Tag
A blog post describing a custom inter-mesh deployment pipeline that bridges staging and production environments using NATS, with a focus on auditability, security, and remedying environment drift.
This blog post argues that GitHub Actions lacks static OIDC audience constraints, unlike GitLab CI/CD, and that this design weakness poses an increasing security risk as OIDC-based federation becomes more common.
An essay arguing that infrastructure tools like Terraform, Chef, Puppet, and Ansible failed to implement promise theory's autonomous agent model, and that LLMs finally supply the missing reasoning layer for truly autonomous infrastructure agents.
A GitHub repository featuring 151 real DevOps/SRE interview records from 85 companies. Questions were recorded verbatim by candidates and cover Kubernetes, Docker, Terraform, AWS, CI/CD, and more, making it convenient for job seekers to prepare by company or topic.
A DevOps engineer recounts interviewing the infrastructure team at ngrok to compare how other teams handle technical disagreements, prompting a personal reexamination of his own work relationships and career.
An analysis of how platform engineering must evolve for AI agents, shifting from rigid golden paths to composable, API-first building blocks that support non-human identities, scoped permissions, and audit trails.
The GitHub outage highlights the fragility of centralized control planes for AI agents, prompting a call for open, decentralized, agent-native build infrastructure with gitlawb cited as an emerging example.
GitHub Actions and Pages are experiencing degraded availability, with workflow runs failing or delayed and some API requests returning errors. GitHub engineers are investigating and applying mitigations.
Cognition's Devin Outposts can now run on Vercel Sandbox, giving developers isolated microVMs with Docker, VPN, and filesystem snapshots for building and testing apps.
Matt Godbolt explains how Compiler Explorer runs on AWS in 2026, covering CloudFront, load balancing, auto-scaling fleets, and infrastructure-as-code with Terraform.
A technical blog post exploring why Karpenter's node consolidation appears counter-intuitive, with cluster capacity staying constant while nodes constantly churn, and explaining the underlying mechanics.
An educational guide that breaks down each stage of a production deployment—builds, artifacts, database migrations, health checks, rolling updates, and rollbacks—and discusses when to use a PaaS versus running your own deployment infrastructure.
The article explains that BYOC (Bring Your Own Cloud) is a spectrum of deployment models, including BYOC-Account, BYOC-VPC, BYOC-K8s, and air-gapped environments, driven by customer needs for data residency, security, cost alignment, and data gravity.
DanKornas announces Harness Open Source, an open source development platform featuring code hosting, automated DevOps pipelines, hosted development environments, and artifact registries.
An essay arguing that software engineers repeatedly reinvent well-solved infrastructure like auth, background jobs, rate limiting, and feature flags, trading proven solutions for custom code that they must maintain and debug.
A technical analysis of why .env files became a de facto configuration standard despite lacking schema, spec, and security semantics, and why teams should replace them with more durable declarations.
This talk explains how to use Nix to achieve full reproducibility from development environments, builds, to cloud deployments, and showcases Antithesis's Nix-based "command set" framework as a replacement for messy scripts.
A developer reflects on moving AI agent workflows to a server and discovering that boring infrastructure concerns like systemd, logging, idempotency, and failure alerts matter more than the agent itself.
This blog post argues that GitHub's collaboration paradigm (branches, pull requests, code reviews) is ill-suited for the modern AI-driven software development era where LLMs and agents generate code at high velocity, calling for rethinking of tools and workflows.
A developer highlights the difficulty of tracking AI agents and non-human identities in modern environments, noting that many agents spin up and disappear without visibility.