docs(posts): reflect the cloud-native-ref refactor in past-year posts (EN/FR)

content/en/post/crossplane_composition_functions/index.md

@@ -60,12 +60,14 @@ These steps are performed in a specific order:
 3. Deployment of various configurations using the previously installed providers, especially the **`Compositions`** and **`Composition Functions`**.
 4. Declarations of _Claims_ to consume the Compositions.
 
-These steps are described through [Flux](https://fluxcd.io/)'s dependencies and can be viewed [here](https://github.com/Smana/demo-cloud-native-ref/tree/main/infrastructure/base/crossplane).
+These steps are described through [Flux](https://fluxcd.io/)'s dependencies and can be viewed [here](https://github.com/Smana/cloud-native-ref/tree/3d095dfb726b941d15d8ef6768211a6880170cee/infrastructure/base/crossplane).
 
 {{% notice tip "Sources" %}}
-All the actions carried out in this article come from this [**git repository**](https://github.com/Smana/demo-cloud-native-ref).
+All the actions carried out in this article come from this [**git repository**](https://github.com/Smana/cloud-native-ref).
 
 There you can find numerous sources that help me construct my blog posts. 🎄 🎁 Feedback is a gift 🙏
+
+The file links below are pinned to the commit from the time of writing, so they show the exact code quoted here. The compositions have since been rewritten in KCL and moved to the [crossplane-configuration](https://github.com/Smana/crossplane-configuration) repository.
 {{% /notice %}}
 
 ## 📦 The Compositions
@@ -87,7 +89,7 @@ Based on the [configuration-rds](https://github.com/upbound/configuration-rds) c
 ❓ How would this _Composition_ then be used if, for example, a developer wishes to have a database?
 They is simply done by declaring a _**Claim**_ which represents the level of abstraction exposed to the users. Let's get a closer look 🔍
 
-[tooling/base/harbor/sqlinstance.yaml](https://github.com/Smana/demo-cloud-native-ref/blob/main/tooling/base/harbor/sqlinstance.yaml)
+[tooling/base/harbor/sqlinstance.yaml](https://github.com/Smana/cloud-native-ref/blob/3d095dfb726b941d15d8ef6768211a6880170cee/tooling/base/harbor/sqlinstance.yaml)
 
 ```yaml
 apiVersion: cloud.ogenki.io/v1alpha1
@@ -118,7 +120,7 @@ Here we observe that it boils down to a **simple** resource with few parameters
 
 * A **PostgreSQL** instance version 15 will be created.
 * The **instance type** is at the discretion of the platform team (the maintainers of the composition). In the above `Claim`, we ask for a small instance, which is interpreted by the composition as `db.t3.small`.
-[infrastructure/base/crossplane/configuration/sql-instance-composition.yaml](https://github.com/Smana/demo-cloud-native-ref/blob/main/infrastructure/base/crossplane/configuration/sql-instance-composition.yaml#L150C18-L150C18)
+[infrastructure/base/crossplane/configuration/sql-instance-composition.yaml](https://github.com/Smana/cloud-native-ref/blob/3d095dfb726b941d15d8ef6768211a6880170cee/infrastructure/base/crossplane/configuration/sql-instance-composition.yaml#L150C18-L150C18)
 ```yaml
 transforms:
   - type: map
@@ -128,7 +130,7 @@ transforms:
       small: db.t3.small
 ```
 
-* The `master` user's password is retrieved from a `harbor-pg-masterpassword` secret, retrieved from an [External Secret](https://github.com/Smana/demo-cloud-native-ref/blob/main/tooling/base/harbor/externalsecret-sqlinstance-password.yaml).
+* The `master` user's password is retrieved from a `harbor-pg-masterpassword` secret, retrieved from an [External Secret](https://github.com/Smana/cloud-native-ref/blob/3d095dfb726b941d15d8ef6768211a6880170cee/tooling/base/harbor/externalsecret-sqlinstance-password.yaml).
 * Once the instance is created, the connection details are stored in a **secret** `xplane-harbor-rds`.
 
 This is where we can fully appreciate the **power of Crossplane Compositions**! Indeed, **many resources** are provisionned under the hood, as illustrated by the following diagram:
@@ -166,7 +168,7 @@ The [**EnvironmentConfigs**](https://docs.crossplane.io/latest/concepts/environm
 
 Since the EKS cluster is created with [Opentofu](https://opentofu.org/), we store its properties using Flux variables. (more info on Flux's variables substitution [here](https://blog.ogenki.io/post/terraform-controller/#substition-de-variables))
 
-[infrastructure/base/crossplane/configuration/environmentconfig.yaml](https://github.com/Smana/demo-cloud-native-ref/blob/main/infrastructure/base/crossplane/configuration/environmentconfig.yaml)
+[infrastructure/base/crossplane/configuration/environmentconfig.yaml](https://github.com/Smana/cloud-native-ref/blob/3d095dfb726b941d15d8ef6768211a6880170cee/infrastructure/base/crossplane/configuration/environmentconfig.yaml)
 
