Category Archives: Sysadmin

Transitioining from bash to zsh

oh-my-zsh

I have know about zsh for a long time now but have never really had a compelling reason to switch my default shell from bash until just recently, I have been hearing more and more people talking about how powerful and awesome zsh is.  So I thought I might as well take the dive and get started since that’s what all the cool kids seem to be doing these days.  At first I thought that changing my shell was going to be a PITA with all the customizations and idiosyncrasies that I have grown accustomed to using bash but I didn’t find that to be the case at all when switching to zsh.

First and foremost, I used a tool called oh-my-zsh to help with the transition.  If you haven’t heard about it yet, oh-my-zsh aims to be a sort of framework for zsh.  This project is a nice clean way to get started with zsh because it give you a nice set of defaults out of the the box without having to do much configuration or tweaking and I found that many of my little tricks and shortcuts were already baked in to to oh-my-zsh, along with a ton of other settings and customizations that I did not have using bash.

From their github page:

oh-my-zsh is an open source, community-driven framework for managing your ZSH configuration. It comes bundled with a ton of helpful functions, helpers, plugins, themes, and few things that make you shout…

Here are just a few of the improvement that zsh/oh-my-zsh offer:

  • Improved tab completion
  • persistent history across all shells
  • Easy to use plugin system
  • Easy to use theme system
  • Autocorrect

The most obvious difference that I have noticed is the improved, out of the box tab completion, which I think should be enough on its own to convince you!  On top of that, most of my tricks and customizations were already turned on with oh-my-zsh.  Another nice touch is that themes and plugins come along as part of the package, which is really nice for easing the transition.

So after spending an afternoon with zsh I am convinced that it is the way to go (at least for my own workfolw).  Of course there are always caveats and hiccups along the way as I’ve learned there are with pretty much everything.

Tuning up tmux

Out of the box, my tmux config uses the default shell, which happens to be bash.  So I needed to modify my ~/.tmux.conf to reflect the switch over the zsh.  It is a pretty straight forward change but is something that you will need to make note of kif you use tmux and are transitioning in to using zsh.

set-option -g default-shell /usr/bin/zsh

I am using Ubuntu 14.04, so my zsh is installed to /usr/bin/zsh.  The other thing that you will need to do is make sure you kill any stale tmux processes after updating to zsh.  I found one running in the background that was blocking me from using the new coonfig.

Goodies

There is a nice command cheat sheet for zsh.  Take some time to learn these shortcuts and aliases, they are great time savers and are very usefull.

oh-my-zsh comes bundled up with a large number of goodies.  At the time of this writing there were 135 plugins as well as a variety of themes.  You can check the plugins wiki page for descriptions for the various plugins.  To turn on a specific plugin you will need to add it to your ~/.zshrc config file.  Find the following line in your config.

plugins=(git)

and add plugins separated by spaces

plugins (git vagrant chef)

You will need to reload the config for the changes to be picked up.

source ~/.zshrc

Most themes are hosted on the wiki, but there is also a web site dedicated to displaying the various themes, which is really cool.  It does a much better job of showing differences between various themes.  You can check it out here.  Themes function in a similar way to plugins.  If you want to change your theme, edit your ~/.zshrc file and select the desired them.

ZSH_THEME="clean"

You will need to reload your config for this option as well.

source ~/.zshrc

Conclusion

If you haven’t already made the switch to zsh I recommend that you at least experiment and play around with it before you make any final decisions.  You may be set in your ways and happy with bash or any other shell that you are used to but for me, all the awesomeness changed my opinion and decide to reevaluate my biases.  If you’re worried about making the switchin, using oh-my-zsh makes the transition so painless there is practically no reason not to try it out.

This post is really just the tip of the iceberg for the capabilities of this shell, I just wanted to expose readers to all of its glory.  Zsh offers so much more power and customization than I have covered in this post and is an amazing productivity tool with little learning overhead.

Let me know if you have any awesome zsh tips or tweaks that folks should know about.

7 useful but hard to remember Linux commands

I have found myself using these commands over and over so I decided I’d take the time to go ahead and document them for future me as well as readers because I find these commands pretty useful.  I just always manage to forget them, hence the title of the post.  The smart thing to do would be to create aliases for these commands but I have just been too lazy and some of them are run across different servers so it isn’t always a convenient option.

Anyway, let’s go ahead and run through the commands before I forget…

1) du -ah / | sort -n -r | head -n 50

This one is really handy for debugging space issues.  It will list the top 50 files according to file size, with the largest at the top of the list.Notice the “/” will specify the location to search so you can easily modify this one to search different locations, like “/var/log” for example if you are having trouble with growing log files.

