Aug 31

Weaving with Light Pt. 1

This is the first in a series of posts regarding a recent project which integrated handweaving, fiber optics, and electronics. It’s a part of a costume for a cosplayer at work, but I’ll be discussing my part of it.


For those who can’t wait, here’s what the project looks like in the dark:

Handweaving with fiber optics viewed in the dark

Handweaving with fiber optics viewed in the dark

And in the light:

You can still see the glow, it's just not as bright.

You can still see the glow, it’s just not as bright.

In the Beginning

I recently started a new job; when one of my co-workers heard I am a weaver, she approached me with a challenge: to weave fiber optics into a fabric so that it would have an otherworldly glow. Originally the idea was for a Patronus from Harry Potter; we pivoted to a ghost from Ghostbusters.

I spent some time researching on the net; I have only found a couple of other instances of handweavers making fabric with embedded fiber optics. So it’s pushing the envelope in that regard 😉

Just the Facts

  • 200 fiber optic strands, 2m in length
  • 32 bright LEDs
  • Over 100 solder joints
  • 5v input
  • 640 mA draw
  • 2 watt resistor
  • “Skirt” is separated into 8 strands, each 4″ wide
  • 6.25 fiber optics/inch
  • Two types of cotton thread used for fabric structure
  • 30 hours loom time
  • 10 hours prototype
  • 15 hours research and shopping
  • 25 hours constructing wiring and LED Harness
  • LEDs are swappable
  • Two power busses to distribute to LEDs
  • Power regulator has a fan.
  • Almost everything (except fabric) can be swapped out and/or replaced.

I know this is something of a tease, but I’ll write more soon!

Jun 24

Abusing HAProxy: Stupid Simple Easy Dashboards

I wanted a simple way to have a dashboard to show if hosts and services are alive & didn’t want to write much code and/or run up a nagios instance (or anything like that). All I care is whether it’s green or red.

I’d already been setting up HAProxy for a proxy forwarder, so I got the idea to turn on the stats page and just have a set of backends which HAProxy would check.

Sample config follows:

Make the file, then if you don’t even feel like installing haproxy, you could do a:

Point your browser to http://localhost:2001/ and enter user/pass as admin and you’re good to go. It even refreshes every 30 seconds.

Apr 25

Rules for Operations

The following list was compiled in 2012 for a talk on Operations Principles for Developers (Ops4Devs). They are loosely inspired by the list of rules from Zombieland as well as from my experiences and those shared by others. Looking over the list four years later, I believe that they are still (very) applicable for all of IT.

  1. Exercise your environment
  2. Test
  3. Beware of Assumptions
  4. Monitors
  5. Be a smart reporter
    Read the rest of this entry »

Apr 24

DevOps Creed (Work in Progress)

This is a work in progress of a DevOps Creed. It will always be a work in progress as I and others learn and grow. Suggestions are welcome!


I have drunk deep of the DevOps Kool-Aid. From the visions which ensued, I have come to the following….

I Believe:

  • DevOps methodologies lead to systems which are Repeatable, Reproducible, and Reliable.
  • You are not accountable (or responsible) if you will never get a call in the middle of the night.
  • Without shared pain, systems and software will not improve.
  • The goal of operations is not get unexpected calls in the middle of the night. If I am doing my job, then preventable issues are dealt with before they are a problem.
  • Post Mortems need to be blameless and a learning tool to mitigate or prevent future occurrences.
  • ITIL describes a set of best practices; it doesn’t dictate how to implement the practices. Just because they come from “suits” doesn’t mean they’re not valid.
  • Learning is key to growth. Once you stop learning, you’re dead.
  • It is important to question one’s assumptions. How many RFC’s have there been for email over the past three decades?
  • Utopia contains no pets and only cattle. It is an ideal to be pursued.
  • Infrastructure as code and revision control make disaster recovery much less painful.
  • Reduce the likelihood of operator error: automate whenever appropriate.
  • Paired programming and code review works for infrastructure, too.

Apr 11

I am not a Mindreader: a mini-saga

I must confess a severe failing on my part. I am not a mindreader.

I am not privy to the thoughts in your head. I do not know your needs or desires. And I am certainly not aware of your expectations.

This is why requirement documents exist. Please use them.

