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@varbear shared a link, 9 hours ago
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I built a programming language using Claude Code

Cutlet usesClaude Code. The LLM emits every line. Source, build steps, and examples live on GitHub. It runs on macOS and Linux and ships aREPL. It supports arrays, strings, double numbers, a vectorizingmeta-operator, zip/filter indexing, prototypal inheritance, and a mark-and-sweepGC. Development ra.. read more  

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@varbear shared a link, 9 hours ago
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Using Rust and Postgres for everything: patterns learned over the years

Rust and PostgreSQL are considered the best tools in the software world due to their performance and reliability. Rewriting a backend service from Go to Rust led to significant improvements in processing speed and memory usage. Using sqlx for database operations and leveraging PostgreSQL features li.. read more  

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Why value streams and capability maps are your new governance control plane

The piece flips enterprise AI fromgenerativetoagentic. Agents getstructured autonomyto perceive, plan, and execute across systems. It turnsvalue streammaps into a control plane withautonomy zones,halt-on-exceptiongates, cryptographicflight recorders, andpolicy-as-code. Result: less hallucination and.. read more  

Why value streams and capability maps are your new governance control plane
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@varbear shared a link, 9 hours ago
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A new chapter for the Nix language, courtesy of WebAssembly

Determinate Nix introduces experimental WebAssembly host calls. It lets Nix invoke Wasm modules, pass and return complex Nix values, and support Rust, C++, and Zig toolchains. It runs on Wasmtime/Cranelift and slashes runtime and memory: Fibonacci test 0.33s vs 79.33s, 30MB vs 4.5GB. Per-call instan.. read more  

A new chapter for the Nix language, courtesy of WebAssembly
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@varbear shared a link, 9 hours ago
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Cracking the Python Monorepo

Outlines a Python monorepo setup that pairsuvworkspaces withDaggerandBuildKitcaching. Builds container stages programmatically. Keeps things cache-friendly and predictable. Parsespyproject.tomland extracts the workspace graph. Copies required local packages into intermediate stages. Installs them in.. read more  

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@kaptain shared a link, 9 hours ago
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Running Agents on Kubernetes with Agent Sandbox

Agent Sandbox unveils the Sandbox CRD to map long-lived, singleton AI agents onto Kubernetes. It adds stable identity and lifecycle primitives. It supports runtimes like gVisor and Kata Containers. It enables zero-scale resume. It includes SandboxWarmPool with SandboxClaim and SandboxTemplate to kil.. read more  

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@kaptain shared a link, 9 hours ago
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RAM is getting expensive, so squeeze the most from it

The Register contrastszramandzswap. It flags a patch that claims up to 50% fasterzramops. It notes Fedora enableszramby default. It details thatzramprovides compressed in‑RAM swap (LZ4).zswapcompresses pages before writing to disk and requires on‑disk swap... read more  

RAM is getting expensive, so squeeze the most from it
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@kaptain shared a link, 9 hours ago
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Securing Production Debugging in Kubernetes

The post prescribes an on-demand SSH gateway pod. It usesshort-lived, identity-bound credentialsandKubernetes RBACto grant scoped, auditable debug sessions. It recommends anaccess brokerthat binds Roles to groups, issues ephemeral certs and OpenSSH user certificates, rotates CAs, enforces command-le.. read more  

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The Invisible Rewrite: Modernizing the Image Promoter

SIG Release rewrote theimage promotercore. It cut 20% of the code. It added apipeline engine,cosignsigning, andSLSAattestations. Signing now sits separate fromsignature replication. Registry reads run in parallel - plan time dropped ~20m → ~2m. Per-request timeouts, retries, and HTTP connection reus.. read more  

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Kubernetes v1.36 - Sneak Peek

Kubernetes v1.36 (Apr 22, 2026) enablesHPAScaleToZeroby default. That lets theHPAuseminReplicas: 0and read only controller-owned pod metrics. The release swaps long-lived image-pull secrets forephemeral KSA tokens. It deprecatesIPVS, retiresIngress NGINX, and aligns withcontainerd 2.x. The release f.. read more  

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).