Cloud computing provides computing resources and storage that can be accessed by any system connected to the Internet. Generally, this takes the form of virtual machines (VMs) and storage both in the VMs (direct attached) and over the network (usually block devices formatted and exported with NFS). Typically, users configure the VMs with their operating system and applications of choice, perhaps configure some storage, and start running. After that, the data is copied back to permanent storage (perhaps local). However, this is not the only way to utilize cloud resources. In this article, I'll focus on the storage aspect of the cloud, which can be used for backups and duplicates of data on a large or small scale.
Amazon S3 Storage
Although several cloud storage options are available, I'll focus on Amazon S3  because, arguably, Amazon is the thousand-pound gorilla in cloud storage. The exact details of S3 are not public, but you can think of it as an object-based storage system. To begin using S3, you create one or more buckets. Each bucket contains objects, and you have no limits on the number of objects per bucket. Each object is a file and any associated metadata (e.g., ACLs).
Currently, each object can be up to 5 terabytes (TB) in size accompanied by up to 2KB of metadata. However, S3 can only work with 5GB files in a single write operation, so S3 breaks files larger than 5GB into multiple pieces. You typically interact with the objects (files) with a few simple commands: write (
PUT), read (
GET), or delete (
DELETE). The usual method of interacting with S3 is via a web console . Amazon also offers a command-line interface (CLI)  that can be used to interact with S3. The basic command begins with
aws s3; then, you can use the common Linux commands of
rm to manipulate objects (files) in a specified bucket. For example,
$ aws s3 ls s3://mybucket
lists the objects in your bucket. You can also used a
sync command to synchronize the objects in a bucket with a local directory. You can find S3 command documentation online .
Several open source projects, such as
s3cmd , are very similar to Amazon's CLI tools. With
s3cmd, you can copy and move files and sync directories with your S3 bucket, and you can use
s3sync  to sync to S3 (somewhat like
rsync). If you are running Windows, these Amazon S3 clients are available for backing up data to Amazon S3:
- Amazon S3 Transfer Engine  is a free tool.
- TntDrive  offers a free trial.
- S3 Browser  is a free tool.
- CloudBerry Explorer for Amazon S3  has a free version and a Pro version.
- Bucket Explorer  offers a free trial period, but it is a commercial product.
You can also find smartphone apps for interacting with S3, and you can even interact with S3 in your Firefox browser using S3Fox Organizer . The Linux world also has tools for treating Amazon S3 as an rsync target. The best-known tool is probably
boto_rsync , a Python tool that uses rsync to sync from a local directory to an S3 bucket, as well as s3sync and Duplicity .
A number of Amazon SDK libraries  can be used to build S3 applications, and S3 has an API  that describes how to interact with the bucket(s) and objects in the bucket (see the box "Operations."). The S3 API Quick Reference Card  illustrates the functions used to interact with an object storage system.
Basically, you can write the object (
PUT), read the object (
GET), delete the object (
DELETE), and retrieve information about the object (
HEAD), which is infinitely more simple than POSIX, which has a long, long laundry list of functions for interacting with files. Several projects have taken the object storage paradigm and mapped it to a conventional filesystem by using FUSE, so the filesystems are in userspace:
- s3fs (FuseOverAmazon)
- s3fs (Fedora hosted)
Notice I listed a number of "s3fs" projects, but they are different from each other. Overall, it is really interesting how developers have taken a very simple storage solution with basically three commands and mapped it to a classic filesystem. This approach has wonderful potential, because you can now treat object storage as a regular filesystem, allowing you to use the regular tools you use for backup and replication.
Object storage has been around for a while, but I argue that Amazon S3 popularized it. Subsequent object storage solutions use the same concepts of
DELETE and have different implementations of them, as well as other features. Although the Amazon cloud is large  – five times larger than the next 14 cloud providers – cloud storage is growing rapidly with many providers.
Wouldn't it be nice to be able to use a different or several cloud storage providers from the same backup or replication tool? One complicating factor is that you have to assume the data is accessible. Therefore, you need to start thinking about encrypting your data while encrypting the data transmission to your storage back end. Encryption should be a non-optional part of your data plans.
