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 # Copy-on-write filesystems
 
-FIXME
+Container engines rely on copy-on-write to be able
+to start containers quickly, regardless of their size.
+
+We will explain how that works, and review some of
+the copy-on-write storage systems available on Linux.
+
+---
+
+## What is copy-on-write?
+
+- Copy-on-write is a mechanism allowing to share data.
+
+- The data appears to be a copy, but is only
+  a link (or reference) to the original data.
+
+- The actual copy happens only when someone
+  tries to change the shared data.
+
+- Whoever changes the shared data ends up
+  using their own copy instead of the shared data.
+
+---
+
+## A few metaphors
+
+--
+
+- First metaphor:
+  <br/>white board and tracing paper
+
+--
+
+- Second metaphor:
+  <br/>magic books with shadowy pages
+
+--
+
+- Third metaphor:
+  <br/>just-in-time house building
+
+---
+
+## Copy-on-write is *everywhere*
+
+- Process creation with `fork()`.
+
+- Consistent disk snapshots.
+
+- Efficient VM provisioning.
+
+- And, of course, containers.
+
+---
+
+## Copy-on-write and containers
+
+Copy-on-write is essential to give us "convenient" containers.
+
+- Creating a new container (from an existing image) is "free".
+
+  (Otherwise, we would have to copy the image first.)
+
+- Customizing a container (by tweaking a few files) is cheap.
+
+  (Adding a 1 KB configuration file to a 1 GB container takes 1 KB, not 1 GB.)
+
+- We can take snapshots, i.e. have "checkpoints" or "save points"
+  when building images.
+
+---
+
+## AUFS overview
+
+- The original (legacy) copy-on-write filesystem used by first versions of Docker.
+
+- Combine multiple *branches* in a specific order.
+
+- Each branch is just a normal directory.
+
+- You generally have:
+
+  - at least one read-only branch (at the bottom),
+
+  - exactly one read-write branch (at the top).
+
+  (But other fun combinations are possible too!)
+
+---
+
+## AUFS operations: opening a file
+
+- With `O_RDONLY` - read-only access:
+
+  - look it up in each branch, starting from the top
+
+  - open the first one we find
+
+- With `O_WRONLY` or `O_RDWR` - write access:
+
+  - if the file exists on the top branch: open it
+
+  - if the file exists on another branch: "copy up"
+    <br/>
+    (i.e. copy the file to the top branch and open the copy)
+
+  - if the file doesn't exist on any branch: create it on the top branch
+
+That "copy-up" operation can take a while if the file is big!
+
+---
+
+## AUFS operations: deleting a file
+
+- A *whiteout* file is created.
+
+- This is similar to the concept of "tombstones" used in some data systems.
+
+```
+ # docker run ubuntu rm /etc/shadow
+
+ # ls -la /var/lib/docker/aufs/diff/$(docker ps --no-trunc -lq)/etc
+ total 8
+ drwxr-xr-x 2 root root 4096 Jan 27 15:36 .
+ drwxr-xr-x 5 root root 4096 Jan 27 15:36 ..
+ -r--r--r-- 2 root root    0 Jan 27 15:36 .wh.shadow
+```
+
+---
+
+## AUFS performance
+
+- AUFS `mount()` is fast, so creation of containers is quick.
+
+- Read/write access has native speeds.
+
+- But initial `open()` is expensive in two scenarios:
+
+  - when writing big files (log files, databases ...),
+
+  - when searching many directories (PATH, classpath, etc.) over many layers.
+
+- Protip: when we built dotCloud, we ended up putting
+  all important data on *volumes*.
+
+- When starting the same container multiple times:
+
+  - the data is loaded only once from disk, and cached only once in memory;
+
+  - but `dentries` will be duplicated.
+
+---
+
+## Device Mapper
+
+Device Mapper is a rich subsystem with many features.
+
+It can be used for: RAID, encrypted devices, snapshots, and more.
+
+In the context of containers (and Docker in particular), "Device Mapper"
+means:
+
+"the Device Mapper system + its *thin provisioning target*"
+
+If you see the abbreviation "thinp" it stands for "thin provisioning".
+
+---
+
+## Device Mapper principles
+
+- Copy-on-write happens on the *block* level
+  (instead of the *file* level).
+
+- Each container and each image get their own block device.