 ```yaml
 apiVersion: apiextensions.crossplane.io/v1alpha1
@@ -187,7 +189,7 @@ data:
 
 These variables can then be used in _Compositions_ via the **`FromEnvironmentFieldPath`** directive. For instance, to allow pods to access our RDS instance, we allow the VPC's CIDR as follows:
 
-[infrastructure/base/crossplane/configuration/irsa-composition.yaml](https://github.com/Smana/demo-cloud-native-ref/blob/main/infrastructure/base/crossplane/configuration/irsa-composition.yaml)
+[infrastructure/base/crossplane/configuration/sql-instance-composition.yaml](https://github.com/Smana/cloud-native-ref/blob/3d095dfb726b941d15d8ef6768211a6880170cee/infrastructure/base/crossplane/configuration/sql-instance-composition.yaml#L85-L105)
 
 ```yaml
 - name: SecurityGroupIngressRule
@@ -218,7 +220,7 @@ These functions are executed in a **sequential** manner (in `Pipeline` mode), wi
 
 But **let's get back to our RDS composition 🔍!** It indeed uses this new way of defining `Compositions` and consists of three steps:
 
-[infrastructure/base/crossplane/configuration/sql-instance-composition.yaml](https://github.com/Smana/demo-cloud-native-ref/blob/main/infrastructure/base/crossplane/configuration/sql-instance-composition.yaml)
+[infrastructure/base/crossplane/configuration/sql-instance-composition.yaml](https://github.com/Smana/cloud-native-ref/blob/3d095dfb726b941d15d8ef6768211a6880170cee/infrastructure/base/crossplane/configuration/sql-instance-composition.yaml)
 
 ```yaml
 apiVersion: apiextensions.crossplane.io/v1

content/en/post/series/agentic_ai/ai-coding-agent/index.md

@@ -18,7 +18,7 @@ thumbnail = "thumbnail.png"
 +++
 
 {{% notice info "Update 2026-08-18" %}}
-After several months of using [Superpowers](https://github.com/obra/superpowers), I moved [cloud-native-ref](https://github.com/Smana/cloud-native-ref) over to it entirely: the in-house SDD variant described below is now retired. The reasoning behind it — platform constitution, review personas, verification against a real cluster — still holds; what changed is the mechanism. I cover this in [part 2 of the series](/post/series/agentic_ai/ai-coding-tips/).
+After several months of using [Superpowers](https://github.com/obra/superpowers), I moved [cloud-native-ref](https://cnref.ogenki.io) over to it entirely: the in-house SDD variant described below is now retired. The reasoning behind it — platform constitution, review personas, verification against a real cluster — still holds; what changed is the mechanism. I cover this in [part 2 of the series](/post/series/agentic_ai/ai-coding-tips/).
 {{% /notice %}}
 
