The evolution of Data Centers on the path to automation is a process of constant review and continuous improvement. Therefore, our commitment at Bjumper to conducting this annual survey is essential to assess the maturity of the market and its players.
One of the fundamental aspects closely related to process automation is how time affects our daily tasks, from operation and maintenance to the comprehensive management of our systems and organizations. Specifically related to Data Centers, this can be seen in something as common, yet equally critical, as how much downtime the service experiences, which results in financial penalties; the time that equipment remains powered on unnecessarily or at least at its maximum capacity; or the penalties that may result from failing to meet an SLA for a Colo regarding response time to an incident.
To refresh the concept of maturity or for new readers, the image below illustrates the path to automation in the management of critical infrastructure:
Management scheme for the path to automation.
Starting with the first step on Monitoring and Information, this year we've gone a bit further in terms of the data being monitored by different organizations, opting to obtain greater granularity in the information (having data, data per room, per row, per rack, and per server or device) on the three most important variables: power, consumption, and temperature, taking into account the data maturity level as shown below:
Level of maturity of the monitored data
The appreciation of the gathered and subsequently analyzed information has allowed us to reach encouraging conclusions, with data primarily monitored by rack or by server for both power and consumption, although the same doesn't apply to temperature. This is often logical because temperature is mainly measured and controlled within each aisle, as they can have hot air containment from the equipment or cool air intake to cool the devices.
On the other hand, having data sources in a single automated update source is fundamental for making infrastructure management simpler, more direct, and efficient. The survey data in this regard shows that only 6% of the respondents have the best scenario for this metric, while the majority of the sample is in the less favorable scenario as illustrated below:
Level of Digitalization of Data Sources and Information Storage Mode
In this line of thought, we find closely related to data sources the method of identifying IT assets, the management of maintenance processes, and process documentation.
Firstly, IT asset identification had a result of 59% of respondents using a unique code for each item, with only 69% of these relying on the standard equipment label, lacking one more step to fully and uniformly digitize this information.
Technology for IT asset identification encoding
On the other hand, maintenance process management shows a low level of maturity. The data obtained indicates that 38% of the respondents perform this process manually with various sources of information, and 50% use a legacy corporate ticketing tool that is not specific to data center operations.
Moving on to the second stage on the path to automation, we encounter Proactive Infrastructure Capacity Management, as well as possible scenarios that may occur and how to anticipate them.
Regarding the second stage, the information obtained about process documentation revealed a positive situation related to events and monitoring, with 60% of the respondents having this data automated. However, in the following aspects, manual documentation is more prevalent, indicating that there is significant work to be done to advance on the path to automation: Move, Add, Change (MAC) processes (47% manual), incident contingency (62% manual), ongoing optimization (66% manual and 20% undocumented), and documentation related to certifications/audits (65% manual and 18% undocumented).
It is worth noting that the ability to obtain information automatically (in 2 clicks) from the respondents in the sample mostly pertains to general facility data, such as Power Usage Effectiveness (PUE), followed by cost/utilization of infrastructure by service/application. This is quite noteworthy because the latter type of information is in the highest level of maturity, while the former is still in the early stages of the path to automation. This shows the significant interest of the respondents in knowing the specific cost/utilization of facilities to enable accurate sectorized billing for colocation companies or to identify operational improvements within the enterprise sector.
Type of information obtained automatically (2 clicks).
He indicators we have obtained regarding the number of people operating the sites, whether they are internal or external, and the staff turnover provide a clear approximation to the data indicated in the previous paragraph, thus establishing a relationship that, for medium to large infrastructures, most of the personnel are external and experience higher staff turnover. This not only makes it challenging for the company to establish a well-structured roadmap for automation but also makes it difficult to define clear and concise procedures for planning and implementing a new IT team (equipment renewal or infrastructure expansion). Below, the average time for this action is detailed, along with how this time is obtained:
Method for obtaining the average time from planning to commissioning of new equipment:
As we reach the end of the maturity scale, the transition to Energy and Process Optimization and Automation, where technology, processes, and people are integrated, is very clear to the respondents. They emphasize the importance of adapting working methods to make the most of new technologies. Furthermore, there have been remarkable changes in the stages on the path to automation between last year and the present year. :
Evolution of the Path to Automation
Antagonistically, there are certain issues that still require work and consensus on general guidelines and steps to follow in order to have fully automated facilities.
Regarding the advantages of automation, 57% of the respondents indicated that the main advantage of automation is risk minimization, 33% mentioned cost reduction, and only 10% cited revenue increase. While risk minimization is often the most visible outcome of automating a process, cost reduction can be more significant with a proper technical advisory study.
In line with the issues that require further focus for continued maturation, 47% of the sample stated that they have no monitoring or automation projects planned for the next 12 to 24 months, in contrast to their aspirations regarding their position on the maturity pyramid (75% expressed a desire to be at the highest level). Closely related to this point is the conclusion that there is a need for a higher level of detailed knowledge about what it takes to evolve correctly and systematically towards automation.
Key factors for the success of automation.
As we have been able to evaluate, tracking the level of maturity linked to last year's and this year's survey has shown us that the market is very well aligned with clear and concise concepts in certain aspects, while in others, there remains an exciting and challenging path to follow, which will undoubtedly bring benefits in terms of profitability, sustainability, and, above all, efficiency in resource utilization, making the management of our facilities less critical.
We would like to thank all the survey participants for sharing their experiences and for making this market a more open and participatory environment. Together as a community, we can better understand how to collaborate to become more efficient and improve.
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