- [Docs] Renamed Blog to Changelog, plus reorganized posts

- [Docs] Added the `0.15.1` post to `Changelog`
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diff --git a/README.md b/README.md
@@ -29,11 +29,10 @@ Supported providers: AWS, GCP, Azure, Lambda, TensorDock, Vast.ai, and DataCrunc
 
 ## Latest news ✨
 
-- [2024/01] [dstack 0.15.0: Resources, authentication, and more](https://dstack.ai/blog/2024/02/08/resources-authentication-and-more/) (Release)
-- [2024/01] [dstack 0.14.0: OpenAI-compatible endpoints preview](https://dstack.ai/blog/2024/01/19/openai-endpoints-preview/) (Release)
-- [2023/12] [dstack 0.13.0: Disk size, CUDA 12.1, Mixtral, and more](https://dstack.ai/blog/2023/12/22/disk-size-cuda-12-1-mixtral-and-more/) (Release)
-- [2023/11] [dstack 0.12.3: Vast.ai integration](https://dstack.ai/blog/2023/11/21/vastai/) (Release)
-- [2023/10] [dstack 0.12.2: TensorDock integration](https://dstack.ai/blog/2023/10/31/tensordock/) (Release)
+- [2024/01] [dstack 0.15.1: Kubernetes integration preview](https://dstack.ai/changelog/0.15.1/) (Release)
+- [2024/01] [dstack 0.15.0: Resources, authentication, and more](https://dstack.ai/changelog/0.15.0/) (Release)
+- [2024/01] [dstack 0.14.0: OpenAI-compatible endpoints preview](https://dstack.ai/changelog/0.14.0/) (Release)
+- [2023/12] [dstack 0.13.0: Disk size, CUDA 12.1, Mixtral, and more](https://dstack.ai/changelog/0.13.0/) (Release)
 
 ## Installation
 

diff --git a/docs/blog/index.md b/docs/blog/index.md
@@ -1 +1,2 @@
-# Blog
+# Blog
+
diff --git a/docs/blog/posts/say-goodbye-to-managed-notebooks.md b/docs/blog/posts/say-goodbye-to-managed-notebooks.md
@@ -1,14 +1,11 @@
 ---
-title: Say goodbye to managed notebooks!
 date: 2023-06-29
 description: Discover how cloud dev environments can benefit ML engineers and why why they are gaining popularity over managed notebooks .
 slug: say-goodbye-to-managed-notebooks
 ---
 
 # Say goodbye to managed notebooks
 
-__Why managed notebooks are losing ground to cloud dev environments.__
-
 Data science and ML tools have made significant advancements in recent years. This blog post aims to examine the
 advantages of cloud dev environments (CDE) for ML engineers and compare them with web-based managed notebooks.
 

diff --git a/docs/blog/.authors.yml → docs/changelog/.authors.yml b/docs/blog/.authors.yml → docs/changelog/.authors.yml
diff --git a/docs/changelog/index.md b/docs/changelog/index.md
@@ -0,0 +1 @@
+# Changelog
diff --git a/...sts/lambda-cloud-ga-and-docker-support.md → docs/changelog/posts/0.10.5.md b/...sts/lambda-cloud-ga-and-docker-support.md → docs/changelog/posts/0.10.5.md
@@ -1,15 +1,11 @@
 ---
 date: 2023-07-14
 description: The latest update improves Lambda integration and adds custom Docker images support.
-slug: "lambda-cloud-ga-and-docker-support"
-categories:
-- Releases
+slug: "0.10.5"
 ---
 
 # dstack 0.10.5: Lambda integration, Docker support, and more
 
-__The latest release improves Lambda Cloud integration and adds support for Docker.__
-
 In the previous update, we added initial integration with <a href="https://lambdalabs.com" target="_blank">Lambda Cloud</a>. With today's release, this integration has
 significantly improved and finally goes generally available. Additionally, the latest release adds support for
 custom Docker images.

diff --git a/docs/blog/posts/services-preview.md → docs/changelog/posts/0.10.7.md b/docs/blog/posts/services-preview.md → docs/changelog/posts/0.10.7.md
@@ -1,14 +1,10 @@
 ---
 date: 2023-08-07
 description: "The latest update introduces services, a new configuration type for easier deployment."
-slug: "services-preview"
-categories:
-- Releases
+slug: "0.10.7"
 ---
 
-# dstack 0.10.7: Introducing services to simplify deployment
-
-__The latest update introduces services, a new configuration type for easier deployment.__
+# dstack 0.10.7: Services
 
