A GitLab pipeline can build, test, and deploy successfully while still shipping a vulnerable package. Passing CI does not always mean the release is safe. It only means the checks you configured passed. That is why GitLab CI security scanning matters. Dependency scanning, secret detection, and package audits help teams catch vulnerable open source components before they reach production. GitLab Ultimate includes built-in security features, but Free and Premium users can still build strong pip... Read more ›
Wherein I realise pointed-headed bosses were right the whole time, and kloc is actually a really good metric for measuring teams. Read more ›
Free, comprehensive security reference guides for every major AWS service. Attack vectors, misconfigurations, CLI commands, and detection indicators - TocConsulting/aws-security-cards Read more ›
DevOps engineer building reliable cloud infrastructure, automated delivery pipelines, and thoughtful products with AWS, Docker, Kubernetes, and GitHub Actions. Read more ›
There's a moment in almost every RAG project where someone asks the question that decides your next two years of ops work: "Do we actually need a vector database, or can Postgres just do this?" It's a better question than it sounds, because the honest answer isn't "use Pinecone" or "use Postgres." It's "it depends on numbers you probably haven't measured yet": how many vectors, how aggressively you filter, how much you care about the absolute ceiling of queries per second. Most teams pick bas... Read more ›
The MCP Gateway Registry is an open-source (Apache 2.0 License) project from the Agentic Community that provides a single, governed control plane for every AI asset in an organization: MCP) servers, AI agents, skills, and custom assets. It is both a gateway (one entry point that routes client reques Read more ›
Analysts say Redmond still has billions of reasons to keep backing its flagship DBMS, even as Azure, Postgres, and AI hog the spotlight Read more ›
Databricks has unified analytical and transactional processing in its Lakehouse, and added large-sca ... Read more ›
From pretraining to RLHF/GRPO — every algorithm hand-written in pure PyTorch. Read more ›
Most Kubernetes observability failures aren't caused by a lack of data but by a lack of shared context between metrics, logs, traces, and infrastructure events. This article outlines a signal-first observability strategy built around consistent service identity, bounded metric cardinality, OpenTelemetry instrumentation, and unified event correlation, helping teams move from symptom to root cause without jumping across disconnected tools. Read more ›
New chapter in Learning data analytics and data science. The focus now is on Pandas as a Python library alongside Matplotlib and Seaborn for data visualization. Am writing this article to guide beginners who are already or beginning the data analytics and data science profession. Introduction to Python Data Analysis In modern world Data has become most valuable asset. Business, healthcare institutions, financial and even social media platforms rely heavily on data to make informed decisions. ... Read more ›
I’ve been working on in meshoptimizer recently; in the process I stumbled upon two optimizations that I did not end up using but I thought they might be fun to write about! The optimizations that actually made it in require some higher level background / explanations that will have to wait until another day :) Both optimizations discussed here touch upon two new (for me) features of AVX-512 that I haven’t had a chance to experiment with until now, and both apply to the same problem: how to de... Read more ›
Contextual valuation is a well-documented phenomenon in reinforcement learning, typically manifesting as range normalization in outcome representation. However, recent findings have revealed systematic deviations from this model, particularly when three options with equally spaced values are presented. In this study, we hypothesize that these distortions in outcome normalization arise from attentional processes. To test this, we conduct three experiments with 105 participants in total while s... Read more ›
I can't find a broad general-use benchmark for swarm intelligence comparable to the way LLMs have. Context: We've been building a swarm intelligence and looking to measure how accurate outcomes are compared to single model results. Suggestions welcome. Read more ›
Five surfaces collapsed into one declarative layer. Here's the full story of Materialized Lake Views in Microsoft Fabric - from syntax to the new GA capabilities The post appeared first on . Read more ›
We have the pleasure of celebrating the birthday of Blaise Pascal by announcing the release of OCaml version 5.5.0. Some of the highlights in OCaml 5.5.0 are: Module-dependent Functions Modules can now be used as function arguments in a form of lightweight functors. For instance, we can define a function for printing a map generated by the Map.Make functor: let pp_map (module M: Map.S) pp_key pp_v ppf set = if M.is_empty set then Format.fprintf ppf "ø" else let pp_sep ppf () = Fo... Read more ›
The ZFS partition/volume expansion is generally not an ultra hard task … but needs one step at a time approach. Today we will follow them one by one to expand GELI encrypted ZFS disk. There is only one potential problem – and I faced that recently with one of the other VMs I manage. If […] Read more ›
A repository for cody. Contribute to juancgarza/cody development by creating an account on GitHub. Read more ›
Introduction To master Power BI, you need to understand how data is structured, connected, and stored. Here is a comprehensive, structured guide to Modelling, Joins, Relationships, and Schemas in Power BI. Data Modeling in Power BI Data modeling is the process of identifying, organizing and defining the types of data a business collects and the relationships between them. It uses diagrams, symbols and textual definitions to visually represent how data is captured, stored and used. A well-desi... Read more ›