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Case Study
API Enablement at Target (2015)
Target is the sixth largest retailer in the US and spends over $1 billion on
technology annually. Heather Mickman, a director of development for Target,
described the beginnings of their DevOps journey: “In the bad old days, it
used to take ten different teams to provision a server at Target, and when
things broke, we tended to stop making changes to prevent further issues,
which of course makes everything worse.”
The hardships associated with getting environments and performing deploy-
ments created significant difficulties for development teams, as did getting
access to data they needed. As Mickman described:
The problem was that much of our core data, such as infor-
mation on inventory, pricing, and stores, was locked up in
legacy systems and mainframes. We often had multiple
sources of truths of data, especially between e-commerce
and our physical stores, which were owned by different teams,
with different data structures and different priorities....The
result was that if a new development team wanted to build
something for our guests, it would take three to six months
to build the integrations to get the data they needed. Worse,
it would take another three to six months to do the manual
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92 • Part II
testing to make sure they didn’t break anything critical,
because of how many custom point-to-point integrations
we had in a very tightly coupled system. Having to manage
the interactions with the twenty to thirty different teams,
along with all their dependencies, required lots of project
managers, because of all the coordination and handoffs. It
meant that development was spending all their time waiting
in queues, instead of delivering results and getting stuff done.
This long lead time for retrieving and creating data in their systems of record
was jeopardizing important business goals, such as integrating the supply
chain operations of Target’s physical stores and their e-commerce site, which
now required getting inventory to stores and customer homes. This pushed
the Target supply chain well beyond what it was designed for, which was
merely to facilitate the movement of goods from vendors to distribution
centers and stores.
In an attempt to solve the data problem, in 2012 Mickman led the API
Enablement team to enable development teams to “deliver new capabilities
in days instead of months.”
They wanted any engineering team inside of
Target to be able to get and store the data they needed, such as information
on their products or their stores, including operating hours, location, whether
there was as Starbucks on-site, and so forth.
Time constraints played a large role in team selection. Mickman explained that:
Because our team also needed to deliver capabilities in days,
not months, I needed a team who could do the work, not
give it to contractors—we wanted people with kickass engi-
neering skills, not people who knew how to manage contracts.
And to make sure our work wasn’t sitting in queue, we needed
to own the entire stack, which meant that we took over the
Ops requirements as well....We brought in many new tools
to support continuous integration and continuous delivery.
And because we knew that if we succeeded, we would have
to scale with extremely high growth, we brought in new tools
such as the Cassandra database and Kafka message broker.
When we asked for permission, we were told no, but we did
it anyway, because we knew we needed it.
In the following two years, the API Enablement team enabled fifty-three
new business capabilities, including Ship to Store and Gift Registry, as well
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Chapter 7 • 93
as their integrations with Instacart and Pinterest. As Mickman described,
“Working with Pinterest suddenly became very easy, because we just provided
them our APIs.”
In 2014, the API Enablement team served over 1.5 billion API calls per month.
By 2015, this had grown to seventeen billion calls per month spanning ninety
different APIs. To support this capability, they routinely performed eighty
deployments per week.
These changes have created major business benefits for Target—digital sales
increased 42% during the 2014 holiday season and increased another 32%
in Q2. During the Black Friday weekend of 2015, over 280k in-store pickup
orders were created. By 2015, their goal is to enable 450 of their 1,800
stores to be able to fulfill e-commerce orders, up from one hundred.
“The API Enablement team shows what a team of passionate change agents
can do,” Mickman says. “And it help set us up for the next stage, which is to
expand DevOps across the entire technology organization.”
CONCLUSION
Through the Etsy and Target case studies, we can see how architecture and
organizational design can dramatically improve our outcomes. Done incor-
rectly, Conway’s Law will ensure that the organization creates poor outcomes,
preventing safety and agility. Done well, the organization enables developers
to safely and independently develop, test, and deploy value to the customer.
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How to Get Great
Outcomes by Integrating
Operations into the Daily
Work of Development
Our goal is to enable market-oriented outcomes where many small teams can
quickly and independently deliver value to the customer. This can be a chal-
lenge to achieve when Operations is centralized and functionally-oriented,
having to serve the needs of many different development teams with potentially
wildly different needs. The result can often be long lead times for needed Ops
work, constant reprioritization and escalation, and poor deployment
outcomes.
We can create more market-oriented outcomes by better integrating Ops
capabilities into Dev teams, making both more efficient and productive. In
this chapter, we’ll explore many ways to achieve this, both at the organizational
level and through daily rituals. By doing this, Ops can significantly improve
the productivity of Dev teams throughout the entire organization, as well as
enable better collaboration and organizational outcomes.
At Big Fish Games, which develops and supports hundreds of mobile and
thousands of PC games and had more than $266 million in revenue in 2013,
VP of IT Operations Paul Farrall was in charge of the centralized Operations
organization. He was responsible for supporting many different business
units that had a great deal of autonomy.
Each of these business units had dedicated development teams who often
chose wildly different technologies. When these groups wanted to deploy
new functionality, they would have to compete for a common pool of scarce
Ops resources. Furthermore, everyone was struggling with unreliable Test
and Integration environments, as well as extremely cumbersome release
processes.
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96 • Part II
Farrall thought the best way to solve this problem was by embedding Ops
expertise into Development teams. He observed, “When Dev teams had
problems with testing or deployment, they needed more than just technology
or environments. What they also needed was help and coaching. At first, we
embedded Ops engineers and architects into each of the Dev teams, but there
simply weren’t enough Ops engineers to cover that many teams. We were able
to help more teams with what we called an
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