2) git checkout — .

I don’t use this one very often, which is probably why I manage to forget it so easily.  But I really like it.  Sometimes I will be working on a git repo across different machines at the same time and will run in to conflicts committing to the repo or more likely I committed changes on one machine and just need to pull down the newest changes but can’t since I have made modifications.  For those scenarios you can run the above command quickly reset your git changes quickly and easily.

3) tmux kill-window -t 3

i use tmux for my terminal and window manager on all my workstations and love it.  If you haven’t heard of it, take a look here.  Sometimes the sessions can get stuck so it becomes necessary to close the window without destroying the tmux session.  Again, this doesn’t happen very often so it is sometimes hard for me to remember the exact syntax but this one is a handy little trick for managing tmux windows and sessions.

4) grep -r “text”

I know, I should really have this one memorized by now.  I am trying to remember but I don’t find myself using this one all that often even though it is really powerful and useful.  This will essentially search through every file recursively and spit out the text pattern that you feed to it.

5) kill $(pgrep process)

This one is handy when there are a large number of stuck processes and you need to blow them all out with one command.  For example if the chrome browser ever gets stuck with a million tabs open, there are likely a large number of processes all with the same – or similar names.  If you pass all or part of the process name in to this command pgrep will find them and kill will destroy them

6) docker rm $(docker ps -a -q)

I have been using Docker more and more recently and every once in awhile I find myself with a large number of dead Docker processes that need to be cleaned up.  This command will blow out all of these stale processes at once.  This is nice because Docker processes take up a large amount of disk space and often times can fill up your drives without you being aware.  I have been able to reclaim large amounts of disk space with this command.

7) watch -n 10 df -ah

This is another good one for checking disk space issues.  It will update you every ten seconds with the disk utilization of the system.  Pretty straight forward but a great tool to help troubleshooting space issues.

That’s all I have for now, there are lots more but these are the most useful ones that I find myself forgetting the most often, hopefully this post will serve as a nice reminder.  If you have any cool or useful commands that you would like to share feel free to comment and I will update the post to include them.

Recover a Grafana dashboard

Grafana uses Elasticsearch (optionally) to store its dashboards.  If you ever migrate your Graphite/Grafana servers or simply need to grab all of your dashboards from the old server then you will likely be looking for them in Elasticsearch.  Luckily, migrating to a new server and moving the dashboards is and uncomplicated and easy to do process.  In this post I will walk through the process of moving Grafana dashboards between servers.

This guide assumes that Elasticsearch has been installed on both old and new servers.  The first thing to look at is your current Grafana config.  This is the file that you probably used to set up your Grafana environment originally.  This file resides in the directory that you placed your Grafana server files in to, and is named config.js.  There is a block inside this config file that tells Elasticsearch where to save dashboards, which by default is called “grafana-dashboards” which should look something like this:

/**
 * Elasticsearch index for storing dashboards
 *
 */
 grafana_index: "grafana-dash-orig",

Now, if you still have access to the old server it is merely a matter of copying this Elasticsearch directory that houses your Grafana dashboard over to the new location. By default on an Ubuntu installation the Elasticsearch data files get placed in to the following path:

/var/lib/elasticsearch/elasticsearch/nodes/0/indices/grafana-dashboards

Replace “0″ with the node if this is a clustered Elasticsearch instance, otherwise you should see the grafana-dashboard directory.  Simply copy this directory over to the new server with rsync or scp and put it in a temporary location for the time being (like /tmp for example).  Rename the existing grafana-dashboards directory to something different, in case there are some newly created dashboards that you would like to retrieve.  Then move the original dashboards (from the old server) from the /tmp directory in to the above path, renaming it to grafana-dashboard.  The final step is to chown the directory and its contents.  The steps for accomplishing this task are similar to the following.

On the old host:

cd /var/lib/elasticsearch/elasticsearch/nodes/0/indices/
rsync -avP -e ssh grafana-dashbaords/ user@remote_host:/tmp/

On the new host:

cd /var/lib/elasticsearch/elasticsearch/nodes/0/indices/
mv grafana-dashboards grafana-dash-orig
mv /tmp/grafana-dashboards ./grafana-dashboards
chown -R elasticsearch:elasticsearch grafana-dashboards

You don’t even need to restart the webserver or Elasticsearch for the old dashboards to show up.  Just reload the page and bam.   Dashboards.

grafana dashboard

Cloud Backup Tutorial

I have been knee deep in backups for the past few weeks, but I think I can finally see light at the end of the tunnel.  What looked like a simple enough idea to implement turned out to be a much more complicated task to accomplish.  I don’t know why, but there seems to be practically no information at all out there covering this topic.  Maybe it’s just because backups suck?  Either way they are extremely important to the vitality of a company and without a workable set of data, you are screwed if something happens to your data.  So today I am going to write about managing cloud data and cloud backups and hopefully shine some light on this seemingly foreign topic.

