Add EnvVar vs os.getenv section

docs/content/guides/dagster/using-environment-variables-and-secrets.mdx

@@ -106,7 +106,7 @@ Refer to the [Dagster Cloud Branch Deployments example](#example-2-dagster-cloud
 
 ### From Dagster configuration
 
-[Configurable Dagster objects](/concepts/configuration/config-schema) - such as ops, assets, resources, I/O managers, and so on - can accept configuration from environment variables. Dagster provides a native way to specify environment variables in your configuration. These environment variables are retrieved at launch time, rather than on initialization as with `os.getenv`.
+[Configurable Dagster objects](/concepts/configuration/config-schema) - such as ops, assets, resources, I/O managers, and so on - can accept configuration from environment variables. Dagster provides a native way to specify environment variables in your configuration. These environment variables are retrieved at launch time, rather than on initialization as with `os.getenv`. Refer to the [next section](##using-envvar-vs-osgetenv) for more info.
 
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@@ -147,6 +147,15 @@ Refer to the [Handling secrets section](#handling-secrets) and [Per-environment
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+### Using EnvVar vs os.getenv
+
+We just covered two different ways to access environment variables in Dagster. So, which one should you use? When choosing an approach, keep the following in mind:
+
+- **When `os.getenv` is used**, the variable's value is retrieved when Dagster loads the [code location](/concepts/code-locations) and **will** be visible in the UI.
+- **When `EnvVar` is used**, the variable's value is retrieved at runtime and **won't** be visible in the UI.
+
+<EnvVarsBenefits />
+
 ---
 
 ## Handling secrets
@@ -249,7 +258,7 @@ defs = Definitions(
 
 Let's review what's happening here:
 
-- We've created a dictionary of resource definitions, `resources`, named after our `local` and `production` environments. In this example, we're using a [Pandas Snowflake I/O manager](/\_apidocs/libraries/dagster-snowflake-pandas).
+- We've created a dictionary of resource definitions, `resources`, named after our `local` and `production` environments. In this example, we're using a [Pandas Snowflake I/O manager](/_apidocs/libraries/dagster-snowflake-pandas).
 - For both `local` and `production`, we constructed the I/O manager using environment-specific run configuration. Note the differences in configuration between `local` and `production`, specifically where environment variables were used.
 - Following the `resources` dictionary, we define the `deployment_name` variable, which determines the current executing environment. This variable defaults to `local`, ensuring that `DAGSTER_DEPLOYMENT=PRODUCTION` must be set to use the `production` configuration.