Fix broken links

README.md

@@ -48,14 +48,14 @@ Here are some points that can help you decide if adopting Cartography is a good
   - What are the backup policies for my datastores?
 - Battle-tested in production by [many companies](#who-uses-cartography).
 - Straightforward to extend with your own custom plugins.
-- Provides a useful data-plane that you can build CSPM applications on top of.
+- Provides a useful data-plane that you can build automation and CSPM (Cloud Security Posture Management) applications on top of.
 
 ### What Cartography is not
 - A near-real time capability.
   - Cartography is not designed for very fast updates. Cartography writes to the database in a batches (not streamed).
   - Cartography is also limited by how most upstream sources only provide APIs to retrieve assets in a batched manner.
 - By itself, Cartography does not capture data changes over time.
-  - Although we do include a [drift detection](docs/root/usage/drift-detect.md) feature.
+  - Although we do include a [drift detection](https://lyft.github.io/cartography/usage/drift-detect.html) feature.
   - It's also possible to implement other processes in your Cartography installation to make this happen.
 
 
@@ -65,7 +65,7 @@ Here are some points that can help you decide if adopting Cartography is a good
 Start [here](https://lyft.github.io/cartography/install.html) to set up a test graph and get data into it.
 
 ### Setting up Cartography in production
-When you are ready to try it in production, read [here](docs/root/ops.md) for recommendations on getting cartography spun up in your environment.
+When you are ready to try it in production, read [here](https://lyft.github.io/cartography/ops.html) for recommendations on getting cartography spun up in your environment.
 
 ## Usage
 
@@ -76,7 +76,7 @@ When you are ready to try it in production, read [here](docs/root/ops.md) for re
 Now that data is in the graph, you can quickly start with our [querying tutorial](https://lyft.github.io/cartography/usage/tutorial.html). Our [data schema](https://lyft.github.io/cartography/usage/schema.html) is a helpful reference when you get stuck.
 
 ### Building applications around Cartography
-Directly querying Neo4j is already very useful as a sort of "swiss army knife" for security data problems, but you can also build applications and data pipelines around Cartography. View this doc on [applications](docs/root/usage/applications.md).
+Directly querying Neo4j is already very useful as a sort of "swiss army knife" for security data problems, but you can also build applications and data pipelines around Cartography. View this doc on [applications](https://lyft.github.io/cartography/usage/applications.html).
 
 
 ## Community

docs/root/install.md

@@ -30,15 +30,15 @@ Time to set up a test machine to run Cartography. Cartography _should_ work on b
 
             ⚠️ For local testing, you might want to turn off authentication via property `dbms.security.auth_enabled` in file NEO4J_PATH/conf/neo4j.conf
 
-1. Configure your data sources. See the configuration section of [each relevant intel module](../root/modules) for more details.
+1. Configure your data sources. See the configuration section of [each relevant intel module](https://lyft.github.io/cartography/modules) for more details.
 
 1. **Get and run Cartography**
 
     1. Run `pip install cartography`
 
         - This will install cartography in the current Python virtual environment. We recommend creating a separate virtual environment for just Cartography and its dependencies.
 
-    1. Finally, let's sync some data into the test graph. In this example we will use AWS. Refer to each module's [specific configuration section](../root/modules) on how to set them up.
+    1. Finally, let's sync some data into the test graph. In this example we will use AWS. Refer to each module's [specific configuration section](https://lyft.github.io/cartography/modules) on how to set them up.
 
         - For one account using the `default` profile defined in your AWS config file, run
 
@@ -67,4 +67,4 @@ Time to set up a test machine to run Cartography. Cartography _should_ work on b
         - Review the various AWS environment variables: https://docs.aws.amazon.com/cli/v1/userguide/cli-configure-envvars.html
         - Cartography uses the boto3 Python library to access AWS, so remember that boto3's standard order of precedence when retrieving credentials applies: https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html#configuring-credentials
 
-    1. Enjoy! Next set up other data providers, see our [Operations Guide](ops.html) for tips on running Cartography in production, view our [usage instructions](../../README.md#usage) for querying tips, and think of [applications](../root/usage/applications.md) to build around it.
+    1. Enjoy! Next set up other data providers, see our [Operations Guide](ops.html) for tips on running Cartography in production, view our [usage instructions](https://lyft.github.io/cartography/usage/tutorial.html) and [schema](https://lyft.github.io/cartography/usage/schema.html) for querying help, and think of [applications](https://lyft.github.io/cartography/usage/applications.html) to build around it.

docs/root/modules/index.rst

@@ -1,5 +1,4 @@
 .. toctree::
-    :hidden:
     :glob:
 
     */index

docs/root/ops.md

@@ -35,13 +35,13 @@ how that process works.
 
 Each sync run has an `update_tag` associated with it,
 which is the [Unix timestamp of when the sync started](https://github.com/lyft/cartography/blob/8d60311a10156cd8aa16de7e1fe3e109cc3eca0f/cartography/sync.py#L131-L134).
-See our [docs for more details](../dev/writing-intel-modules.md#handling-cartographys-update_tag).
+See our [docs for more details](https://lyft.github.io/cartography/dev/writing-intel-modules.html#handling-cartographys-update_tag).
 
 ### Cleanup jobs
 
 Each node and relationship created or updated during the sync will have their `lastupdated` field set to the
 `update_tag`. At the end of a sync run, nodes and relationships with out-of-date `lastupdated` fields are considered
-stale and will be deleted via a [cleanup job](../dev/writing-intel-modules.md#cleanup).
+stale and will be deleted via a [cleanup job](https://lyft.github.io/cartography/dev/writing-intel-modules.html#cleanup).
 
 ### Sync frequency
 

docs/root/usage/applications.md

@@ -24,6 +24,6 @@ It can be beneficial to periodically extract graph data into data warehouses lik
 
 ## Other useful dashboard options
 
-[Neodash]() is great for mocking up views on top of graph data and can help you build a "home-made CSPM" very quickly.
+[Neodash](https://github.com/neo4j-labs/neodash) ([video tutorial](https://www.youtube.com/watch?v=Ygzj0Y4cYm4)) is great for mocking up views on top of graph data and can help you build a "home-made CSPM" very quickly.
 
 ![pipeline-neodash.png](../images/pipeline-neodash.png)