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Contents
Weekly Tech | Mar 10, 2025 | 10 Contents
Things I have learned about Tech Leadership
TechDocs at Grab: Cultivating a culture of quality documentation
GitHub for Beginners: How to get started with GitHub Copilot
Rain: A key-value store for Strava’s scale
Container orchestration: Docker Swarm vs Kubernetes
Standardizing UX at Scale: How Agoda Developed Its Experience Principles
How We Transformed Payment Rule Management with Git as a Database
Video: How to run dependency audits with GitHub Copilot
A case for QLC SSDs in the data center
Building a Spark observability product with StarRocks: Real-time and historical performance analysis
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1. Things I have learned about Tech Leadership
BBC Product & Technology - Medium
📣️ newtler Comments
This is recommended for anyone considering a role in tech leadership.
📄 Summary
Leadership involves empowering team members rather than micromanaging them.
Collective decision-making fosters motivation and better ideas than a top-down approach.
Building trust and maintaining good relationships are crucial for effective influence and team dynamics.
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2. TechDocs at Grab: Cultivating a culture of quality documentation
Grab Tech
📣️ newtler Comments
This is recommended for anyone looking to improve their organization's documentation culture.
📄 Summary
The TechDocs team at Grab implemented a Docs-as-Code approach to integrate documentation into engineering workflows, fostering a culture of quality documentation.
Key steps included assessing current processes, establishing clear policies, empowering teams with tools, and tracking metrics to celebrate successes.
Training and workshops were introduced to enhance writing skills and collaboration, while ongoing feedback loops were established to continuously improve documentation practices.
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3. GitHub for Beginners: How to get started with GitHub Copilot
The GitHub Blog
📣️ newtler Comments
This guide is essential for anyone looking to enhance their coding efficiency with AI assistance.
📄 Summary
GitHub Copilot is an AI pair programmer that helps users write code faster and is compatible with various IDEs.
The installation process varies by IDE, with detailed steps provided for both VS Code and JetBrains IDEs.
Users can utilize features like code completion and Copilot Chat to gain insights and improve their coding tasks.
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4. Rain: A key-value store for Strava’s scale
strava-engineering - Medium
📣️ newtler Comments
This is recommended for those looking to understand efficient data management at scale.
📄 Summary
Rain is a key-value store designed to handle large, immutable datasets efficiently, improving deployment times and reducing memory usage.
It leverages Apache Spark for data processing and allows for seamless updates and schema changes without service redeployment.
The system incorporates multiple caching layers to optimize data retrieval and supports local development environments for faster iteration.
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5. Container orchestration: Docker Swarm vs Kubernetes
Credera Engineering - Medium
📣️ newtler Comments
This article is essential for anyone deciding between Docker Swarm and Kubernetes for container orchestration.
📄 Summary
It outlines the strengths and weaknesses of both Docker Swarm and Kubernetes, helping users choose based on their project's complexity and scale.
Docker Swarm is highlighted for its simplicity, low resource overhead, and faster deployment, making it suitable for smaller environments.
Kubernetes is presented as the more robust option for large-scale applications, offering advanced features and extensive community support, albeit with a steeper learning curve.
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6. Standardizing UX at Scale: How Agoda Developed Its Experience Principles
Agoda Engineering - Medium
📣️ newtler Comments
This article is essential for understanding how to create a standardized UX framework in a global context.
📄 Summary
Agoda developed Experience Principles to ensure consistency and usability across its products, addressing the challenge of defining 'good UX'.
The principles were created through industry benchmarking, brainstorming workshops, and stakeholder alignment, focusing on intuitive design, trust, and inclusivity.
Integrating these principles into the design process has led to improved design quality, reduced UX issues, and a more collaborative environment.
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7. How We Transformed Payment Rule Management with Git as a Database
Agoda Engineering - Medium
📣️ newtler Comments
This article is highly beneficial for teams looking to improve their payment rule management processes.
📄 Summary
Agoda's Payment team faced challenges with traditional database management due to the complexity and risk of errors in modifying payment rules.
They implemented Git as a database, leveraging its version control, auditability, and structured review workflows to enhance rule management.
The new system allows for user-friendly management of rules, automated validation, and safer deployments, significantly improving efficiency and scalability.
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8. Video: How to run dependency audits with GitHub Copilot
The GitHub Blog
📣️ newtler Comments
This guide is essential for developers struggling with manual dependency management.
📄 Summary
It highlights the limitations of manual dependency audits, such as being error-prone and time-consuming.
The article provides a step-by-step approach to automate dependency management using GitHub Copilot, GitHub Actions, and Dependabot.
It emphasizes the benefits of automation, including improved security, reduced manual effort, and better documentation of dependency issues.
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9. A case for QLC SSDs in the data center
Engineering at Meta
📣️ newtler Comments
This is recommended for those exploring innovative storage solutions in data centers.
📄 Summary
QLC flash technology offers a balance between HDDs and TLC SSDs, providing higher density and improved power efficiency.
The adoption of QLC is expected to enhance server and rack-level byte densification while lowering acquisition and power costs.
Meta is actively integrating QLC storage into its data centers, recognizing its potential for optimizing storage cost, performance, and power efficiency.
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10. Building a Spark observability product with StarRocks: Real-time and historical performance analysis
Grab Tech
📣️ newtler Comments
This article is highly beneficial for those looking to enhance their Spark observability tools.
📄 Summary
It discusses the transition from a fragmented observability system to a unified platform using StarRocks, addressing previous limitations.
The new architecture simplifies data ingestion and management, allowing for real-time and historical performance analysis of Spark jobs.
Key features include materialised views for improved query performance, dynamic partitioning for efficient data management, and a comprehensive web application for user-friendly access.
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About newtler
This is a newsletter operated by newtler. ‘newtler’ is a social-based content reader service that allows you to receive new posts from any media of your choice, not just tech blogs, all in one place! 😎
Top comments (1)
Solid roundup this week! The BBC tech leadership piece highlights practical insights on trust and collective decision-making—useful for anyone stepping into that role. Grab’s TechDocs approach with Docs-as-Code is a smart way to embed documentation into workflows, especially for teams aiming to improve consistency. The GitHub Copilot guide is a handy starting point for beginners, though I’d like to see more on its limitations. Agoda’s UX principles and Git-as-database solutions also stand out for tackling real scalability challenges. Good mix of topics—worth a read!