It's 2022. Developers have seen it all. They've tried it all. But it seems all is just not enough. The quest for simple has led us to a path of complexity that is often needless. Or is it? Was it all just a lie? Was it all about job security?

As the world moves towards businesses that demand even more developer resources, can we as an industry come together and think about how we can make the world a simpler place? Or will complexity take over even more?

In Part 2 of Silver Bullet Syndrome, we'll see where we are as an industry, and more importantly, have we finally found the Silver Bullet. 

Distributed systems are inherently complex and exposed to failures in their components. While distributed algorithms try to do their best in handling node and network failures, it is often not possible to mask them. In the presence of failures, systems that thrive for high availability need to allow users to always submit operations and observe the local state (ensuring local-first), leading to potential divergence. Designs with Conflict-free Replicated Data Types (CRDTs) have been used extensively to guarantee that it is possible to converge to a state that reflects concurrent operations. Recent proposals show that it is possible to go beyond state convergence and use CRDTs as a basis for providing additional system-wide guarantees on individual data items, non-negative inc/dec counters, and cross-item guarantees such as referential integrity. This talk introduces the main concepts underpinning CRDTs and these recent proposals. 
 

Distributed systems are inherently complex and exposed to failures in their components. While distributed algorithms try to do their best in handling node and network failures, it is often not possible to mask them. In the presence of failures, systems that thrive for high availability need to allow users to always submit operations and observe the local state (ensuring local-first), leading to potential divergence. Designs with Conflict-free Replicated Data Types (CRDTs) have been used extensively to guarantee that it is possible to converge to a state that reflects concurrent operations. Recent proposals show that it is possible to go beyond state convergence and use CRDTs as a basis for providing additional system-wide guarantees on individual data items, non-negative inc/dec counters, and cross-item guarantees such as referential integrity. This talk introduces the main concepts underpinning CRDTs and these recent proposals. 
 

Did you ever see a Distributed Deep-Learning Platform as a Service? Sure not, it’s challenging! Join this session to discover OpenDeepHealth, a PaaS built on top of Kubernetes and designed from principles with a multi-tenancy first approach!

OpenDeepHealth (ODH) is a hybrid HPC/cloud infrastructure designed and developed by the University of Torino in the DeepHealth European project. The goal was to provide a self-service platform for Deep Learning, allowing domain experts to bring their own data and run training and inference workflows in a multi-tenant container-native environment. Kubernetes, the de-facto standard for container orchestration, is the perfect framework for building such a distributed system, optimising resource usage and allowing a horizontal scaling of the infrastructure.

StreamFlow, the ODH workflow engine, can schedule and coordinate different workflow steps on top of a diverse set of execution environments, ranging from single Pods to entire HPC centres. As a result, each step of a complex Data Analysis pipeline can be scheduled on the most efficient infrastructure. At the same time, the underlying run-time layer automatically takes care of workers’ lifecycle, data transfers, and fault-tolerance aspects.

ODH implements a novel form of multi-tenancy called “HPC Secure Multi-Tenancy”, specifically designed to support AI applications on critical data. Thanks to Capsule, the multi-tenant Kubernetes operator, ODH can enforce multi-tenancy at the cluster level, avoiding privilege escalations and exploits, minimising operational costs, and enforcing custom policies to access external HPC facilities.

Finally, ODH provides multi-tenant distributed Jupyter Notebooks as a service through the Dossier platform. This feature gives domain experts a high-level, well-known programming model to write portable and reproducible Deep Learning pipelines, augmenting standard notebooks with resource segregation, data protection and computation offloading capabilities.

Did you ever see a Distributed Deep-Learning Platform as a Service? Sure not, it’s challenging! Join this session to discover OpenDeepHealth, a PaaS built on top of Kubernetes and designed from principles with a multi-tenancy first approach!

