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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

I began writing this article in early July 2023 but began to feel a little underwhelmed by it and so left it unfinished. In this post, I’m going to break these processes down into each of: ? Caching them at the other end: How long should we cache files on a user’s device? in this article.

Cache 291
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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. Fault-tolerance. Interoperability with Hadoop.

Big Data 154
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Key Advantages of DBMS for Efficient Data Management

Scalegrid

This article cuts through the complexity to showcase the tangible benefits of DBMS, equipping you with the knowledge to make informed decisions about your data management strategies. It comprises a collection of interrelated data and a set of software tools that aid in the access, processing, and management of data.

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Maximally optimizing image loading for the web in 2021

CSS - Tricks

Set far-out expires headers on images and have a cache-busting strategy (like changing the file name). You need to make sure your AVIF version is both better and smaller, which feels like a manual process right now. Direct Link to Article — Permalink. Use content-visibility: auto; Send AVIF when you can.

Cache 119
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MySQL Performance Tuning 101: Key Tips to Improve MySQL Database Performance

Percona

A finely tuned database processes queries more efficiently, leading to swifter results. An unoptimized indexing strategy can impede data insertion and retrieval operations. Inefficient query design, such as utilizing SELECT * instead of specifying necessary columns, can escalate data transfer and processing overhead.

Tuning 52
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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

Over the course of this post, we will talk about our approach to this migration, the strategies that we employed, and the tools we built to support this. This allows the app to query a list of “paths” in each HTTP request, and get specially formatted JSON (jsonGraph) that we use to cache the data and hydrate the UI.

Latency 233
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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

Connection pooling: Minimizing connection overhead and improving response times for frequently accessed data by implementing mechanisms for connection pooling and caching strategies. Throughput: The throughput of an application is directly influenced by the speed at which the database can process and serve queries.

Tuning 52