You are viewing content from a past/completed QCon

Presentation: Building a Reliable Cloud Based Bank in Java

Track: Enterprise Languages

Location: Bayview AB

Duration: 2:55pm - 3:45pm

Day of week: Wednesday

Level: Intermediate

Persona: Architect, Backend Developer, Developer, JVM

Share this on:

This presentation is now available to view on

Watch video with transcript

What You’ll Learn

  • Learn about building a modern, cloud-based bank leveraging Java.
  • Understand why Starling chose Java for their back-end system
  • Learn some of the strategies Starling deployed on their journey to CI/CD and the cloud.


Consumer banking is a risk adverse industry when it comes to new technology. So how do you build a bank in the cloud with a rapid release cycle while still maintaining the reliability that consumers need?

This talk will be about the experience of Starling Bank, a mobile-only, cloud-based bank that launched in the UK in 2017. We will look at the system architecture of the bank, the design principles that give us the ability to release quickly and reliably, and why we decided to build the back end using Java.


When you selected Java to build a modern, cloud-based architecture for Starling, is it correct to say that you went for the guarantee of Java's longevity rather than for the rapid iteration cycle you might get from a smaller, more opinionated language?


Yes, absolutely. Our aim and focus are much more long-term than many startups, and because of that, we are prioritizing the aspect of reliability. This goes to the heart of my talk. We want to guarantee stability because we will be around in years to come.


Why Java in particular?


There were two key reasons that we chose Java.

Java is well-known and well-maintained. We're seeing a lot of problems currently in government and banking IT, where programs were written ages ago, back in the 70s and 80s, in languages that no one uses or maintains anymore. The people who work with those languages are retiring or dying off, and it's getting more and more difficult for these institutions to maintain their systems. When it comes to banking, we've got to think not only about where we're going to be in a year's time or five years' time, we've got to work out where the bank is going to be in decades' time. We’re thinking over these time scales because banking tends to move more slowly than other fields. So you need reliability to be there; you need to make sure that the bank is going to be there in the far future, which is what customers and regulators require. Customers want a guarantee that their bank will be there in five, 10, 15 years, and so on. So we need to know that we're going to have a pool of developers to maintain and improve the system in 'X' years' time. And Java looks like a good bet for that because it's been around for 20 years, so we have more confidence that it will be around in 20 years more than some other languages.

The other reason we use Java is that Java is very noisy when it comes to exception handling. You can easily generate exceptions and generate noise. We quite like that because it helps us monitor what's going on and helps us quickly identify where there's a problem so we can go in and fix it. That speaks again to reliability as the goal.


What's the main message of your talk? What are you driving to help people learn about Starling?


The main message of the talk is that you can build a system that is as reliable as banking requires which at the same time allows you to regularly push out new features to customers and deliver what they need.

The key takeaway in SF will be different from what it is in London. In London, you end up talking to financial institutions that really care about reliability. They want to make sure they don't destroy anything and so they're afraid to go forward to deploying many times a day. The message then is that you can deploy once a day while at the same time maintaining that reliability.

Tech companies in SF are more used to be able to deploy hundreds and thousands of times a day to production, you're used to this continual deployment pipeline. But what if you absolutely had to guarantee that everything worked? What if you absolutely had to guarantee that if a customer instructed a payment, it would definitely only go out once—not twice and not zero times? We have this additional challenge, but we still manage to meet it. We still manage to deploy reasonably consistently while at the same time having this increased reliability burden that you need in banking. So emphasizing guaranteed reliability will be more the message of the talk in SF.

Speaker: Jason Maude

Lead Engineer @StarlingBank

Jason Maude is a coder, coach, debater, and public speaker. He has over a decade of experience working in the financial sector, primarily in creating and delivering software. He is passionate about creating teams and explaining complex technical concepts to those who are convinced that they won't be able to understand them. He currently works at Starling Bank as one of their lead engineers and host of the Starling podcast.

Find Jason Maude at


  • Practices of DevOps & Lean Thinking

    Practical approaches using DevOps and a lean approach to delivering software.

  • Operationalizing Microservices: Design, Deliver, Operate

    What's the last mile for deploying your service? Learn techniques from the world's most innovative shops on managing and operating Microservices at scale.

  • Bare Knuckle Performance

    Killing latency and getting the most out of your hardware

  • Architectures You've Always Wondered About

    Next-gen architectures from the most admired companies in software, such as Netflix, Google, Facebook, Twitter, & more

  • Machine Learning for Developers

    AI/ML is more approachable than ever. Discover how deep learning and ML is being used in practice. Topics include: TensorFlow, TPUs, Keras, PyTorch & more. No PhD required.

  • Production Readiness: Building Resilient Systems

    Making systems resilient involves people and tech. Learn about strategies being used from chaos testing to distributed systems clustering.

  • Surviving Uncertainty: Regulation, Risk, and Compliance

    With so much uncertainty, how do you bulkhead your organization and technology choices? Learn strategies for dealing with uncertainty.

  • Languages of Infra

    This track explores languages being used to code the infrastructure. Expect practices on toolkits and languages like Cloudformation, Terraform, Python, Go, Rust, Erlang.

  • Building & Scaling High-Performing Teams

    Building, maintaining, and growing a team balanced for skills and aptitudes. Constraint theory, systems thinking, lean, hiring/firing and performance improvement

  • Evolving the JVM

    The JVM continues to evolve. We’ll look at how languages like Kotlin, Graal, Clojure, and Java are evolving the JDK. Expect polyglot, multi-VM, performance, and more in this track.

  • Trust, Safety & Security

    Privacy, confidentiality, safety and security: learning from the frontlines.

  • JavaScript & Transpiler/WebAssembly Track

    JavaScript is the language of the web. Latest practices for JavaScript development in and how transpilers are affecting the way we work. We’ll also look at the work being done with WebAssembly.

  • Modern Operating Systems

    Applied, practical & real-world deep-dive into industry adoption of OS, containers and virtualization, including Linux on.

  • Software Supply Chain

    Securing the container image supply chain (containers + orchestration + security + DevOps).

  • Modern CS in the Real World

    Thoughts pushing software forward, including consensus, CRDT's, formal methods & probabilistic programming.

  • Tech Ethics: The Intersection of Human Welfare & STEM

    What does it mean to be ethical in software? Hear how the discussion is evolving and what is being said in ethics.

  • Optimizing Yourself: Human Skills for Individuals

    Better teams start with a better self. Learn practical skills for IC.

  • Modern Data Architectures

    Today’s systems move huge volumes of data. Hear how places like LinkedIn, Facebook, Uber and more built their systems and learn from their mistakes.