So I’m still not entirely sold on the urgency or importance of “chatops.”
I’m a huge fan of Google Assistant neé Now. I wish that I could replace Siri with it daily. It can answer nearly any question you throw at it, and it is smart enough to do contextual things that resemble conversations. For fun, I just asked Siri to navigate me to my favorite winery from Lewisville, TX to Grapevine, TX, Messina Hof while away. Here’s what it came back with:
Not very useful. What’s a Messina?
Google Assistant, on the other hand, knows what’s up…kind of:
It didn’t get me to the Grapevine location my fiancée and I always go to, but it (a) knew I was talking about Messina Hof, and (b) navigated me to their biggest vineyard in Bryan, TX (a.k.a Aggieland, opinions notwithstanding).
Here’s the thing, though: in almost every case, I will probably open Google Maps and search for the location there. I’m sure that, in the near future, Assistant will be knowledgable enough to know the exact location I want and whether I should stop for gas and a coffee on the way there (Google’s awesome new phone will probably help accelerate that). In the present, however, it’s a lot faster to do all of that from the app.
Which kind of explains my issue with chatops.
PagerDuty (awesome on-call management app, highly recommend) explains that, holistically, chatops:
…is all about conversation-driven development. By bringing your tools into your conversations and using a chat bot modified to work with key plugins and scripts, teams can automate tasks and collaborate, working better, cheaper and faster.
Since this is DevOps and that definition wouldn’t be complete without referring to tooling of some sort, remember this?
Think that, but with your infrastructure, more Slack, more modern Web and fewer early 2000s nostalgia:
The overall goal of chatops is to use communication mediums that we take advantage of on a daily basis to manage workflows and infrastructure more seamlessly. (To me, email automation would not only squarely fit in with this design pedagogy, but, as discussed later, would also probably be the most compatible and far-reaching solution for people.)
I’m not saying ChatOps isn’t awesome.
There are several frameworks out there that enable companies and teams to start playing around. Hubot, by Github, is the most well-known one. It works with just about every messaging platform out there, including Lync if you have a XMPP gateway set up. Slack integrations and webhooks are also very popular for companies using that product. When implemented correctly, chatops can be quite powerful.
Being able to say phrases like /deploybot deploy master of <project> to preprod or /beachbot create a sandbox environment for myawesometool from carlosnunez’s fork on Slack or Jabber and action on them would be incredibly neat, not to mention incredibly fast. This can be immensely valuable in several high-touch situations such as troubleshooting unexpected issues with infrastructure or automating product releases from a common tool.
More mature implementations can go much, much deeper than that.
I listened to an extremely interesting episode of Planet Money recently that explained an interesting period of growth for Subaru in the late 1990s to early 2000s. Subaru was struggling to compete with booming Japanese automakers at the time. They were producing cheaper cars faster and were successful in aggressively targetting the mid-market that Subaru classically did well in. Growth eventually went negative, and morales plummeted with it.
In the late 1990s, they made a discovery while trying to find a modicum of success with what they currently had. They discovered that out of their entire lineup of products, only one was selling consistently: the Impreza. They sought to find out why.
What they found was surprising. They saw that this car, and only this car, had a strong positive correlation with female buyers, specifically females that lived together. So they, with the help of Mulryan/Nash, their ad agency, tried something rash: they aimed to exclusively target homosexual couples in almost all of their ad campaigns.
Their sales soared. In fact, they were the only auto manufacturer to generate revenue during the 2008 Global Financial Crisis.
(Check out the full story here if you’re interested in learning more!)
Wouldn’t it have been awesome if they had bots that scoured sales demographics data from their network of dealerships and turn the identified trends covered within into emails or chats that marketing or sales managers can parse and make these same decisions on? How much faster do you think they would have been able to identify this and action on it? How many other trends could they have uncovered and made potential sales on?
That’s what I think when I hear about ChatOps. But let’s get back to reality.
I’m saying that it’s just not that crucial.
There are a lot of things that have to be done “right” before chatops can work. Monitoring and alerting have to be on point, especially for implementing things like automated alert or alarm bots. Creating new development environments have to be automated or at least have a consistent process from which automation can occur. Configuration management has to exist and has to be consistent for deployment bots to work. The list goes on.
Here in lies the rub: for engineers, accomplishing these things from a command-line tool is just as simple, and developers and engineers tend to spend just as much time with their tools as their IM client. Furthermore, implementing new systems introduces complexity, so introducing chatops to an organization when their tooling needs improvement will usually lead to my Messina-that-isn’t-Messina Hof situation from before where the quality of both toolsets ultimately suffers. So if the goal of implementing chatops is to make engineering’s life easier (or to make it easier for non-technical people to gain more understandable views into their tech), there might be easier and more important wins to be had first.
It’s not the end-all-be-all…yet.
Financial companies, tech-friendly law firms and news organizations use chatops to help model the state of markets, find trends in big law to identify new opportunities and uncover breaking news to broadcast around the world. The intrinsic value of ChatOps is definitely apparent.
That said, the foundation of the house comes first. Infrastructure, process and culture have to be solid and at least somewhat automated before chatops can make sense.
I’m a DevOps consultant for ThoughtWorks, a software company striving for engineering excellence and a better world for our next generation of thinkers and leaders. I love everything DevOps, Windows, and Powershell, along with a bit of burgers, beer and plenty of travel. I’m on twitter @easiestnameever and LinkedIn at @carlosindfw.