THE ABILITY TO EXPAND COMPUTE AND CAPACITY INDEPENDENTLY ALLOWS US TO MAKE CHANGES TO THE PLATFORM BASED ON NEED AS OPPOSED TO VENDOR ARCHITECTURE .
END USER INSIGHT END USER INSIGHT
THE ABILITY TO EXPAND COMPUTE AND CAPACITY INDEPENDENTLY ALLOWS US TO MAKE CHANGES TO THE PLATFORM BASED ON NEED AS OPPOSED TO VENDOR ARCHITECTURE .
How has the industry transformed in recent years in terms of data output and the ways in which it relies on data centres today ?
Although the technology within the data centres has changed significantly over the years and some of the types of data have changed , the core requirement of needing low latency access to our data has not – low latency is key to our success . Our artistic process relies on , and is accelerated by , quicker iteration and computational feedback from our computer systems . We continue to invest in systems which reduce our I / O latency with larger capacity and IOP data sets .
How quickly must data centres scale to support computational demands including the enormous amounts of data being processed and how is this managed efficiently ?
The data centre ’ s capacity for artistic growth is complicated by the fact that the concept of artistic growth , like art itself , is subjective . However , to manage this growth I subscribe to the concept of two important observations , or ‘ laws ’, that bring some predictability to the process . The first is the omnipresent Moore ’ s Law which I ’ ve modified in terms of Data Capacity Growth and Computational Processing Growth . By trending both over time we can be fairly predictive about how often we double these two factors . Over a long enough sampling period , CPU and data both tend to normalise . I can then use these doubling rates to plan data centre cooling and power needs in the future , as well as our computation and data storage needs .
The second less-known Law is Blinn ’ s Law which states ‘ rendering time tends to remain constant , even as computers get faster ’. This is mainly due to the observation that as artists have more computational resources they tend to invent new technologies , or as they would say ‘ looks ’, that will utilise those additional resources . This has a lot to do with the creative process of Dailies in which artists typically gather in the mornings to review the renders that were generated the night before . To fit the overnight window of time needed to have Dailies in the morning , artists tend to naturally create renders that fit within the two-to-four hour per job timeframe .
How crucial is a Disaster Recovery strategy for avoiding downtime at an organisation such as yours ?
This is a question I grapple with constantly because there can be a significant financial cost associated with various levels and aspects of recovery . I tend to break recovery up into three categories : immediate individual recovery , mediumterm production workflow recoveries and long-term fileserver recoveries . Each has its own methods and costs associated with the recovery process depending on the time required and the technology used .
What new techniques were you able to consider since working with VAST ?
From a production data storage perspective , Pixar traditionally would tier our data from high-performance / lowcapacity storage to low-performance / high-capacity storage . However , in about 2016 , this model started to break down as our artistic processes evolve . In general , the higher performance tiers that vendors were offering were not growing capacity fast enough to keep up with our creative pipelines . The VAST platform became the best solution for us as it allows us to continue to expand and grow our highperformance and high-capacity pipelines without artistic compromise . Specifically , the all-flash tier allows us to expand without having to consider slowness at the disk aggregate level . The ability to expand compute and capacity independently allows us to make changes to the platform based on need as opposed to vendor architecture . Finally , the persistent memory layer enables various compression and deduplication techniques within the VAST software that gives us the best overall compression we ’ ve ever experienced .
How do you maintain the smooth and seamless delivery of the technology ?
Using any methods we can ! I think it ’ s safe to say that the production process is not necessarily smooth and predictable , and it ’ s not really meant to be . Each project we work on can have its own look and therefore its own I / O profile . We need to be able to pivot quickly , which for us means being willing and able to rearchitect per project if necessary . Therefore , the storage team tends to focus on technologies that can integrate scale-out performance and capacity within a short duration of time .
How has your work with VAST enabled you to continue producing timeless cinematic magic and what does the future hold ?
VAST has been a great collaborator over the past few years and was the foundational technology that we leveraged to produce volumetric characters for our features Soul and Elemental . Their engineering and sales teams engage with us to help us incorporate solutions that allow us to continuously evolve our artistic vision . Additionally , we have moved all data which could be considered for AI training to VAST . In collaboration with the VAST team , we continue to develop new production techniques and technologies to grow at the speed of art . � www . intelligentdatacentres . com
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