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OpenStack @ FOSDEM ’14

January 9, 2014 2 comments

Every year, free and open source developers from all over Europe and beyond converge in cold Brussels for a week-end of talks, hacking and beer. OpenStack will be present !

We have a number of devroom and lightning talks already scheduled:

Saturday 12:20 in Chavanne (Virtualization and IaaS devroom)
Autoscaling best practices
Marc Cluet will look into autoscaling using Heat and Ceilometer as examples.

Saturday 13:00 in Chavanne (Virtualization and IaaS devroom)
Network Function Virtualization and Network Service Insertion and Chaining
Balaji Padnala will present NFV and how to deploy it using OpenStack and OpenFlow Controller.

Saturday 13:40 in Chavanne (Virtualization and IaaS devroom)
oVirt and OpenStack Storage (present and future)
Federico Simoncelli will cover integration between oVirt and Glance/Cinder for storage needs.

Saturday 15:00 in Chavanne (Virtualization and IaaS devroom)
Why, Where, What and How to contribute to OpenStack
I will go through a practical introduction to OpenStack development and explain why you should contribute if you haven’t already.

Saturday 16:20 in Chavanne (Virtualization and IaaS devroom)
Hypervisor Breakouts – Virtualization Vulnerabilities and OpenStack Exploitation
Rob Clark will explore this class of interesting vulnerabilities from an OpenStack perspective.

Saturday 17:40 in Chavanne (Virtualization and IaaS devroom)
oVirt applying Nova scheduler concepts for data center virtualization
Gilad Chaplik will present how oVirt could reuse OpenStack Nova scheduling concepts.

Sunday 10:00 in U.218A (Testing and automation devroom)
Preventing craziness: a deep dive into OpenStack testing automation
Me again, in a technical exploration on the OpenStack gating system and its unique challenges.

Sunday 13:40 in Chavanne (Virtualization and IaaS devroom)
Tunnels as a Connectivity and Segregation Solution for Virtualized Networks
Join Assaf Muller for an architectural, developer oriented overview of (GRE and VXLAN) tunnels in OpenStack Networking.

Sunday 16:20 in Chavanne (Virtualization and IaaS devroom)
Bring your virtualized networking stack to the next level
Mike Kolesnik will look into integration opportunities between oVirt and OpenStack Neutron.

Sunday 17:00 in Ferrer (Lightning talks room)
Putting the PaaS in OpenStack
Dirk Diane Mueller will give us an update on cross-community collaboration between OpenStack, Solum, Docker and OpenShift.

Sunday 17:20 in Ferrer (Lightning talks room)
Your Complete Open Source Cloud
Dave Neary should explain how to mix OpenStack with oVirt, OpenShift and Gluster to build a complete private cloud.

We’ll also have a booth manned by OpenStack community volunteers ! I hope to see you all there.

Categories: Cloud, Openstack

Lessons and outcomes from the Hong-Kong summit

November 13, 2013 Leave a comment

Just back from an amazing week at the OpenStack Summit in Hong-Kong, I would like to share a number of discussions we had (mainly on the release management track) and mention a few things I learned there.

First of all, Hong-Kong is a unique city. Skyscrapers built on vertiginous slopes, crazy population density, awesome restaurants, shops everywhere… Everything is clean and convenient (think: Octopus cards), even as it grows extremely fast. Everyone should go there at least one time in their lives !

On the Icehouse Design Summit side, the collaboration magic happened again. I should be used to it by now, but it is still amazing to build this level playing field for open design, fill it with smart people and see them make so much progress over 4 days. We can still improve, though: for example I’ll make sure we get whiteboards in every room for the next time :). As was mentioned in the feedback session, we are considering staggering the design summit and the conference (to let technical people participate to the latter), set time aside to discuss cross-project issues, and set up per-project space so that collaboration can continue even if there is no scheduled “session” going on.

I have been mostly involved in release management sessions. We discussed the Icehouse release schedule, with a proposed release date of April 17, and the possibility to have a pre-designated “off” week between release and the J design summit. We discussed changes in the format of the weekly project/release status meeting, where we should move per-project status updates off-meeting to be able to focus on cross-project issues instead. During this cycle we should also work on streamlining library release announcements. For stable branch maintenance, we decided to officially drop support for version n-2 by feature freeze (rather than at release time), which reflects more accurately what ended up being done during the past cycles. The security support is now aligned to stable branch support, which should make sure the vulnerability management team (VMT) doesn’t end up having to maintain old stable branches that are already abandoned by the stable branch maintainers. Finally, the VMT should review the projects from all official programs to come up with a clear list of what projects are actually security-supported and which aren’t.

