Immutable Container Layers for Cloud Startup and Resource Sharing
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Solution Overview
Problem
Cloud-based environments face challenges with startup latency and inefficient resource sharing due to the need for separate virtual computing environments for each user code, leading to slow environment setup times and significant computing power waste from warm module queues.
Innovation Solution
A system that organizes code portions into immutable layers using a package manager and containerization platform, enabling efficient reuse and sharing of layers across multiple environments through a local cache and just-in-time image generation, leveraging a dominator algorithm to compress dependencies and satisfy layer constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If separate virtual computing environments are created for each user code, then code isolation and security are improved, but startup latency increases and resource sharing efficiency deteriorates
Solution Approach 1:
The virtual computing environment is segmented into immutable layers that can be independently cached and shared. Each layer represents a discrete unit of code or dependency that can be reused across multiple environments, allowing the system to maintain isolation while avoiding redundant setup time for identical components.
Solution Approach 2:
Immutable layers are pre-built and cached before being needed for environment creation. The system performs preliminary actions by constructing layers once and storing them for rapid reuse, eliminating the need to recreate identical environment portions for each user code execution.
2Reliability
If separate virtual computing environments are created for each user code, then code isolation is improved, but computing power waste from warm module queues increases
Solution Approach 1:
Multiple virtual computing environments that share common dependencies are merged at the layer level. The system combines identical or compatible layers from different environment requests into a shared cache, allowing multiple isolated environments to leverage the same pre-built code portions and eliminating redundant computation.
Solution Approach 2:
Instead of creating complete duplicate environments, the system creates lightweight copies that reference shared immutable layers. User-specific modifications are applied as thin overlays on top of shared base layers, dramatically reducing the computational resources needed to maintain isolated environments.
3Productivity
If container layers are downloaded and extracted for each environment, then environment setup is completed, but startup times increase from 5-20 minutes
Solution Approach 1:
Container layers are downloaded, validated, and prepared in advance and stored in a cache. When an environment needs to be created, the system retrieves pre-prepared layers from cache rather than downloading and extracting them at runtime, reducing startup time from minutes to seconds.
4Productivity
If layers are shared across virtual machines, then resource efficiency is improved, but layer security and isolation concerns arise
Solution Approach 1:
The security model extracts the immutability property from the layer content and makes it the foundation of the security guarantee. By taking out the mutation operation entirely and allowing only read-only access to cached layers, the system enables sharing while maintaining isolation through the inability of user code to modify shared layers.
Data Source
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AI summary
A package manager used with a containerization platform can organize code portions into immutable layers. Collections of layers can be organized and saved together as an executable unit. Disclosed solutions recognize that because layers do not change, they can be reused by the same user and can also serve as shared building blocks for multiple environments running simultaneously. To facilitate sharing layers, a system can analyze which ones are common to multiple environments and allow multiple simultaneous environments to share common layers. Layer compression and dominator algorithms can be used to address inherent layer constraints. To facilitate use of existing layers for efficient start-up, code packages can be organized into base layers and additional layers, and commonly-used layers can be cached. New or unique environment requests can combine previously-cached base layers and additional layers to avoid redundant calculations. A just-in-time approach can combine layers into new images on the fly and cache the new images for later use.