Construct a safe information visualization software utilizing the Amazon Redshift Knowledge API with AWS IAM Id Heart

In at this time’s data-driven world, securely accessing, visualizing, and analyzing information is important for making knowledgeable enterprise selections. Tens of hundreds of consumers use Amazon Redshift for contemporary information analytics at scale, delivering as much as 3 times higher price-performance and 7 instances higher throughput than different cloud information warehouses.

The Amazon Redshift Knowledge API simplifies entry to your Amazon Redshift information warehouse by eradicating the necessity to handle database drivers, connections, community configurations, information buffering, and extra.

With the newly launched function of Amazon Redshift Knowledge API help for single sign-on and trusted identification propagation, you possibly can construct information visualization functions that combine single sign-on (SSO) and role-based entry management (RBAC), simplifying consumer administration whereas imposing acceptable entry to delicate data.

As an example, a world sports activities gear firm promoting merchandise throughout a number of areas wants to visualise its gross sales information, which incorporates country-level particulars. To take care of the proper degree of entry, the corporate desires to limit information visibility based mostly on the consumer’s position and area. Regional gross sales managers ought to solely see gross sales information for his or her particular area, corresponding to North America or Europe. Conversely, the worldwide gross sales executives require full entry to your entire dataset, masking all nations.

On this put up, we dive into the newly launched function of Amazon Redshift Knowledge API help for SSO, Amazon Redshift RBAC for row-level safety (RLS) and column-level safety (CLS), and trusted identification propagation with AWS IAM Id Heart to let company identities hook up with AWS companies securely. We reveal find out how to combine these companies to create a knowledge visualization software utilizing Streamlit, offering safe, role-based entry that simplifies consumer administration whereas ensuring that your group could make data-driven selections with enhanced safety and ease.

Resolution overview

We use a number of AWS companies and open supply instruments to construct a easy information visualization software with SSO to entry information in Amazon Redshift with RBAC. The important thing elements that energy the answer are as follows:

• IAM Id Heart and trusted identification propagation – IAM Id Heart can simplify consumer administration by enabling SSO throughout AWS companies. This enables customers to authenticate with their company credentials managed of their company identification supplier (IdP) like Okta, offering seamless entry to the appliance. We discover how trusted identification propagation allows managing application-level entry management at scale and exercise logging throughout AWS companies, like Amazon Redshift, by propagating and sustaining identification context all through the workflow.
• Exterior IdP – We use Okta as an exterior IdP to handle consumer authentication. Okta connects to IAM Id Heart, permitting customers to authenticate from exterior methods whereas sustaining centralized identification administration inside AWS. This makes positive that consumer entry and roles are persistently maintained throughout each AWS companies and exterior instruments.
• Amazon Redshift Serverless workgroup, Amazon Redshift Knowledge API, and Amazon Redshift RBAC – Amazon Redshift is a totally managed information warehouse service that permits for quick querying and evaluation of huge datasets. On this answer, we use the Redshift Knowledge API, which affords a easy and safe HTTP-based connection to Amazon Redshift, eliminating the necessity for JDBC or ODBC driver-based connections. The Redshift Knowledge API is the beneficial methodology to attach with Amazon Redshift for net functions. We additionally use RBAC in Amazon Redshift to reveal entry restrictions on gross sales information based mostly on the area column, ensuring that regional gross sales managers solely see information for his or her assigned areas, whereas international gross sales managers have full entry.
• Streamlit software – Streamlit is a extensively used open supply software that permits the creation of interactive information functions with minimal code. On this answer, we use Streamlit to construct a user-friendly interface the place gross sales managers can view and analyze gross sales information in a visible, accessible format. The appliance will combine with Amazon Redshift, offering customers with entry to the info based mostly on their roles and permissions.

The next diagram illustrates the answer structure for SSO with the Redshift Knowledge API utilizing IAM Id Heart.

The consumer workflow for the info visualization software consists of the next steps:

