“Shipping” code may start with the completion of development but it doesn’t end until after the operational delivery process ends. Just like any fulfillment process, shipping is actually just the kick off of an often arduous journey that ultimately delivers the app to the end user.
Back in the old days (when they still let me write code) one of our favorite phrases was “ship it” to indicate completeness of a task. That’s because the ultimate goal was, of course, to “ship” the code off to the users so they could start doing whatever it was they were going to do with it*.
But the reality was, of course, even when we were really ready to “ship it” to users that it didn’t actually get to users for varying amounts of time. Like shipping anything today, it depends on the shipment method. In terms of today’s enterprise IT, “shipping method” is really a metaphor for the operational approach to deploying all the infrastructure – the “middle boxes” – with the services required to actually deliver a secure, fast and available application to its ultimate users.
We know from various studies that this takes time. From days to weeks to even months. And we know we don’t like that and we want to improve it. Which is where DevOps comes in, or NetOps or SDN or SDDC or SDO or whatever you want to call it.
Speeding up the deployment process is certainly one of the goals of operationalizing the network, but without a baseline how do we know if we’ve gotten faster in the first place?
That’s a piece of the DevOps puzzle we’ve been ignoring – the need to measure the deployment process. You might notice that “measure” is bolded and in red, that a visual clue meant to reinforce the importance of the measurement aspect of DevOps. If you aren’t measuring how long it takes to deliver that app from dev to its destination – production use by an end-user – then you have no idea which pieces of the process are holding you back. You can’t effectively determine where automation might be applied to improve the time it takes to get to market. You don’t know exactly where the obstacles are that need to be addressed in the first place.
While we can make some assumptions based on long experience and research and point to handoffs across the IT silos, the reality is that there probably isn’t just one handoff between ops and the network and there may be multiple intra-IT group handoffs. For example, the network ops that handles provisioning network services might not be the same team that handles load balancing and performance services. But they’re both within the “network” silo. There may be multiple handoffs back and forth as various services also need networking services on top of the ones required by the app itself.
Without some kind of measurement of how long each of the various steps is taking it’s impossible to determine exactly where the bottlenecks in the app deployment process are in your organization. I can not only determine where that Minecraft Lego set I ordered for my son’s birthday is right now, I can see how long it’s taken to get from each point in the process. I know it goes from point A to point B in X days, and from point B to point C in Y days, and I know if there’s a winter storm that it’s going to cause a slowdown in that second step (which is called a movement in the logistics vernacular, in case you were wondering. I knew you were, you’re welcome!)
Measure Twice. Automate Once.
The hidden value in setting out to measure the deployment process is in pulling together an understanding of the process itself. It’s in finding redundancies and discovering sub-processes that are running in serial but could be running in parallel to improve them. It’s not necessarily about automating the whole thing up front, it’s about understanding what the process is and making it more efficient – whether through elimination, reorganization or automation (or all three).
You don’t simply want to be automating things willy nilly without any idea whether it’s going to do any good. As my dad taught me about working with wood, you measure twice and cut once. With DevOps you want to measure twice (at least) and automate once. Otherwise you may be wasting cycles on one-off tasks or tasks so specific to one application that automation has no real value because it’s not the same across applications.
The key is to start with defining what you’re going to measure, do the measurement and then analyze it to determine what you need to improve.
Because automating just for automation’s sake isn’t any more fruitful in the end than adopting technology for technology’s sake.
* I say “whatever” because over the course of my career I’ve worked on tax software, GIS software, communications and transportation and logistics systems. There’s a lot of variance there in what end users might be doing with “the app”.
A successful DevOps depends on marshalling people for this to happen, which usually involves convincing employees and entire teams to change how they work. And doing that hinges exclusively on the adoption of the requisite culture. For a large and established organization, this might mean not only completely changing direction ... Read More