70% of storage buyers in Tintri’s study admit miscalculating storage needs when planning new capacity.
According to research conducted by Tintri at IPExpo in London in October 2017, nearly a quarter (24%) of storage capacity planning decisions are made by IT leaders on the basis of a ‘best guess’ or no planning at all. In addition, three quarters of the respondents in the study operate with up to 20% of their storage capacity unused, keeping it in place as a buffer to maintain predictable performance.
When planning storage capacity needs, 42% of the respondents rely on previous experience, but only 12% run a simulation project to help accurately guide decisions. Just under 10% of the respondents carry out no planning at all for future needs, and only one fifth (22%) rely on input from technology vendors or partners.
The research also revealed that accurate storage capacity planning is a challenge for most buyers, with 70% of the respondents reporting that they have underestimated (43%) or overestimated (27%) their needs. In addition, 77% of the respondents reported that up to a fifth of their storage capacity is unused, except as acting as a buffer to maintain performance. At the extremes, 37% revealed that more than a fifth of their storage capacity is unused, with only 10% able to report that they operate with 5% unused storage capacity or less.
“While previous experience and knowledge are valuable methods to help predict future storage needs, many environments are becoming too complex to rely on that approach anymore,” commented Scott Buchanan, Chief Marketing Officer at Tintri. “Guesswork leads to performance issues or overprovisioning—and with the analytics tools available today, it’s simply unnecessary.”
“Our customers understand the importance of precise planning. It saves them anguish and it saves them money. And in our experience, the most accurate planning is only possible when you’re working with granular analytics,” said John N. Brescia, CTO at Virtix IT. “That’s part of Tintri’s value—its analytics are based on the actual behavior of each individual virtual machine. By using up to three years of historical data to forecast future resource needs, Tintri helps our customers reduce guessing.”