Here are the important things you need to know to implement AI into your data center operations successfully
Artificial intelligence (AI) is revolutionizing data center and cloud management. It can help automate and streamline your operations, provide exceptional customer experiences, empower staff, and do much more.
But taking advantage of AI’s opportunities often requires tackling some challenges and unknowns, such as how much more computing power and storage you need to crunch massive amounts of data. Or how does your organization cultivate the skills to work with the technology successfully? What is the evolving cost equation between cloud and on-premises solutions? How do you address security threats? And how do you realize your ROI from an investment in AI?
AI presents data center and cloud management trends essential to your business. To help you explore the possibilities and avoid the pitfalls of this paradigm shift for data centers, read on.
Talent Transformation: Upskilling for the Future
The tech industry has always struggled to find enough skilled workers to meet its needs. For example, the 2023 Uptime Institute Global Data Center Survey reveals that qualified staff shortages have plagued the data industry for the past decade.
The situation is heightened in the era of data centers and cloud management AI. With the growing demand for data centers (which also need to ramp up their data capacities), staff with the right skills are in short supply. Many businesses face the challenges of attracting skilled employees in a highly competitive job market (and keeping them after they’re employed) and imparting new skills to existing staff.
In some cases, by implementing the most advanced AI and machine learning (ML) technology, data centers can supplement human skills, lessening the staff shortage problem. Also, if a business implements state-of-the-art data center AI and cloud management AI, this, in turn, can be used to attract highly skilled workers who want to be employed by cutting-edge firms.
Once qualified staff are hired, companies must implement a continuous learning strategy (including upskilling existing employees) to retain talent. They also have to be committed to evolving their operations as new uses for technology are discovered.
By adopting AI technology, data centers can make their operations more efficient, saving money, decreasing the demand for more workers, and improving the working conditions for existing staff.
Cloud vs. On-Premises: A Dynamic Balance
Among the major data center and cloud-management trends is the tendency for many firms to embrace hybrid models and infrastructure. This is where you take a holistic approach to simplifying your overall infrastructure, lowering the cost of ownership, increasing security, and accelerating time to market with the right combination of cloud tools and on-site infrastructure.
Finding the correct balance often involves solving the constantly changing cost equation between cloud and on-premises infrastructure in the context of AI workloads. A data center that has found the migration to the cloud to be more expensive than originally expected might decide to bring certain workloads (especially ones with predictable demands) in-house for savings and efficiency.
While investing in hardware and facilities for an in-house setup can be expensive initially, the cost can be lessened with successful management over time. An on-premises setup can overcome scalability challenges with the right modular, scalable infrastructure investments.
And, of course, AI in cloud computing and machine learning models can provide benefits in a hybrid infrastructure, including:
- Automation and efficiency
- Data insights and analysis
- Better tools for strategic decision-making
- Generating more site traffic with intelligent automation
- Cost-effective scalability
- Greater flexibility
Securing the Future: Evolving Security Landscape
Most security professionals feel that AI poses security threats with its data-driven applications. These can include sensitive information accidentally exposed by large language models (LLMs) and AI-driven attacks on systems.
While AI can pose security threats, it also can provide solutions with increasingly powerful AI-driven threat detection systems. Security and safety can also be achieved with the support of the right partner, who can help you implement and manage secure technology solutions.
These can include:
- Implementing efficient ways to assess and ensure compliance
- Developing a controlled environment that maintains security
- Offering an experienced engineering team that can help you address the technical security requirements to safeguard your organization’s system’s networks, applications, and data from digital attacks
Feeding the Beast: Data Availability for AI Models
Many AI applications require reliable, real-time access to high-quality, clean, accurate, and consistent data. With poor data, you run the risk of making mistakes and poor decisions. Proper data governance helps you to implement standard data collection and management processes that make\ sure that there is consistency across different data sources, which is important for training efficient AI models.
You may also have to deal with governance rules that cover the security of sensitive information and the strict privacy requirements of regulations such as GDPR (General Data Protection Regulation) and CCPA (California Consumer Privacy Act), which can levy heavy fines when transgressed.
One way to store a vast amount of centrally located, usable data is to create a “data lake.” This flexible storage repository can hold vast amounts of raw, structured, semi-structured, and unstructured data. These can include many different data types and sources, ranging from text and log files to database exports.
Data lakes can be created with on-premises technologies such as traditional data storage solutions and frameworks or with cloud-management tools such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
Automation Revolution: Leveraging AI and Machine Learning
The role of AI and ML in automating data center and cloud management tasks is already significant and continuing to grow. AI and ML algorithms excel at discerning patterns in datasets. They then use predictive analytics to apply their learning to future tasks, automating and optimizing many daily tasks.
The benefits of the technology include:
- Optimizing resource management
- Making real-time improvements to data center cooling systems
- Improving workload management
- Spotting problems before they occur
- Creating better customer experiences
- Putting in place proactive security measures
- Reducing error rates
While AI provides remarkable capabilities, it still needs to work with human oversight at every stage of its development. Without human input, the AI systems wouldn’t have the data they need to complete tasks, answer queries, and provide valuable results. People must fine-tune AI systems to perform new functions, meet new guidelines, and better analyze new data.
CoreBTS: Your Partner in AI-Driven Solutions
To understand and implement the important AI and ML technologies needed to help your business survive and thrive in this new era, it’s important to have a trusted partner specializing in digital transformation. This is where CoreBTS comes in. We have a history rooted in infrastructure and cloud technology, with \a particular focus on creating and managing workloads in hybrid cloud environments.
We can help you create and implement an AI strategy for your business and understand all the associated costs so there are no surprises.
Contact our team today for a customized assessment that will provide you with real intelligence on incorporating artificial intelligence into your business.
