NEWS! High demand: #JCON2026 workshops are live. #GenAI #RAG #Caching & security – with #Java experts @rick_ossies @TimteBeek @MohammadAliEN @svenruppert @brunoborges @sKriemhild & ...
Tickets are limited. Some may get a free @jcon_conference pass.
Read: https://javapro.io/2026/03/16/high-demand-workshops-at-jcon-europe-2026-tickets-available-now/
Your Rails app reruns the same queries and renders the same HTML on every request. Rails has 5 built-in caching strategies and most devs use maybe 1.
Russian doll caching is the one that changes everything. Nest caches, add touch: true, only the changed record re-renders.
Full tutorial with code.
#rubyonrails #caching #performance #SQL #Code #Rails #Ruby
https://medium.com/@heyjoshlee/getting-started-with-caching-in-ruby-on-rails-0c3f346132c6
#Development #Comparisons
Native JSON modules are finally real · From build-time convenience to a runtime primitive https://ilo.im/16bfm8
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#JSON #ESM #Caching #Runtime #Bundlers #Browsers #WebDev #Frontend #JavaScript
Need efficient in-memory caching that automatically handles memory pressure? 𝑁𝑆𝐶𝑎𝑐ℎ𝑒 offers a robust solution - but only if you understand its constraints and best uses.
🔗: https://livsycode.com/best-practices/nscache-in-swift-a-practical-guide/ by Artem Mirzabekian
Greetings, traveler! Caching rarely looks like a hard problem—until an app starts rendering heavy feeds, repeatedly mapping rich text, or decoding the same assets on every scroll. At that point, the difference between “working” and “smooth” is often a cache layer placed in the right spot. On iOS, NSCache is a great fit for this
A full day. Only workshops. Real Java problems. Testing, #SupplyChainSecurity #Caching #Performance #GenAI & #RAG — with @FHHabermann @rick_ossies @TimteBeek @MohammadAliEN @svenruppert @brunoborges @sKriemhild & more.
Which one’s yours? More: https://javapro.io/2026/03/16/high-demand-workshops-at-jcon-europe-2026-tickets-available-now/
So, decided to get them rookie `/queue` numbers up so did a quick bit of caching. For a 12-job queue, I went from 240 RPS (Python/Flask) to 680 (Golang/Gin) then to 3400 RPS with some proper caching. The `/workers` endpoint would benefit as well, but I think its performant enough though I may end up adding a bit of caching later.
Hot on the heels of sitting on it for more than a year, and finally getting around to fixing ancient bugs and performance shortcomings...
NEW: slabbis v0.1.2
slabbis is a Go cache library with an optional Redis-compatible server. Embed it directly in your Go service for in-process performance, or run it standalone over RESP2 — same cache, same interface, two deployment models.
Repo:
https://github.com/ha1tch/slabbis#readme
Release
https://github.com/ha1tch/slabbis/releases/tag/v0.1.2
v0.1.2 is a focused performance release. The short version: MGET went from the weakest operation to beating Redis outright, and tail latency on mixed workloads dropped significantly. A new perf/ directory ships a full benchmark report with charts.
Highlights
% Cache.GetInto — zero-allocation sibling of GetCopy
% Server GET and MGET now use a sync.Pool
% MGET streaming response: array header written first
% MGET throughput: 68k --> 162k ops/s (RESP), now ahead of Redis at 145k/s
% MGET in-process: 804k --> 1.86M ops/s; p999 1.70ms --> 64µs
% perf/ — benchmark report (LaTeX + matplotlib) with five charts comparing in-process vs slabbis-RESP vs Redis across two versions
Changelog:
https://github.com/ha1tch/slabbis/blob/main/CHANGELOG.md
#golang #foss #cache #redis #performance #programming #cache #caching #cloud #redis
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