Java Programming Tutorials & Engineering Articles

As AI coding assistants shift the developer's primary role from writing boilerplate to reviewing and maintaining systems, language choice becomes critical for long-term architectural integrity. Go directly addresses this new paradigm by utilizing its strict compiler, integrated toolchain, and uncompromising readability to provide deterministic guardrails that help AI models self-correct and generate highly standardized code. By enforcing ecosystem-wide consistency and strict backward compatibility, the Go platform empowers engineering teams to efficiently verify, optimize, and maintain high-velocity, AI-generated output in production environments.

Enterprise Java developers have a new superpower—drive GitHub Copilot from idiomatic Java code with annotations, virtual threads, and more.

Real-time AI agents break traditional request-response load balancing paradigms because they rely on long-lived, stateful bidirectional streams that obscure true server capacity. To solve this, developers must implement application-level session tracking directly within the runtime to accurately measure the committed concurrent workload of active conversations. By feeding these precise session counts alongside standard CPU utilization metrics into a hybrid routing algorithm, infrastructure can effectively distribute stateful AI traffic and prevent individual backend bottlenecks.

ClickHouse was released in open source on Jun 15 2016, ten years ago. Since then, it became the most popular open source analytical database with more than 2000 contributors.

ClickHouse now has an official ADBC driver, giving Ruby, R, C, and every other ADBC-aware tool zero-conversion, Arrow-native access to ClickHouse without a dedicated client for each language.

Answering the questions of "why we built ADK 2.0". This explains the rationale, some of the features, and why a developer should consider upgrading. This will be published the day after ADK go 2.0 launches.

Event destinations are central to Stripe integrations but hard to get right. Event notification handlers encapsulate the setup and wiring, letting you focus on business logic and surface errors at development time instead of in production.

Celebrating the first anniversary of the Agent-to-Agent (A2A) protocol, this blog post highlights how the framework enables autonomous AI agents to securely collaborate and hand off tasks without the rigidity of traditional APIs. By delegating complex workflows to specialized peer agents, A2A prevents context pollution, ensures data privacy, and simplifies application design through modularity. To demonstrate this ecosystem in action, the post spotlights FoldRun—an agentic interface for life sciences that orchestrates complex protein structure predictions—alongside diverse A2A use cases spanning commerce, data streaming, DevOps, and telecommunications.

How Airbnb built a Kubernetes sidecar to deliver dynamic configuration reliably at scale.

We all know the stereotypes of working at enterprise tech companies: endless bureaucracy and behemoth codebases running on a years-old language version. Most organizations know they should modernize quickly, but haven’t figured out how to build an upgrade path compatible with a large codebase. The recurring cost of upgrading keeps most large JVM codebases trailing behind the latest Java versions.

Google has announced the launch of version 0.1.0 of the Agent Development Kit (ADK) for Kotlin, alongside a specialized ADK library for Android. This open-source framework simplifies the creation of AI agents by managing complex orchestration, session sharing, and error handling across cloud and edge environments. The release supports hybrid orchestration, enabling developers to build multi-agent systems where a cloud-based model can seamlessly offload specific tasks to local, on-device models like Gemini Nano to enhance user privacy.

The path from a trained AI model to production should be smooth, but rarely is. Many teams invest weeks fine-tuning models, only to discover that exporting to a…

How Airbnb built a lightweight workflow engine to solve durable execution.

By Alex Kotliarskyi, Victor Zhu, and Zach Brock

The launch of Agent Development Kit (ADK) for Go 1.0 marks a significant shift from experimental AI scripts to production-ready services by prioritizing observability, security, and extensibility. Key updates include native OpenTelemetry integration for deep tracing, a new plugin system for self-healing logic, and "Human-in-the-Loop" confirmations to ensure safety during sensitive operations. Additionally, the release introduces YAML-based configurations for rapid iteration and refined Agent2Agent (A2A) protocols to support seamless communication across different programming languages. This framework empowers developers to build complex, reliable multi-agent systems using the high-performance engineering standards of Golang.

Google has released version 1.0.0 of the Agent Development Kit (ADK) for Java, introducing powerful new features like Google Maps grounding, built-in URL fetching, and a standardized Agent2Agent protocol for cross-framework collaboration. The update enhances agent control through a new "App" and "Plugin" architecture, which allows for global logging, automated context window management via event compaction, and "Human-in-the-Loop" workflows for action confirmations. Additionally, the release provides robust session and memory services using Google Cloud integrations like Firestore and Vertex AI to manage long-term state and large data artifacts.

By Bo Xu, Danny Zhang, and Rohit Arunachalam

Anna Sulkina, Senior Director of Engineering at Airbnb, shares her career journey from growing up in Eastern Ukraine during the collapse of the Soviet Union to leading Application & Cloud Infrastru...

The article discusses the advancements in scaling long-running autonomous coding agents, focusing on the challenges and solutions encountered while coordinating multiple agents to complete complex ...

Airbnb's Pay as a Local initiative launched 20+ locally relevant payment methods (LPMs) across multiple global markets in 14 months.

The article discusses key benchmarks conducted over the past year that reveal insights into performance optimization in ClickHouse.

The article discusses Uber's collaboration with Oracle Cloud Infrastructure (OCI) and Ampere Computing to optimize the OCI AmpereOne M A4 Compute instances.

The 2025 Cloudflare Radar Year in Review highlights significant trends in internet traffic, the rise of AI, post-quantum encryption, and the increase in DDoS attacks.

The article discusses ClickHouse's journey of integrating Rust into its predominantly C++ codebase without undertaking a complete rewrite.

This article discusses Uber's implementation of Apache Pinot to manage and analyze its extensive inventory and catalog data efficiently.

The article discusses the advancements in on-device AI powered by MediaTek's Neural Processing Unit (NPU) and the introduction of the LiteRT NeuroPilot Accelerator.

This article discusses how Uber improved MySQL cluster uptime by adopting MySQL Group Replication (MGR) at scale.

This article discusses the improvements made to MySQL cluster uptime at Uber through the implementation of MySQL Group Replication (MGR).

Shopify open-sources Tangle, an ML experimentation platform built to solve six common failure modes in machine learning development.

This article discusses the development and optimization of background coding agents at Spotify, focusing on context engineering to enhance their functionality in code migration tasks.

FishDB is a generic retrieval engine developed by LinkedIn to replace the legacy FollowFeed system, enhancing scalability and performance for their feed infrastructure.

The article discusses Uber's implementation of I/O observability for its massive petabyte-scale data lake, focusing on the challenges and solutions in monitoring data access patterns across its hyb...

The article discusses Shopify's innovative approach to building a high-performance product search engine that integrates Machine Learning (ML) models with C++ speed.

The article announces the addition of Go to the Agent Development Kit (ADK), an open-source toolkit for building AI agents.