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1. #Construct 3 recompress images drivers#
2. #Construct 3 recompress images full#
3. #Construct 3 recompress images plus#
4. #Construct 3 recompress images free#

In our earlier posts, we have described dynamic generation of thumbnail sizes and perceptual compression. With a couple simple configuration changes, we freed up more than 8% of our storage. This was our simplest approach to the problem (by far), but it resulted in a large gain.

#Construct 3 recompress images free#

So we combined our our two just-in-case areas into one and reduced our free space threshold to that level. Trade lore states that disks should remain 10% free to avoid performance degradation, but we found 5% to be sufficient for our workload. This resulted in about 13% of our storage going unused. 5% of our storage was reserved space for snapshots, useful for undoing accidental deletes or writes, and 8.5% was held free in reserve. We also had two distinct areas of just-in-case space. Users only rarely delete or change images once uploaded. We discovered that our settings were based on assumptions about high write and delete loads that didn’t hold.

Adjusting Storage ThresholdsĪs we dug into the problem, we looked at our storage systems in detail. We sketched out a few and cover three that we implemented below: adjusting thresholds on our storage systems, rolling out existing savings approaches to more images, and deploying lossless JPG compression. There are also a number of engineering approaches to controlling storage costs. To name a few: storing lower quality images or re-compressing, charging users for their data usage, incorporating advertising, selling associated products such as prints, and tying storage to purchases of handsets.

In response to these costs, photo storage services have pursued a variety of product options. And iPhone images are far from the largest. On iPhones, increasing camera resolution, burst mode and the addition of short animations (Live Photos) have increased bytes-per-image rapidly enough to keep storage cost per image roughly constant. Unfortunately, these lower costs per byte are counteracted by other forces. NAS vendors have also delivered large price reductions. For example, S3 costs dropped from $0.15 per gigabyte month in 2009 to $0.03 per gigabyte-month in 2014, and cloud storage vendors have added low-cost options for data that is infrequently accessed. Cost per image hasn’t changed significantly. Thankfully, our costs, and every large service’s costs, are different than storing naively at S3, but remain significant.Ĭost per byte have decreased, but bytes per image from iPhone-type platforms have increased.

This compounds as new users sign up and existing users continue to take photos at an accelerating rate.

#Construct 3 recompress images plus#

At a thousand images each, storage in a service similar to S3 would cost over $250 million per year (or $1.25 / user-year) plus network and other expenses. Stored naively in a cloud service similar to S3, this day’s worth of data would cost over $30,000 per year, and continue to incur costs every year.Īnd a very large service will have over two hundred million active users. These photos require an average of 3.25 megabytes of storage each, totalling over 80 terabytes of data. On a very high-traffic day, Flickr users upload as many as twenty-five million photos. The Cost StoryĪ little back-of-the-envelope math shows storage costs are a real concern.

#Construct 3 recompress images full#

These projects have been very successful, but our storage cost is still significant.Īt the beginning of 2016, we challenged ourselves to go further - to go a full year without needing new storage hardware. We’ve described multiple techniques to get this cost down over the years: use of COS, creating sizes dynamically on GPUs and perceptual compression.

#Construct 3 recompress images drivers#

One of the largest cost drivers in running a service like Flickr is storage.