adjusted for unique situations, and existing policies can be imported.
- Formation of current IT resource topology: the tool must generate the current topology of IT resources, from which it collects data and monitors the state and load of the CPU, storage systems, RAM, and local network in real time.
- Formation of predictive IT resource topology: the solution must generate a predictive topology for optimizing power usage and perform resource balancing at the level of physical hosts, hypervisors, and orchestrators in both automatic and semi-automatic modes (with operator confirmation).
- Load balancing: the digital product must provide recommendations based on forecasts and the current state of infrastructure and balance resources.
Smart AI Balancer Solution
One of our solutions, Smart AI Balancer, has been designed for the automatic optimization of IT resources using AI technologies. It increases the efficiency of computing resources usage while maintaining high reliability and fault tolerance.
The solution fully meets the requirements and has already proved to address all other main tasks expected of a modern IT infrastructure management solution. Below are some key product features that make Smart AI Balancer essential for savvy tech companies:
The solution fully meets the requirements and has already proved to address all other main tasks expected of a modern IT infrastructure management solution. Below are some key product features that make Smart AI Balancer essential for savvy tech companies:
- Real-time equipment monitoring: tracks the status and load of the CPU, hard drive, RAM, and local network in real time for a complete understanding of resource usage.
- Load balancing: offers both automatic and semi-automatic (operator-confirmed) load balancing of computing resources to maximize efficiency and reduce energy consumption when resources are scarce.
- Tracking unused capacity: identifies and tracks unused reserved capacities to minimize losses-hot standby is more reliable and efficient, especially in modern microservices environments.
- Forecasting: analyzes historical resource consumption data for each VM and creates individual consumption models.
- Planning: considers various infrastructure changes and their consequences.
- Detailing: transparently shows the entire path of the company's IT infrastructure resources.
- Support for multiple hypervisors and orchestrators: is compatible with various hypervisors and orchestrators from different manufacturers, enabling it to operate in a multi-cloud environment and facilitate the migration of computing infrastructure from one solution to another.
- Flexible configuration and placement rules of IT resources: provides a system that can be easily reconfigured according to any IT resource placement rules based on the company's unique requirements.
Conclusion
When designing any information system, one of the key aspects is performance planning and resource optimization. The load on data centers is variable, so it is essential to distribute the load effectively and balance reserves correctly during peaks and unforeseen circumstances.
With our Smart AI Balancer, clients can increase the efficiency of their IT resources by 30% and protect their IT infrastructure from failures. Additional advantages include an acceptable cost, suitable for both large businesses and medium-sized enterprises, as well as continuous improvements and updates based on user needs and market trends.
With our Smart AI Balancer, clients can increase the efficiency of their IT resources by 30% and protect their IT infrastructure from failures. Additional advantages include an acceptable cost, suitable for both large businesses and medium-sized enterprises, as well as continuous improvements and updates based on user needs and market trends.