1. The consumer (whether or not a regional gross sales supervisor or international gross sales supervisor) accesses the Streamlit software, which is built-in with SSO to supply a seamless authentication expertise.
2. The appliance redirects the consumer to authenticate by way of Okta, the exterior IdP. Okta verifies the consumer’s credentials and returns an ID token to the appliance.
3. The appliance makes use of the token issued by Okta to imagine a job and short-term AWS Id and Entry Administration (IAM) session credentials to name the IAM Id Heart AssumeRoleWithWebIdentity API and IAM AssumeRole API in later steps.
4. The appliance exchanges the Okta ID token for a token issued by IAM Id Heart by calling the IAM Id Heart CreateTokenWithIAM API utilizing the short-term IAM credentials from the earlier step. This token makes positive that the consumer is authenticated with AWS companies and is tied to the IAM Id Heart consumer profile.
5. The appliance requests an identity-enhanced IAM position session utilizing the IAM Id Heart token by calling the AssumeRole
6. The appliance makes use of the identity-enhanced IAM position session credentials to securely question Amazon Redshift for gross sales information. The credentials make it possible for solely licensed customers can work together with the Redshift information.
7. Because the question is processed, Amazon Redshift checks the identification context supplied by IAM Id Heart. It verifies the consumer’s position and group membership, corresponding to being part of the North American area or the worldwide gross sales supervisor group.
8. Based mostly on the consumer’s identification and group membership, and utilizing Amazon Redshift RBAC and row-level safety, Amazon Redshift makes an authorization resolution. The teams for the illustration will be broadly categorised into the next classes:
   1. Regional gross sales managers will likely be granted entry to view gross sales information just for the particular nation or area they handle. As an example, the AMER North American Gross sales Supervisor will solely see gross sales information associated to North America. Equally, the entry management based mostly on EMEA and APAC areas will present row-level safety for the respective areas.
   2. The worldwide gross sales managers will likely be granted full entry to all areas, enabling them to view your entire international dataset.

The setup consists of two predominant steps:

1. Provision the sources for IAM Id Heart, Amazon Redshift and Okta:
   1. Allow IAM Id Heart and configure Okta because the IdP to handle consumer authentication and group provisioning.
   2. Create an Okta software to authenticate customers accessing the Streamlit software.
   3. Arrange an Amazon Redshift IAM Id Heart connection software to allow trusted identification propagation for safe authentication.
   4. Provision an Amazon Redshift Serverless
   5. Create the tables and configure RBAC inside the Redshift workgroup to implement row-level safety for various IAM Id Heart federated roles, mapped to IAM Id Heart teams.
2. Obtain, configure, and run the Streamlit software:
   1. Create a buyer managed software in IAM Id Heart for the Redshift Knowledge API shopper (Streamlit software) to allow safe API-based queries and create the required IAM roles
   2. Configure the Streamlit software.
   3. Run the Streamlit software.

Stipulations

It is best to have the next stipulations:

Provision the sources for IAM Id Heart, Amazon Redshift, and Okta

On this part, we stroll by way of the steps to provision the sources for IAM Id Heart, Amazon Redshift, and Okta.

Allow IAM Id Heart and configure Okta because the IdP

Full the next steps to allow IAM Id Heart and configure Okta because the IdP to handle consumer authentication and group provisioning:

1. Create the next customers and teams in Okta:
   1. Ethan International with e mail ethan@instance.com, in group exec-global
   2. Frank Amer with e mail frank@instance.com, in group amer-sales
   3. Alex Emea with e mail alex@instance.com, in group emea-sales
   4. Ming Apac with e mail ming@instance.com, in group apac-sales

2. Create an IAM Id Heart occasion within the AWS Area the place Amazon Redshift goes to be deployed. A corporation occasion sort is beneficial.
3. Configure Okta because the identification supply and allow computerized consumer and group provisioning. The customers and teams will likely be pushed to IAM Id Heart utilizing SCIM protocol.

The next screenshot reveals the customers synced in IAM Id Heart utilizing SCIM protocol.

Create an Okta software

Full the next steps to create an Okta software to authenticate customers accessing the Streamlit software:

1. Create an OIDC software in Okta.
   1. Copy and save the shopper ID and shopper secret wanted later for the Streamlit software and the IAM Id Heart software to attach utilizing the Redshift Knowledge API.
   2. Generate the shopper secret and set sign-in redirect URL and sign-out URL to http://localhost:8501 (we are going to host the Streamlit software domestically on port 8501).
   3. Below Assignments, Managed entry, grant entry to everybody.
2. Create an OIDC IdP on IAM the console. The next screenshot reveals an IdP created on the IAM console.

Arrange an Amazon Redshift IAM Id Heart connection software

Full the next steps to create an Amazon Redshift IAM Id Heart connection software to allow trusted identification propagation for safe authentication:

1. On the Amazon Redshift console, select IAM Id Heart connection within the navigation pane.
2. Select Create software.
3. Identify the appliance redshift-data-api-okta-app.
4. Notice down the IdP namespace. The default worth AWSIDC is used for this put up.
5. Within the IAM position for IAM Id Heart entry part, you might want to present an IAM position. You possibly can go to the IAM console and create an IAM position known as RedshiftOktaRole with the next coverage and belief relationship. RedshiftOktaRole is utilized by the Amazon Redshift IAM Id Heart connection software to handle and work together with IAM Id Heart.
   1. The coverage connected to the position wants the next permissions:

      {
        "Model": "2012-10-17",
        "Assertion": [
          {
            "Effect": "Allow",
            "Action": [
              "sso:DescribeApplication",
              "sso:DescribeInstance"
            ],
            "Useful resource": [
              "arn:aws:sso:::instance/",
              "arn:aws:sso:::application//*"
            ]
          }
        ]
      }