One of the most interesting S3 backup/filesystem tools is
s3ql . It creates a POSIX-like filesystem in user space (FUSE) using object storage or other storage as the target. Its major features are:
- Encryption: Thanks to Mr. Snowden, we now know that the US government has access to far more of our data and communications than we realized. Therefore, if I'm going to back up my data to cloud storage, I want to make sure the data is encrypted. S3QL encrypts all data using a 256-bit AES key. An additional SHA-256 HMAC checksum protects the data from manipulation.
- Compression: S3QL compresses the data before storing, using either LZMA, bzip2, or gzip. This compression takes place before the data is encrypted.
- De-duplication: The data to be stored can be de-duplicated if the files have identical content. It works across all files stored in the filesystem, but it can also work if only some parts of the files are identical (i.e,. not the entire file).
- Copy-on-Write/Snapshotting: S3QL can duplicate directory trees without the use of any additional storage space (target storage). If one of the copies is modified, then only the part of the data that has been modified will take up additional storage space. You can use this capability to create intelligent snapshots that preserve the state of a directory at different points in time using a minimum amount of space.
- Dynamic Size: The size of an S3QL filesystem can grow or shrink dynamically as required.
- Transparency: An S3QL filesystem behaves like a local filesystem, in that it supports hard links, symlinks, typical permissions, extended attributes (
xattr) and file sizes up to 2TB.
- Immutable Trees: With S3QL, directory trees can be made immutable so that their contents can't be changed in any way whatsoever.
- Range of Back Ends: S3QL has a range of back ends (what I call targets, but which S3QL calls storage back ends), such as Google storage, Amazon S3, Amazon Reduced Redundancy Storage (RRS), OpenStack Swift, Rackspace Cloud Files, S3-compatible targets, local filesystems, and even filesystems accessed using
sshfs, which are treated as a local filesystems.
- Caching: You can configure a cache for S3QL to improve apparent performance, perhaps taking advantage of a local SSD for data caching.
S3QL has other aspects that I really like, and I'll mention them throughout the remainder of the article.
Building and Installing S3QL
S3QL is primarily written in Python and comes in two versions: Python 2.7 (an older version of
s3ql) and Python 3.3 (the more modern version). I chose to use the Python 2.7 version because
s3ql has several dependencies and building it from scratch might not be the easiest thing to do. You do need to pay careful attention to the installation instructions . In my case, I followed the instructions provided for CentOS on my CentOS 6.4 system. The instructions are very good and very accurate – be sure you read them all before installing S3QL. Briefly, I will mention some highlights of the installation process that I hope will help you.
To begin, turn off SELinux and reboot. You can find instructions for how to do this all over the web, but be sure the instructions are compatible with the security of your systems. After installing the dependencies, I followed the instructions for installing Python 2.7 from the PUIAS repo . In case you are wondering, PUIAS is a project of the members of Princeton University and the Institute for Advanced Studies (IAS). Although these credentials don't make the site automatically safe, I did a little checking, and I think their repo is very safe.
Conveniently, Python 2.7 was installed alongside my existing Python. PUIAS even produces a distro called Springdale that might be worth checking out. (It looks to be based on CentOS 6.4.) Next, I installed SQLite from the Atomicorp repo . I always like to check out repos that people suggest before I use them, and in this case I was satisfied enough to continue. The instructions had me install SQLite version 3.7.9: It is very important to remember this version number. The next step was to install Python APSW , where APSW stands for "Another Python SQLite Wrapper." You have to download the version of APSW that matches the version of SQLite you installed (see the previous step). This is critical; I tried several different versions of APSW that didn't match the version of SQLite I installed, and the S3QL build always failed.
After installing a few more Python packages, I built and installed S3QL itself. It was very easy to build, but when I ran the "test" as part of the installation (
python2.7 setup.py test), I got an assertion error. I have no idea if this is expected behavior or not, but after testing S3QL for a few days, I didn't run into any unexpected behavior. When you install S3QL, be sure to pay attention to where the various pieces are installed. They should be part of the standard path, but it's always good to document where things are located.
