What Makes a Good DevOps Tool?

We had an interesting discussion the other day about what made a “good” DevOps tool.  The assertion is that a good citizen or good “link” in the toolchain has the same basic attributes regardless of the part of the system for which it is responsible. As it turns out, at least with current best practices, this is a reasonably true assertion.  We came up with three basic attributes that the tool had to fit or it would tend to fall out of the toolchain relatively quickly. We got academic and threw ‘popular’ out as a criteria – though supportability and skills availability has to be a factor at some point in the real world. Even so, most popular tools are at least reasonably good in our three categories.

Here is how we ended up breaking it down:

  1. The tool itself must be useful for the domain experts whose area it affects.  Whether it be sysadmins worried about configuring OS images automatically, DBAs, network guys, testers, developers or any of the other potential participants, if the tool does not work for them, they will not adopt it.  In practice, specialists will put up with a certain amount of friction if it helps other parts of the team, but once that line is crossed, they will do what they need to do.  Even among development teams, where automation is common for CI processes, I STILL see shops where they have a source control system that they use day-to-day and then promote from that into the source control system of record.  THe latter was only still in the toolchain due to a bureaucratic audit requirement.
  2. The artifacts the tool produces must be easily versioned.  Most often, this takes the form of some form of text-based file that can be easily managed using standard source control practices. That enables them to be quickly referenced and changes among versions tracked over time. Closed systems that have binary version tracking buried somewhere internally are flat-out harder to manage and too often have layers of difficulty associated with comparing versions and other common tasks. Not that it would have to be a text-based artifact per se, but we had a really hard time coming up with tools that produced easily versioned artifacts that did not just use good old text.
  3. The tool itself must be easy to automate externally.  Whether through a simple API or command line, the tool must be easily inserted into the toolchain or even moved around within the toolchain with a minimum of effort. This allows quickest time to value, of course, but it also means that the overall flow can be more easily optimized or applied in new environments with a minimum of fuss.

We got pretty meta, but these three aspects showed up for a wide variety of tools that we knew and loved. The best build tools, the best sysadmin tools, even stuff for databases had these aspects. Sure, this is proof positive that the idea of ‘infrastructure as code’ is still very valid. The above apply nicely to the most basic of modern IDEs producing source code. But the exercise became interesting when we looked at older versus newer tools – particularly the frameworks – and how they approached the problem. Interestingly we felt that some older, but popular, tools did not necessarily pass the test.  For example, Hudson/Jenkins are weak on #2 and #3 above.  Given their position in the toolchain, it was not clear if it mattered as much or if there was a better alternative, but it was an interesting perspective on what we all regarded as among the best in their space.

This is still an early thought, but I thought I would share the thought to see what discussion it would stimulate. How we look at tools and toolchains is evolving and maturing. A tool that is well loved by a particular discipline but is a poor toolchain citizen may not be the right answer for the overall organization. A close second that is a better overall fit might be a better answer. But, that goes against the common practice of letting the practitioners use what they feel best for their task. What do you do? Who owns that organizational strategic call? We are all going to have to figure that one out as we progress.

DevOps is about Building Fords, not Ferraris

There is an interesting obsession with having the ‘ultimate’ of whatever you’re talking about. This applies to most things in our society: jobs, houses, televisions, cars. You name it, there is an ‘ultimate’ version that everyone aspires to have. There is a lot of good to this behavior, to be sure. I believe strongly that everyone should be trying to get better all the time. Though I would point out that it is healthier to regard the ultimate [whatever] as a consequence or benefit of getting better rather than an end unto itself.

But it’s usually bad to want the ‘ultimate’ in your software delivery process. Goldplating has always been an enemy in software projects and there is evidence of it in how a lot of organizations have traditionally delivered software. It usually shows up in the culture, where high-intervention processes lead to hero cults and aspirations to be the ultimate ‘hero’ who gets releases out the door. Old-school, old-world hand craftsmanship is the order of the day. DevOps is the exact opposite of this approach. It focuses on a highly repeatable, scalable, and mass-produced approach to releasing software. And frequently.