   2. The position makes use of the next belief relationship:

      {
        "Model": "2012-10-17",
        "Assertion": [
          {
            "Effect": "Allow",
            "Principal": {
              "Service": [
                "redshift.amazonaws.com",
                "redshift-serverless.amazonaws.com"
              ]
            },
            "Motion": [
              "sts:AssumeRole",
              "sts:SetContext"
            ]
          }
        ]
      }

6. Depart Trusted Id propagation part unchanged, then select Subsequent. You will have the choice to decide on AWS Lake Formation or Amazon S3 Entry Grants to be used circumstances like utilizing Amazon Redshift Spectrum to question exterior tables in Lake Formation. In our use case, we solely use Amazon Redshift native tables so we don’t select both.
7. Within the Configure shopper connections that use third-party IdPs part, select No.
8. Evaluation and select Create software.
9. When the appliance is created, navigate to your IAM Id Heart connection redshift-data-api-okta-app and select Assign so as to add the teams that have been synced in IAM Id Heart utilizing SCIM protocol from Okta.

We are going to allow trusted identification propagation and third-party IdP (Okta) on the shopper managed software for the Redshift Knowledge API in a later step as an alternative of configuring it within the Amazon Redshift connection software.

The next screenshot reveals the IAM Id Heart connection software created on the Amazon Redshift console.

The next screenshot reveals teams assigned to the Amazon Redshift IAM Id Heart connection for the managed software.

Provision a Redshift Serverless workgroup

Full the next steps to create a Redshift Serverless workgroup. For extra particulars, discuss with Making a workgroup with a namespace.

1. On the Amazon Redshift console, navigate to the Redshift Serverless dashboard.
2. Select Create workgroup.
3. Enter a reputation on your workgroup (for instance, redshift-tip-enabled).
4. Change the Base capability to eight RPU within the Efficiency and price management
5. You possibly can configure community and safety based mostly in your digital personal cloud (VPC) and subnet you need to create the workgroup.
6. Within the Namespace part, create a brand new namespace on your workgroup. (For instance, redshift-tip-enabled-namespace).
7. Within the Database title and password part, choose Customise admin consumer credentials and set the admin consumer title and create a password. Notice them down to make use of in a later step to configure RBAC in Amazon Redshift.
8. Within the Id Heart connections part, select Allow for the cluster possibility and choose the Amazon Redshift IAM Id Heart software created within the earlier step (redshift-data-api-okta-app).
9. Affiliate an IAM position with the workgroup that has the next insurance policies connected. Make it the default position to make use of.
   1. AmazonS3ReadOnlyAccess
   2. AmazonRedshiftDataFullAccess
   3. AmazonRedshiftQueryEditorV2ReadSharing
10. Depart different settings as default and select Subsequent.
11. Evaluation the settings and create the workgroup.

Wait till the workgroup is accessible earlier than persevering with to the subsequent steps.

Create the tables and configure RBAC inside the Redshift Serverless workgroup

Subsequent, you employ the Amazon Redshift Question Editor V2 on the Amazon Redshift console to connect with the workgroup you simply created. You create the tables and configure the Amazon Redshift roles comparable to Okta teams for the teams in IAM Id Heart and use the RBAC coverage to grant customers privileges to view information just for their areas. Full the next steps:

1. On the Amazon Redshift console, open the Question Editor V2.
2. Select the choices menu (three dots) subsequent to the Redshift workgroup title and select Edit connection.
   
3. Choose Different methods to attach and use the database consumer title and password to attach.
4. Within the question editor, run the next code to create the gross sales desk and cargo the info from Amazon Easy Storage Service (Amazon S3):

   # Create the desk
   CREATE TABLE IF NOT EXISTS public.sales_data (
       SKU VARCHAR(50),
       Product_Name VARCHAR(255),
       Class VARCHAR(100),
       Amount INT,
       Sales_Price DECIMAL(10,2),
       Timestamp TIMESTAMP,
       Metropolis VARCHAR(100),
       Region_Code VARCHAR(10),
       Nation VARCHAR(10),
       Latitude DECIMAL(10,6),
       Longitude DECIMAL(10,6),
       Inhabitants INT,
       Elevation INT,
       Timezone VARCHAR(50)
   );
   
   # Load information from S3 to desk
   COPY public.sales_data
   FROM 's3://redshift-blogs/redshift-data-api-idc/sales_data.csv'
   IAM_ROLE default
   CSV
   IGNOREHEADER 1
   DELIMITER ','
   TIMEFORMAT 'auto';
   
   # Create Redshift roles for the teams in IDC, the position format is Namespace:IDCGroupName
   CREATE ROLE "AWSIDC:amer-sales";
   CREATE ROLE "AWSIDC:emea-sales";
   CREATE ROLE "AWSIDC:apac-sales";
   CREATE ROLE "AWSIDC:exec-global";
   
   --Create RLS coverage
   CREATE RLS POLICY eu_region_filter
   WITH (timezone VARCHAR(50))
   USING (timezone LIKE 'Europe%');
   
