Documenting code, one commit at a time.
The devlog-ist/landing project focuses on creating a compelling landing experience. Recent work centered on improving SEO and ensuring proper sitemap discovery.
The Cloudflare CDN was overriding the application's robots.txt, which prevented search engines from discovering the sitemap. This negatively impacted SEO performance.
To bypass the CDN override, a
Maintaining a consistent URL structure is crucial for search engine optimization (SEO). Duplicate content, even with slight variations in the URL (like the presence or absence of "www"), can confuse search engines and dilute your website's ranking potential.
Search engines like Google treat example.com and `www.example.
We've recently refactored and optimized our AI token usage tracking to improve performance and maintainability. This involved extracting duplicated queries and enhancing user filtering.
The primary focus was on improving the efficiency of retrieving daily and monthly tenant AI usage data. This was achieved through two key changes:
Application performance is often a critical factor in user experience and overall system efficiency. This post delves into several strategies for enhancing performance, focusing on database query optimization, efficient data handling, and code-level improvements.
Inefficient database queries can be a major bottleneck. One common issue is the N+1
This post explores several strategies for optimizing data access within an application, focusing on caching and query reduction techniques. Efficient data handling is crucial for maintaining performance, especially as application scale.
Caching is a fundamental technique for reducing database load and improving response times.
We recently optimized a background job responsible for post-generation in our application, specifically focusing on how it handles premium access checks. Initially, the job was configured to check user-level premium access, which led to inefficiencies. This post outlines the problem, the solution, and the benefits we observed.
Developers often strive for efficiency, but sometimes, optimizing too early can lead to more problems than solutions.
Optimizing code before understanding its performance bottlenecks can waste time and introduce unnecessary complexity. It's tempting to micro-optimize, but it's crucial to identify the actual performance-critical sections first.
This post delves into optimizing SQL queries for product ranking and data aggregation, focusing on common pitfalls and effective strategies to enhance performance and accuracy. We'll explore techniques to address memory errors, improve query speed, and ensure data integrity when dealing with complex relationships and large datasets.