Apr 07

Cloudera Manager Disaster Recovery with JSON Deployment Dump

Cloudera Manager is fairly opinionated. In its defence, it pretty much needs to be given that it needs to wrangle multiple underlying Open Source projects. Each of these, in turn, have their own quirks and opinions.

The following is a description of how to recover a Cloudera Manager cluster post disaster, assuming that you have a copy of the deployment. I will say that this is something of a hack; it treats the cluster a bit too much like a pet, but you could make a case that the Cloudera Manager’s deployment dump behaves similarly to infrastructure as code.

One of the tricks I’d previously discovered which can help is that the /var/lib/cloudera-scm-agent/uuid file can either be generated by the agent or you can choose your own. It is used by the Cloudera Manager as a primary key for hosts on which the agent lives. In the case of a disaster or server crash, if replacement hostnames and IP addresses remain the same (since they are set once within Cloudera Manager and cannot change) then the hosts can be dropped back into the cluster without creating multiple records of the same hostname. A means of doing so would be something like:

Note the call to tr above. The uuid file is used explicitly, so if there are any linefeeds in the file, the linefeed becomes part of the UUID inside Cloudera Manager. While it is legal, this can make some API calls awkward.

However, if you aren’t able to reuse the same UUID(s), or if the UUID is overwritten, say by Puppet, after the cluster is created, all is not lost. You likely will have some cleanup to perform, but it’s not

The Cloudera Manager API is very powerful and opens up many possibilities — not the least of which is opening a door into the mind of the Manager and how it thinks. One of the calls, /cm/deployment, I had figured would work for backing up and restoring the state of a cluster. I’d tested it previously in a single node cluster, so I knew it could work — at least in the small!

I had an opportunity to test my theory in a larger cluster this evening.

The basic symptoms were a dashboard full of red and no messages in the logs when you attempted to restart a server — you could start the Agent, but it wouldn’t do much good — it wasn’t speaking to the Manager.

I determined (after some experimentation) that the reason why they weren’t speaking very well was that the UUID was being overwritten by Puppet. I started giggling. In a warped, BOFH sense, it is actually pretty funny what was causing the cluster to misbehave. All I could think was that the cluster was most definitely borked by a master!


The Cloudera Manager instance was still available so I had a starting point from which to work — although if I’d had a backup of the deployment configuration it would still have worked if the cluster was totally dead.

I set out to replace the hostId entries and figured that was all I would need to do. Turns out there was a bit more than just that.

Here are a basic set of steps in order to recover:

Note: Replace MANAGER with the name of the host on which the Cloudera Manager is located. Also, replace the authentication user/pass as needed — it’s unlikely (I hope!) that you’re still using admin/admin for user/pass.

  1. If the cluster is still up, then dump the hosts. The information you need is in the deployment, but it’s convenient to pull it from the hosts: curl -u 'admin:admin' http://MANAGER:7180/api/v11/hosts > hosts.json

  2. If you don’t have a dump of the deployment, you can get one via:
    curl -u 'admin:admin' http://MANAGER:7180/api/v11/cm/deployment > deployment.json

  3. In this case, I needed all of the new uuid’s. You may be able to skip ahead to step 7 if the uuid’s haven’t changed. There may be modifications needed for the IP/Hosts if your replacement cluster is on a different network. Or you could use this to create a template and reproduce it in different networks.

  1. We’re going to use sed to replace all of the UUID entries. The following ruby code will generate our sed script for us:

  1. Paranoia Check time. Look at the output sedder.sed script. If the UUID’s are generated, then there is a good chance that they will have a “\n” in them. Consequently you may need to edit the sed script..

  2. Run the script which was just generated: bash -x sedder.sed

  3. At this point, there is likely some more fixing needed. The following is needed because:

    When specifying roles to be created, the names provided for each role must not conflict with the names that CM auto-generates for roles. Specifically, names of the form “<service name>-<role type>-<arbitrary value>” cannot be used unless the <arbitrary value> is the same one CM would use. If CM detects such a conflict, the error message will indicate what is safe to use. Alternately, a differently formatted name should be used. — Cloudera Manager API

    Cloudera Manager played fickle and didn’t think that the “arbitrary” values it thought safe previously were still any good. I searched a bit, but could not find anything to tell how it calculates those arbitrary safe values :-/. They are a large hexadecimal number; I was able to identify that part, which led (after much experimentation) to the following fix.