   CREATE RLS POLICY apac_region_filter
   WITH (timezone VARCHAR(50))
   USING (timezone LIKE 'Asia%');
   
   CREATE RLS POLICY amer_region_filter
   WITH (timezone VARCHAR(50))
   USING (timezone LIKE 'America%');
   
   --Connect coverage
   ATTACH RLS POLICY eu_region_filter ON sales_data TO ROLE "AWSIDC:emea-sales";
   ATTACH RLS POLICY apac_region_filter ON sales_data TO ROLE "AWSIDC:apac-sales";
   ATTACH RLS POLICY amer_region_filter ON sales_data TO ROLE "AWSIDC:amer-sales";
   
   --Activate RLS on desk
   ALTER TABLE public.sales_data ROW LEVEL SECURITY ON;
   GRANT IGNORE RLS TO ROLE "AWSIDC:exec-global";

IAM Id Heart will map the teams into the Redshift roles within the format of Namespace:IDCGroupName. Subsequently, create the position title as AWSIDC:emea-sales and so forth to match them with Okta group names synced in IAM Id Heart. The customers will likely be created mechanically inside the teams as they log in utilizing SSO into Amazon Redshift.

Obtain, configure, and run the Streamlit software

On this part, we stroll by way of the steps to obtain, configure, and run the Streamlit software.

Create a buyer managed software in IAM Id Heart for the Redshift Knowledge API shopper

With a view to begin a trusted identification propagation workflow and permit Amazon Redshift to make authorization selections based mostly on the customers and teams from IAM Id Heart (provisioned from the exterior IdP), you want an identity-enhanced IAM position session.

This requires a few IAM roles and a buyer managed software in IAM Id Heart to deal with the belief relationship between the exterior IdP and IAM Id Heart and management entry for the Redshift Knowledge API shopper, on this case, the Streamlit software.

First, you create two IAM roles, then you definitely create a buyer managed software for the Streamlit software. Full the next steps:

1. Create a brief IAM position (we named it IDCBridgeRole) to change the token with IAM Id Heart (assuming you don’t have an current IAM identification to make use of). This position will likely be assumed by the Streamlit software with AssumeRoleWithWebIdentity to get a brief set of position credentials to name the CreateTokenWithIAM and AssumeRole APIs to get the identity-enhanced position session.
   1. Connect the next coverage the position:

      {
          "Model": "2012-10-17",
          "Assertion": [
              {
                  "Effect": "Allow",
                  "Action": "sso-oauth:CreateTokenWithIAM",
                  "Resource": "*"
              },
              {
                  "Effect": "Allow",
                  "Action": "sts:SetContext",
                  "Resource": "*"
              },
              {
                  "Effect": "Allow",
                  "Action": "sts:AssumeRole",
                  "Resource": "*"
              }
          ]
      }

   2. Within the belief relationship, present your AWS account ID and IdP’s URL. The trusted principal to make use of is the Amazon Useful resource Identify (ARN) of oidc-provider you created earlier.

      {
          "Model": "2012-10-17",
          "Assertion": [
              {
                  "Effect": "Allow",
                  "Principal": {
                      "Federated": "arn:aws:iam:::oidc-provider/"
                  },
                  "Action": "sts:AssumeRoleWithWebIdentity"
              }
          ]
      }

2. Create an IAM position with permissions to entry the Redshift Knowledge API (we named it RedshiftDataAPIClientRole). This position will likely be assumed by the Streamlit software with the improved identities from IAM Id Heart after which used to authenticate requests to the Redshift Knowledge API.
   1. Connect the AmazonRedshiftDataFullAccess AWS managed coverage. AWS recommends utilizing the precept of least privilege in your IAM coverage.
   2. Prohibit the belief relationship to the IDCBridgeRole ARN created within the earlier step), and supply your AWS account ID:

      {
          "Model": "2012-10-17",
          "Assertion": [
              {
                  "Sid": "Statement1",
                  "Effect": "Allow",
                  "Principal": {
                      "AWS": "arn:aws:iam:::role/IDCBridgeRole"
                  },
                  "Action": [
                      "sts:AssumeRole",
                      "sts:SetContext"
                  ]
              }
          ]
      }

Now you possibly can create the shopper managed software.

