· via AWS
Standing up an internal developer portal on AWS with Port: the productivity case, what a portal changes for teams and a fast path to a working one.
#aws #platform-engineering
· via Spacelift
MCP without the hype: the architecture, how servers and clients talk, a demo project, and where the protocol sits next to plain APIs and tools.
#ai-agents #devops-tooling
· via Spacelift
The three pillars treated practically: what metrics, logs and traces each answer, an OpenTelemetry implementation path and guidelines that scale.
#devops-tooling #platform-engineering
· via Spacelift
Release management that fits DevOps: the stages from planning to rollback, the friction points teams hit and practices that keep releases boring.
#devops-tooling #platform-engineering
· via StackGuardian
Where AI lands in platform work: infrastructure automation, smarter self-service, predictive reliability, security and cost, with adoption stages.
#platform-engineering #ai-agents
· via Spacelift
The AWS monitoring landscape mapped: native services and third-party tools compared, with the practices that make any of them actually useful.
#aws #devops-tooling
· via StackGuardian
Cloud security practices made enforceable: the implementation challenges, the practices worth codifying and turning both into automated guardrails.
#iac #devops-tooling #security
Reflections from KubeCon + CloudNativeCon Europe 2025 in London: AI-enabled platform engineering, unified observability, and FinOps as Kubernetes turns ten.
#kubernetes #opinion
· via Spacelift
Why teams overestimate their automation maturity: the gap between having pipelines and trusting them, the usual pitfalls, and ways to close it.
#opinion #iac #platform-engineering
· via Spacelift
EKS Auto Mode examined: what AWS now manages for you, how it compares with other EKS options, a deployment tutorial and where the limits sit.
#kubernetes #aws
· via Qodo
Test coverage beyond the percentage: what the metrics really measure, where AI improves gap analysis and generation, and the risks of trusting it.
#ai-agents #devops-tooling
· via Qodo
TDD and code assistants combined: how tests written first constrain generation, a working AI-TDD loop, and the advantages with their caveats.
#ai-agents #devops-tooling
· via Qodo
A selection checklist for AI code assistants: language support, integration, context handling, output quality, security terms, cost and team fit.
#ai-agents #devops-tooling
· via Spacelift
Two tools that keep getting compared for the wrong reasons: what each is for, where they genuinely overlap, and how they work well together.
#ansible #devops-tooling
· via Spacelift
Monitoring and observability separated properly: what each does, how they relate, when each is enough and how to build toward both sensibly.
#devops-tooling #platform-engineering
· via StackGuardian
The case for self-service infrastructure: what it is, the value for teams and organizations, an implementation path and the honest challenges.
#platform-engineering #iac
· via Spacelift
The DevOps numbers worth watching: DORA four plus the supporting metrics, how to implement the measurement and which tools track them honestly.
#devops-tooling #platform-engineering
AWS AI Practitioner Certification exam study notes, exam pointers, and cheat sheet.
#aws #certifications
· via AWS
Governance for big AWS estates: why reactive cleanup fails at scale, a proactive Terraform platform strategy and a real customer case applying it.
#aws #terraform #iac
· via Spacelift
The two Kubernetes node scaling approaches compared: how each provisions capacity, where they differ in practice and which fits which cluster.
#kubernetes #aws