+
+- At any given time, it is possible to take a snapshot:
+
+  - of an existing container (to create a frozen image),
+
+  - of an existing image (to create a container from it).
+
+- If a block has never been written to:
+
+  - it's assumed to be all zeros,
+
+  - it's not allocated on disk.
+
+(That last property is the reason for the name "thin" provisioning.)
+
+---
+
+## Device Mapper operational details
+
+- Two storage areas are needed:
+  one for *data*, another for *metadata*.
+
+- "data" is also called the "pool"; it's just a big pool of blocks.
+
+  (Docker uses the smallest possible block size, 64 KB.)
+
+- "metadata" contains the mappings between virtual offsets (in the
+  snapshots) and physical offsets (in the pool).
+
+- Each time a new block (or a copy-on-write block) is written,
+  a block is allocated from the pool.
+
+- When there are no more blocks in the pool, attempts to write
+  will stall until the pool is increased (or the write operation
+  aborted).
+
+- In other words: when running out of space, containers are
+  frozen, but operations will resume as soon as space is available.
+
+---
+
+## Device Mapper performance
+
+- By default, Docker puts data and metadata on a loop device
+  backed by a sparse file.
+
+- This is great from a usability point of view,
+  since zero configuration is needed.
+
+- But it is terrible from a performance point of view:
+
+  - each time a container writes to a new block,
+  - a block has to be allocated from the pool,
+  - and when it's written to,
+  - a block has to be allocated from the sparse file,
+  - and sparse file performance isn't great anyway.
+
+- If you use Device Mapper, make sure to put data (and metadata)
+  on devices!
+
+---
+
+## BTRFS principles
+
+- BTRFS is a filesystem (like EXT4, XFS, NTFS...) with built-in snapshots.
+
+- The "copy-on-write" happens at the filesystem level.
+
+- BTRFS integrates the snapshot and block pool management features
+  at the filesystem level.
+
+  (Instead of the block level for Device Mapper.)
+
+- In practice, we create a "subvolume" and 
+  later take a "snapshot" of that subvolume.
+
+  Imagine: `mkdir` with Super Powers and `cp -a` with Super Powers.
+
+- These operations can be executed with the `btrfs` CLI tool.
+
+---
+
+## BTRFS in practice with Docker
+
+- Docker can use BTRFS and its snapshotting features to store container images.
+
+- The only requirement is that `/var/lib/docker` is on a BTRFS filesystem.
+
+  (Or, the directory specified with the `--data-root` flag when starting the engine.)
+
+---
+
+class: extra-details
+
+## BTRFS quirks
+
+- BTRFS works by dividing its storage in *chunks*.
+
+- A chunk can contain data or metadata.
+
+- You can run out of chunks (and get `No space left on device`)
+  even though `df` shows space available.
+  
+  (Because chunks are only partially allocated.)
+
+- Quick fix:
+
+```
+ # btrfs filesys balance start -dusage=1 /var/lib/docker
+```
+
+---
+
+## Overlay2
+
+- Overlay2 is very similar to AUFS.
+
+- However, it has been merged in "upstream" kernel.
+
+- It is therefore available on all modern kernels.
+
+  (AUFS was available on Debian and Ubuntu, but required custom kernels on other distros.)
+
+- It is simpler than AUFS (it can only have two branches, called "layers").
+
+- The container engine abstracts this detail, so this is not a concern.
+
+- Overlay2 storage drivers generally use hard links between layers.
+
+- This improves `stat()` and `open()` performance, at the expense of inode usage.
+
+---
+
+## ZFS
+
+- ZFS is similar to BTRFS (at least from a container user's perspective).
+
+- Pros:
+
+  - high performance
+  - high reliability (with e.g. data checksums)
+  - optional data compression and deduplication
+
+- Cons:
+
+  - high memory usage
+  - not in upstream kernel
+
+- It is available as a kernel module or through FUSE.
+
+---
+
+## Which one is the best?
+
+- According to Michael Crosby (core Docker maintainer), overlay2!
+
+- Overlay2 is available on all modern systems.
+
+- Its memory usage is better than Device Mapper, BTRFS, or ZFS.
+
+- The remarks about *write performance* shouldn't bother you:
+  <br/>
+  data should always be stored in volumes anyway!
+