3. On the IAM Id Heart console, select Purposes within the navigation pane.
4. Select Add software.
5. Select I’ve an software I need to setup, choose the OAuth 2.0 software sort, and select Subsequent.
6. Enter a reputation for the appliance, for instance, RedshiftStreamlitDemo.
7. In Person and group project methodology, select Don’t require project. This implies all of the customers provisioned in IAM Id Heart from Okta can use their Okta credentials to register to the Streamlit software. You possibly can alternatively choose the Require assignments possibility and choose the customers and teams you need to permit entry to the appliance.
8. Within the AWS entry portal part, select Not seen, then select Subsequent.
9. Within the Authentication with trusted token issuer part, choose Create trusted token issuer, then enter the Okta issuer URL and enter a reputation for the trusted token issuer.
10. Within the map attribute, use the default e mail to e mail mapping between the exterior IdP attribute and IAM Id Heart attribute, then create the trusted token issuer.
11. Choose the trusted token issuer you simply created.
12. Within the Aud declare part, use the shopper ID of the Okta software you famous earlier, then select Subsequent.
13. Within the Specify software credentials part, select Edit the appliance coverage and use the next coverage:

    {
      "Model": "2012-10-17",
      "Assertion": [
        {
          "Effect": "Allow",
          "Principal": {
            "Service": "redshift-data.amazonaws.com"
          },
          "Action": "sso-oauth:*",
          "Resource": "*"
        }
      ]
    }

14. Select Submit.
    

After the appliance is created, you possibly can view it in on the IAM Id Heart.

15. Select Purposes within the navigation pane, and find the Buyer managed functions tab.
    
    

16. Select the appliance to navigate to the appliance particulars web page.
17. Within the Trusted functions for identification propagation part, select Specify trusted functions and choose the setup sort as Particular person functions and specify entry, then select Subsequent.
18. Select Amazon Redshift because the service, then select Subsequent.
19. Within the Software that may obtain requests part, select the Amazon Redshift IAM Id Heart software you created, then select Subsequent.
20. Within the Entry Scopes to use part, test the redshift:join
21. Evaluation after which select Belief software.
    

Configure and run the Streamlit software

Now that you’ve the roles and the shopper managed software in IAM Id Heart, you possibly can create an identity-enhanced IAM position session, which is essentially the most crucial step to allow trusted identification propagation. Following steps present an outline of Streamlit software code to create the identity-enhanced IAM position session.

1. Authenticate with and retrieve the id_token from the exterior IdP (Okta).
2. Name CreateTokenWithIAM utilizing the exterior IdP issued id_token to acquire an IAM Id Heart issued id_token.
3. Use AssumeRoleWithWebIdentity to acquire short-term IAM credentials (by assuming IDCBridgeRole, defined later).
4. Extract the sts:identity_context from the IAM Id Heart issued id_token.
5. Assume the position RedshiftDataAPIClientRole with the AssumeRole API and insert the sts:identity_context to acquire the identity-enhanced IAM position session credentials.

Now you should utilize these credentials to make requests to the Redshift Knowledge API, and Amazon Redshift will be capable to use the identification context for authorization selections.

At this level, it’s best to have all of the required sources for creating the Streamlit software. Full the next steps to check the Streamlit software:

1. Obtain the Streamlit software code and modify the configuration part of the code based mostly on the sources provisioned earlier:

# TIP Token change configuration
AWS_REGION = "" # us-east-1
TOKEN_EXCHANGE_APP_ARN = "" # The ARN of the IDC customer-managed-App created earlier
TOKEN_GRANT_TYPE = "urn:ietf:params:oauth:grant-type:jwt-bearer" # mounted worth, please do not change
TEMP_ROLE_ARN = "" # The position created on this step for customers to imagine with AssumeRoleWithWebIdentity(IDCBridgeRole)
ENHANCED_ROLE_ARN = "" # The position created on this step for customers to imagine for the Id-enhanced position session with IAM Id Heart(RedshiftDataAPIClientRole)
IDENHANCED_ROLE_SESSION_NAME = "rs-idc-tip-session" # Use any title for the session 
ROLE_DURATION_SECS = 3600  # 1 hour

# Okta OAuth configuration, substitute with your individual Okta Area
OKTA_DOMAIN = ""
AUTHORIZE_URL = f"https://{OKTA_DOMAIN}/oauth2/v1/authorize"
TOKEN_URL = f"https://{OKTA_DOMAIN}/oauth2/v1/token"
REFRESH_TOKEN_URL = f"https://{OKTA_DOMAIN}/oauth2/v1/token"
REVOKE_TOKEN_URL = f"https://{OKTA_DOMAIN}/oauth2/v1/revoke"
LOGOUT_URL = f"https://{OKTA_DOMAIN}/oauth2/v1/logout"
CLIENT_ID = "" # The shopper id of the Okta app created for the Streamlit app in 2.
CLIENT_SECRET = "" # The shopper id of the Okta app created for the Streamlit app in 2.
REDIRECT_URI = "http://localhost:8501" # That is for dev/check function solely
SCOPE = "openid profile e mail" # Please don't change
WORKGROUP_NAME = "" #The title of the created Redshift Workgroup
DATABASE = "dev" # The database set for the Workgroup

We advocate internet hosting this software on an Amazon Elastic Compute Cloud (Amazon EC2) occasion for manufacturing use circumstances, and utilizing AWS Secrets and techniques Supervisor for delicate data just like the CLIENT_ID and CLIENT_SECRET supplied as configuration parameters within the code for simplicity.

