Keystone Token Performance: Liberty vs Mitaka

A number of performance improvements were made in Keystone Mitaka, including caching the catalog, which should make token creation faster according to the Keystone developers. In this blog post, I will test this assertion.

My setup is unique to how I run keystone, you may be using different token formats, different backends, different web servers, and a different load balancer architecture. The point here is just to test Mitaka vs Liberty in my setup.

Keystone Setup

I’m running a 3 node Keystone cluster on virtual machines running in my OpenStack cloud. The nodes are fronted by another virtual machine running haproxy. The keystone cluster is using round-robin load balancing. I am requesting the tokens from a third virtual machine via the VIP provided by haproxy. The keystone nodes have 2 VCPUs + 4G RAM.

Keystone is running inside a docker container, which runs uwsgi. uwsgi has 2 static threads.

  • The Mitaka code is based on stable/mitaka from March 22, 2016.
  • The Liberty code is based on stable/liberty from March 16, 2016.

Note: I retested again with branches from April 17 and April 15 respectively, results were the same.

Keystone is configured to use Fernet tokens and the mysql backend.

I did not rebuild the machines, the mitaka runs are based on nodes upgraded to Mitaka from Liberty.

Experimental Setup

I am doing 20 benchmark runs against each setup, delaying 120 seconds in between each run. The goal here is to even out performance changes based on the fact that these are virtual machines running in a cloud. The tests run as follows:

  • Create 200 tokens serially
  • Validate 200 tokens serially
  • Create 1000 tokens concurrently (20 at once)
  • Validate 500 tokens concurrently (20 at once)

The code for running these benchmarks, which I borrowed from Dolph Mathew’s and made a bit easier to use, is available on github. Patches welcome.

Results

Is Mitaka faster? Answer: No.

Something is amiss in Mitaka Fernet token performance and there is a serious degradation here.

The charts tell the story, each chart below shows how many requests per second can be handled, and concurrent validation is the most concerning because this is the standard model of what a cloud is doing. Dozens of API calls being made at once to tens of services and each one wants to validate a token.

Liberty vs Mitaka: No Caching

So you can see that concurrent validation is much slower. Let’s also compare with memcache enabled:

Liberty vs Mitaka with Caching

Let’s look at raw data which is more damning due to the scale on the charts:

Data

Notes

I spent some time thinking about why this might be slower and I see one clue, the traffic to memcache (shown using stats command) in Mitaka is 3-4x what it is in Liberty. Perhaps Keystone is caching too much or too often? I don’t really know but that is an interesting difference here.

I’m hopeful that this gets fixed or looked at in Newton and backported to Mitaka.

Possible sources of error:

  • These are VMs, could have noisy neighbors. Mitigation: Run it a whole lot. Re-run on new VMs. Run at night.
  • Revocation events. Mitigation: Check and clear revocation table entries before running perf tests.

I’d really like someone else to reproduce this, especially using a different benchmarking tool to confirm this data. If you did, please let me know.

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OpenStack Deployments Book: The Home Stretch

Over the past year, I’ve been working with Elizabeth K Joseph (pleia on IRC) on a book about OpenStack deployments. The idea of this book is that sysadmins and engineers can read it and follow along by setting up OpenStack. This way they can get a feel for how it works, how to diagnose issues, and plan their deployments.

Deployments Book

So how did this project develop? Well, Liz had approached me in Vancouver about the book and we met to discuss it. During a summit lunch overlooking the harbor, we went over scope and responsibilities and with some caveats, I signed on as a contributing author. My main role would be to write puppet code to install and run OpenStack. The idea is that this code would be in a form where users could choose the bits and pieces they wanted to try out and match that against cloud use cases. This would be incorporated into the book’s idea of “OpenStack recipes”. So off and on over the next 12 months, I’ve been reviewing content, discussing strategy, and writing puppet code. Much of the code that I did for this book was actually done in the upstream OpenStack puppet modules, and being core in those modules made that much easier. I’ve watched those modules get more and more mature during the 12 months we worked on this book. During the time we worked on the book we’ve switched from Kilo to Liberty to Mitaka, and although there’s always some bugs during a switch, each one has had less and less.

So where is this book at now? Well the good news is that as of tonight we’re officially code complete and mostly text complete. We’ll continue to work out some kinks and bugs over the next month or so and the book looks like it’s on track for a summer release.

Aside from pre-ordering, you can follow along for updates on the book in a few different ways. Check the website for some updates from Liz (coming soon): http://deploymentsbook.com/. Also follow the official OpenStack Deployments Book twitter feed: @deploymentsbook

Once we publish, I’ll also post an update here.

