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Fix broken links (cartography-cncf#1359)
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### Summary
> Describe your changes.

Fixes broken links in the docs.

Signed-off-by: Daniel Brauer <[email protected]>
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achantavy authored and danbrauer committed Oct 31, 2024
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8 changes: 4 additions & 4 deletions README.md
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Expand Up @@ -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.


Expand All @@ -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

Expand All @@ -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
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6 changes: 3 additions & 3 deletions docs/root/install.md
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Expand Up @@ -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

Expand Down Expand Up @@ -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.
1 change: 0 additions & 1 deletion docs/root/modules/index.rst
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.. toctree::
:hidden:
:glob:

*/index
4 changes: 2 additions & 2 deletions docs/root/ops.md
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Expand Up @@ -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

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2 changes: 1 addition & 1 deletion docs/root/usage/applications.md
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Expand Up @@ -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)

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