For this instance, we use the Okta group URL (/oauth2/v1/). You should utilize the shopper authorization servers as nicely, for instance, the default authorization server, however ensure that all URLs are utilizing the identical authorization server. Confer with Authorization servers for extra details about authorization servers in Okta.

After you modify the script for the Streamlit software, you possibly can run it utilizing a Python digital atmosphere.

2. Create a Python digital atmosphere. The appliance has been examined efficiently with variations v3.12.8 and v3.12.2.

It’s worthwhile to set up the next packages, that are required libraries for the Streamlit software code you downloaded in your digital atmosphere:

• streamlit
• streamlit_oauth
• boto3
• pyjwt
• pydeck
• pandas

3. You possibly can set up these libraries instantly utilizing the next command with the necessities file:

   pip set up -r https://redshift-blogs.s3.us-east-1.amazonaws.com/redshift-data-api-idc/necessities.txt

4. Take a look at the Streamlit software within the Python digital atmosphere with the next command:

   streamlit run /path/to/st_app.py

5. Log in with the consumer ming@instance.com from the apac-sales group.
   

The identity-enhanced position session credentials will show on the highest of the web page after profitable authentication with Okta.

For the APAC area supervisor, it’s best to solely see the info from the nations within the Asia-Pacific area based mostly on the row-level safety filter you configured earlier.

6. Sign off and log again in with the worldwide govt consumer, ethan@instance.com from the exec-global

It is best to see the info in all areas.

You possibly can attempt different regional customers’ logins and it’s best to see solely the info within the area they belong to.

Trusted identification propagation deep dive

On this part, you stroll by way of the Python code of the Streamlit software and clarify how trusted identification propagation works. The next is an evidence of key elements of the appliance code.

predominant()

The predominant() operate of the Streamlit software implements the previous steps to get the identity-enhanced IAM position session utilizing the get_id_enhanded_session() operate, which wraps the login to get the identity-enhanced position session credentials:

def predominant():
    # Create OAuth2Component occasion
    oauth2 = OAuth2Component(
        CLIENT_ID, 
        CLIENT_SECRET, 
        AUTHORIZE_URL, 
        TOKEN_URL, 
        REFRESH_TOKEN_URL, 
        REVOKE_TOKEN_URL)
    
    # Different setup code omitted
    
    # Deal with OAuth authentication with Okta
    if not st.session_state.is_authenticated or is_token_expired():
        # Present the login button if not authenticated
        st.title("Login to the Demo app")
        outcome = oauth2.authorize_button("Login with Okta", REDIRECT_URI, SCOPE)
        if outcome and "token" in outcome:
            # Save the token in session state and mark the consumer as authenticated
            st.session_state.token = outcome.get("token")
            st.session_state.user_email = get_user_email_from_token(st.session_state.token.get("id_token"))
            st.session_state.aws_creds = get_id_enhanced_session(st.session_state.token.get("id_token"))
            st.session_state.is_authenticated = True
            st.rerun()
    else:
        
        st.json(st.session_state.aws_creds)
        st.title("Whole Gross sales by Metropolis")
    
        if not is_token_expired():
            # Use the improved credentials to create the Redshift shopper
            redshift_client = boto3.shopper("redshift-data", region_name=AWS_REGION,
                                        aws_access_key_id=st.session_state.aws_creds['AccessKeyId'],
                                        aws_secret_access_key=st.session_state.aws_creds['SecretAccessKey'],
                                        aws_session_token=st.session_state.aws_creds['SessionToken'])
        else:
            st.error("Session expired. Please re-authenticate.")
            logout()
            
    # extra code for question execution and information visualizetion omitted

We use the Streamlit st.session_state supplied by Streamlit to retailer necessary session states, together with the authentication standing in addition to further data like consumer data and the AWS identity-enhanced position session credentials.

get_id_enhanced_session()

The get_id_enhanced_session() operate code has three steps:

1. We use the id_token (variable title: jwt_token) from Okta in JWT format to name the AssumeRoleWithWebIdentity API to imagine the position IDCBridgeRole. It’s because the consumer doesn’t have any AWS credentials to work together with the IAM Id Heart API. For those who plan to host this software in an AWS atmosphere with an IAM position obtainable, for instance, on an EC2 occasion, you should utilize the position related to Amazon EC2 to make the decision to the IAM Id Heart APIs with out creating IDCBridgeRole, however ensure that the EC2 position has the required permissions we specified for IDCBridgeRole.
2. After we’ve got the credentials of the short-term position, we use them to make a name to the CreateTokenWithIAM API of IAM Id Heart. This API handles the change of tokens by taking within the id_token from Okta and returning an IAM Id Heart issued token, which will likely be used later to get the identity-enhanced position session. For extra data, discuss with the CreateTokenWithIAM API reference.
3. Lastly, we extract the sts:identity_context from the IAM Id Heart issued id_token and go it to the AWS Safety Token Service (AWS STS) AssumeRole That is performed by together with the sts:identity_context within the ContextAssertion parameter inside ProvidedContexts, together with ProviderArn set to arn:aws:iam::aws:contextProvider/IdentityCenter.

def get_id_enhanced_session(jwt_token):
    """
    Obtains an identity-enhanced session by assuming a brief IAM position,
    making a token with IAM, and assuming an enhanced position session.
    