Which brings me back to the contrast between a Ferrari and a Ford. A Ferrari is pretty much the ultimate sports car and ultimate sports car brand. There really is very little not to like. But the cars are exotics still built with expensive materials using manual, old world techniques. To be fair, Ferrari has a super-modern robotic process for a lot of their precision work, but they add a lot of customization and hand-finishing. And they ship a very few thousand releases (cars) each year. Sustaining such a car in the real world involves specially trained mechanics named Giuseppe, long waits for parts from Italy, and even shipping the car across the state if you don’t live close to a qualified shop. No biggie – if you can afford the car, you can afford the maintenance. But, let’s face it, they are a ‘money is no object’ accessory.

Ford has shipped a variety of performance models over the years based on the Mustang platform. In fact, there have been years where Ford has shipped more performance Mustangs in a week than Ferrari would ship cars in that YEAR. And there is a magic there for a DevOps geek. Plain ol’ Ford Motor Company has started selling a 200mph Mustang this year for about $60K. There’s nothing too exotic about it. You can go to your local Ford dealer and buy it. It can be purchased at one dealer and serviced at any other dealer anywhere in the country. Parts? No problem – most of them are in local warehouses stationed strategically so that no dealer would have to keep a customer waiting too long for common items. A lot of stuff can be had from your local AutoZone because, well, it’s “just” a Mustang.

The lesson, though, is that Ford has an economy of scale by virtue of the volume of Mustangs it produces. No, a Mustang is not as nice or as custom as a Ferrari. It is as common and mass-produced as anything. But a 200mph car that anyone can buy for noticeably less than a house, get parts easily, and have serviced at thousands of locations is an amazing and magical thing. It teaches a solid lesson about scalability and sustainability that should be inspirational for DevOps teams.

And maybe, just maybe, if your company does a good enough job at sustainably delivering your software, you might be able to afford that Ferrari someday…

PS – for Chevy zealots. I realize the Corvette cleared 200 on a “volume” platform first. But the 200mph Plastic Fantastic looks more exotic relative to the Mustang – which has a plain “sporty commuter” or even rental fleet version with a V6. And the common example of the economies of scale mean that the 200mph Shelby Mustang is still a bargain relative to the 200mph capable ‘vette, which is the point of this post.

DevOps DARPA Style

I think spending a lot of time on DevOps may skew my interpretation of different trends and articles.  To me it seems that everyone is trying to reinvent and “lean out” there design to engineering flow to be faster, more iterative, and generally more responsive to conditions in our rapidly changing world.  Faster is, of course, relative depending on what you are talking about.  I recently saw this article on the MIT Technology Review about DARPA (always a source of cool advanced engineering ideas) undertaking a rapid approach for getting a new tank designed and built.

Article here:  http://www.technologyreview.com/news/509311/darpa-wants-to-remake-manufacturing/

The article thematically addresses concepts like ensuring a common understanding of the design among contributing engineers and moving manufacturing knowledge closer to the design stage so it is actually a part of the design thinking.  My DevOps skew made the immediate association of how similar this was to the collaboration implicit with Agile and DevOps.  Everyone needs to know the architecture and Ops needs to be involved directly with development while development is underway to ensure rapid Continuous Delivery cycles.  It’s a good perspective on how applicable these concepts are on a much broader scale and in varied industries.

I figure that if these guys can do it with metal in the context of a tank, it has to be possible with whatever software or virtualization problem I”m dealing with.  Though it does make me want better toys for our office.  I have to believe that DARPA has cooler Nerf guns…

Slides from Agile Austin Talk 2-12-2013

This post slides from my talk at Agile Austin on February 12, 2013.

I want to thank the group for the opportunity and the audience for the great interaction!

Link to slides:  DevOps Beyond the Basics – FINAL

A System for Changing Systems – Part 9

The last capability area in the framework is that of Monitoring. I saved this for last because it is the one that tends to be the most difficult to get right. Of course, commensurate with the difficulty is the benefit gained when it is working properly. A lot of the difficulty and benefit with Monitoring comes from the fact that knowing what to look at, when to look at it and what NOT to look at are only the first steps. It also becomes important to know what distributed tidbits of information to bring together if you actually want a complete picture of your application environment.