Part of being a cloud based company means dealing with cloud based storage.  Some of the terms involved are slightly different than the standard backup and storage terminology.  Things like buckets, object based storage, S3, GCS, boto all come to mind when dealing with cloud based storage and backups.  It turns out that there are a handful of tools out there for dealing with our storage requirements which I will be discussing today.

The Google and Amazon API’s are nice because they allow for creating third party tools to manage the storage, outside of their official and standard tools.  In my journey to find a solution I ran across several, workable tools that I would like to mention.  The end goal of this project was to sync a massive amount of files and data from S3 storage to GCS.  I found that the following tools all provided at least some of my requirements and each has its own set of uses.  They are included here in no real order:

  • duplicity/duply – This tool works with S3 for small scale storage.
  • Rclone – This one looks very promising, supports S3 to GCS sync.
  • aws-cli – The official command line tool supported by AWS.

S3cmd – This was the first tool that came close to doing what I wanted.  It’s a really nice tool for smallish amounts of files and has some really nice and handy features and is capable of syncing S3 buckets.  It is equipped with a number of nice and handy options but unfortunately the way it is designed does not allow for reading and writing a large number of files.  It is a great tool for smaller sets of data.

s3s3mirror – This is an extremely fast copy tool written in Java and hosted on Github.  This thing is awesome at copying data quickly.  This tool was able to copy about 6 million files in a little over 5 hours the other day.  One extremely nice feature of this tool is that it has an intelligent sync built in so it knows which files have been copied over.  Even better, this tool is even faster when it is running reads only.  So once your initial sync has completed, additional syncs are blazing fast.

This is a jar file so you will need to have Java installed on your system to run it.

sudo apt-get install openjdk-jre-headless

Then you will need to grab the code from Github.

git clone git@github.com:cobbzilla/s3s3mirror.git

And to run it.

./s3s3mirror.sh first-bucket/ second-bucket/

That’s pretty much it.  There are some handy flags but this is the main command. There is an -r flag for changing the retry count, a -v flag for verbosity and troubleshooting as well as a –dry-run flag to see what will happen.

The only down side of this tool is that it only seems to be supported for S3 at this point – although the source is posted to Github so could easily be adapted to work for GCS, which is something I am actually looking at doing.

Gsutil – The Python command line tool that was created and developed by Google.  This is the most powerful tool that I have found so far.  It has a ton of command line options, the ability to communicate with other cloud providers, open source and is under active development and maintenance.  Gsutil is scriptable and has code for dealing with failures – it can retry failed copies as well as resumable transfers, and has intelligence for checking which files and directories already exist for scenarios where synchronizing buckets is important.

The first step to using gsutil after installation is to run through the configuration with the gsutil config command.  Follow the instructions to link gsutil with your account.  After the initial configuration has been run you can modify or update all the gsutil goodies by editing the config file – which lives in ~/.boto by default.  One config change that is worth mentioning is the parallel_process_count and parallel_thread_count.  These control how much data can get shoved through gsutil at once – so on really beefy boxes you can crank this number up quite a bit higher than its default.  To utilize the parallel processing you simply need to set the -m flag on your gsutil command.

gsutil -m sync/cp gs://bucket-name

One very nice feature of gsutil is that it has built in functionality to interact with AWS and S3 storage.  To enable  this functionality you need to copy your AWS access_id and your secret_access_key in to your ~/.boto config file.  After that, you can test out the updated config to look at your buckets that live on S3.

gsutil ls s3://

So your final command to sync an S3 bucket to Google Cloud would look similar to the following,

gsutil -m cp -R s3://bucket-name gs://bucket-name

Notice the -R flag, which sets the copy to be a recursive copy instead everything in one bucket to the other, instead of a single layer copy.

