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@kala shared a link, 3ย weeks, 4ย days ago
FAUN.dev()

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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@kala shared a link, 3ย weeks, 4ย days ago
FAUN.dev()

Claudeโ€™s next enterprise battle is not models: itโ€™s the agent control plane

New data shows Microsoft and OpenAI leading agent orchestration, but Anthropic's rising stake signals a shift in control of AI infrastructure. Anthropic's move from model to orchestration layer hints at a strategic battle over agent runtime platforms where operational AI work happens... read more ย 

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@kala shared a link, 3ย weeks, 4ย days ago
FAUN.dev()

Tokenomics: the 62.5-minute rule for Claude's cache

Ryan Skidmore works out the tokenomics of Anthropic's prompt cache and lands on a single rule: if you expect to need a cached prefix again within 62.5 minutes, keep refreshing it with cheap reads; past that, let it expire and rewrite, because a 5-minute cache write costs 1.25x base input and a read .. read more ย 

Tokenomics: the 62.5-minute rule for Claude's cache
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@devopslinks shared a link, 3ย weeks, 4ย days ago
FAUN.dev()

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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@devopslinks shared a link, 3ย weeks, 4ย days ago
FAUN.dev()

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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@devopslinks shared a link, 3ย weeks, 4ย days ago
FAUN.dev()

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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@devopslinks shared a link, 3ย weeks, 4ย days ago
FAUN.dev()

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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@devopslinks shared a link, 3ย weeks, 4ย days ago
FAUN.dev()

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, 3ย weeks, 5ย days 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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@cristiandeluxe started using tool WordPress , 3ย weeks, 5ย days ago.
Xygeni is an AI-powered Application Security (AppSec) and Software Supply Chain Security platform designed for modern AI-first development environments. It helps organizations secure the entire software development lifecycle (SDLC) (from code and dependencies to CI/CD pipelines, cloud infrastructure, and runtime applications) through a unified, developer-friendly platform.

Built to address the growing complexity of AI-assisted development, Xygeni combines SAST, SCA, DAST, IaC Security, Secrets Detection, CI/CD Security, Malware Defense, Build Security, and ASPM into a single platform with real-time visibility and risk-based prioritization.

Xygeni goes beyond traditional AppSec tooling by focusing on exploitability, remediation risk, and automation. Its AI-powered capabilities help teams detect vulnerabilities, malicious packages, secrets leakage, and supply chain attacks while automatically recommending or applying secure fixes directly inside IDEs, pull requests, and AI-assisted workflows.

The platform also provides advanced governance and visibility for modern AI-driven development practices, including copilots, agents, plugins, and autonomous workflows. Through Xygeni DevAI and CoreAI, security teams can enforce guardrails, automate remediation, analyze business impact, and reduce operational overhead without slowing developer productivity.

With integrated malware detection, runtime-aware prioritization, SBOM generation, artifact attestation, anomaly detection, and CI/CD protection, Xygeni enables organizations to proactively secure software delivery from code to cloud while maintaining compliance with evolving security frameworks and software supply chain standards.