We’re all very aware of how Google has used Borg, its internal container orchestration platform, to seemingly effortlessly scale its own infrastructure. And we also know that many cutting-edge organizations are using Kubernetes, the open source project directly descended from Borg, to run their own operations. But sometimes the examples of the webscale or cutting-edge organizations are less impactful than an expose of how an existing organization is using a product to modernize its operation.
So, given that context, it was interesting to hear from BlackRock, the world’s largest asset manager, about how they are applying Kubernetes to their own unique challenges. BlackRock is, of course, the world’s largest asset manager. The company operates a very controlled static deployment scheme, which has allowed for scalability over the years. But in their data science division, there was a need for more dynamic access to resources. Says Michael Francis, a Managing Director in BlackRock’s Product Group, which runs the company’s investment management platform:
We want to be able to give every investor access to data science, meaning Python notebooks, or even something much more advanced, like a MapReduce engine based on Spark. Managing complex Python installations on users’ desktops is really hard because everyone ends up with slightly different environments. We have existing environments that do these things, but we needed to make it real, expansive and scalable. Being able to spin that up on demand, tear it down, make that much more dynamic, became a critical thought process for us. It’s not so much that we had to solve our main core production problem, it’s how do we extend that? How do we evolve?
BlackRock had already run an earlier pilot using Docker. Drawing on the learnings from that pilot, Francis put together a cross-sectional team of 20 to build an investor research web app using Kubernetes with the goal of getting it into production within one quarter. As he tells it:
Our goal was: How do you give people tools rapidly without having to install them on their desktop?
The results were impressive – the team hit the goal within 100 days. Francis is pleased with the results and is planning on using Kubernetes for lots of other application workloads as time goes on. But whole Francis is bullish, he’s also pragmatic and admits that it will be 6-12 months before they’re ready to make a large scale decision, preferring instead to gain experience of running the system in production.
While readers from smaller companies will perhaps not be overly impressed with this 100-day goal, for a large enterprise like BlackRock, this is indeed impressive. For a company like BlackRock, even equipment procurement can take 100 days sometimes, let alone from inception to delivery. Karl Wieman, a Senior System Administrator believes that, for BlackRock, it was an aggressive schedule, but it moved the dial. In fact, the project achieved two goals: It solved a business problem (creating the needed web app) as well as provided real-world, in-production experience with Kubernetes. Says Francis:
It’s not so much that we had to solve our main core production problem, it’s how do we extend that? How do we evolve? The ultimate success of this project, beyond delivering the app, lies in the fact that we’ve managed to integrate a radically new thought process into a controlled infrastructure that we didn’t want to change.
And BlackRock, despite not yet being ready to make the shift en masse, seems pretty bullish about Kubernetes. The company had already experimented with other cloud-native environments, but the team liked that Kubernetes was open source, and felt the winds were blowing in the direction of Kubernetes long term. Says Uri Morris, Vice President of Production Operations:
Typically we make technology choices that we believe are going to be here in 5-10 years’ time, in some form. And right now, in this space, Kubernetes feels like the one that’s going to be there. When you see that the non-Google committers to Kubernetes overtook the Google committers, that’s an indicator of the momentum.
Beyond the success of the particular application this team created, developing the muscle memory around using Kubernetes was the key goal – the BlackRock team now have in-production experience with Kubernetes that they can continue to build on—and a complete framework for rolling out new applications.
MyPOV
Science experiments are fun and all, but it’s when these experiments really hit the road within large, traditional organizations that the magic happens. The BlackRock story is one such example and one which you can be sure the CNCF will be talking about at length.