There is one final tool that I’d like to cover, which isn’t a command line tool but turns out to be incredibly useful for copying large sets of data from S3 in to GCS, which is the GCS Online Import tool.  Follow the link and go fill out the interest form listed and after a little while you should hear from somebody from Google about setting up and using your new account.  It is free to use and the support is very good. Once you have been approved for using this tool you will need to provide a little bit of information for setting up sync jobs, your AWS ID and key, as well as allowing your Google account to sync the data.  But it is all very straight forward and if you have any questions the support is excellent.  This tool saved me from having to manually sync my S3 storage to GCS manually, which would have taken at least 7 days (and that was even with a monster EC2 instance).

Ultimately, the tools you choose will depend on your specific requirements.  I ended up using a combination of s3s3mirror, AWS bucket versioning, the Google cloud import tool and gsutil.  But my requirements are probably different from the next person and each backup scenario is unique so a combination of these various tools allows for flexibility to accomplish pretty much all scenarios.  Let me know if you have any questions or know of some other tools that I have failed to mention here.  Cloud backups are an interesting and unique challenge that I am still mastering so I would love to hear any tips and tricks you may have.

Chef data bags with Test Kitchen

As a step towards integrating your Chef cookbooks with Jenkins CI and your testing/release pipeline it is important to make sure that local changes pass unit and integration tests before being accepted and committed into version control.  For example, when running test kitchen it is important to fully simulate what data bags and encrypted data bags are doing on a local box for many tests to pass correctly.  So, today I would like to focus on a stumbling block towards Jenkins and integration testing that I ran in to recently.  There are a few lessons that I learned along the way that I would like to share to help clarify things a little bit because there wasn’t much good info out there on how to do this.

First, I need to give credit where it is due.  This post was a great resource in my journey to find a solution to my test kitchen data bag issue.

The largest roadblock I found along the way was that the version of test kitchen I was using was being shipped with chef-solo as the primary driver.  There has been a lot of discussion around this topic lately and (from what I understand) has pretty much become the general consensus within the Chef community that chef-solo should be replaced by chef-zero.  There are a number of advantages to using chef-zero instead of chef-solo, including a lesson I learned the hard way, which is that chef-zero has the ability to act as a stand alone Chef server – unlocking the ability to store data bags and encrypted data bags without having to do any sort of wacky hacking to get Chef to compile and converge correctly.

There was a good post written recently that expounds more on the benefits of using chef-zero instead of chef-solo.  It is here, and is definitely worth the read if you are interested in learning more about the benefits of chef-zero.

So with that knowledge in mind, here is what a newly updated sample .kitchen.yml file might look like:

--- 
driver: 
 name: vagrant 
 
provisioner: 
 name: chef_zero 
 
platforms: 
 - name: ubuntu-13.10-i386 
 - name: centos-6.4-i386 
 
suites: 
 - name: default 
 data_bags_path: "test/integration/data_bags" 
 run_list: 
 - recipe[recipe-to-test] 
 attributes:

It’s a pretty straight forward config.  The biggest change that you will notice in this config is that instead of using chef-solo as the provisioner it has been changed to chef-zero – I now know that it makes all the difference in the world.  The next big change to observe is the data_bags_path in the suites section.  This bit of configuration basically tells the Chef provisioner to go look at the specified file path when chef-zero spins up and use that to store data bag, encrypted data bag or other information that potentially would live on the Chef server that client’s would use.

So in the test/integration/data_bags directory I have a directory and json file inside that directory for the specific data I am interested in, called sensu/ssl.json.  This file essentially contains the same information that is stored on the Chef server about the ssl certificates used for live hosts in the production environment, just mirrored into a sandbox/integration testing environment.

If you’re interested, here is a sample of what the  ssl.json file might look like:

{ 
 "id": "ssl", 
 "server": { 
 "key": "-----BEGIN RSA PRIVATE KEY-----gM
 "cert": "-----BEGIN CERTIFICATE-----gM
 "cacert": "-----BEGIN CERTIFICATE-----gM
 }, 
 "client": { 
 "key": "-----BEGIN RSA PRIVATE KEY-----gM
 "cert": "-----BEGIN CERTIFICATE-----gM
 } 
}

Note that the “id” is “ssl”.  As far as I know the file name must match up to the id when you are creating this json file.

Now you should be able to create and converge your test recipe with test kitchen:

kitchen create ubuntu
kitchen converge ubuntu

If you have any difficulty, let me know.  I tried to be thorough in this write up but could have accidentally skipped important information.  The main keys or takeaways though should be 1) use chef-zero wherever possible and 2) make sure you have your data bag paths and files created correctly and referenced correctly in your .kitchen.yml file.  Finally, if you are still having issues, make sure you have triple checked the spelling and json syntax of your paths and configs.