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Message Please note that the part information is already included in the email that is sent to the sellers. Subscribe to the TPI Newsletter. If the implementation offers file system events, the container state as it relates to a specific event must reflect the host file system state at the time the event was generated if no container modifications pertain to related file system state.
If flush or sync operations are performed, relevant data must be written back to the host file system. Between flush or sync operations containers may cache data written, metadata modifications, and directory structure changes. All containers hosted by the same runtime must share a consistent cache of the mount. When any container sharing a delegated mount terminates, changes to the mount must be written back to the host file system. If a delegated mount is shared with a cached or a consistent mount, those portions that overlap must obey cached or consistent mount semantics, respectively.
Besides these constraints, the delegated configuration offers the container runtime a degree of flexibility:. Containers may retain file data and metadata including directory structure, existence of nodes, etc indefinitely and this cache may desynchronize from the file system state of the host. Implementors should expire caches when host file system changes occur, but this may be difficult to do on a guaranteed timeframe due to platform limitations. If changes to the mount source directory are present on the host file system, those changes may be lost when the delegated mount synchronizes with the host source directory.
The cached configuration provides all the guarantees of the delegated configuration, and some additional guarantees around the visibility of writes performed by containers. As such, cached typically improves the performance of read-heavy workloads, at the cost of some temporary inconsistency between the host and the container.
Implementations must obey delegated Semantics If the implementation offers file system events, the container state as it relates to a specific event must reflect the host file system state at the time the event was generated. Container mounts must perform metadata modifications, directory structure changes, and data writes consistently with the host file system, and must not cache data written, metadata modifications, or directory structure changes.
If a cached mount is shared with a consistent mount, those portions that overlap must obey consistent mount semantics. Some of the flexibility of the delegated configuration is retained, namely:. Implementations may permit delegated Semantics 6. The consistent configuration places the most severe restrictions on the container run-time.
For directories mounted with consistent the container and host views are always synchronized: writes performed within the container are immediately visible on the host, and writes performed on the host are immediately visible within the container.
The consistent configuration most closely reflects the behavior of bind mounts on Linux. However, the overheads of providing strong consistency guarantees make it unsuitable for a few use cases, where performance is a priority and maintaining perfect consistency has low priority. Implementations must obey cached Semantics Container mounts must reflect metadata modifications, directory structure changes, and data writes on the host file system immediately.
The default configuration is identical to the consistent configuration except for its name. Crucially, this means that cached Semantics 4 and delegated Semantics 5 that require strengthening overlapping directories do not apply to default mounts. This is the default configuration if no state flags are supplied.
Performance tuning for volume mounts shared filesystems Estimated reading time: 8 minutes Docker Performance implications of host-container file system consistency With Docker distributions now available for an increasing number of platforms, including macOS and Windows, generalizing mount semantics during container run is a necessity to enable workload optimizations.