    Save the following to fixer.awk:

    Execute it via: awk -f fixer.awk deployment.json >

  4. More Paranoia. Look at the output JSON text — if it looks borked, then don’t deploy it!

  5. Install the fixed deployment

At this point, if all has gone well, it accepts the deployment. You’ll need to restart the cluster(s). I strongly suggest starting the Management Cluster first.

After the dust settles, you’ll have a repaired and/or newly deployed cluster.

In my case, I was mostly there when I found that puppet was also overwriting the Manager server entry in
/etc/cloudera-scm-agent/config.ini with localhost


Good luck and let me know what you think.

Mar 30

Interesting Feature of Dockerfile Volume Directives

I’ve been rewriting a cleanroom version of the hadoop-in-a-box — just about finished. And, truth be told, the code, all in all, is a bit tighter than the original encumbered version.

However, I ran into an interesting feature of Volumes — I had thought perhaps to optimize things a bit, but it caused some unexpected behavior at O’dark thirty.

There are some directories and files that really need to be outside of the container for purposes of efficiency and reducing overhead:

  • hdfs related directory trees — All of the writes soon lead to confusion in the storage drivers I’ve used.
  • parcels on the worker nodes — these are also painful when there are constraints of memory

I thought I’d get ahead of the curve and add Volume declarations to the base Dockerfile. For a variety of reasons I bootstrap the container in which the Cloudera Manager is running — it certainly helps to speed things up and it also removes human intervention from a few steps. However, one of the directory trees, /opt, is one of the ones where I want to have different behaviors between the manager and the worker nodes. So, I went through the process of bootstrapping, downloading parcels to the manager and commiting the container only to find that they’d disappeared.

After a few cycles of this and looking inside the container and exported tar images, it occurred to me that I was seeing issues with /opt/cloudera permissions which I hadn’t previously and files were disappearing. A quick check of the documentation revealed the following nuggets (emphasis my own):

The VOLUME instruction creates a mount point with the specified name and marks it as holding externally mounted volumes from native host or other containers…
The docker run command initializes the newly created volume with any data that exists at the specified location within the base image….
Note: If any build steps change the data within the volume after it has been declared, those changes will be discarded.

So, I was downloading the parcels only to have them go to the great bit-bucket in the sky. Premature optimization is the Enemy.

After removing the volume declaration and rebuilding the images, everything worked as expected.

I am curious if there’s a way to “undeclare” a volume which was in a parent dockerfile. I’ve not had a chance yet to play with it, however.

Mar 17

Docker, Cgroups, Memory Constraints, and Java: A Cautionary Tale, or Here be Reapers (sometimes)

TL;DR: Java and cgroups/Docker memory constraints don’t always
behave as you might expect. Always explicitly specify JVM heap
sizes. Also be aware that kernel features may not be enabled. And Linux… lies.

I’ve recently discovered an interesting “quirk” in potential
interactions between Java, cgroups, Docker, and the kernel which can
cause some surprising results.

Unless you explicitly state heap sizes, the JVM makes guesses about
sizing based on the host on which it runs. In general on any “server
class” machine — which now refers to just about anything other than a
Windows desktop or a Raspberry Pi — by default specifies a maximum
heap size of approximately 1/4 of the ram on the host. Where this
becomes interesting is that specifying the amount of memory available
to a container does not affect what the jvm believes is available.

Last year I wrote in
Looking Inside a JVM: -XX:+PrintFlagsFinal
about finding the values configured in the JVM at runtime. By not
specifying a heap size, I get the following on a host with 12G of ram:

Notice that the MaxHeapSize is ~3GB.

You ever look inside of Java …. in Docker? — Half Brewed

It’s the same. Ok, let’s set the max memory size of the container to
256m (-m 256m) and try again:

Note the Warning…. we’ll come back to it later (much later)

And… it’s the same.

Fabio Kung has written an interesting discussion of
Memory inside Linux containers
and the reasons for why system calls do not return the amount of
memory inside a container. In short, the various tools and system
calls (including those which the JVM invoke) were created before
cgroups and have no concept that such limits might exist.

