Implementing Clean Architecture

Programming Stage — 45 minutes Clean Architecture Programming

Has implementing Clean Architecture become more of an ideal than a reality in your projects?
Despite its clear rules and intended separations, the complexity of growing codebases and the crunch of time often render these principles invisible in practice. When projects technically fail, the culprit is frequently uncontrolled complexity – where Clean Architecture remains a concept on paper, not in code.In this session, I will show how to get predictability by implementing Clean Architecture through structure, rather than relying on discipline and code reviews only. I’ll show how to create a structure that makes it easy to write the code that follows your architecture and at the same time it makes it difficult to write the code that doesn’t.You will walk away with a recipe and building blocks for creating a foundation in code that sustains Clean Architecture and the level of quality in your code that can control the complexity of the project.This structure will enforce separation of concerns and how dependencies are created. It will deliver predictability by creating a Code Desing that is maintainable, extensible and reusable. Read More...

• Florin Coros [Software Solution Architect | Technical Trainer — Code Desing - onCodeDesign.com]

The evolving role of programmers in Automated Trading: Speed in stock markets&crypto

Programming Stage — 30 minutes Programming

A programming-centric session on the innovative software built in the name of speed, with a focus on why programming is crucial for information extraction for research purposes. 

• Owain Lloyd [Chief Technology Officer — Flow Traders]

GenAI Tools Are Shaping the Future of Software

Programming Stage — 30 minutes Generative AI Programming Software Development

Exploring the transformative impact of Generative AI (GenAI) tools on the software development industry, this presentation delves into how these tools are reshaping the entire software development lifecycle. 
We’ll discuss the current landscape, benefits, and the implications of this rapid adoption on the workforce and companies. We’ll also touch upon the potential risks and ethical considerations, and how companies can prepare for this paradigm shift. 
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• Alin Turcu [Engineering Director — Cognizant Romania]

Practical introduction to OpenTelemetry tracing

Programming Stage — 45 minutes Open Source Microservices Programming

Tracking a request’s flow across different components in distributed systems is essential.
With the rise of microservices, their importance has risen to critical levels. Some proprietary tools for tracking have been used already: Jaeger and Zipkin naturally come to mind. Observability is built on three pillars: logging, metrics, and tracing. OpenTelemetry is a joint effort to bring an open standard to them. Jaeger and Zipkin joined the effort so that they are now OpenTelemetry compatible. In this talk, I’ll describe the above in more detail and showcase a (simple) use case to demo how you could benefit from OpenTelemetry in your distributed architecture.
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• Nicolas Fränkel [Head of Developer Advocacy — Garm Solutions]

Networking & Lunch Break

Programming Stage — 1 hour

Platform Engineering: DevOps Evolution or a Fancy Rename?

Programming Stage — 45 minutes DevOps Programming

Everyone’s talking about Platform Engineering these days. 
Even Gartner featured it in its Hype Cycle for Software Engineering. But what is Platform Engineering really about? Is it the next stage in the evolution of DevOps? Is it just a fancy rebrand for DevOps or SRE? And most importantly - do I need it?

In this talk Horovits will look into the accumulated experience of larger organizations, the common pains that drive them to adopt Platform Engineering, and what DevOps responsibilities it covers. The talk will also share insights from the recent whitepaper published by the Cloud Native Computing Foundation’s TAG App Delivery. 

Horovits will also provide guidance on which organizations should adopt Platform Engineering and at which point in their DevOps maturity lifecycle. This talk will equip you with the fundamentals to assess Platform Engineering for your organization.
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• Dotan Horovits [DevOps Specialist & CNCF Ambassador — N/A]

Pragmatic fault tolerant systems

Programming Stage — 30 minutes Programming

Leverage actor model concurrency in order to build fault tolerant systems

• Adrian Magdaș [Chief Technology Officer — Nexttech]

Improve your Multi-Factor Auth with Firebase and Vonage APIs

Programming Stage — 45 minutes Programming

In this talk, Amanda Cavallaro will demonstrate how to use the Vonage APIs for SIM swap detection and verification through SMS alongside Firebase services for hosting, database, and storing logic. 
The demo application includes a simple bank dashboard and a login form. If the SIM Swap API detects that a phone number was swapped recently, the verification code will not be sent, and additional security measures will be applied. A verification code will be sent via the Verify v2 API to authenticate the user if no recent swap is detected.
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• Amanda Cavallaro [Developer Advocate — Vonage]