 We can all see it — AI is shaking things up in a major way. The field is evolving so fast that keeping up with every new development is nearly impossible. As for measuring the impact on our daily lives and how we work, it's still too early to tell. One thing is certain though: in tech, it's a **revolution**!
@@ -40,7 +40,7 @@ Most importantly, I'll try to demonstrate through concrete examples that this ne
   <tr>
     <td><img src="repo_gift.png" style="width:80%;"></td>
     <td style="vertical-align:middle; padding-left:10px;" width="70%">
-The examples below come from my work on the <strong><a href="https://github.com/Smana/cloud-native-ref">Cloud Native Ref</a></strong> repository. It's a full-fledged platform combining EKS, Cilium, VictoriaMetrics, Crossplane, Flux and many other tools.
+The examples below come from my work on the <strong><a href="https://cnref.ogenki.io">Cloud Native Ref</a></strong> project (<a href="https://github.com/Smana/cloud-native-ref">source on GitHub</a>). It's a full-fledged platform running on both AWS EKS and GCP GKE, combining Cilium, VictoriaMetrics, Crossplane, Flux and many other tools.
     </td>
   </tr>
 </table>
@@ -343,7 +343,7 @@ For those steeped in Kubernetes, here's an analogy 😉: the spec defines the **
 {{% notice tip "My SDD variant for Platform Engineering" %}}
 > **Update 2026-08-18** — this in-house workflow has been replaced by [Superpowers](https://github.com/obra/superpowers). The section is kept as written: it describes what actually ran for several months.
 
-For [cloud-native-ref](https://github.com/Smana/cloud-native-ref), I created a variant inspired by GitHub Spec Kit that I'm evolving over time. I'll admit it's still quite experimental, but the results are already impressive.
+For [cloud-native-ref](https://cnref.ogenki.io), I created a variant inspired by GitHub Spec Kit that I'm evolving over time. I'll admit it's still quite experimental, but the results are already impressive.
 
 **🛡️ Platform Constitution** — Non-negotiable principles are codified in a [constitution](https://github.com/Smana/cloud-native-ref/blob/main/docs/platform-constitution.md): `xplane-*` prefix for IAM scoping, mandatory zero-trust networking, secrets via External Secrets only. Claude checks every spec and implementation against these rules.
 
@@ -562,5 +562,5 @@ Given my affinity for open source, I'm looking at exploring open alternatives: *
 - [Building Effective Agents](https://www.anthropic.com/research/building-effective-agents) — Anthropic Research
 
 ### Resources
-- [Cloud Native Ref](https://github.com/Smana/cloud-native-ref) — My reference repo
+- [Cloud Native Ref](https://cnref.ogenki.io) — My reference platform · [GitHub repo](https://github.com/Smana/cloud-native-ref)
 - [SWE-bench Leaderboards](https://www.swebench.com/) — Reference benchmark

content/en/post/series/agentic_ai/ai-coding-tips/index.md

@@ -41,7 +41,7 @@ Let's be honest: once you're used to Claude Code, expectations run high. I won't
 
 * **Skills**: specialized capabilities loaded on demand (creating PRs, security audits, writing designs)
 * **Subagents and hooks**: automatic triggers (desktop notification, pre-commit validation) and delegation to isolated contexts
-* **SDD** with **superpowers**: I tried several flavours (github-specs, gsd); this is the one I settled on, for how simple it is to use while still guaranteeing a complete workflow that respects good practices — [cloud-native-ref](https://github.com/Smana/cloud-native-ref) moved over to it entirely in August 2026
+* **SDD** with **superpowers**: I tried several flavours (github-specs, gsd); this is the one I settled on, for how simple it is to use while still guaranteeing a complete workflow that respects good practices — [cloud-native-ref](https://cnref.ogenki.io) moved over to it entirely in August 2026
 * **Automode** on POCs, with a careful review of the first iteration before letting it run
 
 This workflow plays to **Claude's specific strengths**: Opus reasoning on the critical passages, the 1M context window in beta, and very reliable _function-calling_.
@@ -71,7 +71,7 @@ Files are **cumulative**: Claude loads all of them from most global to most loca
 
 ### What I put in mine
 
-Here's what the `CLAUDE.md` for [cloud-native-ref](https://github.com/Smana/cloud-native-ref) actually contains:
+Here's what the `CLAUDE.md` for [cloud-native-ref](https://github.com/Smana/cloud-native-ref/blob/main/CLAUDE.md) actually contains:
 
 - **Build/test/lint commands** — the first lines, so Claude knows how to validate its work
 - **Project conventions** — `xplane-*` prefix for IAM, Crossplane composition structure, KCL patterns
@@ -80,7 +80,7 @@ Here's what the `CLAUDE.md` for [cloud-native-ref](https://github.com/Smana/clou
 
 What I **don't** put in it: exhaustive documentation (that's what [Skills](/post/series/agentic_ai/ai-coding-agent/#skills-unlocking-new-powers) are for), long code examples (I reference existing files instead), and obvious instructions Claude already knows.
 
