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@laura_garcia shared a post, 5 hours ago
Software Developer, RELIANOID

💡 Third-Party Vendors: The Hidden Cybersecurity Risk

In today’s hyper-connected world, digital supply chains are only as secure as their weakest link. One single vendor can open the door to ransomware, outages, or worse. At RELIANOID, we take this risk seriously. 🔒 That’s why we apply: ✅ Continuous vendor risk assessments ✅ Real-time monitoring of thi..

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@varbear shared a link, 6 hours ago
FAUN.dev()

Unconventional PostgreSQL Optimizations

PostgreSQL 18 now supportsvirtual generated columns, indexable expressions without burning storage. Perfect for standardizing queries in analytics-heavy pipelines. Pair that withplanner constraint exclusion(constraint_exclusion=on), and Postgres can dodge irrelevant table scans based on constraints... read more  

Unconventional PostgreSQL Optimizations
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@varbear shared a link, 6 hours ago
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Software engineering when machine writes the code

In 1968, computer scientists identified the "software crisis" - the existing methods of programming were struggling to handle the power of computers. Today, AI coding assistants are accelerating productivity, but concerns arise about understanding the code they generate, the implications for debuggi.. read more  

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@varbear shared a link, 6 hours ago
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The challenges of soft delete

"Soft delete" sounds gentle. It isn't. Slapping adeleted_atcolumn on every table pollutes queries, drags down migrations, and leaves tombstones all over production. This post digs into saner options:PostgreSQL triggers,event archiving in the app layer, andCDC via WAL. Each separates the dead stuff f.. read more  

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@varbear shared a link, 6 hours ago
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How I Taught GitHub Copilot Code Review to Think Like a Maintainer

Vibe coding has made contributing to open source easier, but the high number of contributions to the AI agent framework goose has posed a challenge. An AI Code Review agent like Copilot can help review PRs, but tuning its feedback is crucial for reducing noise and increasing value. By providing clea.. read more  

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@kaptain shared a link, 7 hours ago
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Experimenting with Gateway API using kind

A new guide shows how to runGateway APIlocally withkindandcloud-provider-kind. It spins up a one-node Kubernetes cluster in Docker - complete with LoadBalancer Services and a Gateway API controller. Cloud vibes, zero cloud bill. Fire it up to deploy demo apps, test routing, or poke around with CRD e.. read more  

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@kaptain shared a link, 7 hours ago
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Cluster API v1.12: Introducing In-place Updates and Chained Upgrades

Cluster API v1.12.0 addsin-place updatesandchained upgrades, so machines can swap parts without going down, and clusters can jump versions without drama. KubeadmControlPlaneandMachineDeploymentsnow choose between full rollouts or surgical patching, depending on what changed. The goal: keep clusters .. read more  

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@kaptain shared a link, 7 hours ago
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Ingress NGINX: Statement from the Steering and Security Response Committees

Kubernetes is cutting offIngress NGINXin March 2026. No more updates. No bug fixes. No security patches. Done. Roughly half of cloud-native setups still rely on it, but it's been understaffed for years. If you're one of them, it's time to move. There’s no plug-and-play replacement, but the ecosystem.. read more  

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@kaptain shared a link, 7 hours ago
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Run a Private Personal AI with Clawdbot + DMR

Clawdbot just plugged intoDocker Model Runner (DMR). That means you can now run your own OpenAI-compatible assistant, locally, on your hardware. No cloud. No per-token fees. No data leaking into the void!.. read more  

Run a Private Personal AI with Clawdbot + DMR
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@kaptain shared a link, 7 hours ago
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New Conversion from cgroup v1 CPU Shares to v2 CPU Weight

A new quadratic formula now mapscgroup v1 CPU sharestocgroup v2 CPU weight. Why? Because the old linear approach messed with CPU fairness; especially at low share values. This fix nails prioritization where it counts. It lands at theOCI runtime layer, live inrunc v1.3.2andcrun v1.23, so containers 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).