Welcome to Keep Your Cool - a series tackling simple cooling optimization strategies for the busy data center operators by former busy data center operator, Gregg Haley.

I have been avoiding trying out ChatGPT since its first introduction. Being an old school practitioner, I was reluctant to communicate with a machine. Would it understand what I was asking for? However, having seen some examples posted on LinkedIn, by people whom I know and respect, and having watched the 60 Minutes program last night - where Scott Pelle was typing in requests, I broke down this morning and gave it a shot.

My disclaimer is that I am a Principal Consultant at Purkay Labs, where our primary product is the AUDIT-BUDDY portable, temporary, monitoring tool used for measuring and managing airflow in the data center which we use to perform Assessment Services.  

I was amazed at the speed of the answers, the quality of the response, as to what my query was interpreted as versus what I had in my mind..

Query 1 - second attempt

I had neglected to save the first query's response and logged back retyping exactly what the first query asked. However I received a more detailed response. So I guess If you don’t like the first answer, ask again?

My Query: List the best energy efficiency practices for data centers.

Data centers are essential for storing and processing large amounts of data, but they can also be incredibly energy-intensive. Here are some of the best energy efficiency practices for data centers:

1. Virtualization: By consolidating multiple servers onto a single physical machine, virtualization reduces the overall number of servers needed to run a data center, resulting in significant energy savings.

2. Airflow management: By using hot and cold aisle containment, blanking panels, and floor grates, data centers can optimize airflow and reduce energy consumption by cooling only the necessary areas.

3. Energy-efficient hardware: When selecting servers and other hardware, choose models that are designed to be energy efficient, such as those with low-power processors, high-efficiency power supplies, and variable-speed fans.

4. Temperature management: By raising the temperature in the data center, IT managers can reduce cooling costs without negatively impacting the equipment. Most equipment can operate within a wider range of temperatures than traditionally thought.

5. Lighting: Switching to energy-efficient LED lighting can reduce energy consumption in a data center by up to 40%.

6. Renewable energy: Installing solar panels or other renewable energy sources on or near a data center can offset some or all of the facility's energy consumption.

7. Power management: By using tools to manage and monitor power usage, IT managers can identify and address inefficiencies in real-time.

8. Energy-efficient cooling systems: Upgrading to more efficient cooling systems, such as air-side economizers or water-side economizers, can significantly reduce energy consumption.

9. Server and hardware management: Reducing idle time, consolidating or eliminating underutilized hardware, and prioritizing energy-efficient hardware usage can contribute to energy savings in data centers.

10. Regular maintenance: By regularly maintaining hardware and equipment, IT managers can ensure that everything is running at maximum efficiency and identify potential issues before they become major problems.

These were all good answers to the query presented. But since my mind was set on getting a more precise answer on the importance of Airflow Management - I tried a second query.

Query 2

My Query: Explain how airflow management improves data center operating efficiency.

Airflow management is a critical component of data center design and operation, and it plays a key role in improving data center operating efficiency. Proper airflow management helps ensure that equipment receives the necessary cooling to operate at optimal temperatures, while minimizing energy usage and reducing the risk of equipment failure.

Here are some ways in which airflow management can improve data center operating efficiency:

1. Reducing Hot Spots: Hot spots occur when air is not flowing efficiently through the data center, resulting in areas that are significantly warmer than others. These hot spots can cause equipment to overheat and fail, leading to costly downtime. Proper airflow management helps reduce hot spots by ensuring that air is distributed evenly throughout the data center.

2. Improving Cooling Efficiency: Efficient cooling is essential to data center operation, as it helps prevent equipment from overheating and failing. Proper airflow management helps improve cooling efficiency by ensuring that cold air is delivered where it is needed most, and that hot air is removed from the data center as quickly as possible.

3. Reducing Energy Usage: By optimizing airflow management, data centers can reduce the amount of energy needed to cool equipment. This can lead to significant cost savings over time, as energy is one of the largest expenses associated with data center operation.

4. Extending Equipment Lifespan: Overheating is a leading cause of equipment failure in data centers. By ensuring that equipment is properly cooled through effective airflow management, data center operators can extend the lifespan of their equipment and reduce the risk of costly downtime.

In summary, proper airflow management is essential for improving data center operating efficiency. It helps prevent equipment failure, reduces energy usage, and extends the lifespan of equipment.

Conclusion

I was encouraged that the second attempt at Query1 provided a more detailed list of practices that can be taken to improve data center efficiency. Query 2 was a narrower ask and I feel it gave good general answers. 

Could I have written the answers ChatGPT provided? I feel with my many years of experience I’d have come close to duplicating ChatGPT; however, I would never have been able to develop those responses in seconds. 

Will I use ChatGPT again in the future? Yes, and as I refine my requests the responses should more accurately reflect what I am asking for. The old saying “Garbage in Garbage out” should be updated to “Garbage in Gospel out”. As correct and spot on as AI can be, it can also be off target and misleading. My exploration was in an area of knowledge I am comfortable with and allowed me to qualify the accuracy of the responses. Stay tuned as I move from baby steps to jogging with ChatGPT.

About the Author

Gregg Haley is a data center and telecommunications executive with more than 30 years of leadership experience. Most recently served as the Senior Director of Data Center Operations - Global for Limelight Networks. Gregg provides data center assessment and optimization reviews showing businesses how to reduce operating expenses by identifying energy conservation opportunities. Through infrastructure optimization energy expenses can be reduced by 10% to 30%.

In addition to Gregg's data center efforts, he has a certification from the Disaster Recovery Institute International (DRII) as Business Continuity Planner. In November of 2005, Gregg was a founding member and Treasurer of the Association of Contingency Planners - Greater Boston Chapter, a non-profit industry association dedicated to the promotion and education of Business Continuity Planning. Gregg had served on the chapter's Board of Directors for the first four years. Gregg is also a past member of the American Society of Industrial Security (ASIS). Gregg currently serves as the Principal Consultant for Purkay Labs.