OpenDeepHealth (ODH) is a hybrid HPC/cloud infrastructure designed and developed by the University of Torino in the DeepHealth European project. The goal was to provide a self-service platform for Deep Learning, allowing domain experts to bring their own data and run training and inference workflows in a multi-tenant container-native environment. Kubernetes, the de-facto standard for container orchestration, is the perfect framework for building such a distributed system, optimising resource usage and allowing a horizontal scaling of the infrastructure.

StreamFlow, the ODH workflow engine, can schedule and coordinate different workflow steps on top of a diverse set of execution environments, ranging from single Pods to entire HPC centres. As a result, each step of a complex Data Analysis pipeline can be scheduled on the most efficient infrastructure. At the same time, the underlying run-time layer automatically takes care of workers’ lifecycle, data transfers, and fault-tolerance aspects.

ODH implements a novel form of multi-tenancy called “HPC Secure Multi-Tenancy”, specifically designed to support AI applications on critical data. Thanks to Capsule, the multi-tenant Kubernetes operator, ODH can enforce multi-tenancy at the cluster level, avoiding privilege escalations and exploits, minimising operational costs, and enforcing custom policies to access external HPC facilities.

Finally, ODH provides multi-tenant distributed Jupyter Notebooks as a service through the Dossier platform. This feature gives domain experts a high-level, well-known programming model to write portable and reproducible Deep Learning pipelines, augmenting standard notebooks with resource segregation, data protection and computation offloading capabilities.

Public, Private, Hybrid…Multi-Cloud?

As the cloud development options and architectures continue to evolve, we’ve finally found ourselves at the next new thing: Multi-Cloud. What is it? Do we really need it? How would you take advantage of a multi-cloud solution?

In this talk, I'd like to describe a few real-world use cases where a multi-cloud solution is currently in production, specifically when it comes to data.

Specifically, we’ll see how multi-cloud helps:

• Data Sovereignty scenarios
• Fulfill varied client cloud requirements
• Developers have more freedom in choosing services
• Achieve greater availability

A demo on how to setup a multi-cloud cluster will also be shown.

The audience will leave with a more confident understanding of real-world, multi-cloud use cases and see how to create their own!

In 2010 the DevOps movement set about solving the blockage on the path to production. The wall of confusion. Developers would throw new software releases, new features and new products over the wall to operations who were tasked with supporting these apps in production. As a community, we've been tearing down the wall of confusion for a decade (sometimes building new and different walls where it stood) and we've learnt a thing or two along the way. In this talk, Hannah will reflect on how we've often "shifted left" the wrong way, and how we might approach this familiar problem in new ways that set our teams up for success. 

You don’t always hear architecture and frontend development in the same sentence, however, in modern development cycles, this is changing. Whether you are frontend, backend, or DevOps, this talk is going to give you an inside look at how we incorporated frontend architecture of angular-based apps within a bitcoin treasury management platform that is used by large enterprise businesses. In this talk, Daniel will speak about the technology stack chosen, backend-for-frontend and API gateway patterns, monorepos vs multirepo, platform events consumption by the frontend, and more.

In recent years the software industry has begun to pay attention to the field of Resilience Engineering, a relatively new field that studies complex systems and how they behave under unexpected conditions. One concept that has emerged from Resilience Engineering is Graceful Extensibility. Systems that have a high degree of Graceful Extensibility are not brittle: they do not collapse quickly when unusual demands are made on them, and they can adapt to changing conditions.

Many kinds of natural systems demonstrate graceful extensibility - Dr Richard Cook’s talk on the resiliency of bone is a perfect example. Software systems, unfortunately, are typically much more brittle than organic systems - even the largest organisation experiences outages. There is no silver bullet to address the problem that the sheer complexity of software systems causes. However, there are a number of architectural and organisational patterns that we can use to increase the Graceful Extensibility of our systems: from basic circuitbreaking and ratelimiting to more advanced design concepts such as constant-work systems and cellular architectures, as well as organisational practices that help us to spot the signals that our systems are approaching their limits. This talk will dive into these technical and organisational elements of resiliency in distributed software systems.

