Lecture-05: Data Centers in Database (DBMS)

 What is a data center?

A data center is a physical location that stores computing machines and their related hardware equipment. It contains the computing infrastructure that IT systems require, such as servers, data storage drives, and network equipment. It is the physical facility that stores any company’s digital data.

A data center is a facility that houses computer systems and related components, including storage, server and network systems, in a highly controlled environment. These facilities are designed to ensure that critical data is stored and processed in a secure, reliable, and highly available manner.

Modern data centers also provide cloud services, which enables businesses to access computing resources and data storage on-demand over the internet.

    Figure: Data Center

Data centers bring several benefits, such as: 

1)      Backup power supplies to manage power outages

2)      Data replication across several machines for disaster recovery

3)      Temperature-controlled facilities to extend the life of the equipment

4)      Easier implementation of security measures for compliance with data laws 

What are the core components of data centers?

Elements of a data center are generally divided into the following primary categories:

1)     Facility. This includes the physical location with security access controls and sufficient square footage to house the data center's infrastructure and equipment.

2)     Networking equipment. This equipment supports the storage and processing of applications and data by handling tasks such as switching, routing, load balancing and analytics.

3)     Enterprise data storage. A modern data center houses an organization's data systems in a well-protected physical and storage infrastructure along with servers, storage subsystems, networking switches, routers, firewalls, cabling and physical racks.

4)     Support infrastructure. This equipment provides the highest available sustainability related to uptime. Components of the support infrastructure include the following:

a.      Power distribution and supplemental power subsystems.

b.     Electrical switching.

c.      UPSes.

d.     Backup generators.

e.  Ventilation and data center cooling systems, such as in-row cooling configurations and computer room air conditioners.

f.      Adequate provisioning for network carrier connectivity.

5)     Operational staff. These employees are required to maintain and monitor IT and infrastructure equipment around the clock.

 

 What are the types of data centers?

Depending on the ownership and precise requirements of a business, a data center's size, shape, location and capacity can vary.

Common data center types include the following:

• Enterprise data centers. These proprietary data centers are built and owned by organizations for their internal end users. They support the IT operations and critical applications of a single organization and can be located both on premises and off-site.
• Managed services data centers. Managed by third parties, these data centers provide all aspects of data storage and computing services. Companies lease, instead of buy, the infrastructure and services.
• Cloud-based data centers. These off-site distributed data centers are managed by third-party or public cloud providers, such as Amazon Web Services, Google or Microsoft. Based on an infrastructure-as-a-service model, the leased infrastructure enables customers to provision a virtual data center within minutes.
• Colocation data centers. These rental spaces inside colocation facilities are owned by third parties. The renting organization provides the hardware, and the data center provides and manages the infrastructure, including physical space, bandwidth, cooling and security systems. Colocation is appealing to organizations that want to avoid the large capital expenditures associated with building and maintaining their own data centers.
• Edge data centers. These are smaller facilities that solve the latency problem by being geographically closer to the edge of the network and data sources. Edge data centers also enhance application performance and customer experience, particularly for real-time, data-intensive tasks, such as big data analytics, artificial intelligence and content delivery.
• Hyperscale data centers. Synonymous with large-scale providers, such as Amazon, Meta and Google, these hyperscale computing infrastructures maximize hardware density, while minimizing the cost of cooling and administrative overhead.
• Micro data centers. Micro data centers are compact design data centers associated with edge computing. While smaller than traditional data centers, micro data centers deliver comparable functionalities. They simplify edge computing setup through quick deployment, needing less space and power. A standard micro data center container or locker typically houses less than 10 servers and 100 virtual machines.

 

A green data center is an energy-efficient facility designed to minimize environmental impact.

Traditional data centers often consume vast amounts of electricity and generate a lot of heat.

Green data centers leverage advanced technologies and sustainable practices to optimize energy usage and reduce their carbon footprint

What are the standards of a data center?

data centers can be defined by various levels of reliability or resilience, sometimes referred to as data center tiers. In 2005, the American National Standards Institute and the Telecommunications Industry Association published standard ANSI/TIA-942, "Telecommunications Infrastructure Standard for Data Centers," which defines four tiers of data center design and implementation guidelines.

Tiers can be differentiated by available resources, data center capacities or uptime guarantees. The Uptime Institute defines data center tiers as follows:

• Tier I. These are the most basic types of data centers, and they incorporate a UPS. Tier I data centers don't provide redundant systems but should guarantee at least 99.671% uptime.
• Tier II. These data centers include system, power and cooling redundancy and guarantee at least 99.741% uptime. An annual downtime of 22 hours can be expected from a Tier II data center.
• Tier III. These data centers provide partial fault tolerance, 72 hours of outage protection, full redundancy and a 99.982% uptime guarantee.
• Tier IV. These data centers guarantee 99.995% uptime -- or no more than 26.3 minutes of downtime per year -- as well as full fault tolerance, system redundancy and 96 hours of outage protection.

Beyond the basic issues of cost and facility size, sites are selected based on a multitude of criteria, such as geographic location, seismic and meteorological stability, access to roads and airports, availability of energy and telecommunications, and even the prevailing political environment.

Once a site is secured, the data center architecture can be designed with attention to the mechanical and electrical infrastructure, as well as the composition and layout of the IT equipment. All these issues are guided by the availability and efficiency goals of the desired data center tier.

  

Key challenges faced by data centers

Data centers face many key challenges:

1. Firstly, security is a major challenge for data centers. Data centers must protect sensitive data from cyber threats. For example, hacking, malware, and phishing attacks.
2. Secondly, Power and cooling are also important challenges. Data centers require significant amounts of energy to operate. Moreover, they generate a considerable amount of heat. This can lead to overheating. To avoid disruptions, it must be effectively dispersed.
3. Thirdly, Data center modernization is another challenge. Older data centers may not be equipped to handle modern computing requirements. Thus, regular upgrades to a data center’s components are not unusual. Whether the aim is to increase processing power, general efficiency, storage capacity, or something else.
4. Fourthly, for this same reason, storage systems are an ongoing challenge. The amount of stored data continues to grow at an exponential rate.
5. Lastly, the demand for processing power, keeps growing. As machine learning and artificial intelligence, require great amounts of computational capacity.