My Summer Sabbatical from Open Source and Volunteerism

tl;dr open source vacation

I’ve always enjoyed being part of communities. Whether it’s in software, the Ubuntu community, the Puppet community, the OpenStack community, etc. Or whether it’s outside of software, doing volunteer work for the US Forest Service or my son’s scout group. While I enjoy these activities and consider them to also be hobbies, they are massive time sinks and that time has to come from somewhere. I have the unfortunate personal habit of signing up for more work than I can or should do at the expense of other activities. I don’t want to call it burn-out but it does cause me to be frustrated, which I’ve noticed I’ve become more and more. So I’ve decide that I want to enjoy my summer to it’s fullest extent, so to that end I announced that I was detaching from opensource/volunteer work for the summer.

I’ve gotten a bunch of questions already so here goes:

Q: Why?
A: See Above

Q: Why announce it?
A: Because it makes it easier for me to say “no” to something and people won’t wonder where I disappeared to.

Q: Do you still like us?
A: Yes.

Q: Will you still be on IRC/mailing lists etc.
A: Yes, this is still my full time job. I will be online and available during normal work hours. I will probably stop my IRC bouncer.

Q: Will you still be pushing commits to opensource stuff?
A: Yes, for my day job.

Q: Okay so what won’t you be doing?
A: I won’t be on IRC 24/7. I probably won’t be replying to emails on the operators mailing list. I won’t be pushing stuff to osops. I won’t be doing any packaging work. I won’t be on my laptop every evening working on stuff.

Q: So what will you be doing?
A: Riding bikes with my wife & kids. Hiking and camping. Working on beer recipes. Trying new breweries. Cleaning my basement. Sitting on my patio. In other words, like a normal person, work during work hours, don’t work during non-work hours.

OpenStack Summit Talks

It’s become tough for me to go back and find links to talks I’ve given at past OpenStack summits and conferences so I’m making this page as an index that I can point people at. So here they all are in chronological order. A quick note, if you hear us talking about things like CI process and the talk is old, there’s likely to be significant improvements since then.

OpenStack Live – Sunnyvale – April 2015

Deploying an OpenStack Cloud at Scale at Time Warner Cable (no video, slides only)

OpenStack Summit – Vancouver – April 2015

Building Clouds with OpenStack Puppet Modules – good overview of the OpenStack puppet modules and how they will mix with your code to build running cloud.

Getting DNSaaS to Production with Designate – the process we went through to get Designate into production and how we wrote a Designate sink handler.

A CI/CD Alternative to Push & Pray for OpenStack – great overview of a full CI/CD process for OpenStack deployments, using Ansible, puppet, gerrit, and Jenkins. This contains updated information from the OpenStack Live talk above.

Real World Experiences with Upgrading OpenStack at Time Warner Cable – an overview of our upgrade process and pitfalls in going from the Juno to Kilo release.

PuppetConf – Portland – September 2015

Practical CI/CD with Puppet Code and Configuration – a deep dive into our CI/CD process with a puppet focus. If you use Puppet code this applies generally, if you use Puppet & OpenStack watch this and the talk from Vancouver.

OpenStack Summit – Tokyo – October 2015

Proud to be a Noob: How to Make the Most of Your First OpenStack Summit – a panel discussion on how to get the most out of your first OpenStack summit, watch before Austin!

Duct-tape, Bubblegum, and Bailing Wire: 12 Steps in Operating OpenStack – A humorous look at the trials and tribulations of running OpenStack as an operator.

OpenStack Summit – Austin – April 2016 – coming soon

Videos coming soon! Hope to see you there.

Get Ready for Fernet Tokens – Fernet is coming. Are you prepared? Come to this talk to understand how they work and how to operate them.

Moving a Running OpenStack Cloud to a New Data Center – Our data center is out of space, but we need more capacity. What to do? Move the cloud of course! But don’t upset customers in the process, it has to stay running! Come hear about how we did it.

Experiences and Priorities for Private Cloud Keystone and Public Cloud Keystone – a panel discussion with other operators about Keystone’s present, priorities, and futures.

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Consuming Keystone CADF Events From RabbitMQ

This started with a simple requirement: “I’d like to know when users or projects are added or removed and who did the action”

As it turns out there’s no great way to do this. Sure you can log it when a user is deleted:

"DELETE /v2.0/users/702b12ec7f0e4f7d93945eebb95705e1 HTTP/1.1" 204 - "-" "python-keystoneclient"

The only problem is that ‘702b12ec7f0e4f7d93945eebb95705e1’ is meaningless without the DB entry which is now conveniently gone.