    Args:
        jwt_token (str): The JWT id token from the identification supplier.
    
    Returns:
        dict or None: The improved session credentials if profitable, in any other case None.
    """
    logging.data("Beginning identity-enhanced session course of.")

    # Step 1: Assume a brief IAM position with the supplied JWT token
    temp_credentials = assume_role_with_web_identity(jwt_token)
    if not temp_credentials:
        logging.error("Did not assume position with net identification.")
        return None

    # Step 2: Use the short-term credentials to create a token with IAM
    id_token = create_token_with_iam(jwt_token, temp_credentials)
    if not id_token:
        logging.error("Did not create ID token with IAM.")
        return None

    # Step 3: Use the ID token to imagine an enhanced position session
    enhanced_creds = assume_enhanced_role_session(id_token, temp_credentials)
    if not enhanced_creds:
        logging.error("Did not assume enhanced position session.")
        return None

    logging.data("Efficiently obtained identity-enhanced session credentials.")
    return enhanced_creds

assume_role_with_web_identity()

The assume_role_with_web_identity() operate code is as follows. We initialize the STS shopper, decode the JWT token, after which assume the position with the net identification.

def assume_role_with_web_identity(jwt_token):
    """
    Assumes an IAM position utilizing an internet identification token and returns the short-term credentials.

    Args:
        jwt_token (str): The JWT token for authentication, sometimes issued by an exterior identification supplier.

    Returns:
        dict: Non permanent IAM credentials (Entry Key, Secret Key, Session Token) or None if an error happens.
    """
    attempt:
        # Initialize the STS shopper
        sts_client = boto3.shopper('sts', region_name=AWS_REGION)
        
        # Decode the JWT token with out verifying signature (for debugging functions)
        decoded_jwt = jwt.decode(jwt_token, choices={"verify_signature": False})
        logging.debug(f"Decoded JWT Token: {decoded_jwt}")

        # Put together the request for AssumeRoleWithWebIdentity
        assume_role_request = {
            'RoleArn': TEMP_ROLE_ARN,
            'RoleSessionName': 'WebIdentitySession',
            'WebIdentityToken': jwt_token,
            'DurationSeconds': DURATION_SECS  # 1 hour
        }

        # Name the AssumeRoleWithWebIdentity API
        assume_role_response = sts_client.assume_role_with_web_identity(**assume_role_request)
        
        # Extract the short-term credentials from the response
        temp_credentials = assume_role_response['Credentials']
        logging.data("Non permanent credentials efficiently obtained.")
        
        # Return the short-term credentials
        return temp_credentials

    besides ClientError as e:
        logging.error(f"Error calling AssumeRoleWithWebIdentity: {e}")
        return None
    besides jwt.ExpiredSignatureError:
        logging.error("JWT token has expired.")
        return None
    besides jwt.DecodeError:
        logging.error("Error decoding JWT token.")
        return None
    besides Exception as e:
        logging.error(f"Surprising error: {e}")
        return None

create_token_with_iam()

The create_token_with_iam() operate code is known as to get the id_token from IAM Id Heart. The jwt_token is the id_token in JWT format issued by Okta; the id_token is the IAM Id Heart issued id_token.

def create_token_with_iam(jwt_token, temp_credentials):
    """
    Creates an IAM token utilizing the supplied JWT token and short-term credentials.

    Args:
        jwt_token (str): The JWT token to change for an IAM token.
        temp_credentials (dict): Non permanent AWS credentials for assuming the position.
    
    Returns:
        str or None: The IAM token if profitable, in any other case None.
    """
    logging.data("Beginning token creation course of with IAM.")
    
    # Initialize the SSO OIDC shopper with short-term credentials
    attempt:
        sso_oidc_client = boto3.shopper(
            'sso-oidc', 
            region_name=AWS_REGION, 
            aws_access_key_id=temp_credentials['AccessKeyId'],
            aws_secret_access_key=temp_credentials['SecretAccessKey'],
            aws_session_token=temp_credentials['SessionToken']
        )
    besides Exception as e:
        logging.error(f"Error initializing SSO OIDC shopper: {e}")
        return None

    # Put together the request for CreateTokenWithIAM
    token_request = {
        'clientId': TOKEN_EXCHANGE_APP_ARN,
        'grantType': TOKEN_GRANT_TYPE,
        'assertion': jwt_token
    }