 Until now, `dstack` has supported `dev-environment` and `task` as configuration types. Even though `task` 
 may be used for basic serving use cases, it lacks crucial serving features. With the new update, we introduce

diff --git a/docs/blog/posts/multiple-clouds.md → docs/changelog/posts/0.11.0.md b/docs/blog/posts/multiple-clouds.md → docs/changelog/posts/0.11.0.md
@@ -1,16 +1,11 @@
 ---
-title: "dstack 0.11.0: Multi-cloud and multi-region projects"
 date: 2023-08-22
 description: "The latest update now automatically finds the cheapest GPU across clouds and regions."
-slug: "multiple-clouds"
-categories:
-- Releases
+slug: "0.11.0"
 ---
 
 # dstack 0.11.0: Multi-cloud and multi-region projects
 
-__The latest update now automatically finds the cheapest GPU across clouds and regions.__
-
 The latest release of `dstack` enables the automatic discovery of the best GPU price and availability across multiple
 configured cloud providers and regions.
 

diff --git a/docs/blog/posts/simplified-cloud-setup.md → docs/changelog/posts/0.12.0.md b/docs/blog/posts/simplified-cloud-setup.md → docs/changelog/posts/0.12.0.md
@@ -1,15 +1,11 @@
 ---
 date: 2023-10-18
 description: "The latest update makes it much easier to configure clouds and enhances the Python API."
-slug: "simplified-cloud-setup"
-categories:
-- Releases
+slug: "0.12.0"
 ---
 
 # dstack 0.12.0: Simplified cloud setup, and refined API
 
-__The latest update simplifies cloud configuration and enhances the Python API.__
-
 For the past six weeks, we've been diligently overhauling `dstack` with the aim of significantly simplifying the process
 of configuring clouds and enhancing the functionality of the API. Please take note of the breaking
 changes, as they necessitate careful migration.

diff --git a/docs/blog/posts/tensordock.md → docs/changelog/posts/0.12.2.md b/docs/blog/posts/tensordock.md → docs/changelog/posts/0.12.2.md
@@ -1,15 +1,11 @@
 ---
 date: 2023-10-31
 description: "With dstack 0.12.2, you can now effortlessly orchestrate TensorDock's cloud GPUs, leveraging their highly competitive pricing."
-slug: "tensordock"
-categories:
-- Releases
+slug: "0.12.2"
 ---
 
 # dstack 0.12.2: TensorDock integration 
 
-__With dstack 0.12.2, enjoy highly competitive pricing for cloud GPU with TensorDock.__
-
 At `dstack`, we remain committed to our mission of building the most convenient tool for orchestrating generative AI
 workloads in the cloud. In today's release, we have added support for TensorDock, making it easier for you to leverage
 cloud GPUs at highly competitive prices.

diff --git a/docs/blog/posts/vastai.md → docs/changelog/posts/0.12.3.md b/docs/blog/posts/vastai.md → docs/changelog/posts/0.12.3.md
@@ -1,16 +1,11 @@
 ---
-title: "dstack 0.12.3: Vast.ai integration"
 date: 2023-11-21
 description: "With dstack 0.12.3, you can now develop, train and deploy gen AI models using affordable cloud GPUs."
-slug: "vastai"
-categories:
-- Releases
+slug: "0.12.3"
 ---
 
 # dstack 0.12.3: Vast.ai integration
 
-__With dstack 0.12.3, you can now use Vast.ai's GPU marketplace as a cloud provider.__
-
 `dstack` simplifies gen AI model development and deployment through its developer-friendly CLI and API. 
 It eliminates cloud infrastructure hassles while supporting top cloud providers (such as AWS, GCP,
 Azure, among others).

diff --git a/...s/disk-size-cuda-12-1-mixtral-and-more.md → docs/changelog/posts/0.13.0.md b/...s/disk-size-cuda-12-1-mixtral-and-more.md → docs/changelog/posts/0.13.0.md
@@ -1,15 +1,11 @@
 ---
 date: 2023-12-22
 description: "Configurable disk size, updated CUDA drivers, Mixtral guide, and more."
-slug: "disk-size-cuda-12-1-mixtral-and-more"
-categories:
-- Releases
+slug: "0.13.0"
 ---
 
 # dstack 0.13.0: Disk size, CUDA 12.1, Mixtral, and more
 
-__The update brings configurable disk, updates CUDA drivers, and features Mixtral guide.__
-
 As we wrap up this year, we're releasing a new update and publishing a guide
 on deploying Mixtral 8x7B with `dstack`.
 