But if you had an async way to get events from Keystone, you could solve this yourself. That was my idea with my Keystone CADF Event Logger tool. Before we dive into the tool, some quick background on CADF events. You can read the DMTF mumbo-jumbo at the link in the previous sentence, but just know, Keystone CADF events log anything interesting that happens in Keystone. They also tell you who did it, from where they did it, and when they did it. All important things for auditing. (This article from Steve Martinelli has some more great background)

So how does this solve my problem? CADF events still just log ids, not names. My solution was a simple rabbit consuming async daemon that cached a user and project names locally and used it to do lookups. Here’s an example of what it does:

Logs user auth events

Note that V2 doesn’t log much info on these, although that is fixed in Liberty I believe.

INFO 2015-09-24 15:09:27.172 USER AUTH: success: nova
INFO 2015-09-24 15:09:27.524 USER AUTH: success: icinga
INFO 2015-09-24 15:09:27.800 USER AUTH: success: neutron
INFO 2015-09-24 15:09:27.800 USER AUTH: failure: neutron

Log user/project crud events

Note again V2 issues here with Kilo leave us with less than full info.

USER CREATED: success: user ffflll at 2015-09-18 16:00:10.426372 by unknown (unknown) (project: unknown (unknown)).
USER DELETED: success: user ffflll at 2015-09-18 16:02:13.196172 by unknown (unknown) (project: unknown (unknown)).

Figures it out when rabbit goes away

INFO 2015-11-11 20:46:59.325 Connecting to 1.2.3.4:5672
ERROR 2015-11-11 22:16:59.514 Socket Error: 104
WARNING 2015-11-11 22:16:59.515 Socket closed when connection was open
WARNING 2015-11-11 22:16:59.515 Disconnected from RabbitMQ at top-secret-internal-company-url.com:5672 (0): Not specified
WARNING 2015-11-11 22:16:59.516 Connection closed, reopening in 5 seconds: (0) Not specified

Setup

This requires that Keystone is configured to talk to rabbit and emit CADF events. The previously referenced blog from Steve Martinelli has good info on this. Here’s what I set:

notification_format=cadf
notification_driver=messaging
notification_topics=keystone_to_cadf_logger

This code also assumes that /var/log/keystone_cadf is there and writable. I setup this with puppet in my environment.

You should ensure Keystone is talking to Rabbit and has made the queues and exchanges before trying the program.

Usage

I designed this to run in a docker container, which explains the overly full requirements.txt, you can probably get away with the requirements.txt.ORIG. After you build it (python ./setup.py build && python ./setup.py install, just run it by passing in creds for Keystone and for RabbitMQ. You can also use environment variables which is I how I ran in it my docker container.

source openrc
keystone-cadf-logger --rabbit_user rabbit --rabbit-pass pass1 --rabbit-host dev-lb.twc.net

Issues

So what issues exist with this? First some small ones. The code that parses the events is horrible and I hate it, but it worked. You can probably improve it. Second, the big issue. In our environment this code introduced a circular dependency between our control nodes, where rabbit runs, and our keystone nodes which now need to talk to rabbit. For this reason, we ended up not deploying this code, even thought I had all the puppet and docker portions working. If you don’t have this issue, then this code will work well for you. I also don’t have much operating experience with this, it might set all your disks on fire and blow up in spectacular fashion. I planned to deploy it to our dev environment and tweak things as needed. So if you operate it, do it cautiously.

Tweaks

If you are interested in more event types, just change the on_message code. You might also want to change the action that happens. Right now it just logs, but how about emailing the team anytime a user is removed or noting it in your team chat.

Conclusion

This code consists of a few parts and I hope at least some of it is useful to someone. It was fun to write and I was a bit disappointed that we couldn’t fully use it, but I hope that something in here, even if it’s just the async rabbit code might be useful to you. But what about our requirement? Well, we’ll probably still log CADF events locally on the Keystone node and consume them, or we might write a pipeline filter that does something similar, whatever we decide I will update on this site. So please pull the code and play with it!

Github Link

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Keystone Token Revocations Cripple Validation Performance

Having keystone token revocation events cripples token validation performance. If you’ve been following any of the mailing lists posts on this topic, then you already know this since it’s been discussed (here) and (here). In this post I explore the actual impact and discuss what you can do about it.

What Are Revocations?