In this talk, Micronaut creator Graeme Rocher, will demonstrate how you can quickly build optimized Microservices with Micronaut & GraalVM Native Image. Attendees will learn how the combination of GraalVM Native Image and Micronaut can lead to efficient, highly performance, and optimized applications that can be perfectly deployed to containerized environments like Kubernetes.

In this talk Micronaut creator, Graeme Rocher, will demonstrate how to develop Serverless applications in a completely Cloud agnostic way with Micronaut and deploy them efficiently with GraalVM native image.

Everybody talks about security but no one actually knows how to start let alone solve issues when it is not working. We always fall back on “that” guy. With this presentation, I hope that at the end of the talk I inspired some people to become that guy.

Certificates are everywhere: in between; on the server; and even on your own devices. Even the people who don’t know what a certificate is, still look for the lock in the address bar. And if they don’t, they should. For people working with certificates daily, “Zero Trust” is something that is a standard that has been around since TLS 1.0, not a new buzzword. 

When explaining to someone what that lock in the address bar actually means is something you probably need to be working with certificates daily, just to know what that lock actually portrays. Getting from a simple unsecured HTTP connection to an HTTPS connection using a certificate that is not self-signed used to be a lot harder than it is now. Or is it?

Do you know the difference between TLS and SSL, HTTP and HTTPS or even mTLS. Not to mention async vs sync encryption with RSA, DES? If yes no need to join this talk, all others are invited to explore the wonderful world of security and encryption. This talk takes you down the rabbit hole of encryption and certificates and how they are connected with each other. At the end of the talk, you will understand the terms, CER, DER, CRT, PEM, Certificates, CA, Root CA, TLS, SSL and even mTLS and be able to join the discussion at work related to certificates and a bit more.

The accelerating pace of cloud-native development is enabling faster innovation, but it is also leaving behind an increasing vulnerability backlog. Developers are overwhelmed with vulnerabilities without knowing their actual risk and where to focus remediation efforts. 

Just trying to make sense of the noise already takes precious time away from coding, slowing down the process. Not to mention the frustration of dedicating time to vulnerabilities that don’t matter because they incur no real risk. 

Discover how to filter out the noise with runtime intelligence and quickly prioritise critical issues.

The remarkable advances in Data, Analytics and AI have fostered a widespread adoption of Machine Learning (ML) capabilities within many products and services we use and consume everyday, ranging from navigation apps up to health-support systems. Nonetheless, implementing ML solutions is still a complex endeavour, and many organizations are struggling to fully exploit the strategic advantages of AI.

In this talk, we’ll cover the key concepts that are critical to harness Data & AI leveraging what we have learned from implementing complex software and data-heavy developments in multiple projects. We’ll go through the three stages that we consider when dealing with data products, and we’ll also introduce the principles of Machine Learning Ops (MLOps), a concept that has gained momentum over the last months.

Adyen provides payments processing and financial services to many marketplaces like eBay, GoFundMe, or Wix among many others. In this setting, any individual can sign up and start selling or providing services and thus there is a need for strong requirements around behaviour monitoring to prevent illegal or damaging situations.

This talk will take you through our journey when solving for behaviour prediction and monitoring an ever-growing dataset. A journey based on several iterations first on posing the problem, designing the right algorithms and then implementing and deploying a live system that leverages the open source tech stack to juggle real-time events together with numerically-heavy machine-learning-based pattern extraction.

May contain unpleasant truths.

In order to support modern systems’ needs, we have to be distributed. But, it is easier said than done. Let’s see together what challenges we have in such systems and strategies we can use to overcome them.

We are all aware of the fallacies of distributed computing. Alongside them, there are other things we should consider as well. At AxonIQ, one of our core products is Axon Server which acts as a Messaging Platform and Event Store. In other words, a system that is by its nature distributed across several machines to be more reliable and scalable.