You should definitely read through the User's Guide , which explains the steps for using S3QL and has some good ideas and tips for its use. Be sure to read the section titled "Important Rules to Avoid Losing Data" before using S3QL. As an exercise, I decide to use S3QL against a local filesystem on a spare drive I had in my system (a simple ext4 filesystem on a drive mounted as
The first step is to build the S3QL filesystem on the mounted filesystem (Listing 1). First, notice that I created the file as root. Second, the prefix for the local filesystem is
local://. You need to include both forward slashes in this prefix. The path after the prefix is
/mnt/data1, where you need to include the first forward slash (absolute path). Thus, you get the local filesystem as
local:///mnt/data1. Also notice that during filesystem creation, you will be prompted to enter the passphrase for encryption. Do not lose this passphrase, or you won't be able to decrypt your data. At the same time, don't do anything silly like writing it down. I'm not a security expert, but you should use a fairly long passphrase and make it easy to remember; on the other hand, don't use easy-to-find phrases or dictionary words.
Listing 1: Build S3QL Filesystem
01 [root@home4 ~]# mkfs.s3ql local:///mnt/data1 02 Before using S3QL, make sure to read the user's guide, especially 03 the 'Important Rules to Avoid Loosing Data' section. 04 Enter encryption password: 05 Confirm encryption password: 06 Generating random encryption key... 07 Creating metadata tables... 08 Dumping metadata... 09 ..objects.. 10 ..blocks.. 11 ..inodes.. 12 ..inode_blocks.. 13 ..symlink_targets.. 14 ..names.. 15 ..contents.. 16 ..ext_attributes.. 17 Compressing and uploading metadata... 18 Wrote 0.00 MiB of compressed metadata.
After creating an S3QL filesystem, I checked the mountpoint,
/mnt/data1 (Listing 2). A few files are created as a result of the S3QL filesystem creation process. You can see these directories in the listing.
Listing 2: Check Mountpoint
01 [root@home4 ~]# ls -lstar /mnt/data1 02 total 36 03 16 drwx------ 2 root root 16384 Nov 10 10:00 lost+found 04 4 drwxr-xr-x. 3 root root 4096 Nov 10 10:00 .. 05 4 -rw-r--r-- 1 root root 294 Nov 10 10:07 s3ql_passphrase 06 4 -rw-r--r-- 1 root root 243 Nov 10 10:07 s3ql_seq_no_1 07 4 -rw-r--r-- 1 root root 556 Nov 10 10:07 s3ql_metadata 08 4 drwxr-xr-x 3 root root 4096 Nov 10 10:07 .
Now, I'm ready to mount the filesystem using the
mount.s3ql command at
/mnt/s3ql (Listing 3). While mounting the filesystem, I was asked for my passphrase. Notice that I checked the mountpoint to see what was there. Because the file
lost+found was present, I was confident that the filesystem had been mounted properly. Just to be sure, I checked using the
mount command (Listing 4). Notice the last line in the output. The S3QL filesystem is mounted. I also checked the local mountpoint,
/mnt/data1, to see if anything had changed (Listing 5).