A token is revoked for any number of reasons, but basically when it’s revoked, it’s invalid. Here are some of the reasons that revocation events will be generated:

  • The token is intentionally invalidated via the API
  • A user is deleted
  • A user has a role removed
  • A user is removed from a project
  • A user logs out of Horizon
  • A user switches projects in Horizon

Of these events the last two are by far the most common reasons that revocation events are being generated in your cloud.

How Are Revocation Events Used?

How this works varies some based on the token type, but lets assume that a token comes in that is non-expired. We know that either from decrypting it (Fernet) or from looking it up in the DB (UUID). But before Keystone can bless the token, it needs to check the revocation table to ensure that the token is still valid. So it loads the table called revocation_event and takes a peek. Also when it does this load, Keystone does a little house-keeping and removes and revocation events that are on tokens that are already expired. The time a revocation event lives is the same as the token. It does not make sense to have a 3 hour old revocation event when the longest token can live is 1 hour. The unfortunate thing with this algorithm is that it locks the table, slowing down other revocations even more and if it takes too long, leads to deadlocks and failed API calls.

Why Should You Care About Token Validation?

Keystone token validation underlies every single API call that OpenStack makes. If keystone token validation is slow, everything is slow. Validation takes place for example when you make a nova call, nova has to be sure that the token is okay first before performing the action.

Results

If you want to see the experimental setup, skip below, but most of you will want the numbers first!

The chart below shows two runs of the benchmark which checks concurrent token validations. You will see that as soon as you have revocation events, performance falls significantly. There are two lines on the chart. The first line, blue, is our current packaged version of Keystone which is Kilo++/Liberty. The second line in red, shows the performance of a version of Liberty from July 17 with this patch applied. The hope with the patched code is that smarter use of deletes would improve performance, it does not in a measurable way. It may however reduce deadlocks, but I am unable to validate that since my environment is not under any real load.

Benchmark Results

Note: Do not put too much stock into the fact that the red line starts slower than the blue, instead focus on the shape of the curve. There’s too many possible variables in my testing (like what my hypervisor is doing and all the other changes between versions) to compare them apples to apples.

Experimental Setup

For the experimental setup all the systems are guests running in our production cloud built using vagrant-openstack and our standard puppet automation code. The nodes are as follows:

  • 3 keystone nodes
  • 1 haproxy load balancer
  • a puppet master, which also runs the benchmarks

The nodes are running Ubuntu and a version of Keystone from master from May 2015. They are using Fernet tokens that expire after two hours. mysql is setup as a 3 node Galera cluster that preferentially uses one node. The systems were not otherwise busy or doing much else.

The test itself tries to do 20 validations at once up to 4000 of them. It talks to the load balancer which is setup to do round-robin connections.

Given all the variables here, I don’t expect you to replicate these numbers, but rather viewed relative to each other.

Running the Benchmark

For the benchmark code, I used a modified version of Dolph’s benchmark experiment. The modified code is here (note that the detection of whether ab is installed is broken feel free to send me a fix).

Usage:

./benchmark.sh [Keystone Node or LB] [admin_password]

Generating Revoked Tokens

Here’s my kinda hacky script to generate and revoke tokens, it could be better if it just used curls for both. Usage is to pass in a number of tokens to create and then revoke as arg1 and then a valid token as arg2 that you’ve previously generated.

echo "getting & revoking $1 tokens"
for i in $(eval echo "{1..$1}")
do
TOKEN=`keystone token-get | grep id | grep -v tenant_id | grep -v user_id | awk '{ print $4 }'`
curl -X DELETE -i -H "X-Auth-Token: $2" "${OS_AUTH_URL}/tokens/${TOKEN}"
done

Solutions?

Here are a few ideas I’d recommend. First get a baseline of how many revocations you have on a regular basis, this should mainly be from people signing out of Horizon or switching projects in Horizon. For us it’s about 20-30. This is how you check.

mysql -u root keystone -e "select count(id) from revocation_event;"

Once you get a normal number, I’d recommend putting a threshold check into Icinga.

Watch your testing too, we have some regression tests that create users, roles, etc and generates about 500 revocation events.

If you have a spike of events, and you’re not worried about rogue users, you can simply truncate the table.

mysql -u root keystone -e "truncate table revocation_event;"

This has security implications so make sure you know what you are doing.

Another idea is writing a no-op driver for revocations, this essentially disables the feature and again has security implications.

Finally, I’d recommend enabling caching for revocation events you still get the same curve, but you’ll start out at a higher performance value.

