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@devopslinks shared a link, 1ย month, 3ย weeks ago
FAUN.dev()

Figma's next-generation data caching platform

Figma rearchitected their storage systems to support scalability, including horizontally sharding their Postgres stack and building FigCache, a stateless proxy service for Redis. FigCache decouples connection scalability from Redis, centralizes traffic routing, enhances security, and provides end-to.. read more ย 

Figma's next-generation data caching platform
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@devopslinks shared a link, 1ย month, 3ย weeks ago
FAUN.dev()

Reducing our monorepo size to improve developer velocity

Dropbox cut itsmonorepofrom 87GB to 20GB. It ran a GitHubโ€‘approved serverโ€‘sidegit repack, tuned bywindow/depth. Clone times dropped to under 15 minutes. Engineers traced growth to Gitโ€™s 16โ€‘char path heuristic. That heuristic mispairedi18nfiles. They tested--path-walklocally, then ran phased replica .. read more ย 

Reducing our monorepo size to improve developer velocity
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@devopslinks shared a link, 1ย month, 3ย weeks ago
FAUN.dev()

Donโ€™t trust, verify

Daniel Stenberg, creator of curl, argues that software security should be built on verification rather than trust, outlining the many ways a widely used project like curl could be compromised - from malicious insiders and breached credentials to hacked distribution sites and CI tool exploits. To cou.. read more ย 

Donโ€™t trust, verify
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@laura_garcia shared a post, 1ย month, 3ย weeks ago
Software Developer, RELIANOID

how to migrate ADC services from Array Networks APV Series to RELIANOIDโ€”step by step.

Migrating from legacy ADC platforms doesnโ€™t have to be complex. In our latest Knowledge Base article, we walk you through how to migrate ADC services from Array Networks APV Series to RELIANOIDโ€”step by step. ๐Ÿ” What youโ€™ll find inside: - Clear terminology mapping between both platforms - Practical mi..

Knowledge base migrate ADC services from ARRAY NETWORKS APV SERIES to RELIANOID
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@laura_garcia shared a post, 1ย month, 4ย weeks ago
Software Developer, RELIANOID

DevOpsCon Amsterdam 2026

- ๐——๐—ฒ๐˜ƒ๐—ข๐—ฝ๐˜€๐—–๐—ผ๐—ป ๐—”๐—บ๐˜€๐˜๐—ฒ๐—ฟ๐—ฑ๐—ฎ๐—บ ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ ๐—ถ๐˜€ ๐—ท๐˜‚๐˜€๐˜ ๐—ฎ๐—ฟ๐—ผ๐˜‚๐—ป๐—ฑ ๐˜๐—ต๐—ฒ ๐—ฐ๐—ผ๐—ฟ๐—ป๐—ฒ๐—ฟ! - Amsterdam, Netherlands April 20โ€“24, 2026 Simplify complexity, amplify agility, and accelerate innovation. Join DevOpsCon Amsterdam 2026 โ€” one of the leading conferences for professionals working with CI/CD, Kubernetes, Platform Engineering, ..

devopscon amsterdam april 26
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@sanjayjoshi shared a post, 1ย month, 4ย weeks ago

10+ Shadcn Table Components, Blocks & Tools

A curated list of Shadcn table components and blocks you can use in React and Next.js projects to build clean, flexible, and production-ready data tables faster.

Thumbnail Shadcn Table
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@sancharini shared a post, 1ย month, 4ย weeks ago

Black Box Testing Techniques to Improve Test Coverage

Learn black box testing techniques to improve test coverage. Explore methods like equivalence partitioning, boundary value analysis, and more with practical examples.

black box testing techniques
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@laura_garcia shared a post, 1ย month, 4ย weeks ago
Software Developer, RELIANOID

๐—ช๐—ผ๐—ฟ๐—น๐—ฑ ๐—ค๐˜‚๐—ฎ๐—ป๐˜๐˜‚๐—บ ๐——๐—ฎ๐˜†

๐Ÿš€ ๐—ช๐—ผ๐—ฟ๐—น๐—ฑ ๐—ค๐˜‚๐—ฎ๐—ป๐˜๐˜‚๐—บ ๐——๐—ฎ๐˜† ๐—ถ๐˜€ ๐—ต๐—ฒ๐—ฟ๐—ฒโ€ฆ and itโ€™s not just science fiction anymore. Quantum computing is rapidly moving from theory to realityโ€”and with it comes a ๐—บ๐—ฎ๐˜€๐˜€๐—ถ๐˜ƒ๐—ฒ ๐˜€๐—ต๐—ถ๐—ณ๐˜ ๐—ถ๐—ป ๐—ฐ๐˜†๐—ฏ๐—ฒ๐—ฟ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜† that organizations simply canโ€™t ignore. Hereโ€™s the uncomfortable truth: ๐Ÿ‘‰ The same technology that promises breakthrou..

quantum_computing_relianoid
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@hamzmu shared a link, 1ย month, 4ย weeks ago
Fellow, Rootly

Using Graphify to turn Incident Data into a Knowledge Graph

Karpathy said we should build LLM knowledge bases. 48 hours later made Graphify was made: one command, full semantic knowledge graph.

We applied the idea to incident data turning them into a queryable and interactable semantic graph. This lets us see past fixes, predict failures, cluster services, cut alert noise, and reveal team load in seconds.

If youโ€™re using Rootly, here is a small plugin to explore your incident data.

Check it out: github.com/Rootly-AI-Labs/rootly-graphify-importer

Interactive knowledge graph visualization of incident management data showing clustered services, alerts, and responders with connected nodes and relationships in Graphify
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@laura_garcia shared a post, 1ย month, 4ย weeks ago
Software Developer, RELIANOID

Strengthen Your MFA with Google Authenticator and RELIANOID

๐Ÿ” Strengthen Your MFA with Google Authenticator and RELIANOID At RELIANOID, we take authentication seriously. We've just published a new technical guide on how to integrate Google Authenticator into the RELIANOID MFA Portal, using Active Directory or LDAP to manage user secrets. โœ… Understand TOTP vs..

2FA with AD_LDAP and Google Authenticator
GPT (Generative Pre-trained Transformer) is a deep learning model developed by OpenAI that has been pre-trained on massive amounts of text data using unsupervised learning techniques. GPT is designed to generate human-like text in response to prompts, and it is capable of performing a variety of natural language processing tasks, including language translation, summarization, and question-answering. The model is based on the transformer architecture, which allows it to handle long-range dependencies and generate coherent, fluent text. GPT has been used in a wide range of applications, including chatbots, language translation, and content generation.

GPT is a family of language models that have been trained on large amounts of text data using a technique called unsupervised learning. The model is pre-trained on a diverse range of text sources, including books, articles, and web pages, which allows it to capture a broad range of language patterns and styles. Once trained, GPT can be fine-tuned on specific tasks, such as language translation or question-answering, by providing it with task-specific data.

One of the key features of GPT is its ability to generate coherent and fluent text that is indistinguishable from human-generated text. This is achieved by training the model to predict the next word in a sentence given the previous words. GPT also uses a technique called attention, which allows it to focus on relevant parts of the input text when generating a response.

GPT has become increasingly popular in recent years, particularly in the field of natural language processing. The model has been used in a wide range of applications, including chatbots, content generation, and language translation. GPT has also been used to create AI-generated stories, poetry, and even music.