Apart from the release management program, I’m involved in two pet projects: Rootwrap and StoryBoard. Rootwrap should be split from the oslo-incubator into its own package early in the Icehouse cycle, and its usage in Nova, Cinder and Neutron should be reviewed to result in incremental strengthening. StoryBoard (our next-generation task tracker) generated a lot of interest at the summit, I expect a lot of progress will be made in the near future. Its architecture might be overhauled from the current POC, so stay tuned.

Finally, it was great meeting everyone again. Our PTLs and Technical Committee members are a bunch of awesome folks, this open source project is in great hands. More generally, it seems that we not only designed a new way of building software, we also created a network of individuals and companies interested in that kind of open collaboration. That network explains why it is so easy for people to jump from one company to another, while continuing to do the exact same work for the OpenStack project itself. And for developers, I think it’s a great place to be in: if you haven’t already, you should definitely consider joining us.

 

Categories: Openstack

An analysis of the Technical Committee election

October 23, 2013 Leave a comment

When we changed the Technical Committee membership model to an all-directly-elected model a few months ago, we proposed we would enable detailed ballot reporting in order to be able to test alternative algorithms and run various analysis over the data set. As an official for this election, here is my analysis of the results, hoping it will help in the current discussion on a potential evolution of the Foundation individual members voting system.

Condorcet method

In the OpenStack technical elections, we always used the Condorcet method (with the Schulze completion method), as implemented by Cornell’s CIVS public voting system. In a Condorcet vote, you rank your choices in order of preference (it’s OK to rank multiple choices at the same level). To calculate the results, you simulate 1:1 contests between all candidates in the set. If someone wins all such contests, he is the Condorcet winner for the set. The completion method is used to determine the winner when there is no clear Condorcet winner. Most completion methods can result in ties, which then need to be broken in a fair way.

Condorcet spread

One thing we can analyze is the spread of the rankings for any given candidate:

TCelection

On that graph the bubbles on the left represent the number of high rankings for a given candidate (bubbles on the right represent low rankings). When multiple candidates are given the same rank, we average their ranking (that explains all those large bubbles in the middle of the spectrum). A loved-or-hated candidate would have large bubbles at each end of the spectrum, while a consensus candidate would not.

Looking at the graph we can see how Condorcet favors consensus candidates (Doug Hellmann, James E. Blair, John Griffith) over less-consensual ones (Chris Behrens, Sergey Lukjanov, Boris Pavlovic).

Proportional Condorcet ?

Condorcet indeed favors consensus candidates (and “natural” 1:1 election winners). It is not designed to represent factions in a proportional way, like STV is. There is an experimental proportional representation option in CIVS software though, and after some ballot conversion we can run the same ballots and see what it would give.

I set up a test election and the results are here. The winning 11 would have included Sergey Lukjanov instead of John Griffith, giving representation to a less-consensual candidate. That happens even  if a clear majority of voters prefers John to Sergey (John defeats Sergey in the 1:1 Condorcet comparison by 154-76).

It’s not better or worse, it’s just different… We’ll probably have a discussion at the Technical Committee to see whether we should enable this experimental variant, or if we prefer to test it over a few more elections.

Partisan voting ?

Another analysis we can run is to determine if there was any corporate-driven voting. We can look at the ballots and see how many of the ballots consistently placed all the candidates from a given company above any other candidate.

7.8% of ballots placed the 2 Mirantis candidates above any other. 5.2% placed the 2 IBM candidates above any other.  At the other end of the spectrum, 0.8% of ballots placed all 5 Red Hat candidates above any other, and 1.1% of the ballots placed all 4 Rackspace candidates above any other. We can conclude that partisan voting was limited, and that Condorcet’s preference for consensus candidates further limited its impact.

What about STV ?

STV is another ranked-choice election method, which favors proportional representation. Like the “proportional representation” CIVS option described above, it may result in natural Condorcet winners to lose against more factional candidates.

I would have loved to run the same ballots through STV and compare the results. Unfortunately STV requires strict ranking of candidates in an order of preference. I tried converting the ballots and randomly breaking similar rankings, but the end results vary extremely depending on that randomness, so we can’t really analyze the results in any useful way.

Run your own analysis !