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Fernet Tokens in Prod

This post is a follow-up to my previous post about Fernet Tokens which you may want to read first.

Last night we upgraded our production OpenStack to a new version of keystone off of master from a couple weeks ago and at the same time switched on Fernet tokens. This is after we let the change soak in our dev and staging environments for a couple weeks. We used this time to assess performance, look for issues, and figure out our key rotation strategy.

The Upgrade

All of our upgrade process is run via ansible. We cherry-pick the change which includes pointing to the repo with the new keystone along with enabling the Fernet tokens and then let ansible drive puppet to upgrade and switch providers. During the process, we go down to a single keystone node because it simplifies the active/active database setup when running migrations. So when this node is upgraded we take a short outage as the package is installed and then the migrations run. This took about 16 seconds.

Once this is done, the other OpenStack services start freaking out. Because we’ve not upgraded to Kilo yet, our version of Keystone middleware is too dumb to request a new token when the old one stops working. So this means we have to restart services that talk to Keystone. We ended up re-using our “rabbit node died, reboot OpenStack” script and added glance to the list since restarting it is fairly harmless even though it doesn’t talk to rabbit. Due to how the timing works, we don’t start this script until puppet is completely done upgrading the single keystone node, so while the script to restart services is quick, it doesn’t start for about 90 seconds after Keystone is ready. This means that we have an API outage of 1-2 minutes. For us, this is not a big deal, our customers are sensitive to “hey I can’t get to my VM” way more than a few minutes of API outage, especially one that’s during a scheduled maintenance window. This could be optimized down substantially if I manually ran the restarts instead of waiting on the full puppet run (that upgrades keystone) to finish.

Once the first node is done we run a full validation suite of V2 and V3 keystone tests. This is the point at which we can decide to go back if needed. The test suite for us took about 2 minutes.

Once we have one node upgraded, OpenStack is rebooted, and validation passes, we then deploy the new package and token provider to the rest of the nodes and they rejoin the cluster one by one. We started in the opposite region so we’d get a endpoint up in the other DC quickly. This is driven by another ansible job that runs puppet and does the nodes one by one.

All in all we finished in about 30 minutes, most of that time was sitting around. We then stayed an extra 30 to do a full set of OpenStack regression tests and everything was okay.

At the end I also truncated the token table to get back all the disk space it was using.

Key Rotation

We are not using any of the built-in Keystone Fernet key rotation mechanisms. This is because we already have a way to get code and config onto all our nodes and did not want to run the tooling on a keystone node directly. If you do this, then you inadvertently declare one node a master and have to write special code to handle this master node in puppet or ansible (or whatever you are using). Instead we decided to store the keys in eyaml in our hiera config. I wrote a simple python script that decrypts the eyaml and then generates and rotates the keys. Then I will take the output and propose it into our review system. Reviewing eyaml encrypted keys is somewhat useless, but the human step is there to prevent something dumb from happening. For now we’re only using 3 keys, since our tokens last 2 hours, we can’t do two rotations in under two hours. The reviewer would know the last time a rotation was done and the last time one was deployed. Since we don’t deploy anywhere near a two hour window, this should be okay. Eventually we’ll have Jenkins do this work rather than me. We don’t have any firm plans right now on how often we’ll do the key rotation, probably weekly though.

To answer a question that’s come up, there is no outage when you rotate keys, I’ve done five or six rotations including a few in the same day, without any issues.

Performance

I will be doing a full post later on about performance once I have more numbers, but the results so far is that token generation is much faster, while validation to be a bit slower. Even if it was about the same, the number of problems and database sync issues that not storing tokens in the DB solves make them worthwhile. We’re also going to (finally) switch to WSGI and I think that will further enhance performance.

Aftermath

Today one of my colleagues bought a bottle of Fernet-Branca for us. All I can say is that I highly recommend not doing a shot of it. Switching token providers is way less painful. (Video of said shot is here)

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Fernet Tokens for Fun & Profit

I’ve been digging into Fernet tokens this past week and getting ready to switch us over to using them. This is the first in a series of blog posts I plan on writing about them. This one will mainly be background on why we’re switching and what we hope to gain. The next post will cover rolling them out which will probably be in a few weeks. For now we’re running these keys in our dev environments for more testing while we focus resources on Kilo upgrades.

What are Fernet Tokens?
How do you explain Fernet tokens? Rather than some lengthy treatise mathematical and identity management theory, just know this: Fernet tokens use shared private keys to avoid having to store or replicate tokens in your database. This makes them super fast, reduces load on your database, and solves replication lag between data centers and nodes within a data center. If your manager asks you, “they’re faster, small, and reduce load on the db”, that should suffice. Dolph Mathews has a good write-up on how much faster they are here. You can also dive into the different token formats for comparison on another of his posts, here.