Monitoring

Monitoring Capability Area

This post could go for pages – and Monitoring is likely going to be a consuming topic as this series progresses, but for the sake of introduction, lets look at the Monitoring capability area. The sub-capabilities for this area encompass the traditional basics of monitoring Events and Trends among them. The challenge for these two is in figuring out which Events to monitor and sometimes how to get the Event data in the first place. The Trends must then be put into a Report format that resonates with management. It is important to invest in this area in order to build trust with management that the team has control as it tries to increase the frequency of changes – without management’s buy-in, they won’t fund the effort. Finally, the Correlation sub-capability area is related to learning about the application system’s behavior and how changes to some part of the system impacts the other parts. This is an observational knowledge base that must be deliberately built by the team over time so that they can put the Events, Trends, and Reports into the most useful contexts and use the information to better understand risks and priorities when making changes to the system.

A System for Changing Systems – Part 8

The fourth capability area is that of Provisioning. It covers the group of activities for creating all or part of an environment in which an application system can run. This is a key capability for ensuring that application systems have the capacity they need to maintain performance and availability. It is also crucial for ensuring that development and test activities have the capacity they need to maintain THEIR performance. The variance with test teams is that a strong Provisioning capability also ensures that development and test teams can have clean dev/test environments that are very representative of prorduction environments and can very quickly refresh those dev/test environments as needed. The sub-capabilities here deal with managing the consistency of envionment configurations, and then quickly building environments to a known state.

Provisioning Capability Area

Provisioning Capability Area

The fifth capability area is closely related to Provisioning. It is the notion of a System Registry capability. This set of capabilities deals with delivering the assumed infrastructure functions (e.g. DNS, e-mail relays, IP ranges, LDAP, etc.) that surround the environments. These capabilities must be managed in such a way that one or more changes to an application system can be added to a new or existing environment with out significant effort or disruption. In many ways this capability area is the fabric in which the others operate. It can also be tricky to get right because this capability area often spans multiple application systems.

System Registry Capability Area

System Registry Capability Area

A System for Changing Systems – Part 7 – Deployment Capabilities

The third capability area is that of Deployment. Deployment deals with the act of actually putting the changes into a given target environment. It is not prescritive of how this happens. Many shops mechanically deal with deployment via their provisioning system. That is obviously a good thing and an efficiency gain by removing a discrete system for performing deployment activities. It is really a best practice of the most mature organizations. However, this taxonomy model is about identifying the capabilities needed to consistently apply changes to a whole application system. And, lets face it, best practices tend to be transient; as new, even better, best practices emerge.

Deployment Capability Area

Deployment Capability Area

Additionally, there are a number of reasons the capability is included in this taxonomy. First of all, the framework is about capabilities rather than technologies or implementations. It is important to be deliberate about how changes are deployed to all environments and simply because some group of those changes are handled by a provisioning tool does not remove the fact that not all are covered nor does it remove the fact that some deliberate work is expended in fitting the changes into the provisioning tool’s structure. Most provisioning tools, for example are set up to handle standard package mechanisms such as RPM. The deployment activity in that scenario is more one of packaging the custom changes. But the provisioning answer is not necessarily a solution for all four core areas of an applpication system, so there needs to be a capability that deals generically with all of them. Finally, many, if not most, shops have some number of systems where there are legacy technical requirements that require deployment to happen separately.

All of that being true, the term “Deployment” is probably confusing given its history and popular use. It will likely be replaced in the third revision of this taxonomy with something more generic, such as “Change Delivery”.

The sub-category of Asset Repository refers to the fact that there needs to be an ability to maintain a collection of changes that can be applied singly or in bulk to a given application system. In the third revision of the taxonomy, it is likely to be joined by a Packaging sub-capability.  Comments and thoughts are welcome as this taxonomy is evolving and maturing along with the DevOps movement.