Merge branch 'managed-k8s' of github.com:hypermodeinc/docs into managed-k8s

Author: johnymontana

dgraph/graphql/quickstart.mdx

@@ -18,7 +18,7 @@ just by deploying the GraphQL schema of your API. Dgraph does the rest!
 
 ## Step 1: Run Dgraph
 
-The easiest way to get Dgraph up and running is on Hypermode.
+The recommended way to get started with Dgraph is by using the official [Dgraph Docker image](https://hub.docker.com/r/dgraph/standalone).
 
 ## Step 2: Deploy a GraphQL Schema
 

dgraph/guides.mdx

@@ -9,5 +9,3 @@ import DgraphWIP from "/snippets/dgraph-wip.mdx"
 
 - [Get Started with Dgraph](/dgraph/guides/get-started-with-dgraph/introduction)
 - [Graph Data Models 101](/dgraph/guides/graph-data-models-101)
-- [Build a To-Do list app](/dgraph/guides/to-do-app/introduction)
-- [Build a Message Board app](/dgraph/guides/message-board-app/introduction)

dgraph/quickstart.mdx

@@ -20,82 +20,12 @@ This guide helps you to understand how to:
 
 ## Run Dgraph and connect the Ratel web UI
 
-The easiest way to get Dgraph up and running in the cloud is using
-[Dgraph on Hypermode](https://hypermode.com/login). If you prefer a local
-development experience with Dgraph we recommend using the official Dgraph Docker
-image. Both options are described below.
+The recommended way to get started with Dgraph for local development is by using the official Dgraph Docker image. 
 
 In this section we'll create a new graph, then we'll connect our new graph to
 [Ratel](./glossary#ratel), the web-based UI for Dgraph.
 
-<Tabs>
-  <Tab title="On Hypermode">
-  <Steps>
-    <Step title="Sign in to Hypermode and create your workspace">
-
-      Open [`hypermode.com/login`](https://hypermode.com/login) in your web browser and sign
-      in to Hypermode to create your account.
-
-      After signing in you'll be prompted to choose a name for your workspace.
-
-      ![Create your Hypermode workspace](/images/dgraph/quickstart/create-workspace.png)
-
-      Enter a name for your workspace and then select **Create workspace**.
-
-    </Step>
-
-  <Step title="Create your graph">
-
-    After creating your Hypermode workspace you'll be prompted to create your first
-    graph.
-
-    ![Create your first Hypermode graph](/images/dgraph/quickstart/create-graph-2.png)
-
-    Enter a name for your graph and choose the hosting location, then select
-    **Create graph**.
-
-    </Step>
-
-  <Step title="View your graph details">
-
-Once your graph is created you'll see the graph details including its status,
-connection string, and API key.
-
-![Graph detail view](/images/dgraph/quickstart/graph-details.png)
-
-We'll use the Dgraph connection string and the API key to connect to our graph
-via Dgraph clients such as Ratel or language SDKs.
-
-Click on the copy icon next to the connection string to copy the Dgraph
-connection string.
-
-  </Step>
-
-  <Step title="Connect the Ratel graph client">
-
-Ratel is a web-based Dgraph client for interacting with your graph. We'll use
-Ratel to execute DQL queries and update the graph schema.
-
-Navigate to [ratel.hypermode.com](https://ratel.hypermode.com) and paste the
-Dgraph connection string you copied in the previous step into the "Dgraph Conn
-String" text box in Ratel then select **Connect** to verify the connection and
-then select **Continue** to access the Ratel console.
-
-![Connecting to Ratel](/images/dgraph/quickstart/ratel-connection-string.png)
-
-The Ratel console is where we can execute DQL queries and mutations and view the
-results of these operations, including visualizing graph data.
-
-![Ratel overview](/images/dgraph/quickstart/ratel-overview.png)
-
-Now we're ready to add data to our graph.
-
-  </Step>
-
-  </Steps>
-    </Tab>
-
-<Tab title="Locally"><Steps>
+<Steps>
       <Step title="Run Dgraph with Docker">
         The [`dgraph/standalone`](https://hub.docker.com/r/dgraph/standalone) Docker image has everything needed to run Dgraph locally.
 
@@ -139,9 +69,6 @@ Now we're ready to add data to our graph.
       </Step>
       </Steps>
 
-</Tab>
-</Tabs>
-
 ## Add data to the graph with a mutation
 
 Graph databases like Dgraph use a data model called the **property graph**,
@@ -507,7 +434,7 @@ the syntax `movies: ~Movie.genre`.
 
 </Steps>
 
-In this quick start we created a new graph instance using Dgraph on Hypermode,
+In this quick start we created a new graph instance using Dgraph,
 added data, queried the graph, visualized the results, and updated the schema of
 our graph.
 

dgraph/self-managed/overview.mdx

@@ -15,9 +15,7 @@ deployment scenarios, including:
 - Running Dgraph on your cloud infrastructure (AWS, Google Cloud and Azure)
 
 This section focuses exclusively on deployment and management for these
-self-managed scenarios. To learn about fully managed options that let you focus
-on building apps and websites, rather than managing infrastructure, or
-[Try Dgraph on Hypermode](https://hypermode.com/sign-up).
+self-managed scenarios.
 
 ## Overview
 

dgraph/v25-preview.mdx

@@ -9,12 +9,7 @@ Dgraph for AI-ready knowledge graphs.
 
 ## Availability
 
-As we prepare for the general availability, we're making a set of preview
-releases available for use on Hypermode and locally. The fastest way to get
-started is to sign up for a free
-[Hypermode account](https://hypermode.com/login).
-
-The run locally, use the Docker image `dgraph/standalone:v25.0.0-preview6`.
+To run locally, use the Docker image `dgraph/standalone:v25.0.0-preview6`.
 
 ```bash
 docker run --rm -it -p 8080:8080 -p 9080:9080 dgraph/standalone:v25.0.0-preview6

dgraph/why-dgraph.mdx

@@ -41,15 +41,4 @@ capabilities enable your AI apps to have logically separated knowledge graphs.
 With thousands of deployments globally, Dgraph is behind some of the world's
 most important applications. From building rocket ships, to self-driving cars,
 to beloved personal computers, to producing clean energy— Dgraph is a trusted
-part of their applications. Self-manage Dgraph or deploy your database to
-Hypermode’s managed Dgraph service.
-
-### Turn-key hosting platform
-
-Hypermode's fully managed Dgraph service eliminates operational overhead while
-maximizing performance. Deploy production-ready graph databases in minutes with
-automatic scaling, backups, and monitoring. Our expert team handles
-infrastructure management, upgrades, and optimization. With enterprise-grade
-security, 99.995% SLA uptime guarantee, and technical support, you can trust
-your most mission-critical workloads to our platform. Migrate existing
-deployments or start fresh with flexible pricing that scales with your needs.
+part of their applications.