-Here's a condensed excerpt from the `CLAUDE.md` of [cloud-native-ref](https://github.com/Smana/cloud-native-ref) to illustrate:
+Here's a condensed excerpt from the `CLAUDE.md` of [cloud-native-ref](https://github.com/Smana/cloud-native-ref/blob/main/CLAUDE.md) to illustrate:
 
 ```markdown
 ## Common Commands

content/en/post/series/agentic_ai/llm-self-hosted-stack/index.md

@@ -38,7 +38,7 @@ This article aims to **lay the foundations** of an alternative meant to evolve a
 * Honestly evaluate what works, what doesn't, and what it really costs
 
 {{% notice tip "The reference repo" %}}
-The whole stack is deployed via GitOps from [**cloud-native-ref**](https://github.com/Smana/cloud-native-ref) — beyond the LLM layer, the repo illustrates **a complete cloud-native ecosystem**:
+The whole stack is deployed via GitOps from [**cloud-native-ref**](https://cnref.ogenki.io) ([source on GitHub](https://github.com/Smana/cloud-native-ref)) — beyond the LLM layer, the project illustrates **a complete cloud-native ecosystem**, running on both AWS EKS and GCP GKE:
 
 * **GitOps** — Flux, continuous reconciliation
 * **Platform engineering** — Crossplane (one YAML claim generates all the Kubernetes plumbing)
@@ -67,7 +67,7 @@ The whole thing is driven by **GitOps** (Flux reconciles everything from [`cloud
 
 ## :electric_plug: The centerpiece: the `InferenceService` abstraction
 
-If you've read some of [my previous articles](/post/crossplane_composition_functions/), you know I particularly like `Crossplane` for providing the right abstraction to end users. It's one of my essential components and lets me expose a **simple, fit-for-purpose interface**. I already have a few: `App`, `SQLInstance`, `EPI` — and now `InferenceService`.
+If you've read some of [my previous articles](/post/crossplane_composition_functions/), you know I particularly like `Crossplane` for providing the right abstraction to end users. It's one of my essential components and lets me expose a **simple, fit-for-purpose interface**. I already have a few: `App`, `SQLInstance`, `EPI` — and now `InferenceService`. All of them are packaged and versioned in a dedicated repository: [crossplane-configuration](https://github.com/Smana/crossplane-configuration).
 
 ### Declaring a new model
 
@@ -135,8 +135,8 @@ Four lines change. Flux reconciles, KEDA readjusts triggers, Karpenter provision
 {{% notice tip "KCL: version, test, validate a composition" %}}
 The composition isn't written as YAML patches (unreadable, untestable) but in [**KCL**](https://kcl-lang.io/) via the [function-kcl](https://github.com/crossplane-contrib/function-kcl) — a **typed** configuration language with **native assertions**. Three direct consequences:
 
-* **Unit tests** — a [`main_test.k`](https://github.com/Smana/cloud-native-ref/blob/main/infrastructure/base/crossplane/configuration/kcl/inference-service/main_test.k) file validates each behavior (`kcl test` runs in CI on every PR).
-* **Versioned OCI packaging** — the composition is published as an OCI image (`oci://ghcr.io/smana/cloud-native-ref/crossplane-inference-service:0.6.0`), referenced by immutable tag.
+* **Unit tests** — a [`main_test.k`](https://github.com/Smana/crossplane-configuration/blob/main/apis/inferenceservice/kcl/main_test.k) file validates each behavior (`kcl test` runs in CI on every PR).
+* **Versioned OCI packaging** — the composition is published as a Crossplane Configuration package (`ghcr.io/smana/crossplane-configuration-aws:v0.4.1`) from the dedicated [crossplane-configuration](https://github.com/Smana/crossplane-configuration) repository, referenced by immutable tag.
 * **Claim schema validated at the API server** — `kubectl apply` rejects inconsistent claims (e.g. `minReplicas > maxReplicas`) **before** the composition is even triggered.
 
