Enterprise Integration Architecture Board Monthly Newsletter - 3#2024

Welcome to the latest edition of the Enterprise Integration Architecture Board Newsletter! In this edition, we're diving into the intricate world of integrating event-driven microservices with request/response APIs, a critical challenge in modern software architecture.

We're showcasing an insightful article by Konrad F?gen from Thoughtworks that uncovers four pivotal lessons for mastering this integration. Konrad, a software developer with extensive experience in fintech, retail, and online marketplaces, brings his passion for software test automation and cloud-native development to the forefront in this insightful piece.

For enterprise integration architects, these four lessons provide a framework for effectively managing the integration of event-driven microservices with request/response APIs. By focusing on idempotent event processing, decoupling event retrieval from processing, utilizing circuit breakers, and implementing rate limiting, you can create a resilient and efficient integration architecture.

Lesson 1: Idempotent Event Processing

Learn how idempotent event processing ensures consistency by making sure each event is processed correctly, even when retries are necessary. This involves using unique identifiers and designing APIs to handle duplicate requests.

Read Part One Here

Lesson 2: Decoupling Event Retrieval from Processing

Discover the benefits of decoupling event retrieval from processing to enhance performance. This strategy prevents slower events from delaying other processes, leveraging concurrent processing and optimized retrieval techniques.

Read Part Two Here

Lesson 3: Using Circuit Breakers

Understand the importance of circuit breakers in managing the availability of request/response APIs. Circuit breakers stop cascading failures by pausing event retrieval when a downstream service is unavailable, resuming it only when stability is restored.

Read Part Three Here

Lesson 4: Implementing Rate Limiting

Explore how rate limiting can help manage API usage limits effectively. By controlling the rate of requests sent to APIs, rate limiting ensures that performance remains consistent and prevents overload.

Read Part Four Here

These lessons are crucial for ensuring robust and efficient integration, especially for systems that depend on third-party services or are undergoing modernization. Dive into Konrad’s article to gain deeper insights and practical strategies for improving your integration efforts.

Resources

• Data Platform Explained [Spotify]
• Survival Strategies for the Noisy Neighbor Apocalypse [Video]
• Thoughtworks Technology Radar: Volume 30 [Link]
• Thoughts on “Modular Monoliths” [Blog]
• Build Well-Documented and Authenticated APIs in Node.js with Fastify [Heroku]
• The Backend for Frontend Pattern [Blog]
• Software Architecture and Design Trends [InfoQ]

• How we fought bad apps and bad actors in 2023 [Security]

• Using the platform engineering maturity model to understand the commitment required for an internal developer platform [ Blog ]
• Cloud CISO Perspectives: Get ready for Next ‘24: What you need to know [Google Cloud]
• Corporate Learning Is Boring — But It Doesn’t Have to Be [HBR]
• Redis vs. the trillion-dollar cabals [Article]
• The Serverless Illusion [Gregor Hohpe]
• Leading a Company That Can Thrive in a Chaotic World [HBR]
• How to correctly review a pull request [Blog]
• Uncovering the Seams in Mainframes for Incremental Modernisation [Martin Flower]
• How Do Open Source Licenses Work? The Ultimate Guide [Article]
• Introducing Konfig: GitLab and Google Cloud preconfigured for startups and enterprises [Brave New Geek]
• Cybersecurity Isn’t Special [Blog]
• 6 Common Leadership Styles — and How to Decide Which to Use When [HBR]
• Mastering Kubernetes for Multi-Cloud Efficiency With Nick Eberts [youtube-video]
• 4 Software Design Principles I Learned the Hard Way [Engineer's Codex]
• The trap of over-engineering and over-design [Reset Hard]

AI News Roundup

• Vector Search: What You Need to Know Before Getting Started [The New Stack]
• Generative AI Design Patterns [Article]
• Build Your GenAI Strategy On A Rock-Solid Foundation (Model) [Forrester]
• Is prompt engineering’s party over? [CIODIVE]
• Fine Tuning Large Language Models: How Vertex AI Takes LLMs to the Next Level [Blog]
• Applying Large Language Models to DoD Software Acquisition: An Initial Experiment [Blog]
• How we built Text-to-SQL at Pinterest [Blog]
• Build the future of AI with Meta Llama 3 [Meta]
• Using AI to Shift the Title Insurance Industry [8thlight]
• How to Use LangChain to Build With LLMs – A Beginner's Guide [Freecodecamp]

• A Beginner’s Guide to Vector Embeddings [Timescale Blog]

• Run scalable, enterprise-grade generative AI workloads with Cohere Command R & R+, now available in Amazon Bedrock [AWS News Blog]

• LLM Hallucinations and Mitigation Strategies [Singlestore Blog]

• Navigating the landscape of AI tools for software delivery [Thoughtworks Insights]

• Building new custom silicon for Meta’s AI workloads [Meta]

• Building an infrastructure for AI’s future [Meta Blog]

• Introducing the next-gen Meta Training and Inference Accelerator [Meta AI]

• Shepherd: How Stripe adapted Chronon to scale ML feature development [Stripe Blog]

• Building LLMs for Code Repair [Replit Blog]

• How Should We Define ‘Open’ AI? [Blog]
• The impact of AI tooling on engineering at ANZ Bank [Blog]

If this topic has caught your interest or you have insights to share, we'd love to hear from you! Reach out to us at hello[at]bluebirdtec.com or connect with us on LinkedIn. Let's keep pushing the boundaries of technology and innovation together. See you in our next update!