![]() ![]() The second variable that impacts calculations is our underlying storage. CPUs horizontally scale by adding more cores, and this works well with the ability to break our object into multiple parts, allowing us to modernize our approach by parallelizing integrity checks. Calculating a SHA256 checksum on 1TB of data in an Amazon Elastic Compute Cloud (Amazon EC2) i3en.2xlarge instance takes 86 minutes. Traditional methods for performing object integrity validation are directly impacted by the size of the file. The final step in creating the ETag is when Amazon S3 adds a dash with the total number of parts to the end. Amazon S3 concatenates the bytes for the MD5 digests together and then calculates the MD5 digest of these concatenated values. MD5 digests are used to determine the ETag for the final object. Amazon S3 calculates the MD5 digest of each individual part. To increase the speed of uploading a file to Amazon S3, large objects are cut into smaller pieces -known as parts-via the multipart API call. Amazon Simple Storage Service (Amazon S3) uses the new checksum feature to gain access to parts of an object that did not previously exist. This enables the calculation to run concurrently and reduces the total time for the checksum to complete. Each part of the file has a unique checksum value, different from the sequential calculation. In this post, we cover a different approach by splitting the calculation across different parts of the file. As the files grow in size the total time to compute the checksum increases and becomes more costly using traditional methods. Performing a checksum on a file entails using an algorithm to iterate sequentially over every byte in a file, and leveraging compute to calculate the checksum. With checksums, users can verify that assets are not altered when copied. Today, the industry uses algorithms to scan a file byte by byte to generate a unique fingerprint for it, known as checksum. ![]() As assets move from one step to the next in a workflow, customers want to make sure the files are not altered by network corruption, hard drive failure, or other unintentional issues. Common assets include digital camera negatives, film scans, post-production renders, and more, all of which are business-critical. Customers in the media and entertainment industry interact with digital assets in various formats. ![]()
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