That’s it for me, but you can run your own analysis by playing with the CSV ballot file yourself ! Download it here, and share the results of your analysis if you find anything interesting !

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Categories: Openstack

Getting to Havana

October 18, 2013 1 comment

Yesterday, as the final conclusion of the 6-month “Havana” development cycle, we released the latest version of OpenStack, the 2013.2 version. It’s now composed of 9 integrated components, which saw the completion of more than 400 feature blueprints and the fixing of more than 3000 reported bugs.

As always, it’s been an interesting week for me. Not as busy as you’d think, but lots of hours, day or night, spent frantically checking dashboards, collecting input from our fearful technical leads, waiting for a disaster to happen and pushing the right buttons at the right moment, finally aligning the stars and releasing everything on time. Yes, I use checklists to make sure I don’t overlook anything:

 

havana2

 

Even if I have plenty of free time between those key hours, I can’t concentrate on getting anything else done, or get something else started (like a blog post). This is why, one day after release, I can finally spend some time looking back on the last stage of the Havana development cycle and see how well we performed. Here is the graph showing the number of release-critical bugs logged against various components (those observing the common feature freeze) as we make progress towards the final release date:

 

havana

 

Personally I think we were a bit late, with RC1s globally landing around October 3 and RC2s still being published around October 15. I prefer when we can switch to “respin only for major regressions and upgrade issues” mode at least a week before final release, not two days before final release. Looking at the graph, we can see where we failed: it took us 11 days to get a grip on the RC bug count (either by fixing the right issues, or by stopping adding new ones, or by refining the list and dropping non-critical stuff). Part of this delay is due to stress recovery after a rather eventful feature freeze. Part of it is lack of prioritization and focus on the right bugs. The rest of the graph pretty much looks like the Grizzly one. We were just at least one week too late.

We’ll explore ways to improve on that during the Icehouse Design Summit in Hong-Kong. One solution might be to add a week between feature freeze and final release. Another solution would be to filter what gets targeted to the last milestone to reduce the amount of features that land late in the cycle, to reduce FeatureFreeze trauma. If you want to be part of the discussion, join us all in Hong-Kong in 18 days !

 

Categories: Openstack

An history of OpenStack open source project governance

June 20, 2013 Leave a comment

Over the last 3 years, the technical governance of the OpenStack open source project evolved a lot, and most recently last Tuesday. As an elected member of that governance body since April 2011, I witnessed that evolution from within and helped in drafting the various models over time. Now seems like a good time to look back in history, and clear a few misconceptions about the OpenStack project governance along the way.

The POC

The project was originally created by Rackspace in July 2010 and seeded with code from NASA (Nova) and Rackspace (Swift). At that point an initial project governance was set up. There was an Advisory Board (which was never really created), the OpenStack Architecture Board, and technical committees for each subproject, each lead by a Technical Lead. The OpenStack Architecture Board had 5 members appointed by Rackspace and 4 elected by the community, with 1-year to 3-year (!) terms. The technical leads for the subprojects were appointed by Rackspace.

By the end of the year 2010 the Architecture Board was renamed Project Oversight Committee (POC), but its structure didn’t change. While it left room for community input, the POC was rightfully seen as fully controlled by Rackspace, which was a blocker to deeper involvement for a lot of the big players in the industry.

It was a danger for the open source project as well, as the number of contributors external to Rackspace grew. As countless examples prove, when the leadership of an open source project is not seen as representative of its contributors, you face the risk of a revolt, a fork of the code and seeing your contributors leave for a more meritocratic and representative alternative.

The PPB

In March 2011, a significant change was introduced to address this perceived risk. Technical leads for the 3 projects (Nova, Swift, and Glance at that point) would from now on be directly elected by their contributors and called Project Technical Leads (PTLs). The POC was replaced by the Project Policy Board (PPB), which had 4 seats appointed by Rackspace, 3 seats for the above PTLs, and 5 seats directly-elected by all the contributors of the project. By spring 2012 we grew to 6 projects and therefore the PPB had 15 members.

This was definitely an improvement, but it was not perfect. Most importantly, the governance model itself was still owned by Rackspace, which could potentially change it and displace the PPB if it was ever unhappy with it. This concern was still preventing OpenStack from reaching the next adoption step. In October 2011, Rackspace therefore announced that they would set up an independent Foundation. By the summer of 2012 that move was completed and Rackspace had transfered the control over the governance of the OpenStack project to the OpenStack Foundation.