What Issues will this solve for us?

Now about the DB replication issues… I cannot tell you how much stuff we had to do to deal with database and replication issues with UUID tokens, here’s a few samples:

  • custom cron job to reap expired tokens
  • force db transactions to a master, despite us being active/active so tokens would be there when asked for
  • hacks to our cross-region icinga checks to allow the tokens to replicate, literally sleep(3)

We’ve even had a service accidentally DOS us by requesting so many tokens the DB couldn’t keep up and keystone ran out of DB threads. Hopefully all this is solved by Fernet tokens.

Will this cause an outage to switch to?

Switching token providers will cause an outage. All the old tokens you’ve issued are now 100% useless. So prep accordingly. I will give some updates to the next blog post on how long this was and what issues we saw when we did it.

Do I need to be only Kilo/Liberty?

  • Horizon – you need a newish copy of django_openstack_auth which I think is in Liberty
  • Keystone – you need to be on Kilo
  • python-keystonemiddleware it’s best to have at least 1.1.0. If you have 1.0, you MUST restart all OpenStack services are switching tokens
  • Everything Else – Shouldn’t matter!

A note on python-keystonemiddleware. In 1.0.0 if a service (say Nova) can’t use it’s token for some reason, it won’t try to get a new one until the old one expires. So if you switch to Fernet’s you have to restart all OpenStack services that talk to Keystone or they will not work. We already have some ansible to do this mainly in response to RabbitMQ issues but it works here too.

How do I get Keys onto the boxes?

All keystone nodes in your cluster need to have the same keys. Fortunately there is the concept of rotation so there’s no outage when switching keys, there’s always a key thats “up next” or “on-deck” so that when you’re rotating you switch to a key that’s already on every box. Now as for getting the keys there. I’m going to use puppet to deploy keys that I store in hiera and rotate with a jenkins job, but there are other ways like a shared FS or rsync. More details on my method once I know it works in a later blog post!

How does key rotation work?

What Fernet Rotation Looks Like

What Fernet Rotation Looks Like

If you read through the information on Fernet tokens, key rotation is by far the most confusing. I’ve sat down with pen and paper and now think I get it, so allow me to explain. I’m going to use a 3 key example here, they keys are named with numbers. I highly encourage you to setup a throwaway Keystone box and use keystone-manage fernet_rotate if you don’t follow this.

You need to know 4 rules about how these keys work first:

  1. The highest numbered key is the current signing key.
  2. The 0 key is the key that will become the next signing key.
  3. All other keys are old keys, they’ve been used in the past and there might be old tokens out there still signing with them depending on your expiration schedule
  4. New keys are always created as key 0.

Starting position, per the rules above.

  • 0 – this is the on-deck key, after the next rotation, it’s primary.
  • 1 – this is the old key, it used to be primary, and its still here in case any old tokens are still signed with it. Next rotation it gets deleted.
  • 2 – this is the current primary key thats used for signing.

Now we do a Rotation…

  • 0 becomes 3
  • 1 gets deleted
  • 2 stays 2
  • a new key becomes 0
A Fernet Rotation in Action

A Fernet Rotation in Action

So How does this work?

Let’s pretend we have a few tokens since this is a running OpenStack cluster. All tokens before the rotation above are signed with 2. We do the rotation, now new tokens are signed with 3. When a token comes in, Keystone tries both 3 and 2 to decode the token, and either should work. At this point we CANNOT rotate again until no more active keys are signed with 2, because 2 is going to be deleted! This means you need to have more tokens if you plan on rotating more frequently or have a long token expiration time. We’re going to rotate roughly weekly, and we have a 2 hour token timeout, so 3 is plenty.

Homework

If you think you get this, try this a homework problem. Assume that you have max_active_keys set to 5 and that you have 5 keys: 0, 4, 5, 6, 7.

  • Which is the current signing key?
  • Which is on-deck or the next key to be used? What will it’s number be after the rotation?
  • Which key will be deleted on next rotation?
  • What happens if a token comes in signed with key 5?
  • What happens if a token comes in signed with key 3?

Other Sources

I gathered a lot of this info from trying stuff but also a lot from blog posts. I’ve referenced two above, but I also want to recommend Lance Bragstad’s blog. Note, Lance’s blog is the only blog in the world where you can read about quinoa recipes and shotgun shot patterns.