diff --git a/docs/blog/posts/openai-endpoints-preview.md → docs/changelog/posts/0.14.0.md b/docs/blog/posts/openai-endpoints-preview.md → docs/changelog/posts/0.14.0.md
@@ -1,15 +1,11 @@
 ---
 date: 2024-01-19
 description: "Making it easier to deploy custom LLMs as OpenAI-compatible endpoints."
-slug: "openai-endpoints-preview"
-categories:
-  - Releases
+slug: "0.14.0"
 ---
 
 # dstack 0.14.0: OpenAI-compatible endpoints preview
 
-__Making it easier to deploy custom LLMs as OpenAI-compatible endpoints.__
-
 The `service` configuration deploys any application as a public endpoint. For instance, you can use HuggingFace's 
 [TGI](https://github.com/huggingface/text-generation-inference) or other frameworks to deploy custom LLMs. 
 While this is simple and customizable, using different frameworks and LLMs complicates the integration of LLMs.

diff --git a/...osts/resources-authentization-and-more.md → docs/changelog/posts/0.15.0.md b/...osts/resources-authentization-and-more.md → docs/changelog/posts/0.15.0.md
@@ -1,15 +1,11 @@
 ---
 date: 2024-02-08
 description: "Resource configuration, authentication in services, model mapping for vLLM, and other improvements."
-slug: "resources-authentication-and-more"
-categories:
-  - Releases
+slug: "0.15.0"
 ---
 
 # dstack 0.15.0: Resources, authentication, and more
 
-__Resource configuration in YAML, authentication in services, and other improvements.__
-
 The latest update brings many improvements, enabling the configuration of resources in YAML files, requiring
 authentication in services, supporting OpenAI-compatible endpoints for vLLM, and more. 
 

diff --git a/docs/changelog/posts/0.15.1.md b/docs/changelog/posts/0.15.1.md
@@ -0,0 +1,125 @@
+---
+date: 2024-02-14
+description: "The latest update brings the initial integration with Kubernetes, and adds the possibility to configure custom VPC for AWS."
+slug: "0.15.0"
+---
+
+# dstack 0.15.1: Kubernetes integration preview
+
+In addition to a few bug fixes, the latest update brings initial integration with Kubernetes (experimental) and adds the
+possibility to configure a custom VPC for AWS. Read below for more details.
+
+<!-- more -->
+
+## Configuring a Kubernetes backend
+
+With the latest update, it's now possible to configure a Kubernetes backend. In this case, if you run a
+workload, `dstack`
+will provision infrastructure within your Kubernetes cluster. This may work with both self-managed and managed clusters.
+
+??? info "Prerequisite"
+To use GPUs with Kubernetes, the cluster must be installed with the
+[NVIDIA GPU Operator](https://docs.nvidia.com/datacenter/cloud-native/gpu-operator/latest/index.html).
+
+To configure a Kubernetes backend, you need to specify the path to the kubeconfig file,
+and the port that `dstack` can use for proxying SSH traffic.
+In case of a self-managed cluster, also specify the IP address of any node in the cluster.
+
+=== "Self-managed"
+
+    Here's how to configure the backend to use a self-managed cluster.
+
+    <div editor-title="~/.dstack/server/config.yml">
+
+    ```yaml
+    projects:
+    - name: main
+      backends:
+      - type: kubernetes
+        kubeconfig:
+          filename: ~/.kube/config
+        networking:
+          ssh_host: localhost # The external IP address of any node
+          ssh_port: 32000 # Any port accessible outside of the cluster
+    ```
+
+    </div>
+
+    The port specified to `ssh_port` must be accessible outside of the cluster.
+
+    For example, if you are using Kind, make sure to add it via `extraPortMappings`:
+
+    <div editor-title="installation/kind-config.yml"> 
+
+    ```yaml
+    kind: Cluster
+    apiVersion: kind.x-k8s.io/v1alpha4
+    nodes:
+    - role: control-plane
+      extraPortMappings:
+      - containerPort: 32000 # Must be same as `ssh_port`
+        hostPort: 32000 # Must be same as `ssh_port`
+    ```
+
+    </div>
+
+=== "Managed"
+    Here's how to configure the backend to use a managed cluster (AWS, GCP, Azure).
+
+    <div editor-title="~/.dstack/server/config.yml">
+
+    ```yaml
+    projects:
+    - name: main
+      backends:
+      - type: kubernetes
+        kubeconfig:
+          filename: ~/.kube/config
+        networking:
+          ssh_port: 32000 # Any port accessible outside of the cluster
+    ```
+
+    </div>
+
+    The port specified to `ssh_port` must be accessible outside of the cluster.
+
+    For example, if you are using EKS, make sure to add it via an ingress rule
+    of the corresponding security group:
+
+    ```shell
+    aws ec2 authorize-security-group-ingress --group-id <cluster-security-group-id> --protocol tcp --port 32000 --cidr 0.0.0.0/0
+    ```
+
+!!! info "NOTE:"
+    While `dstack` supports both self-managed and managed clusters, if you're using AWS, GCP, or Azure, it's generally
+    recommended to corresponding backends directly for greater efficiency and ease of use.
+
+## Specifying a custom VPC for AWS
+
+If you're using `dstack` with AWS, it's now possible to configure a custom VPC via `~/.dstack/server/config.yml`:
+
+<div editor-title="~/.dstack/server/config.yml">
+
+```yaml
+projects:
+- name: main
+  backends:
+  - type: aws
+    vpc_name: my-custom-vpc
+    regions: [us-west-2, eu-west-1]
+    creds:
+      type: default
+```
+
+</div>
+
+In this case, `dstack` will attempt to utilize the VPC with the configured name in each region. If any region lacks a VPC
+with that name, it will be skipped.
+
+!!! info "NOTE:"
+    All subnets of the configured VPC should be public; otherwise, `dstack` won't be able to manage workloads.
+
+## Feedback
+
+Have questions or need help? Drop us a message on our [Discord server](https://discord.gg/u8SmfwPpMd).
+See a bug? Report it to [GitHub issues](https://github.com/dstackai/dstack/issues/new/choose).
diff --git a/docs/blog/posts/gcp-support-just-landed.md → docs/changelog/posts/0.2.md b/docs/blog/posts/gcp-support-just-landed.md → docs/changelog/posts/0.2.md
@@ -1,14 +1,10 @@
 ---
 date: 2023-03-13
 description: The latest update of dstack now supports Google Cloud Platform (GCP).
-slug: "gcp-support-just-landed"
-categories:
-- Releases
+slug: "0.2"
 ---
 
