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@varbear shared a link, 1 month, 2 weeks ago
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Use Python for Scripting!

Shell scripts love to break across macOS and Linux. Blame all the GNU vs BSD quirks;sed,date,readlink, take your pick. The mess adds up fast, especially in build pipelines and CI systems. This post makes the case for a cleaner way:Python 3. Standard library. Predictable behavior. Same results whethe.. read more  

Use Python for Scripting!
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How Reddit Migrated Comments Functionality from Python to Go

Reddit successfully migrated its monolithic, high-traffic Comments service from legacy Python to modern Go microservices with zero user disruption. This was achieved by using a "tap compare" for reads and isolated "sister datastores" for writes, ensuring safe verification of the new code against pro.. read more  

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14x Faster Faceted Search in PostgreSQL with ParadeDB

ParadeDB brings Elasticsearch-stylefacetingtoPostgreSQL, ranked search results and filter counts, all in one shot. No extra passes. It pulls this off with a customwindow function, planner hooks, andTantivy's columnar index under the hood. That's how they’re squeezing out10×+ speedupson hefty dataset.. read more  

14x Faster Faceted Search in PostgreSQL with ParadeDB
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@kaptain shared a link, 1 month, 2 weeks ago
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Why Kubernetes Won: Perfect Timing & Developer Culture

Kubernetes won big because the stars aligned, DevOps took off, Docker exploded, and enterprises finally stopped side-eyeing open source. Then came the institutional tailwind: CNCF pushed hard, GCP bet big, and the rest followed. Kubernetes isn't just tech. It's a new operating model, built in the op.. read more  

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An In-Depth Look at Istio Ambient Mode with Calico

Tigera just wiredIstio Ambient Modeinto Calico. That means you getsidecarless service mesh, think mTLS, L4/L7 policy, and observability, without stuffing every pod with a sidecar. It’s all handled by lean zTunnel and Waypoint proxies. Ports stay visible, soCalico and Istio policiesplay nice. No rewr.. read more  

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Kubernetes Made Simple: A Guide for JVM Developers

A sharp walkthrough for JVM devs shipping aKotlin Spring Boot app on Kubernetes. It covers the full deployment arc, packaging with Docker, wiring upDeploymentandServicemanifests, and managing config withConfigMapsandSecrets. There's a cleanPostgreSQLintegration baked in. It even gets intoheader-base.. read more  

Kubernetes Made Simple: A Guide for JVM Developers
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A Deep Dive into Kubernetes Headless Service

Headless Serviceis a powerfulKubernetesfeature enabling direct pod-to-pod communication forstateful applicationsand preciseservice discoverywithout traditional load balancing.No automatic load balancing, pod IP changes, andspecial use casesmake it ideal for specific scenarios, not general workloads... read more  

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@kaptain shared a link, 1 month, 2 weeks ago
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Kubernetes 1.35 - New security features

Kubernetes 1.35 is done with legacy baggage. cgroups v1? Deprecated. Image pull credentials? Now re-verified by default—no more freeloading. kubectl SPDY API upgrades? Locked down. You’ll needcreatepermissions just to speak the protocol. Expect breakage if your workflows leaned on old assumptions. U.. read more  

Kubernetes 1.35 - New security features
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The “Inception” of Kubernetes: A Deep Dive into vCluster Architecture and Benefits

vCluster, a CNCF sandbox project, spins up real-deal Kubernetes control planes inside pods. Each lives in its own namespace but behaves like a full cluster, admin access, CRDs, Helm, the works. It reuses the host’s worker nodes using a syncer that routes vCluster workloads onto the real thing... read more  

The “Inception” of Kubernetes: A Deep Dive into vCluster Architecture and Benefits
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Compose to Kubernetes to Cloud With Kanvas

Docker just droppedKanvas, a new visual toy for building multi-cloud Kubernetes setups, without drowning in YAML. It bolts onto Docker Desktop and runs onMeshery. Drag and drop services into a topology, then bring them to life across AWS, GCP, or Azure. Mix inpolicy-driven validationandreal-time mut.. read more  

Compose to Kubernetes to Cloud With Kanvas
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.