So, how much memory is actually available to the
JVM? Let’s start with a class which eats memory. I found the following
code at
Java memory test – How to consume all the memory (RAM) on a computer:

We can use the Docker Java container to compile it:

Now that it is compiled, let’s test:

There are a few interesting flags:

Flag Explanation
-XX:OnOutOfMemoryError=”echo Out of Memory” Instruct the
JVM to output a message on
-XX:ErrorFile=fatal.log When a fatal error occurs, an
error log is created with information and the state obtained at the
time of the fatal
error. ([Fatal Error Log – Troubleshooting Guide for Java SE 6 with HotSpot VM](

Betwixt the two flags, we should get some indication of an error….

Testing, Testing….

The tests were performed in a variety of scenarios:

Environment Docker Version Ram Swap Docker Memory Constraint Note(s)
4 Core, Openstack Instance 1.8.3 24G 0 --memory=256m [HCF]( within seconds — the OOMKiller kills the process.
4 Core, Physical 1.10.3 12G 15G --memory=256m Runs for a while and ends with OutOfMemoryError
8 Core, Physical 1.9.1 32G 32G --memory=256m Runs for about 5 minutes and exits with OutOfMemoryError
8 Core, Physical 1.9.1 32G 32G --memory=255m --memory-swap=256m Runs for about 5 minutes and exits with OutOfMemoryError
8 Core, Physical 1.9.1 32G 32G --memory=255m --memory-swap=256m Kernel level swap accounting turned on. OOMKiller strikes almost immediately.

In each case, the OS is Ubuntu 14.04 and the Docker container is java:latest.

I was expecting that the jvm would quickly attempt to grow beyond the container constraints and be killed. In the first test, it behaved as I expected. The container starts and then the logs abruptly end:

Upon inspection of the container, I see that it was killed by the OOMKiller:

Odd behavior, but just as I expected. cgroups is enforcing the amount
of space used by a container, but when the JVM or any other program
queries for the available memory, it doesn’t interfere:

At this point I decided that I had an interesting enough topic to write about. Little did I know but that I was about to go…..

Down the Rabbit Hole

Down the Rabbit Hole

I set down to diligently write about my findings; re-running the test on my laptop (the second entry in the table above), I was surprised to find that it behaved differently.

At first I thought it might be due to differences in Docker versions, so I tried on the 3rd host, where it ran even longer than on the laptop!

(note the insane length of the garbage collection; this should have been my clue that something was seriously weird!)

I didn’t find anything indicating that memory constraints behaved differently between the 1.8.3 and more current versions.

I then wondered if it might be related to HugePageTables. As of 2011, Documentation/cgroups/memory.txt [] states:

Kernel memory and Hugepages are not under control yet. We just manage
pages on LRU.

Ok… let’s see if it’s enabled:

Yup… I had them.

I then disabled HugePages on the 8 core host:

Ok, disabled. I rebooted for paranoia and re-ran my test. Still failed. Grump.

It was time to….

The Docker Run Reference section on memory constraints specifies that there are four scenarios for setting user memory usage:

  1. No memory limits; the container can use as much as it likes. (Default behavior)

  2. Specify memory, but no memory-swap — the container ram is limited and it may use an equivalent amount of swap as memory.

  3. Specify memory and infinite (-1) memory-swap — the container is limited in ram, but not in swap.

  4. Specify memory and memory-swap to set the total amount. In this case, memory-swap needs to be larger than memory:

The total amount is denoted by memory-swap.

Aha! I’ll just set these flags and run my container again…. Drat.

It still isn’t working.

And swap keeps growing and growing….

By now, it’s going on 3AM, but I’m definitely going to figure this out.

At this point I remembered the warning:

A little bit of googling and I find that I need to set a kernel parameter. This can be done via grub.

You will need to edit /etc/default/grub — it is owned by root, so you will likely need to sudo.

On the GRUB_CMDLINE_LINUX line, edit it to add

  • cgroup_enable=memory
  • swapaccount=1

If there are no other arguments, it will look like this:

GRUB_CMDLINE_LINUX="cgroup_enable=memory swapaccount=1"

If there are other arguments, then just add the above; you’ll end up
with something along the lines of:

GRUB_CMDLINE_LINUX="acpi=off noapic cgroup_enable=memory swapaccount=1"

Next sudo update-grub && sudo reboot

Once the host reboots, the warning disappears and jvm is killed as expected:


The reason it behaved as expected on the OpenStack instance was that
there is no swap
on the instance. Since there is no swap to be had,
the container is, by necessity, limited to the size of the memory
specified. And the jvm instance was reaped by the OOMKiller, as I’d expected it would.


