From 38cd7508a1c5d624052e6d30b279c14458dc16ce Mon Sep 17 00:00:00 2001 From: Alex Chantavy Date: Tue, 24 Sep 2024 21:01:52 -0700 Subject: [PATCH] Fix broken links --- README.md | 8 ++++---- docs/root/install.md | 6 +++--- docs/root/modules/index.rst | 1 - docs/root/ops.md | 4 ++-- docs/root/usage/applications.md | 2 +- 5 files changed, 10 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index 6b43a21622..0b1ef2ece1 100644 --- a/README.md +++ b/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 diff --git a/docs/root/install.md b/docs/root/install.md index 981df3e277..5703f52ca0 100644 --- a/docs/root/install.md +++ b/docs/root/install.md @@ -30,7 +30,7 @@ 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** @@ -38,7 +38,7 @@ Time to set up a test machine to run Cartography. Cartography _should_ work on b - 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. diff --git a/docs/root/modules/index.rst b/docs/root/modules/index.rst index 947aa7f149..45dbd14910 100644 --- a/docs/root/modules/index.rst +++ b/docs/root/modules/index.rst @@ -1,5 +1,4 @@ .. toctree:: - :hidden: :glob: */index diff --git a/docs/root/ops.md b/docs/root/ops.md index e9eba95bfe..73a1013585 100644 --- a/docs/root/ops.md +++ b/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 diff --git a/docs/root/usage/applications.md b/docs/root/usage/applications.md index 7d251c730b..66079e9722 100644 --- a/docs/root/usage/applications.md +++ b/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)