Patterns & Practices for Implementing Machine Learning Systems in Production

Programming Stage — 35 minutes Machine Learning Future of Engineering Programming

When implementing ML Systems in Production, engineers focus on the data & ML algorithms aspect of these systems and not enough attention is given to the infrastructure aspect.
To deploy these systems in production systems, one has to consider efficient ways to deploy, monitor, and update the models, feature engineering, store & use huge datasets. This talk covers the infrastructure aspects of ML Systems in production. The focus is not on particular ML algorithms but rather on efficient infrastructure for implementing a wide variety of ML systems in production.  The objective of this talk is to present a framework for best to implement a production ML system based on the choice of algorithms and type of dataset used. Read More...

• Nikhil Barthwal [Staff Software Engineer — Facebook]

Fitbit Labs

Java Stage — 30 minutes Java

The way we understand and manage our health is undergoing a radical shift thanks to the powerful intersection of technology and medical science. This presentation will explore how cutting-edge innovations are revolutionizing healthcare, from the research lab to our everyday lives.

• Radu Popovici [Sr. Engineering Manager — Google]

Hunting with Stream Gatherers

Java Stage — 45 minutes Java

Streams were a very nice addition to Java 8, based on lambdas. They allow streamlined data processing without side effects, taking us gently towards functional style. With newer additions to Java, like records and pattern matching, they shine even more in data-driven flows. 
However, they don’t come without flaws. For starters, the only available extension point was collectors: if your needs for gathering data weren’t satisfied by the whole Collectors ZOO, you could always fall back to creating your own Collector. However, if map, filter or flatMap weren’t enough, you couldn’t add your own intermediate operation. Secondly, parallel streams were limited to ForkJoin pool, effectively rendering them unusable for scenarios involving any IO. Since Java 22, Stream Gatherers are our extension point for intermediate operations in streams. If you’d like to comprehend how they work, find nice use cases and hunt for more performance, this talk is for you.
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• Piotr Przybyl [Senior Developer Advocate — Elastic]

Gemini in Java with Vertex AI and LangChain4j

Java Stage — 45 minutes Java Generative AI

Join me in this session to learn how to use generative AI capabilities with Java and LangChain. We will be using LangChain4J and the libraries it has to integrate with Cloud AI APIs.
We will explore using Gemini. You'll learn how they can be used to solve real-world problems. No prior expertise, preparation, or installation is required. Just come with your laptop, a dash of programming experience, and your imagination.
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• Abdelfettah Sghiouar [Senior Cloud Developer Advocate — Google]

TradeStore: Powering Through Peaks with High Availability and Efficiency

Java Stage — 30 minutes Java

In this session we take a look under the hood of the new TradeStore HA, a crucial application in the trading landscape as we reveal strategies to achieve challenging requirements on availability, reliability, scalability, and throughput in the fast-paced world of a global trading organization." 

• Daniel Sacramento [Team Lead Java Core — Flow Traders]

Networking & Lunch Break

Java Stage — 1 hour

Deserialization exploits in Java: why should I care?

Java Stage — 45 minutes Java

Hackers refer to deserialization in Java as “the gift that keeps on giving”. But what is actually the problem? In most cases, it is not even your own code that creates this security vulnerability. This problem is also not restricted to Java’s custom serialization framework. Similar issues can also occur when deserializing JSON, XML, or YAML.
In this talk, I explain how deserialization vulnerabilities work natively in Java and how attack chains are created. Next, I will show that deserializing XML, JSON, and YAML can also get you into trouble. Many different problems can occur when deserializing data and in this session, I will use several demos to illustrate various security issues.
How do you avoid these issues? I will give you some pointers on how to mitigate these problems in your own applications. At the end of this session, you will have an understanding of the problem space and be able to take action in your code to prevent it. Read More...