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What I Hope to Get From the OpenStack Vancouver Summit

reproduced from content I wrote for SuperUser.

Matt Fischer, principal engineer at Time Warner Cable, shares survival tips for the Summit: backup plans, a beer list and a talk that he promises will be better than “Cats.”

May 11, 2015

The Vancouver summit is about a week away and so it’s time to start my prep work for the summit. This first means making a list of talks I want to go to. It also means making a list of any people I want to meet in person to talk to or people I owe a beer (or three) to. Finally, it means a list of things I want to accomplish at design sessions. If you’ve never been to a Summit before, what you get out of it really depends on how well you dig into the schedule and do some advanced planning.

So with that in mind, here’s my thinking.

Planning for Talks

I have some main focus areas for talks, things I want to come away from the summit knowing more about. These include things for which I’m the “owner” of in the Time Warner Cable OpenStack cloud, but also things I’m just curious about, so in no particular order:

Operations I always want to know how to do things differently or better, so you’ll see me around these rooms a lot. I’m specifically interested in Upgrades, CI/CD, and integrating new features into our cloud.

Heat I’m specifically interested in application catalog capabilities. Designate – I’ve worked some on this in the past few months. Neutron – I always want and need to know more about Neutron, even though it’s not my focus area.

Now with talks you can simply find the ones you like, and if you create an account and sign-in, you can add them to your personalized schedule. This is what I’d recommend to help plan your day. But, there’s a few more tricks that I’d recommend you use.

Review your schedule every morning. If you’re in Vancouver with a team you can divide up talks if you have time conflicts. You may also find that you’ve changed your mind or the schedule has changed, hence the morning review.

Have a backup talk. Sometimes talks are full or maybe you go and it’s not for you. You always need a backup talk.

Make a list of talks you want to watch later. All the talks end up on the OpenStack Foundation’s Youtube channel. Make a list of talks that you didn’t or won’t get to and watch them later. This does not work well for hands-on sessions, so I always opt to go to them.

If you can’t pick a talk by subject, pick by speaker. The speaker makes the talk sometimes more than the subject.

Don’t be afraid to have free time. The summit can be grueling. Leave a space or two in your schedule and visit the vendors or go take a nap.

Planning for People

OpenStack is community driven and the community is made of people. Take time to say “hi” to the people you’ve talked to on IRC or mailing lists.

Take the time to thank someone who fixed a bug for you or better yet buy them a beer. You cannot underestimate the value of having a beer with someone you’ve only previously met online. I cannot emphasize this enough.

Who are the lucky ones on my beer list this year? You’ll have to wait and see, hopefully I’m on yours!

Planning for Design Sessions

For the first time, OpenStack Puppet will be a real OpenStack project and so while previously we’ve had an hour to discuss stuff, this time we will have a full day for design work. Through lots of work over the past year, I’ve become core in OpenStack Puppet, and I hope to spend a good part of my day Tuesday participating in live discussions and work sessions. We have lots of stuff to discuss, the largest item which is dear to me, is when the master branch can drop support for the old stable release. If you’ve been active in other projects, you may have similar issues like this that need closure. These are usually easier to figure out in a room rather than in an IRC meeting. However, many of the design sessions are already planned so it may be too late to get something on the agenda, but it’s not too late to attend and participate. I’d recommend making a list of the things you want to cover and seeing how that lines up with the design session schedule. Please note that the Design Summit and the OpenStack Summit use different schedules hosted on different pages.

Planning for Parties

The OpenStack Summits have a large after-hours social aspect. These are valuable to attend just for camaraderie — you don’t have to drink beer to go and have fun. I generally go to as many of these as possible, they are usually pretty great.

You’re Invited!

I hope to see everyone in Vancouver, and would like to especially invite you to see some of my talks. The descriptions are pretty good, but I thought I’d say a few things about what you could expect to get out of each of them, here they are in chronological order with links so you can add them to your schedule.