Listing 3: Mount S3QL Filesystem
01 [root@home4 ~]# mount.s3ql local:///mnt/data1 /mnt/s3ql 02 Using 10 upload threads. 03 Enter file system encryption passphrase: 04 Using cached metadata. 05 Mounting filesystem... 06 [root@home4 data1]# ls -lstar /mnt/s3ql 07 total 0 08 0 drwx------ 1 root root 0 Nov 10 10:07 lost+found
Listing 4: Check Mounted Filesystem
01 [root@home4 ~]$ mount 02 /dev/sda1 on / type ext4 (rw) 03 proc on /proc type proc (rw) 04 sysfs on /sys type sysfs (rw) 05 devpts on /dev/pts type devpts (rw,gid=5,mode=620) 06 tmpfs on /dev/shm type tmpfs (rw) 07 /dev/md0 on /home type ext4 (rw) 08 none on /proc/sys/fs/binfmt_misc type binfmt_misc (rw) 09 sunrpc on /var/lib/nfs/rpc_pipefs type rpc_pipefs (rw) 10 /dev/sdb1 on /mnt/data1 type ext4 (rw) 11 local:///mnt/data1 on /mnt/s3ql type fuse.s3ql (rw,nosuid,nodev)
Listing 5: Recheck Mountpoint
01 [root@home4 ~]# ls -lstar /mnt/data1 02 total 40 03 16 drwx------ 2 root root 16384 Nov 10 10:00 lost+found 04 4 -rw-r--r-- 1 root root 294 Nov 10 10:07 s3ql_passphrase 05 4 -rw-r--r-- 1 root root 243 Nov 10 10:07 s3ql_seq_no_1 06 4 -rw-r--r-- 1 root root 556 Nov 10 10:07 s3ql_metadata 07 4 drwxr-xr-x. 4 root root 4096 Nov 10 10:08 .. 08 4 -rw-r--r-- 1 root root 262 Nov 10 10:10 s3ql_seq_no_2 09 4 drwxr-xr-x 3 root root 4096 Nov 10 10:10 .
After I mounted the filesystem, there is a new directory with a new sequence. To better understand how I might use S3QL, I decided to simulate making a copy of a user's subdirectory (replication). Because S3QL is mounted like a local filesystem, I could use the
cp command to copy the data. The user is
laytonjb; I decided to copy my
Documents subdirectory to the S3QL filesystem (Listing 6).
Listing 6: Replication
01 [root@home4 ~]# mkdir /mnt/s3ql/laytonjb 02 [root@home4 ~]# cp -r /home/laytonjb/Documents/ /mnt/s3ql/laytonjb/ 03 [root@home4 ~]# df -h 04 Filesystem Size Used Avail Use% Mounted on 05 /dev/sda1 109G 17G 87G 16% / 06 tmpfs 16G 596K 16G 1% /dev/shm 07 /dev/md0 2.7T 192G 2.4T 8% /home 08 /dev/sdb1 111G 1.4G 104G 2% /mnt/data1 09 local:///mnt/data1 1.0T 1.7G 1023G 1% /mnt/s3ql
The first command creates a subdirectory for the user (remember, it's a local filesystem, so I can use the
mkdir command). Then, I did a recursive copy to the mounted filesystem. (I probably should have used the
-p option to preserve the time stamp and ownership information, but this was just a test.)
The copy took a little bit of time (remember it is compressed, de-duped, and encrypted – the holy trinity of data management). The original directory contained about 2.2GB of data, and after the copy, it looked like it was using roughly 1.7GB in S3QL. When I checked the directory listing, I saw all of my original files (a portion of this output is shown in Listing 7). Because I didn't use the
-p option, the owner and group are changed to root, and the time is changed to when the data was copied.
Listing 7: Check Replication
01 [root@home4 ~]# ls -lstar /mnt/s3ql/laytonjb/Documents/ 02 total 897781 03 5265 -rw-r--r-- 1 root root 5390660 Nov 10 10:25 PGAS Languages NCSA 2009.pdf 04 65 -rw-r--r-- 1 root root 65893 Nov 10 10:25 cavp-03.pdf 05 0 drwxr-xr-x 1 root root 0 Nov 10 10:28 FEATURES 06 4173 -rw-r--r-- 1 root root 4272584 Nov 10 10:28 KonigesA-2.pdf 07 0 drwxr-xr-x 1 root root 0 Nov 10 10:28 STORAGE088_2 08 7984 -rw-r--r-- 1 root root 8175616 Nov 10 10:28 CFD_SC07.ppt 09 0 drwxr-xr-x 1 root root 0 Nov 10 10:28 COLLECTL 10 1262 -rw-r--r-- 1 root root 1291267 Nov 10 10:28 00354107.pdf 11 248 -rw-r--r-- 1 root root 253651 Nov 10 10:28 intro.pdf 12 88 -rw------- 1 root root 89206 Nov 10 10:28 PV2009_601.pdf 13 1653 -rw------- 1 root root 1692410 Nov 10 10:28 aiaa.2006.0107.pdf 14 3466 -rw------- 1 root root 3548623 Nov 10 10:28 Kirby-14.pdf 15 485 -rw-r--r-- 1 root root 495791 Nov 10 10:28 aiaa-2007-4581.pdf 16 ...