The TC

At that point the governance was split into two bodies. The first one is the Board of Directors for the Foundation itself, which is responsible for promoting OpenStack, protecting its trademark, and deciding where to best spend the Foundation’s sponsors money to empower future development of OpenStack.

The second body was the successor to the PPB, the entity that would govern the open source project itself. A critical piece in the transition was the need to preserve and improve the independence of the technical meritocracy. The bylaws of the Foundation therefore instituted the Technical Committee, a successor for the PPB that would be self-governed, and would no longer have appointed members (or any pay-to-play members). The Technical Committee would be completely elected by the active technical contributors: a seat for each elected PTL, plus 5 directly-elected seats.

TC 2.0

The TC started out in September 2012 as an 11-member committee, but with the addition of 3 new projects (and the creation of a special seat for Oslo), it grew to 15 members in April 2013, with the perspective to grow to 18 members in Fall 2013 if all projects applying for incubation recently get finally accepted. With the introduction of the “integrated” project concept (separate from the “core” project concept), we faced the addition of even more projects in the future and committee bloat would inevitably ensue. That created a potential for resistance to the addition of “small” projects or the splitting of existing projects (which make sense technically but should not be worth adding yet another TC seat).

Another issue was the ever-increasing representation of “vertical” functions (project-specific PTLs elected by each project contributors) vs. general people elected by all contributors. In the original PPB mix, there were 3 “vertical” seats for 5 general seats, which was a nice mix to get specific expertise but overall having a cross-project view. With the growth in the number of projects, in the current TC we had 10 “vertical” seats for 5 general seats. Time was ripe for a reboot.

Various models were considered and discussed, and while everyone agreed on the need to change, no model was unanimously seen as perfect. In the end, simplicity won and we picked a model with 13 directly-elected members, which will be put in place at the Fall 2013 elections.

Power to the active contributors

This new model is a direct, representative model, where if you recently authored a change for an OpenStack project, you get one vote, and a chance every 6 months to choose new people to represent you. This model is pretty flexible and should allow for further growth of the project.

Few open source projects use such a direct governance model. In Apache projects for example (often cited as a model of openness and meritocracy), the oversight committee equivalent to OpenStack’s TC would be the PMC. In most cases, PMC membership is self-sustaining: existing PMC members ultimately decide, through discussions and votes on the private PMC list, who the new PMC members should be. In contrast, in OpenStack the recently-active contributors end up being in direct control of who their leaders are, and can replace the Technical Committee members if they feel like they are not relevant or representing them anymore. Oh, and the TC doesn’t use a private list: all our meetings are public and our discussions are archived.

As far as open source projects governance models go, this is as open, meritocratic, transparent and direct as it gets.

Categories: Open source, Openstack

The need for releases

April 11, 2013 Leave a comment

The beginning of a new release cycle is as good as any moment to question why we actually go through the hassle of producing OpenStack releases. Twice per year, on a precise date we announce 6 months in advance, we bless and publish source code tarballs of the various integrated projects in OpenStack. Every week we have a meeting that tracks our progress toward this common goal. Why ?

Releases vs. Continuous deployment

The question is particularly valid if you take into account the type of software that we produce. We don’t really expect cloud infrastructure providers to religiously download our source code tarballs every 6 months and run from that. For the largest installations, running much closer to the master branch and continuously deploy the latest changes is a really sound strategy. We invested a lot of effort in our gating systems and QA automated testing to make sure the master branch is always runnable. We’ll discuss at the OpenStack Summit next week how to improve CD support in OpenStack. We backport bugfixes to the stable branches post-release. So why do we continue to single out a few commits and publish them as “the release” ?

The need for cycles

The value is not really in releases. It is in release cycles.

Producing OpenStack involves the work of a large number of people. While most of those people are paid to participate in OpenStack development, as far as the OpenStack project goes, we don’t manage them. We can’t ask them to work on a specific area, or to respect a given deadline, or to spend that extra hour to finalize something. The main trick we use to align everyone and make us all part of the same community is to have a cycle. We have regular milestones that we ask contributors to target their features to. We have a feature freeze to encourage people to switch their mindset to bugfixing. We have weekly meetings to track progress, communicate where we are and motivate us to go that extra mile. The common rhythm is what makes us all play in the same team. The “release” itself is just the natural conclusion of that common effort.