Building Clouds with OpenStack Puppet Modules If you’re curious about how companies use Puppet to deploy OpenStack or about how our community works, you should attend this talk. You will get a couple different views and ideas on using Puppet from Mike Dorman and I, and hear about the community from Emilien Macchi. Monday, May 18 • 4:40 p.m. – 5:20 p.m. http://sched.co/38gd

A CI/CD Alternative to Push and Pray for OpenStack There are lots of CI talks this year, but I promise you will learn something new at this one. Clayton O’Neill and I will cover lots of topics and tools and you will see how we use these tools to get code and config from concept to production. Tuesday, May 19 • 12:05 p.m. – 12:45 p.m. http://sched.co/37lb

Getting DNSaaS to Production with Designate Have your customers been asking for DNSaaS (DNS as-a-Service)? Do you plan on having several people working on it full time as core Designate developers or would you rather just get it deployed with the minimum of pain? If the latter, then this is the talk for you. Clayton and I will cover what work is required, what work we did, and what to watch out for. One special thing that we will cover is how to write your own (or use our) Designate Sink which lets you automatically create records every time a new floating IP is assigned. Wednesday, May 20 • 9:50 a.m. – 10:30 a.m. http://sched.co/380J

Real World Experiences with Upgrading OpenStack at Time Warner Cable There are also lots of Upgrade talks at this summit. In this one, Clayton and I will be telling a story of what happened when we upgraded to Juno. Even though I wasn’t smart enough to put “beer” in the title of my upgrade talk, maybe you can learn some lessons or get some ideas from us. You’ll laugh, you’ll cry, it will be better than “Cats.” Thursday, May 21 • 2:20 p.m. – 3:00 p.m. http://sched.co/37wu

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Scale & Maturity: Thoughts on the OpenStack Mid-Cycle Operators Meetup

A re-post of an article I wrote last week for SuperUser.

A couple weeks back I attended the OpenStack Operators Mid-Cycle Meetup in Philadelphia.

One of the best parts of these meetups is that the agenda is all formed in public and everyone gets a say in it. Some of the things I was most concerned about made the list (RabbitMQ, packaging), some did not get on the main agenda (database maintenance, Puppet), but many side groups formed during the event and these topics were covered at lunch conversations and in the lobby.

The interesting part of this summit was hearing from other operators problems and solutions. This was more focused, yet with a larger audience, than the previous sessions in Paris. I think a real sense of camaraderie and support for shared solutions was achieved.

Puppet OpenStack Discussion at Lunch

As I was listening to people discuss their issues with OpenStack and how others had solved them, I realized that OpenStack operators have different issues at different scales and maturity levels. When I think about scale and maturity, it’s not necessarily about number of nodes or the number of customers, its more about the number of resources you have, the number of services you provide, the maturity of your processes (such as deployment), and to a some extent how many of your problems you’ve solved with automation.

Our team started at a small scale. We had four people and the goal was to stand-up OpenStack. With four people, you are limited in scope and have to judiciously focus your resources. As our team grew and we worked through forming our deployment and automation processes, we’re able to spend more time on improving our service offerings and adding more services. We can also go back and clean up technical debt which you accumulate as you build an OpenStack deployment. Before these tools and processes are fully in place (and they are never perfect), making changes can take away valuable time.

For example, when an operator finds a bug, it takes a lot of resources and time to get a fix for that bug into production. This includes debugging, filing a bug, fixing the code, pushing a fix, begging for reviews, doing a cherry-pick, begging for more reviews, waiting for or building a package, deploying the new code. Many operators stop around the “filing a bug” step of this process.

Medium-sized operators or ones with more mature processes will sometimes work on a fix (depending on the issue), and may or may not have systems in place to allow them to hold the patch locally and build local packages. On the other hand, larger operators who have good systems in place can give the issue to the Team. They may have 10 people working on it, some of them core members. They have a full continuous integration/automation team that has solved package builds and deployments for them.

Our goal has always been to increase our scale of services, not only via more resources but through automation and creating tools/processes that allow us to offer services for the same amount of resource investment. The main reason for this that is our customers don’t care about Keystone or Neutron, these are just building blocks for them, they really want services like Domain Name System (DNS,) load-balancing-as-a-service (LBaaS), firewall-as-a-service (FWaaS) and database-as-a-service (DBaaS). But until the processes and tools are solid for the core components, it’s hard to find time to work on those, because while customers may not know what Keystone is, they sure care when it doesn’t work.

So how does any of this relate to the conference besides I was daydreaming about it in the lobby? What is clear to me after the sessions is that we have some specific areas where we’re going to work on process improvements and tooling.

My top three are:

  1. RabbitMQ monitoring and tooling
  2. Speeding up and clarifying our development & deployment process
  3. Investigating alternatives to heavy-weight OS packages for deploying OpenStack code

When we revisit this again in six months at the next Mid-Cycle, I suspect that number two will remain on the list, probably forever, since you can always make this process better. I’m certain we’ll have a new number one, and I’m pretty hopeful about the options for number three.

What will these investments get us? Hopefully more time for second-level service offerings and happier customers.

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