Golang

3 articles

Agents AI Alexa Amazon Q AMQP Apache Apache Kafka Apache Pulsar Architecture AWS AWS Kinesis Bastion Host Bedrock BRIO Certification Cloud CodeWhisperer Confluent Craft Data Structures Databases Deserializer Dock Docker Elastic ElastiCache Elasticsearch Extreme Go Golang Grafana Hadoop Heartbeat Infrastructure-as-a-Code Java JMS Kafka LangChain LangGraph Laptop Learning Lenovo LinkedIn Linux LLM Logitech Logstash MCP Messaging Metricbeat Multiple Columns MX Anywhere Observability OpenTelemetry Performance Programming Projects Prometheus Protobuf RAG Redis Search Security Serialization Serializer Sorted Set Streaming Terraform ThinkPad Tools Topic Treat Vector Databases VSCode Workaround X1

Data Sharing between Java & Go using Kafka and Protobuf

Thursday, Jul 9, 2020

One of the most incredible things in Apache Kafka is that record values are shapeless, meaning that developers can write any set of bytes they want, and it works just fine. This can be pretty powerful if they share data among different programming languages.

However, this characteristic is sometimes inadequate. It creates coupling problems as producers and consumers need to negotiate a common format that they can rely on to write and read data. Therefore, it is essential to use a neutral format – likely something accepted within the industry, such as Avro, Protobuf, and JSON Schemas. This post will focus on the problems raised by using Protobuf to share data between Java and Go.

Ricardo Ferreira
3 minute read

Multiple Columns with Redis Sorted Set

Tuesday, Mar 3, 2020

Recently I had to build an application that would store and order players in a Redis Sorted Set, but using multiple columns as criteria for the score, instead of just one. After trying to find a proper solution on the web and failing to do so; I decided to put my head to work and figure out an way. This post will show how did I accomplished that.

It turns out that my application has players with the following fields:

Ricardo Ferreira
2 minute read

Confluent Go Client with Docker

Saturday, Feb 29, 2020

If you are reading this blog post then there is a high chance that you’ve been looking for ways to make Confluent’s Go Client for Apache Kafka work with your Docker images but you’re struggling to. Am I right?

Don’t worry, you’ve came to the right place. After struggling with this myself I decided to share the solution that I’ve found with everybody else so we all can spend more time writing code than just wasting time with dependency plumbing.

Ricardo Ferreira
3 minute read

© 2018 - 2026 Ricardo Ferreira

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Open Source

I contribute to LangChain4j, an idiomatic open source Java library for building LLM-powered applications on the JVM. Recent work includes adding native vector search embedding stores so developers can build RAG, recommendation engines, and AI memory systems.

I also ported RedisVL to Go, an open source, AI-native client that brings vector search, semantic caching, LLM memory, semantic routing, rerankers, and an MCP server to the Redis ecosystem for Golang developers.

Public Speaking

I’ve been speaking at conferences since 2008 and doing it full time as part of my work with DevRel since 2018. My talks go deep on the systems I build with: distributed systems and event streaming, AI engineering and vector search, and the data infrastructure that has to hold up when the demo ends and production begins. Some of the events I’ve spoken at include AWS re:Invent, Microsoft Ignite, Google Cloud Next, KubeCon, Oracle OpenWorld, QCon, Strange Loop, Kafka Summit, Pulsar Summit, JavaOne, DevNexus, JFokus, JNation, and All Things Open.

Ricardo Ferreira presenting on the main stage at AI DevWorld
On the main stage at AI DevWorld

You can find my upcoming and past talks on my speaking calendar. Recordings also live on my YouTube channel, and the code I write for talks, demos, and workshops is on my GitHub.

Consulting and Professional Services

If you’d like to hire me as a consultant for your projects, speak at your event, or lead a hands-on workshop for your team, contact me at riferrei@riferrei.com. I can understand the scope of your request and provide a free estimate.

Who am I?

I work at the intersection of AI, data infrastructure, and distributed systems, turning complex technology into things developers can understand and products users love.

Lately, that means hands-on AI engineering: building vector search, semantic caching, agent memory, and RAG into the data layer, and figuring out how to make AI agents secure enough to ship. I contribute to open-source projects like LangChain4j and RedisVL for Golang.

The AI-native work isn’t a pivot. It draws on the same systems-design foundation I’ve built for 20+ years: designing data systems for scale, moving data fast, watching where systems break; now applied to vectors and agents. I have worked on RDBMS and Big Data at Oracle; event streaming with Apache Kafka and Apache Flink at Confluent; observability at Elastic; AI and developer tooling at AWS; and NoSQL and vector stores at Redis. That foundation is exactly what separates AI demos that work on stage from AI systems that survive production.

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