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Worktrees: Git's best kept secret (and why you should use them)

Git worktrees have been around since 2015, but few devs use them like they could. They let you work on multiple branches at once—each in its own directory—without the usual stash-switch-stash-repeat dance. The real power move? Pair them with abare repo. That gives you a clean, central base where ea.. read more  

Worktrees: Git's best kept secret (and why you should use them)
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Using DuckDB in AWS Lambda

DuckDB is an open-source in-process SQL OLAP database management system optimized for analytical queries. It can efficiently handle large datasets in a memory-efficient manner, making it suitable for serverless architectures. A DuckDB Lambda layer can be used to run performant queries on remote data.. read more  

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Dynamo, DynamoDB, and Aurora DSQL

Marc Brooker breaks down the jump fromAmazon DynamotoDynamoDBandAurora DSQL, tracing how the guts of cloud databases have changed. It’s a story about dropping old trade-offs and picking up stronger guarantees. DynamoDB ditches the old hash-ring replication for multi-AZ replica sets backed by Paxos... read more  

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Best Linux distro for developers of 2025

TechRadar rounds up the best Linux distros for devs.Manjarodelivers Arch power without the pain.DebianandUbuntu LTShold steady for those who put uptime over edge.Fedorakeeps the new stuff flowing. Solusrolls with a tight curation hand—smooth updates, no chaos.Mocaccinoaims at Gentoo lovers who want.. read more  

Best Linux distro for developers of 2025
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Can LLMs replace on call SREs today?

ClickHouse ran five LLMs through an autonomous root cause gauntlet using OpenTelemetry data. None nailed it solo. OpenAI’s o3 and Claude Sonnet 4 came closest. GPT-4.1 was the cheapest brain on the block. Things got weird under the hood. Token usage spiked unpredictably. Queries slammed observabili.. read more  

Can LLMs replace on call SREs today?
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Hunting Living Secrets: Secret Validity Checks Arrive in GitHub Advanced Security for Azure DevOps

GitHub Advanced Security for Azure DevOps just got sharper: it now checks if leaked secrets are actuallyvalid. Secrets are flagged asActiveorUnknownby pinging providers in real time. No setup needed. It auto-kicks in for supported secret types. Why care?Because not every secret leak is an emergenc.. read more  

Hunting Living Secrets: Secret Validity Checks Arrive in GitHub Advanced Security for Azure DevOps
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Kubernetes v1.34 Sneak Peek: A Game-Changer for the Kubernetes Expert’s Lifecycle

Kubernetes v1.34 lands August 2025 with a clear agenda: smarter scheduling, tighter control, fewer surprises. Dynamic Resource Allocationgoes stable, letting clusters actually reason about GPUs, FPGAs, and NICs. AI/ML and HPC jobs stop guessing and start requesting what they need. ServiceAccount t.. read more  

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Kubernetes Learning Roadmap

The Kubernetes Learning Roadmap covers key concepts such as understanding Kubernetes use cases, installing Kubernetes locally, interacting with Kubernetes using YAML and kubectl, managing deployments and replica sets, and networking in Kubernetes. Additionally, it includes topics like managing envir.. read more  

Kubernetes Learning Roadmap
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5 of the best distros for building Kubernetes clusters

More devs are spinning upKubernetes clusters on stripped-down Linux distros—thinkRaspberry Pi OS,Debian,Talos Linux,Fedora CoreOS. MicroK8s and k3s make low-power, ARM-first deployments feel less like a science project. Talos Linux? It’s the wildcard—API-only node opsand animmutable, locked-down de.. read more  

5 of the best distros for building Kubernetes clusters
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Critical Kubernetes Capsule Vulnerability Allows Arbitrary Namespace Label Injection

Capsule v0.10.3had a problem. Tenant users could sneak their own labels into system namespaces—an easy way to punch holes in Kubernetes multi-tenancy. v0.10.4shuts that down. It tightens namespace validation and clamps down on label injection... 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).