July 2025¶
Highlight of the Month¶
Summarize my biggest breakthrough, project, or insight in this month:
This month, I've been focusing on system design practice, and it's been an incredibly valuable experience. Preparing for these interviews has helped me strengthen my ability to break down ambiguous problems, structure my thoughts clearly, and communicate trade-offs effectively. Most importantly, I've started to think more like a systems thinker — considering scalability, availability, and reliability in every decision.
Attended¶
- Kubernetes Community Days Taipei 2025
- Kepler
- Crossplane
- Envoy Gateway
- GDG Chunghua Meetup
- System Design Mock Interview with Kevin and Shirley
- Design a Rate Limiter
- Design a Ride-Sharing Service like Uber
- Design a Ticket Booking Service like Ticket Master
- Design a Distributed Message Queue
- Design a Top K Heavy Hitters Service
- Design a Messaging Service like WhatsApp
What I Created or Tried¶
- Published a blog post: How I Learn New Things
- from "unknown unknowns" to "known unknowns" then to "known knowns"
- make mistakes, learn from them, and iterate
- Published a blog post: How I Evaluate a New Tool
- Published a blog post: How WISE Uses Trino and Iceberg to Build a Data Lake at Scale
- Published a blog post: Apache Kafka in Production: Insights from Big Companies
- Published a blog post: Lakebase / Neon
- Published a blog post: The Lakhouse Series: Apache Iceberg Overview
- Published a blog post: The Lakhouse Series: Apache Hudi Overview
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Published a blog post: The Lakehouse Series: From Data Lakes to Data Lakehouses
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Experimented with Pyrefly
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Experimented with FastMCP v2
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Published a blog post: The Lakehouse Series: DuckLake — The Next Big Thing?
- Experimented with DuckDB and DuckLake
What I Learned¶
Short reflections on what I actually learned or became more confident in:
Reflections – Beyond Just Tech¶
Soft-skill insights or workflow/communication/process reflections:
What I Consumed¶
A list of articles, papers, courses, or videos I read/watched/completed:
Read¶
- Design a Ride-Sharing Service Like Uber | Hello Interview
- Consistent Hashing | Hello Interview
- DynamoDB | Hello Interview
- Kafka | Hello Interview
- Lessons Learned from Running Debezium with PostgreSQL on Amazon RDS
- How Discord Stores Trillions of Messages
- Neon
- MindsDB
- Comprehensive Data Catalog Comparison
- Introducing BigQuery metastore, a unified metadata service with Apache Iceberg support
- Running Trino as exabyte-scale data warehouse
- Empowering self-serve data analytics with a text-to-SQL assistant at LinkedIn
- Best practices and insights when migrating to Apache Iceberg for data engineers
- Many clusters and only one gateway - Starburst, Naver, and Bloomberg at Trino Summit 2023
- Visualizing Trino with Superset - Preset at Trino Summit 2023
- Trino workload management - Airbnb at Trino Summit 2023
- An Introduction to the Hudi and Flink Integration
- Building a Real-time Data Lake with Flink CDC
- Evolution to the Data Lakehouse
- What is a data lakehouse? | Databricks Docs
- What's New in Apache Iceberg Format Version 3?
- Apache Iceberg™ v3: Moving the Ecosystem Towards Unification
- 12-Factor Agents
- Practical Guide for Model Selection for Real‑World Use Cases
- Featurestore at Agoda: How We Optimized Dragonfly for High-Performance Caching
- Revolutionizing Real-Time Streaming Processing: 4 Trillion Events Daily at LinkedIn
- Data versioning as your ‘Get out of jail' card – DVC vs. Git-LFS vs. dolt vs. lakeFS
- Unity Catalog | GitHub
- Exploring the Architecture of Apache Iceberg, Delta Lake, and Apache Hudi
- Hudi vs Iceberg vs Delta Lake: Data Lake Table Formats Compared
- Big Metadata: When Metadata is Big Data
- Vortex: A Stream-oriented Storage Engine For Big Data Analytics
- GitHub MCP Exploited: Accessing private repositories via MCP
Watched¶
- Introducing Lakebase - Databricks Co-founder & Chief Architect Reynold Xin
- CAP Theorem Simplified
- System Design Was HARD - Until You Knew the Trade-Offs
- 7 System Design Concepts Explained in 10 Minutes
- Supercharging Wise's Data Lake with Apache Iceberg
- How I build Agentic MCP Servers for Claude Code (Prompts CHANGE Everything)
- Apache Iceberg V3 and Beyond
- Apache Iceberg V3 Ahead
- Architecting an Iceberg Lakehouse
- Tampa Bay DE Meetup: The Who, What and Why of Data Lake Table Formats (Iceberg, Hudi, Delta Lake)
- Watch a Complete NOOB Try DuckDB and DuckLake for the first time
- Introducing DuckLake
- Next Steps: the ability to import and export from existing lakehouse formats like Iceberg and the ability to talk to more databases.
Completed Courses¶
Goals for Next Month¶
Set 2–3 simple goals to stay focused and accountable: