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@kala shared a link, 2ย weeks ago
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AI Is Doing the Testing Now

Brijesh Deb's third "comfortable lie" of software testing is that AI is now doing the testing: coverage dashboards hit 80%+, regression suites maintain themselves, and leadership concludes that risk is handled, while the experienced testers who knew the domain quietly get redeployed or made redundan.. read more ย 

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@devopslinks shared a link, 2ย weeks ago
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Shift Left Did Not Fix It

Shift left has become a buzzword, but merely moving testing earlier doesn't address the core issue of authority and decision-making in quality assurance. AI may offer quicker testing, but it doesn't comprehend risk like human testers do - beware the dangerous lie that AI can replace thorough, critic.. read more ย 

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Terraform is dead

Graham Gilbert argues Terraform is effectively dead, kept alive only by inertia: HCL forced engineers to translate intent (the diagrams, paragraphs, and constraints that actually describe systems) into a DSL that nobody naturally thinks in, while fragmenting infrastructure, application logic, polici.. read more ย 

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The invisible engineering behind Lambdaโ€™s network

AWS engineers explain how the Lambda team rebuilt VPC networking so they can keep per-invocation setup off the hot path and run dense microVM workers at scale... read more ย 

The invisible engineering behind Lambdaโ€™s network
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Finding zombies in our systems: A real-world story of CPU bottlenecks

After a network outage crisis, Pinterest's ML Platform team discovered high Kubernetes agent CPU usage was causing critical Ray training job failures. The team's deep profiling strategy revealed a rarely seen flaw in how Kubelet was handling memory cgroup iterations... read more ย 

Finding zombies in our systems: A real-world story of CPU bottlenecks
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AI in SRE: What's Actually Coming in 2026

AI in SRE is evolving, with true value in Root Cause Analysis and Pre-Change Impact Analysis, not autonomous remediation or AI replacing SREs - it's about collaboration and focus evolution... read more ย 

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@laura_garcia shared a post, 2ย weeks ago
Software Developer, RELIANOID

๐—Ÿ๐—ถ๐—ป๐˜‚๐˜… ๐—ธ๐—ฒ๐—ฟ๐—ป๐—ฒ๐—น ๐˜ƒ๐˜‚๐—น๐—ป๐—ฒ๐—ฟ๐—ฎ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐—ถ๐—ฒ๐˜€

๐Ÿ” ๐—Ÿ๐—ถ๐—ป๐˜‚๐˜… ๐—ธ๐—ฒ๐—ฟ๐—ป๐—ฒ๐—น ๐˜ƒ๐˜‚๐—น๐—ป๐—ฒ๐—ฟ๐—ฎ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐—ถ๐—ฒ๐˜€ are once again forcing enterprises to rethink ๐™ž๐™ฃ๐™›๐™ง๐™–๐™จ๐™ฉ๐™ง๐™ช๐™˜๐™ฉ๐™ช๐™ง๐™š ๐™จ๐™š๐™˜๐™ช๐™ง๐™ž๐™ฉ๐™ฎ ๐™ฅ๐™ง๐™ž๐™ค๐™ง๐™ž๐™ฉ๐™ž๐™š๐™จ. The recent disclosure of โ€œ๐—–๐—ผ๐—ฝ๐˜† ๐—™๐—ฎ๐—ถ๐—นโ€ and โ€œ๐——๐—ถ๐—ฟ๐˜๐˜† ๐—™๐—ฟ๐—ฎ๐—ดโ€ highlights how kernel-level flaws can rapidly evolve into major risks for cloud environments, containers, Kubernetes clusters, and cr..

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AWX is the open source, community supported upstream project for Red Hat Ansible Automation Platform, formerly known as Ansible Tower. It gives teams a web based interface, a full REST API, and a distributed task engine on top of Ansible, turning command line playbook runs into a managed, auditable automation service.

The project began at AnsibleWorks as the commercial Ansible Tower product, and after Red Hat acquired Ansible, it open sourced the codebase as AWX in September 2017, positioning it as the development ground where new features land before they are hardened into the supported Automation Platform controller. With AWX, you organize automation around projects (synced from Git or other source control), inventories (static or dynamically pulled from cloud providers), credentials (stored encrypted and injected at runtime), and job templates that tie a playbook to its inventory and credentials. On top of that, it adds role based access control, a visual dashboard, job scheduling, workflow chaining, webhooks, and real time job output, so multiple teams can run, track, and delegate automation without sharing SSH keys or sitting at a terminal.

Modern AWX runs on Kubernetes or OpenShift through the AWX Operator, which manages installation, upgrades, and scaling declaratively, reflecting its shift from a single host application to a cloud native, container based platform. Because it is the upstream of a paid product, AWX moves fast and ships frequently, which makes it ideal for labs, learning, and self managed deployments, though teams needing formal support and long term stability typically run the downstream Automation Platform instead.