A reference point in time

Singling out a point in time has a number of other benefits. It’s easier to work on documentation if you group your features into a coherent set (we actually considered shortening our cycles in the past, and the main blocker was our capacity to produce good documentation often enough). It’s easier to communicate about OpenStack progress and new features if you do it periodically rather than continuously. It’s easier to have Design Summits every 6 months if you create a common brainstorm / implementation / integration cycle. The releases also serve as reference points for API deprecation rules, for stable release maintenance, for security backports.

If you’re purely focused on the software consumption part, it’s easy to underestimate the value of release cycles. They actually are one of the main reasons for the pace of development and success of OpenStack so far.

The path forward

We need release cycles… do we need release deliverables ? Do we actually need to bless and publish a set of source code tarballs ? My personal view on that is: if there is no additional cost in producing releases, why not continue to do them ? With the release tooling we have today, blessing and publishing a few tarballs is as simple as pushing a tag, running a script and sending an email. And I like how this formally concludes the development cycle to start the stable maintenance period.

But what about Continuous Deployment ? Well, the fact that we produce releases shouldn’t at all affect our ability to continuously deploy OpenStack. The master branch should always be in good shape, and we definitely should have the necessary features in place to fully support CD. We can have both. So we should have both.

Categories: Cloud, Open source, Openstack

Grizzly, the day after

April 5, 2013 2 comments

The OpenStack Grizzly release of yesterday officially closes the Grizzly development cycle. But while I try to celebrate and relax, I can’t help from feeling worried and depressed on the hours following the release, as we discover bugs that we could have (should have ?) caught before release. It’s a kind of postpartum depression for release managers; please consider this post as part of my therapy.

Good

We’d naturally like to release when the software is “ready”, “good”, or “bug-free”. Reality is, with software of the complexity of OpenStack, onto which we constantly add new features, there will always be bugs. So, rather than releasing when the software is bug-free, we “release” when waiting more would not really change the quality of the result. We release when it’s time.

In OpenStack, we invest a lot in automated testing, and each proposed commit goes through an extensive set of unit and integration tests. But with so many combinations of deployment options, there are still dark corners that will only be explored by users as they apply the new code to their specific use case. We encourage users to try new code before release, by publishing and making noise about milestones, release candidates… But there will always be a significant number of users who will not try new code until the point in time we call “release”. So there will always be significant bugs that are discovered (and fixed) after release day.

The best point in time

What we need to do is pick the right moment to “release”: when all known release-critical issues are fixed. When the benefits of waiting more are not worth the drawbacks of distracting developers from working on the next development cycle, or of abandoning the benefits of a predictable time-based common release.

That’s the role of the Release Candidates that we produce in the weeks before the release day. When we fixed all known release-critical bugs, we create an RC. If we find new ones before the release day, we fix them and regenerate a new release candidate. On release day, we consider the current release candidates as “final” and publish them.

The trick, then, is to pick the right length for this feature-frozen period leading to release, one that gives enough time for each of the projects in OpenStack to reach this the first release candidate (meaning, “all known release-critical bugs fixed”), and publish this RC1 to early testers. For Grizzly, it looked like this:

roadtorc

This graph shows the number of release-critical bugs in various projects over time. We can see that the length of the pre-release period is about right: waiting more would not have resulted in a lot more bugs to be fixed. We basically needed to release to get more users to test and report the next bugs.

The Grizzly is still alive

The other thing we need to have is a process to continue to fix bugs after the “release”. We document the most obvious regressions in the constantly-updated Release Notes. And we handle the Grizzly bugs using the stable release update process.

After release, we maintain a branch where important bugfixes are backported and from which we’ll publish point releases. This stable/grizzly branch is maintained by the OpenStack stable maintenance team. If you see a bugfix that should definitely be backported, you can tag the corresponding bug in Launchpad with the grizzly-backport-potential tag to bring it to the team’s attention. For more information on the stable branches, I invite you to read this wiki page.

Being pumped up again

The post-release depression usually lasts a few days, until I realize that not so many bugs were reported. The quality of the new release is actually always an order of magnitude better than the previous releases, due to 6-month worth of improvements in our amazing continuous integration system ! We actually did an incredible job, and it will only get better !

The final stage of recovery is when our fantastic community gets all together at the OpenStack Summit. 4 days to witness and celebrate our success. 4 days to recharge the motivation batteries, brainstorm and discuss what we’ll do over the next 6 months. We are living awesome times. See you there.

Categories: Open source, Openstack
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