• Brian Vermeer [Staff Developer Advocate — Snyk]

Is Java a good fit for serverless? A contextual analysis

Java Stage — 30 minutes Java

When selecting a programming language that best suits the needs of your next project, Java stands out as a robust yet complex option.
But in the dynamic world of serverless computing, is it the best option? This presentation explores Java's role in serverless architectures, balancing its benefits, such as a rich ecosystem and strong performance, against challenges like cold start latency and memory footprints. We will compare it with other competing languages, such as Python, JavaScript and Go, and examine the latest improvements brought by frameworks like Micronaut or Quarkus to provide actionable insights into making informed decisions depending on specific project needs.
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• Andra Ștefan [Engineering Manager and Head of Backend Capability — Deloitte Technology Delivery Center]

A Solid Foundation for GenAI Apps - Exploring Architectural Blueprints for LLM Solutions with Java

Java Stage — 45 minutes Java

This talk will explore the main architectural blueprints for Java GenAI Applications, offering insights on addressing the most typical requirements for such applications, approaching recurrent problems, and breaking them into manageable components to unlock the potential of LLMs with Java.
The talk comprises the most common design patterns for building GenAI solutions with Java, and it will provide some reference architectures and solutions for building LLM-based agents. Code examples with Spring AI, LangChain4J and OpenAI will be presented, along with vector databases.
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• Juarez Barbosa Junior [Sr Principal Java Developer Evangelist — ORACLE]

ML in Java, YES it's possible!

Java Stage — 35 minutes Java Machine Learning

When you think about building and/or deploying machine learning models, Java is not within the top 3 languages that we generally think of.
Nonetheless Java has a strong community, with millions of developers using it as their main language.
With the AI buzz spiking in the past month, All developers, and especially Java developers, need to understand how to build and run apps that use ML. In this session we are going to explore what are our options, as java developers, to build, save and run machine learning models.We are also going to discuss and compare the most 3 popular frameworks (Deeplearning4J, djl and Tribuo), along with a real world example to understand capabilities and tradeoffs of each framework. We will also briefly cover JSR381, an open-source, Java-friendly API for ML, specifically visual recognition. Read More...

• Mohammed Aboullaite [Senior Engineer — Spotify]

Evolutionary Architecture as a good choice

Roundtables — 1 hour

A common practice among software engineers is to define the architecture of a complex system in the beginning and use it as a blueprint for future implementation. This approach works poorly in practice because requirements keep evolving, and the architecture defined initially is hard to change later on. This leads to expensive re-architecting and re-implementation work.Evolutionary Architecture is an approach that treats architecture as an evolvable entity that has no end state but is designed to adapt to ever-changing requirements.
 This approach works poorly in practice because requirements keep evolving, and the architecture defined initially is hard to change later on. This leads to expensive re-architecting and re-implementation work.Evolutionary Architecture is an approach that treats architecture as an evolvable entity that has no end state but is designed to adapt to ever-changing requirements. An evolutionary architecture is defined as one that supports guided, incremental change across multiple dimensions.This approach involves defining a set of architectural characteristics and an objective function called a fitness function, which evaluates how close a prospective design solution is to achieving its objectives. The fitness function is used to make guided incremental changes to the system.Architectural characteristics are defined across multiple dimensions like scalability, security, agility, and ability to test & deploy, and the impact of each incremental change is considered across all dimensions.The objective of this talk is to demonstrate how principles of evolutionary architecture can be used to design systems whose architecture does not degrade over time and develop an understanding of how system changes would impact the system's architectural characteristics across multiple dimensions.Key Learnings:Defining the architecture of a system early on does not work well in practice.Evolutionary Architecture treats architecture as an evolvable entity that has no end state.It supports incremental change across multiple dimensions guided by a fitness function Read More...

• Nikhil Barthwal [Staff Software Engineer — Facebook]

Open table discussions regarding reference Architecture of AI in the Cloud

Roundtables — 1 hour

We invite you to join a round-table discussion on the cloud modernization journey required to integrate an AI solution into your ecosystem. If you're an architect or play a key role in shaping the technical vision for enterprise solutions, we'd love for you to participate and share insights as we learn from each other. 

• Radu Vunvulea [Group Head of Cloud — Endava]