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Development as Ops Training

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It’s become failrly well understood that “Dev” and “Ops” are no longer separate skill sets and are combined into a role called “DevOps”. This role has become one of the hottest and hardest to fill.

At Yieldbot we’ve taken a pretty hardcore approach to putting together Dev and Ops into DevOps that serves us well and should be a great repeatable pattern.

Chef + AWS Consolidated Billing

The underlying philosophy we have is that the development environment should match as closely as possible the production environment. When you’re building an analytics and ad serving product with a worldwide distributed footprint that can be a challenge.

Our first building block is the use of Chef (and on top of that ClusterChef, which is now Ironfan). Using these tools we’ve fully defined each role of the servers in a given region (by defining as a cluster), and all of the services that they run. We coordinate deploys through our Chef server with knife commands, and Chef controls everything from the OS packages that get installed, to the configuration of application settings, to the configuration of DNS names, etc.

The second building block is that every developer at Yieldbot gets their own AWS account as a sandbox. We use the AWS “Consolidated Billing” feature to bring the billing all under our production account. This lets us see a breakdown of everybody’s charges and means we get one single bill to pay.

The last detail is that every developer uses a unique suffix that is used to make resource references unique when global uniqueness is necessary. This is mostly used for resolving S3 bucket names. For any S3 bucket we have in production such as “foo.bar”, the developer will have an equivalent bucket named “foo.bar.<developer>”.

Doing Two Things at Once

With all of that as the status quo, developers are almost always doing two things: developing/testing (the Dev), and learning/practicing how the platform is managed in production (the Ops).

Everyone has their own Chef server, which is interacted with the same way that the production Chef server is. As they deploy the code they are working on into their own working environment, they’re learning/doing exactly what they would do in production.

All of this was put in place over the last year while the developement team was static, during which time we switched from Puppet to Chef.

But the power of this approach really hit home recently as we’ve started to add more people to the team.  The first thing a new hire does is go through our process of getting their development environment set up. There’s still bumps along the way, and they get problems and take part in ironing them out. The great thing about this approach though is that each bump is a lesson about how the production environment works and a lesson in problem solving in that environment.

The Differences

Having said all that, there are a couple differences that we’ve put in place between consciously development and production, with the driving force being cost.

The instances are generally sized smaller, since the scale needed for production is much greater.  Amazon’s recent addition for support of 64-bit on the m1.small was a great help.

We use several databases (a mix of MongoDB, Redis, and an internally developed DB tech) that are distributed on different machines in production that we collapse together onto a single instance with a special role called “devdb”.

More

We’ll have to have some future blog posts about how we import subsets of production data into development for testing, and the like.

We also use Chef with ClusterChef/Ironfan for managing the lifecycle of our dynamic Hadoop clusters. Yet another good topic for a post all its own.

Have experience with a similar approach or ideas about how to make it even better? We want to hear about it.

 

 

Realtime Kills Everything

Our first ad campaigns are live and the results are exciting. The campaign ran on a premium publisher in the women’s lifestyle vertical and beat the publisher’s control group on Click- Through-Rate (CTR) by 77% on the 728 x 90 unit and 194% on the 300 x 250. There were over 1M impressions in the campaign served on this domain over a 2-week period. Yieldbot is now serving the entire campaign.  

Most exciting to us are some of the individual results:

  • The best performing keyword has a CTR of 1.56%. 
  • The best creative unit (a 300 x 250) is getting 1.01%

We are running IAB standard banner units. This is not text. This is not rich media.

According to MediaMind the industry average CTR for the campaign vertical is 0.07%

The most matched keyword intent has a CTR of .43%. It also has a CPC of $5. 

That math works out to an eCPM of $21.44. That’s pretty exciting stuff. Even more so when you factor in that this campaign is running in what was unsold inventory.

When I shared the results with one of our Board Members he asked me, what at the time I thought was a simple question. “Why are the results so good?” But then, I actually had to think hard about the answer. I had to boil down a year of beta testing and then another year of building a scalable platform into what deserved to be a simple answer.

Realtime.

Realtime was my one word answer. Never before was every page view of intent for this publisher's visitors captured in realtime - let alone used to make a call to an ad server at that very moment.

Realtime is different. Realtime kills everything before it. As such, Yieldbot is not building ad technology for the web. We are building web technology for ads. Since nothing is more important for advertising success than timing it makes sense that nothing is more valuable for results than realtime.

Realtime was a big buzzword for a while but the hype has died down. That’s good. In the Hype Cycle we’re now somewhere moving from the “Trough of Disillusionment” to the “Slope of Enlightenment.” It is however this ability of the web to react in realtime that makes the future of the medium so exciting. 

Twitter of course is the best representative example. Twitter changed everything about media that came before it. Used to be that breaking the story was the big deal Now, even online news seemed stodgy compared to people giving realtime updates that planes have landed on rivers, people being killed and opining on a live show right along with it. 

As technology continues to get better at processing the trillions of inputs from millions of people going about their daily lives - doing everything from riding their car to work, buying a pack of chips, surfing the web – the web will respond in realtime. Because of that it will be relevant. The idea of an ad campaign will seem like owning a 32 volumes set of Encyclopedia Britannica. Everything becomes response because the technology is responsive. Calculations need inputs. The web will be measuring just about everything you do and know the moment you are doing it. Nothing will be sold. Everything will be bought.

It’s that realtime pull that creates these new valuations of the media. That new value of the media is what we have been working to create at Yieldbot. That is why these results are so exciting. Best of all, we’re just getting started. We’ve got a bunch of new campaigns about to get underway and we’re only going to get smarter and more relevant. We’ll continue to keep you posted on how it’s going and if you're running Yieldbot you'll know yourself. In realtime.