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Developers don’t care about Kubernetes clusters

Most cloud-native tools obsess over clusters. Not developers. That means poor support for things like promoting code between environments or deploying by feature - not just by repo. The author pushes for a better way: platforms that hide the Kubernetes mess and tame CI/CD. Think feature-driven deplo.. read more  

Developers don’t care about Kubernetes clusters
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udwall: A Tool for Making UFW and Docker Play Nice With Each Other

Hexmos droppedudwall, a declarative firewall manager that finally makesUFWandDockerplay nice. Docker’s notorious for bulldozing past UFW rules via iptables. udwall patches that hole. It syncs rules across both, auto-reconciles changes, backs up configs, and plugs cleanly intoAnsible. No more duct-ta.. read more  

udwall: A Tool for Making UFW and Docker Play Nice With Each Other
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Turning Kubernetes Last Access to Kubernetes Least Access Using KIEMPossible

KIEMPossible is a new open-source tool for Kubernetes entitlement cleanup. It maps out who has access to what - roles, entities, permissions - and shows how those are actually used across your clusters. Think of it as a permission microscope for AKS, EKS, GKE, and even the DIY K8s crowd. It breaks d.. read more  

Turning Kubernetes Last Access to Kubernetes Least Access Using KIEMPossible
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The Grafana trust problem

Grafana’s been busy clearing the shelves.Grafana Agent,Agent Flow, andOnCall? All deprecated. The replacement:Grafana Alloy- a one-stop observability agent that handles logs, metrics, traces, and OTEL without flinching. Meanwhile,Mimir 3.0ships with a Kafka-powered ingestion pipeline. More scalabili.. read more  

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Kubernetes Configuration Good Practices

Stripped down and sharp, the blog lays out Kubernetes config best practices: keep YAML manifests in version control, use Deployments (not raw Pods), and label like you mean it - semantically, not just alphabet soup. It digs into sneaky pain points too, like how YAML mangles booleans (yes≠true), and .. read more  

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You Want Microservices—But Do You Need Them?

Amazon Prime Video ditched its pricey microservices maze and rebuilt as asingle-process monolith, cutting ops costs by 90%. No big press release. Just results. Same move from Twilio Segment. And Shopify. Both pulled their tangled systems back intomodular monoliths- cleaner, faster, easier to test, a.. read more  

You Want Microservices—But Do You Need Them?
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How I Built a 100% Offline “Second Brain” for Engineering Docs using Docker & Llama 3 (No OpenAI)

Senior Automation Engineer built an offline RAG system for technical documents using Ollama, Llama 3, and ChromaDB in a Dockerized microservices architecture. The system enables efficient retrieval and generation of information from PDFs with a streamlined UI. The deployment package, including compl.. read more  

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How to Evaluate LLMs Without Opening Your Wallet

A new mock-based framework lets QA and automation folks stress-test LLM outputs - no API calls, no surprise charges. It runs entirely local, usingpytest fixtures, structured test flows, and JSON schema checks to keep things tight. Test logic stays modular. Cross-validation’s baked in. And if you nee.. read more  

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I tested ChatGPT’s backend API using RENTGEN, and found more issues than expected

A closer look at OpenAI’s API uncovers some shaky ground: misconfiguredCORS headers, missingX-Frame-Options, noinput validation, and borkedHTTP status handling. Large uploads? Boom..crash!CORS preflightrequests? Straight-up denied. So much for smooth browser support... read more  

I tested ChatGPT’s backend API using RENTGEN, and found more issues than expected
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1,500+ PRs Later: Spotify’s Journey with Our Background Coding Agent

Spotify just gave its internal Fleet Management tooling a serious brain upgrade. They've wired inAI coding agentsthat now handle source-to-source transformations across repos - automatically. So far? Over 1,500 AI-generated PRs pushed. Not just lint fixes - these include heavy-duty migrations. They'.. read more  

1,500+ PRs Later: Spotify’s Journey with Our Background Coding Agent
BigQuery is a cloud-native, serverless analytics platform designed to store, query, and analyze massive volumes of structured and semi-structured data using standard SQL. It separates storage from compute, automatically scales resources, and eliminates the need for infrastructure management, indexing, or capacity planning.

BigQuery is optimized for analytical workloads such as business intelligence, log analysis, data science, and machine learning. It supports real-time data ingestion via streaming, batch loading from cloud storage, and federated queries across external data sources like Cloud Storage, Bigtable, and Google Drive.

Query execution is distributed and highly parallel, enabling interactive performance even on petabyte-scale datasets. The platform integrates deeply with the Google Cloud ecosystem, including Looker for BI, Vertex AI for ML workflows, Dataflow for streaming pipelines, and BigQuery ML, which allows users to train and run machine learning models directly using SQL.

Built-in security features include fine-grained IAM controls, column- and row-level security, encryption by default, and audit logging. BigQuery follows a consumption-based pricing model, charging for storage and queries (on-demand or reserved capacity).