Antón Rodríguez
Principal Software Engineer at New Relic
Software Engineer and JUG organizer
A Coruña, Spain
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Antón is a Principal Software Engineer focused on Data in motion. He has a passion for building high-throughput streaming systems and solving the challenges that come with them. He’s also a JUG organiser, blogger, podcaster and speaker.
Principal Software Engineer centrado en Event Streaming y Real-Time Processing con Kafka y tecnologías Cloud. Especializado en montar soluciones SaaS en entornos corporativos. Previamente ha ayudado a mejorar equipos de desarrollo en diferentes facetas: gestión de código, integración continua, buenas prácticas, etc.
Además co-organiza los grupos de usuarios de Java en Coruña y Vigo, y el LaretasGeek, una mesa redonda virtual sobre tecnología
Area of Expertise
Topics
Divide and conquer: strategies for scaling your Kafka Cluster
Are you using Apache Kafka for real-time data processing? As your data grows, you'll need to scale up your Kafka clusters to keep up with the demand. One way to do this is by splitting a large Kafka cluster into smaller ones.
In this talk, I'll share some of my own experiences with splitting Kafka clusters, and explore two approaches in particular: splitting by domain and splitting based on the Cell architecture. Splitting by domain means dividing up your Kafka cluster by business area, while splitting based on the Cell architecture means dividing it up by identical clusters sharded by the ingress traffic. Both approaches have their own challenges, and I'll share some tips and tricks to help you avoid common pitfalls.
I'll examine key considerations, such as networking design, governance, and mirroring. The mirroring process, in particular, can become a bottleneck when scaling up, so I'll explore ways to optimize and automate mirroring to ensure optimal performance. I will also cover the governance aspect of scaling, including how to ensure consistency across multiple clusters and how to manage resources effectively.
To wrap things up, I'll share some real-world examples of successful Kafka cluster scaling, and the lessons learned from those experiences. By the end of this talk, you'll have a better understanding of how to scale up your Kafka clusters by splitting them, with practical insights and tips to help you achieve your goals.
Instrumenting Java applications with OpenTelemetry
This talk shows you how to produce telemetry from your Java services using an open standard to retain control of data. OpenTelemetry allows you to instrument your application code through vendor-neutral APIs, libraries, and tools. It provides the tools necessary for you to gain visibility into the performance of your services and overall latency.
In this session, Anton introduces OpenTelementry and what's the current status in Java. He will show some real examples and all the required resources to start taking advantage of OpenTelemetry to monitor Java applications.
Measuring P99 latency in Event-Driven Architectures with OpenTelemetry
While there are numerous benefits to Event-Driven Architecture, like improved productivity, flexibility, and scalability, they also pose a few disadvantages, such as the complexity of measuring end-to-end latency and identifying bottlenecks in specific services.
This talk shows you how to produce telemetry from your services using an open standard to retain control of data. OpenTelemetry allows you to instrument your application code through vendor-neutral APIs, libraries, and tools. It provides the tools necessary for you to gain visibility into the performance of your services and overall latency.
Anton will share his experience building high-throughput services and strategies to use distributed tracing in an optimal way and without affecting the overall performance of the services.
Data Replication with the Cell Architecture
As part of the Cloud journey, New Relic implemented the cell architecture pattern: a cell is a self-contained installation with a limited lifespan that can satisfy all the operations for a range of users in a specific domain. It's like microservices but for data in motion services.
This architecture provides isolation, cloud cost reduction, and the ability to deploy in different regions or cloud providers, test upgrades, implement rolling upgrades and test different software versions.
But it also introduces challenges. How do we replicate data between cells if they can be created or decommissioned at any moment? How can the replicator react to changes in the traffic flow? In this talk, we'll cover our initial approach to this problem, what we learn in the process and how we plan to improve it in the future.
Schema Management: the elephant in the Cloud room
Schema management is a key component in every big Event Streaming platform. The Schema Registry solution has several advantages: better Data Quality, more performant, Data Evolvability, etc. But when we are working in a multi-datacenter or multi-cloud environments, things start to get complicated.
How do we replicate schemas between different Kafka clusters in separate regions? How do we ensure compatibility even when consumers are using separate Schema Registries? What can we do when we don't have a Schema Registry in one of the sites?
In the last year, Antón has been heavily involved building a platform covering two different Clouds and two on-prem Data Centers. With that experience, he will review the state-of-the-art of the solutions to this problem and what they did.
If you are working with the Schema Registry and you would like to consume or produce your events in the Cloud, this talk will help you with some fresh ideas and the lessons learnt in a similar project.
Monitoring Kafka without instrumentation using eBPF
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.
We’ll see eBPF in action applied to the Kafka world: 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 Kafka observability, this session is for you.
P99 CONF 2022 Sessionize Event
Current 2022: The Next Generation of Kafka Summit Sessionize Event
JNation 2022 Sessionize Event
Kafka Summit London 2022 Sessionize Event
JNation 2021 Sessionize Event
Pulsar Virtual Summit North America 2021 Sessionize Event
Kafka Summit Europe 2021 Sessionize Event
LicorcaConf Sessionize Event
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