-# GCP support just landed
-
-__The 0.2 update adds support for Google Cloud Platform (GCP).__
+# dstack 0.2: GCP integration
 
 With the release of version 0.2 of `dstack`, it is now possible to configure GCP as a remote. All features that were
 previously available for AWS,

diff --git a/docs/blog/posts/introducing-dstack-hub.md → docs/changelog/posts/0.7.0.md b/docs/blog/posts/introducing-dstack-hub.md → docs/changelog/posts/0.7.0.md
@@ -1,15 +1,11 @@
 ---
 date: 2023-04-11
 description: The latest update introduces the server with UI, team management, and more.
-slug: "introducing-dstack-hub"
-categories:
-- Releases
+slug: "0.7.0"
 ---
 
 # dstack 0.7.0: Introducing dstack server
 
-__The latest update introduces the server with UI, team management, and more.__
-
 Last October, we open-sourced the `dstack` CLI for defining ML workflows as code and running them easily on any cloud or
 locally. The tool abstracts ML engineers from vendor APIs and infrastructure, making it convenient to run scripts,
 development environments, and applications.

diff --git a/...posts/azure-support-better-ui-and-more.md → docs/changelog/posts/0.9.1.md b/...posts/azure-support-better-ui-and-more.md → docs/changelog/posts/0.9.1.md
@@ -1,15 +1,11 @@
 ---
 date: 2023-05-22
 description: The latest update introduces Azure support, enables browsing of logs and artifacts through UI, and includes other improvements.
-slug: azure-support-better-ui-and-more
-categories:
-- Releases
+slug: "0.9.1"
 ---
 
 # dstack 0.9.1: Azure integration
 
-__The latest update introduces Azure support among other improvements.__
-
 At `dstack`, our goal is to create a simple and unified interface for ML engineers to run dev environments, pipelines, and
 apps on any cloud. With the latest update, we take another significant step in this direction.
 

diff --git a/docs/docs/installation/index.md b/docs/docs/installation/index.md
@@ -388,7 +388,7 @@ projects:
 
 #### Kubernetes
 
-`dstack` supports both managed and self-managed Kubernetes clusters.
+`dstack` supports both self-managed, and managed Kubernetes clusters.
 
 ??? info "Prerequisite"
     To use GPUs with Kubernetes, the cluster must be installed with the 

diff --git a/docs/docs/reference/server/config.yml.md b/docs/docs/reference/server/config.yml.md
@@ -43,7 +43,7 @@
 
 ##SCHEMA# dstack._internal.core.models.backends.vastai.VastAIAPIKeyCreds
 
-##SCHEMA# dstack._internal.core.models.backends.kubernetes.KubernetesConfig
+##SCHEMA# dstack._internal.server.services.config.KubernetesConfig
 
 ##SCHEMA# dstack._internal.core.models.backends.kubernetes.KubeconfigConfig