 Versions, tests, schema — not just "YAML we copy-paste".
@@ -425,7 +425,7 @@ Let's be clear: today I wouldn't trade my Claude ecosystem. Mainly for **financi
 
 That said, I would have liked to push my use of **OpenCode** further and migrate my Claude setup (skills, MCPs, sub-agents) onto that backend for good — that may be the topic of a future article dedicated to this open-source coding agent.
 
-But I'm keeping the stack alive. The day a Qwen3-Coder-30B-A3B runs cleanly on a quantized L4 — a path documented in [`docs/llm-platform-future-paths.md`](https://github.com/Smana/cloud-native-ref/blob/main/docs/llm-platform-future-paths.md) — the swap will be a few-line PR. That's the **main point** of this demo: positioning yourself to **move fast when the time comes**, rather than scrambling to (re)build everything the day open-weight catches up to the frontier.
+But I'm keeping the stack alive. The day a Qwen3-Coder-30B-A3B runs cleanly on a quantized L4 — a path documented in the [AI platform roadmap](https://cnref.ogenki.io/docs/platform/ai-platform/roadmap/) — the swap will be a few-line PR. That's the **main point** of this demo: positioning yourself to **move fast when the time comes**, rather than scrambling to (re)build everything the day open-weight catches up to the frontier.
 
 And this catch-up isn't only about models: the open-source serving layer evolves just as fast and regularly brings in capabilities previously reserved for proprietary solutions. For instance, [**vLLM-Omni**](https://github.com/vllm-project/vllm-omni) (first stable late 2025) extends `vLLM` to **omni-modality** (text, image, audio, video, as **inputs and outputs**) with the same OpenAI-compatible API, so it plugs directly into the platform described here.
 
@@ -436,9 +436,10 @@ And this catch-up isn't only about models: the open-source serving layer evolves
 ## :bookmark: References
 
 ### Repos
-- [`cloud-native-ref`](https://github.com/Smana/cloud-native-ref) — The complete platform
-- [`docs/decisions/`](https://github.com/Smana/cloud-native-ref/tree/main/docs/decisions) — ADRs (vLLM Production Stack, S3 Files…)
-- [`docs/llm-platform-future-paths.md`](https://github.com/Smana/cloud-native-ref/blob/main/docs/llm-platform-future-paths.md) — Evolution paths
+- [`cloud-native-ref`](https://cnref.ogenki.io) — The complete platform documentation · [source on GitHub](https://github.com/Smana/cloud-native-ref)
+- [`crossplane-configuration`](https://github.com/Smana/crossplane-configuration) — The Crossplane compositions (`App`, `SQLInstance`, `InferenceService`…)
+- [Architecture decisions](https://cnref.ogenki.io/docs/decisions/) — ADRs (vLLM Production Stack, S3 Files…)
+- [AI platform roadmap](https://cnref.ogenki.io/docs/platform/ai-platform/roadmap/) — Evolution paths
 
 ### Technical components
 - [vLLM Production Stack](https://github.com/vllm-project/production-stack) — Production-grade LLM inference

content/en/post/series/observability/logs/index.md

@@ -345,7 +345,7 @@ And start using the Web UI which is exposed using [Cilium and Gateway API resour
 </center>
 
 {{% notice tip "⚙️ Deployment: where to find the full configuration" %}}
-All the configuration used for writing this article can be found in the <strong><a href="https://github.com/Smana/cloud-native-ref">Cloud Native Ref</a></strong> repository.</br>
+All the configuration used for writing this article can be found in the <strong><a href="https://cnref.ogenki.io">Cloud Native Ref</a></strong> project (<a href="https://github.com/Smana/cloud-native-ref">source on GitHub</a>).</br>
 
 The ambition of this project is to be able to <strong>quickly start a complete platform</strong> that applies best practices in terms of automation, monitoring, security, etc. </br>