This was definitely an instance of accidental success!

The most exciting phrase to hear in science, the one that heralds new discoveries, is not ‘Eureka!’ but ‘That’s funny…’ Isaac Asimov

I’m glad I went down the rabbit hole on this one; I learned a good bit even if it took considerably longer than I’d expected.

A few caveats with which to leave you:

  1. It is best to always specify heap sizes when using the JVM. Don’t depend on heuristics. They can, have, and do change from version to version, let alone operating system and a host of other variables.
  2. Assume that the OS lies and there’s less memory than it tells you. I haven’t even mentioned Linux’ “optimistic malloc” yet.
  3. Know thy system. Understand how the different pieces work together.
  4. And remember…. No software, just like no plan, survives contact with the …. user.

Mar 15

Zombie Apocalypse! Docker AUFS + Java + Low Memory …. Hadoop in a Box Cloudera Manager Cluster

TL;DR — When using AUFS in a memory constrained environment, Java can spawn (lots!) of Zombies. A workaround is to change the storage driver to the device mapper.

In working on the Hadoop in a box CDH cluster with Cloudera Manager, I’ve discovered a few interesting things about AUFS. These experiences are with Ubuntu 14.04 and Docker 1.9.1. Others have reported similar results using Java in Docker without CDH.

I did my initial development of the CDH in a box containers in environments with 32G and 24G ram, switching to the latter when I was informed the target was for a host with 24G. With that amount of memory, everything just worked and no zombies. However, people started placing it on hosts with less ram and Java started spawning zombies. So I took a closer look.

I had previously noticed that the amount of cached and buffered memory seemed, to me, awful high, but I know that Linux uses it for optimizing IO. As it turns out, this memory doesn’t seem to be “free-able” when using aufs. Add to this Java, and weird things occur.

Zombies-Silhouette-800pxI tested on a quad core, 12G host, running up the manager and three workers. And then the zombies appeared. In a very short order — minutes — I had 260 zombies! This is in part due to supervisord restarting the failed jvms.

This necessitated a reboot. Once rebooted I started to do some research.

I found a couple of items hinting at issues and workarounds. I then decided to test the device mapper driver and set about converting my aufs rig to device mapper. After a few iterations, the least invasive steps are as follow:

  1. docker ps -aq | xargs docker rm -f
  2. docker images -q | xargs docker rmi
  3. service docker stop
  4. Edit /etc/default/docker and add the following to the end: DOCKER_OPTS="${DOCKER_OPTS} --storage-driver=devicemapper"
  5. service docker start

Now you can restart the cluster. I did so and once things stabilized, started adding services back to the cluster. I did not tweak any parameters, except:

After 2+ hours, no zombies

After 2+ hours, no zombies

I started Zookeeper, HDFS, and Yarn.

Notes and Caveats

  • YMMV, but changing to the device mapper seems to slow things down about 10%. However, I’d rather, particularly in a test/development environment be stable and not spawning zombies!

  • This is not using the LVM backed storage.

  • Ubuntu 14.04 is on Kernel 3.13; other options emerge post 3.18.

  • I have been able to run quite a few more services on an openstack instance with 24G of ram:

    Cluster of 4 Docker containers on an openstack image with 24G ram

    Cluster of 4 Docker containers on an openstack image with 24G ram

Mar 10

Cloudera Manager GUI and API Can Step on Each Other

While learning how the configuration worked — in particular which arguments to pass in order to set non-default values, I discovered that I could lose changes by following these steps:

  1. Use the GUI to set a value and save it. This is just so that you can find the variable. Keep the GUI open.
  2. Dump the deployment to see what the variable name is (curl http://MANAGER:7180/api/v11/cm/deployment?view=export > SOMEFILE)
  3. Call the API, setting the variable to the desired value.
  4. Back in the GUI, either do a reload or look up another configuration parameter. (I’m not sure of the exact steps here, but I think I noticed it happening two different ways)

It appears that the GUI is storing the state (again) when you reload or migrate away from the page. This emerged when I spent a bit of time helping someone figure out why his API calls weren’t changing variables.

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