Let’s see together what it means to build such a system, how to maintain it in (large variety of our customers’) production environments, and lastly, how to offer it as a service in the cloud.

May contain unpleasant truths.

In order to support modern systems’ needs, we have to be distributed. But, it is easier said than done. Let’s see together what challenges we have in such systems and strategies we can use to overcome them.

We are all aware of the fallacies of distributed computing. Alongside them, there are other things we should consider as well. At AxonIQ, one of our core products is Axon Server which acts as a Messaging Platform and Event Store. In other words, a system that is by its nature distributed across several machines to be more reliable and scalable.

Let’s see together what it means to build such a system, how to maintain it in (large variety of our customers’) production environments, and lastly, how to offer it as a service in the cloud.

Embedding quality through every phase of the software delivery lifecycle is not easy, but reducing risk and improving application quality is mandatory in a technologically competitive world. How can we improve our CI/CD pipelines in order to achieve this goal? Fran will walk you through different examples of scaling tests early, automation generated directly from requirements, enabling any team to learn from fast and continuous feedback as well as decrease technical debt, and, finally, improve business outcomes by making data-driven decisions about release readiness.

BPMN is often seen as boring ‘Business Speak’. In reality, it is just a way to automate things, and since it’s called the Internet of Things why not automate those things too! With an estimated 75% of IoT deployments failing to deliver on their promises (and 30% dying in the proof of concept phase) it’s clearly time to approach IoT deployments differently. It’s time to design, implement, build and deploy IoT projects from a business perspective rather than a technical standpoint.

In this talk I’ll go through a complete IoT solution in 3 iterations to show how Business Process Management platforms can quickly iterate on an IoT solution to deliver maximum benefit. Enough business-speak! I’m going to build a Skittles (candy) dispenser based on IoT and controlled by BPMN, with a little AI thrown in! I’ll run the entire demo live, so if the prospect of watching a demo fail in front of a live audience is what gets you excited, this talk is for you! It’s also for you if you’re struggling to build a business case for your IoT project.

APIs are the glue that holds our information systems together. If you run more than a couple of apps, having each of them implement authentication, etc. is going to be an Ops nightmare. You definitely need a central point of management, an API Gateway.

As developers, we live more and more in an interconnected world. Perhaps you’re developing microservices? Maybe you’re exposing your APIs on the web? In all cases, web APIs are the glue that binds our architecture together. In the Java world, we are very fortunate to have a lot of libraries to help us manage related concerns: rate limiting, authentication, service discovery; you name it. Yet, these concerns are cross-cutting. They impact all our applications in the same way. Perhaps libraries are not the optimal way to handle them. API Gateways are a popular and nowadays quite widespread way to move these concerns out of the applications to a central place.

In this talk, I’ll describe in more detail some of these concerns and how you can benefit from an API Gateway. Then, I’ll list some of the available solutions on the market. Finally, I’ll demo APISIX, an Apache-managed project built on top of NGINX that offers quite a few features to help you ease your development.

Imagine a world where you can access metrics, events, traces and logs in seconds without changing code. Even more, a world where you can run scripts to debug metrics as code. In this session, you will learn about eBPF, a powerful technology with origins in the Linux kernel that holds the potential to fundamentally change how Networking, Observability and Security are delivered.

In this session, we’ll see eBPF monitoring in action applied to the Kafka world as an example of a complex Java application: identify Kafka consumers, producers and brokers, see how they interact with each other and how many resources they consume. We’ll even show how to measure consumer lag without external components. If you want to know what’s next in Java and Kafka observability in Kubernetes, this session is for you.

More than ever, dataviz needs to engage broad audiences, evolve beyond conventional chart types, and move beyond the usual infographics. Stefanie will use examples from her practice to explore what a ‘post-infographic’ design approach might look like while sharing tips on how to communicate data with a spirit of openness and experimentation.