It is interesting to look at the local filesystem mountpoint,
/mnt/data1 (Listing 8). A few new directories are created as a result of the data copy, and I'll mention a few quick things about this in a moment.
Listing 8: Local Mountpoint
01 [root@home4 ~]# ls -sltar /mnt/data1 02 total 104 03 16 drwx------ 2 root root 16384 Nov 10 10:00 lost+found 04 4 -rw-r--r-- 1 root root 294 Nov 10 10:07 s3ql_passphrase 05 4 -rw-r--r-- 1 root root 243 Nov 10 10:07 s3ql_seq_no_1 06 4 drwxr-xr-x. 4 root root 4096 Nov 10 10:08 .. 07 4 -rw-r--r-- 1 root root 262 Nov 10 10:10 s3ql_seq_no_2 08 4 -rw-r--r-- 1 root root 556 Nov 10 10:15 s3ql_metadata_bak_0 09 4 -rw-r--r-- 1 root root 602 Nov 10 10:15 s3ql_metadata 10 4 -rw-r--r-- 1 root root 262 Nov 10 10:23 s3ql_seq_no_3 11 4 drwxr-xr-x 4 root root 4096 Nov 10 10:25 . 12 56 drwxr-xr-x 831 root root 57344 Nov 10 10:31 s3ql_data_
S3QL includes a number of very useful tools. One of them,
s3qlstat, can provide some really cool information about what is stored in S3QL (Listing 9). The output contains all kinds of useful information; for example, there are 20,135 directory entries (I assume files) that use 20,137 inodes and 9,283 data blocks.
Listing 9: s3qlstat
01 [root@home4 laytonjb]# s3qlstat /mnt/s3ql 02 Directory entries: 20135 03 Inodes: 20137 04 Data blocks: 9283 05 Total data size: 2171.80 MiB 06 After de-duplication: 1696.35 MiB (78.11% of total) 07 After compression: 1216.23 MiB (56.00% of total, 71.70% of de-duplicated) 08 Database size: 3.81 MiB (uncompressed) 09 (some values do not take into account not-yet-uploaded dirty blocks in cache)
One piece of information I'm interested in is that the original data, when re-duped, decompressed, and decrypted, is 2,171.80MiB. After de-duplication, that went to 1,696.35MiB (a space savings of about 22%) and, when compressed, is about 1,216.23MiB (56% of the original total or 71.7% of the de-duped total). It also shows the database size. I personally love this command for learning about the status of my replicated data.
Unmounting the S3QL filesystem is easy, but you need to use the
s3ql command (Listing 10) and not the OS command,
umount. Please note that the
umount command has to flush the cache, so it won't necessarily return quickly (it depends on how much data is in the cache).
