![]() These images could be taking up a lot of hard drive space and preventing you from taking more photos. Likewise, you might have large images on your phone. Compressing this image would be very useful. ![]() Depending on your needs, this could be too big. A JPG from a professional DSLR camera, for example, could be dozens of megabytes. Why would you want to compress images?ĭepending on the source of an image, the file could be quite large. With lossy compression, how small you want the final file to be will depend on how much loss of quality you’re comfortable with. This results in a smaller file but with a reduced quality. Lossy compression is when the compressor removes excessive or unimportant bits from the original file. This results in a smaller file that has the exact same quality as the original. Lossless compression is when the compression tool removes empty, needless, or duplicated bits from the original file. ![]() There are two types of compression: lossless and lossy. Simply put, it means converting a large file into a smaller file. Interested in learning more? Check out the example library in our SlimToolkit (previously DockerSlim) open source project, or shoot us an email at to request a beta invite.In terms of digital files, compression is the act of encoding information using fewer bits than what’s found in the original file. ![]() Most developers today don’t know, and don’t have time to learn, how to dissect their Docker images, make smart optimizations, and get the right tooling to ship their containers safely and effectively.Īt Slim.AI, we’re working on tools that automate the process of slimming and optimizing images. Slimmed images can also be compressed, usually with the same compression ratios of non-slimmed images. Slim images are faster, more performant, and safer, as the act of slimming an image reduces the attack surface of a container. You may have a different slimmed image in your development environment than you do in staging or production. Slimming an image also reduces the container size, but is a dynamic and use-case specific process. This process is often manual and requires specialized knowledge. This leads to better outcomes across all phases of development. Slimming an image results in a container that has only the code it needs to run and nothing more. When we talk about slimming images, we’re talking about a system of tools and techniques to optimize an image. Compressed images don’t run their primary function is to move smoothly through the pipeline and reduce transfer costs and disk space. The Docker executable even does this for you by default by producing a tarball of your container.
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