Richard COURTOIS

Let's talk about - Redis ➸ Redis wasn't born in a lab – it was born from frustration. 😉 How? ➸ Back in 2009, Salvatore Sanfilippo needed a faster way to analyze website traffic for his startup. Existing databases just couldn't keep up. ➸ So, he built his own solution => Redis (a super-fast data store that lives in your computer's memory.) It was a game-changer, and it's still transforming how we handle data today. 📌 𝐋𝐞𝐭'𝐬 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝 𝐢𝐧 𝐝𝐞𝐭𝐚𝐢𝐥. Redis => REmote DIctionary Server ◾ initially designed to be a remote data structure server accessible over the network. ◾ open-source, in-memory data store. ◾ functions mainly as a key-value database ◾ but goes beyond by offering a variety of data structures like strings, lists, sets, sorted sets, hashes etc. ◾ primarily resides in RAM, providing incredibly fast read and write operations. ◾ options for persistence to disk, ensuring data durability. 𝐑𝐞𝐝𝐢𝐬 𝐢𝐬 𝐟𝐚𝐬𝐭. 𝐖𝐡𝐲? As we discussed, Unlike traditional databases that primarily store data on disk, Redis keeps its entire dataset in memory (RAM). This eliminates the latency associated with disk seeks and reads, allowing for very fast data access. 📌 𝐑𝐄𝐒𝐏 𝐏𝐫𝐨𝐭𝐨𝐜𝐨𝐥 => REdis Serialization Protocol ◾ Redis uses its own binary-safe protocol called RESP for communication. - designed for simplicity and efficiency - less overhead as compared to text-based protocols like HTTP 📌 𝐄𝐯𝐞𝐧𝐭 𝐋𝐨𝐨𝐩 𝐚𝐧𝐝 𝐈/𝐎 𝐌𝐮𝐥𝐭𝐢𝐩𝐥𝐞𝐱𝐢𝐧𝐠 ◾ The heart of Redis => event loop. (single-threaded) ◾ continuously monitors file descriptors (sockets) for client connections and incoming commands. ◾ event-driven architecture, combined with I/O multiplexing (epoll, kqueue, or select) => allows Redis to handle thousands of concurrent clients efficiently without the overhead of multiple threads. ◾ non-blocking I/O operations - not waiting for I/O operations to complete - main thread remains responsive and can quickly process other commands ◾ if main thread encounters a time-consuming operation (like accessing the disk or network), it doesn't halt and wait => delegates the task to the operating system and registers a callback function to be executed once the operation completes. 📌 𝐌𝐞𝐦𝐨𝐫𝐲 𝐅𝐫𝐚𝐠𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐣𝐞𝐦𝐚𝐥𝐥𝐨𝐜 ◾ Redis uses a memory allocator called jemalloc to manage memory efficiently. ◾ Jemalloc helps reduce memory fragmentation, which can occur when objects are allocated and freed repeatedly. 📌 𝐑𝐞𝐝𝐢𝐬 𝐨𝐟𝐟𝐞𝐫𝐬 𝐯𝐚𝐫𝐢𝐨𝐮𝐬 𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐦𝐨𝐝𝐞𝐬. ◾ Standalone - A single instance of Redis. ◾ Cluster - A distributed implementation for scalability and high availability. ◾ Sentinel - High availability for standalone or replicated Redis instances. ◾ Replication - Master-replica setup for data redundancy and read scalability. __ 👍 Follow - Mayank 🗒️ Free Newsletter - https://lnkd.in/dJByxEYY #softwaredevelopment #redis #databases

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Have you ever wondered why AI isn’t delivering weekly, QA-ready product versions yet? Have you questioned whether AI is just another buzzword… or something much bigger? The truth is — the challenge isn’t really the tech. It’s change management. It’s job security anxiety. And often, it’s simply not knowing how to truly leverage AI to build better and faster. We’re not in a tech limitation era anymore. We’re in a mindset limitation era. I wrote a blog unpacking why AI can build, but organizations often can’t let it.

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There's a renewed focus on developer productivity in many organisations, especially with AI coding assistants promising massive gains. But it only really matters if we can measure developer productivity properly in the first place, and then notice how AI is actually shifting things. Laura Tacho, CTO at DX, and someone whose work I am a huge fan of, has an online course on measuring developer productivity and AI impact. But as often happens, the timing wasn't great for those of us in the southern hemisphere. Thankfully, Laura has just added a session that does work for Australia/NZ! 📅 Thursday Sept 4th 🕔 17:00 Sydney / 19:00 Auckland It's a 1-hour live coaching session plus 15+ self-paced videos, a workbook, and a reading list. Link in the comments.

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COBOL isn't dead. In fact, it's running your money right now. The reality nobody talks about: → 95% of ATM transactions run on COBOL → 43% of banking systems depend on it → $3 trillion in daily transactions processed → 70% of business systems still use it But here's the real problem... The average COBOL developer is 55+ years old. They're retiring fast. New grads aren't learning it. Most companies are panicking, rushing to "modernize." But the smart ones know better... Because rewriting these systems costs millions more than maintaining them. And most modernization projects? They fail. While others scramble tomorrow, the prepared companies are quietly investing in COBOL expertise today. That's how the biggest organizations stay ahead - they see opportunity where others see obsolescence.

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