Container Image VMDK Mounting for Virtualized Workloads
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Solution Overview
Problem
Existing approaches for deploying containerized workloads in virtualized environments face significant delays due to the time-consuming process of downloading and extracting entire container images, which increases container bring-up time and resource utilization.
Innovation Solution
Storing container images in a format that the virtual computing instance (VCI) can understand, such as tar, and making them accessible via local or network-based storage, allowing the host control plane to attach and mount the images directly to the VCI, eliminating the need for full image download and extraction before container launch.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If container images are downloaded and extracted before container launch, then the container can be deployed with complete image data, but the container bring-up time increases significantly
Solution Approach 1:
The system performs preliminary actions by downloading and extracting container images in advance before they are needed for container launch. The images are stored in a local cache or image registry, so when a container needs to be created, the image data is already prepared and available, eliminating the delay of downloading and extracting at launch time.
Solution Approach 2:
The system creates copies of container images and stores them in a local cache or image registry. Instead of downloading the full image every time a container is launched, the system uses these pre-copied image files, significantly reducing the time required for container bring-up while maintaining complete image data for reliable deployment.
2Reliability
If entire container images are downloaded and extracted, then the container has full access to all image data, but resource consumption increases
Solution Approach 1:
The system segments the container image into layers and selectively extracts only the necessary layers for container operation. Instead of extracting the entire image, the system identifies and extracts only the required segments, reducing resource consumption while maintaining full image availability for the container.
Solution Approach 2:
The system extracts only the essential components and layers from the container image that are needed for container operation, leaving the rest of the image data stored but not extracted. This selective extraction reduces resource consumption while ensuring the container has access to all necessary image data for reliable deployment.
3Productivity
If container images are stored in a format understandable by VCI (such as tar), then the host control plane can attach and mount images directly, but storage space requirements increase
Solution Approach 1:
The system changes the parameter of image format from compressed archives to uncompressed formats like tar that are directly understandable by VCI. This parameter change allows the host control plane to attach and mount images directly without extraction, significantly improving container launch speed. The system manages the increased storage space requirements through efficient caching and image lifecycle management.
Data Source
AI summary
A method for provisioning images to deploy containerized workloads in a virtualized environment can include bringing up a containerized workload in a virtualized computing environment responsive to receiving a request to run a containerized workload in the virtualized computing environment. Bringing up the containerized workload can include creating a VMDK that includes a container image in shared storage of an image registry responsive to authenticating with the image registry, attaching the VMDK to a virtual computing instance, responsive to receiving a request, made by a container running in the VCI, for a file of the container image in the attached VMDK, retrieving the file from the shared storage, and bringing up the containerized workload using the file.