Listing 10: Unmounting S3QL
01 [root@home4 Documents]# umount.s3ql /mnt/s3ql/ 02 [root@home4 Documents]# ls -lstar /mnt/data1 03 total 696 04 16 drwx------ 2 root root 16384 Nov 10 10:00 lost+found 05 4 -rw-r--r-- 1 root root 294 Nov 10 10:07 s3ql_passphrase 06 4 -rw-r--r-- 1 root root 243 Nov 10 10:07 s3ql_seq_no_1 07 4 drwxr-xr-x. 4 root root 4096 Nov 10 10:08 .. 08 4 -rw-r--r-- 1 root root 262 Nov 10 10:10 s3ql_seq_no_2 09 4 -rw-r--r-- 1 root root 556 Nov 10 10:15 s3ql_metadata_bak_1 10 4 -rw-r--r-- 1 root root 262 Nov 10 10:23 s3ql_seq_no_3 11 56 drwxr-xr-x 831 root root 57344 Nov 10 10:31 s3ql_data_ 12 592 -rw-r--r-- 1 root root 603068 Nov 10 15:10 s3ql_metadata 13 4 -rw-r--r-- 1 root root 602 Nov 10 15:10 s3ql_metadata_bak_0 14 4 drwxr-xr-x 4 root root 4096 Nov 10 15:10 . 15 [root@home4 Documents]# df -h 16 Filesystem Size Used Avail Use% Mounted on 17 /dev/sda1 109G 17G 87G 16% / 18 tmpfs 16G 596K 16G 1% /dev/shm 19 /dev/md0 2.7T 192G 2.4T 8% /home 20 /dev/sdb1 111G 1.5G 104G 2% /mnt/data1
After I unmounted the S3QL filesystem, I examined the local filesystem mountpoint. I couldn't see anything useful in the files, but I decided to look at the directory
/mnt/data1/s3ql_data_ to see what was there, because it looked interesting (Listing 11; the output was very long, so I truncated it). A bunch of directories and files were binary; using
cat didn't tell me anything (it was gibberish), so it looks like the encryption and compression worked.
Listing 11: /mnt/data1/s3ql_data
01 [root@home4 Documents]# ls -s /mnt/data1/s3ql_data_/ 02 total 167780 03 4 100 4 466 4 832 12 s3ql_data_341 4 s3ql_data_671 04 4 101 4 467 4 833 36 s3ql_data_342 8 s3ql_data_672 05 4 102 4 468 4 834 44 s3ql_data_343 12 s3ql_data_673 06 4 103 4 469 4 835 16 s3ql_data_344 276 s3ql_data_674 07 4 104 4 470 4 836 56 s3ql_data_345 472 s3ql_data_675 08 4 105 4 471 4 837 4 s3ql_data_346 2216 s3ql_data_676 09 ...
You can explore some very interesting things about S3QL, such as its caching capability (by default, a directory named
~/.s3ql in the user's root directory). This can be exploited or even relocated somewhere else.
You can also explore other storage back ends. For example, setting up an Amazon S3 account isn't too difficult, and if you only back up a little bit of data, it's easy to afford when you are just learning. Be sure to read the section in the documentation on account authentication  and how you use your S3 login and password (or any storage back end requiring authentication).
Another option is a storage back end that doesn't even have to be exported via a protocol such as NFS. If you can access a system associated with the storage via
ssh, you can use
sshfs to access the S3QL file storage. (Read the section  on how to use
sshfs to mount storage on your client.)
Once you've accessed the system, you can create an S3QL filesystem and use it like any other back-end storage. A point that may be lost on people is that S3QL is a filesystem like any other, local or network based.
You can use it as a backup target for something like rsync, or with rsnapshot  or RIBS , which both use rsync. S3QL just becomes the "rsync target," then you can use one of the S3QL back ends as you want for backups or data replication (disaster recovery). You can also use your favorite file-based backup or replication tool.
Increasing amounts of data are pushing the need for backups or data replication. With petabyte storage systems becoming very common, particularly for high-performance computing systems, it can be difficult to have enough on-site hardware for backup or replication operations. Why not use cloud storage for this? However, using cloud storage typically means using object-based storage, so how do you use the
HEAD commands to make copies or backups?
S3QL, one of the tools for object-based storage for backups or rsync (replication), has huge potential. It has one of the most important features in today's climate: encryption.
Additionally, it has compression and de-dupe capabilities, as well as dynamic sizing. A really interesting aspect of S3QL is that it offers several back-end storage options: Amazon S3, Rackspace Cloud Files, OpenStack Swift, and Google Storage, as well as S3-compatible targets and local filesystems.
Don't forget that S3QL behaves just like a filesystem, so you can use the classic tools against it, including backup or replication tools such as rsync. Give S3QL a whirl – it has some really cool features.