    # Name the CreateTokenWithIAM API
    attempt:
        token_result = sso_oidc_client.create_token_with_iam(**token_request)
        id_token = token_result['idToken']
        logging.data(f"Efficiently obtained ID Token: {id_token}")
        return id_token
    besides ClientError as e:
        logging.error(f"Error calling CreateTokenWithIAM API: {e}")
        return None
    besides KeyError as e:
        logging.error(f"Lacking anticipated area in response: {e}")
        return None

Within the CreateTokenWithIAM name, we go the next parameters:

• clientId – The ARN of the IAM Id Heart software for the Redshift Knowledge API shopper
• grantType – urn:ietf:params:oauth:grant-type:jwt-bearer
• assertion – The id_token (jwt_token) issued by Okta

The idToken issued by IAM Id Heart is returned.

assume_enhanced_role_session()

The assume_enhanced_role_session() operate makes use of the ID token to imagine an identity-enhanced position session:

def assume_enhanced_role_session(id_token, temp_credentials):
    """
    Assumes an identity-enhanced IAM position session utilizing the supplied ID token and short-term credentials.

    Args:
        id_token (str): The ID token containing the identification context.
        temp_credentials (dict): Non permanent AWS credentials for assuming the position.

    Returns:
        dict or None: The credentials for the identity-enhanced IAM position session, or None on failure.
    """
    logging.data("Extracting identification context from ID token.")
    identity_context = extract_identity_context_from_id_token(id_token)

    if not identity_context:
        logging.error("Did not extract identification context from ID token.")
        return None

    attempt:
        # Initialize STS shopper with short-term credentials
        sts_client = boto3.shopper(
            'sts',
            region_name=AWS_REGION,
            aws_access_key_id=temp_credentials['AccessKeyId'],
            aws_secret_access_key=temp_credentials['SecretAccessKey'],
            aws_session_token=temp_credentials['SessionToken']
        )

        # Put together AssumeRole request with identification context
        assume_role_request = {
            'RoleArn': ENHANCED_ROLE_ARN,
            'RoleSessionName': IDENHANCED_ROLE_SESSION_NAME,
            'DurationSeconds': ROLE_DURATION_SECS,
            'ProvidedContexts': [{
                'ContextAssertion': identity_context,
                'ProviderArn': "arn:aws:iam::aws:contextProvider/IdentityCenter"
            }]
        }

        # Name the AssumeRole API
        logging.data("Calling STS AssumeRole for identity-enhanced session.")
        assume_role_response = sts_client.assume_role(**assume_role_request)

        enhanced_role_credentials = assume_role_response['Credentials']
        logging.data("Efficiently assumed enhanced position.")
        
        return enhanced_role_credentials

    besides ClientError as e:
        logging.error(f"Error calling AssumeRole: {e}")
        return None

extract_identity_context_from_id_token()

The extract_identity_context_from_id_token() operate extracts the sts:identity_context:

def extract_identity_context_from_id_token(id_token):
    """
    Extracts the identification context from a decoded JWT token.

    Args:
        id_token (str): The JWT token containing identification context.

    Returns:
        dict or None: The extracted identification context if obtainable, in any other case None.
    """
    logging.data("Decoding ID token to extract identification context.")

    attempt:
        # Decode the JWT token (with out signature verification)
        decoded_jwt = jwt.decode(id_token, choices={"verify_signature": False})

        logging.debug(f"Decoded JWT Claims: {decoded_jwt}")

        # Extract the identification context from the token
        for key in ('sts:identity_context', 'sts:audit_context'):
            if key in decoded_jwt:
                return decoded_jwt[key]

        logging.warning("No legitimate identification context discovered within the token.")
        return None

    besides Exception as e:
        logging.error(f"Error decoding JWT: {e}")
        return None

Now you might have the identity-enhanced position session credentials to name the Amazon Redshift Knowledge API.

execute_statement() and fetch_results()

The execute_statement() and fetch_results() capabilities reveal find out how to run Redshift queries and retrieve question outcomes with trusted identification propagation for visualization:

def execute_statement(sql, redshift_client):
    """
    Executes a SQL assertion on Amazon Redshift utilizing the supplied Redshift Knowledge API shopper.

    Args:
        sql (str): The SQL question to execute.
        redshift_client (boto3.shopper): The Redshift Knowledge API shopper.

    Returns:
        str: The execution ID of the assertion.

    Raises:
        ClientError: If an error happens throughout execution.
    """
    attempt:
        response = redshift_client.execute_statement(
            WorkgroupName=WORKGROUP_NAME,
            Database=DATABASE,
            Sql=sql 
        )
        return response["Id"]
    
    besides ClientError as e:
        error_code = e.response.get('Error', {}).get('Code', '')
        
        if error_code == 'ExpiredTokenException':
            logging.error("Session expired. Logging out...")
            logout()
        else:
            logging.error(f"Error executing assertion: {e}")
            increase
            
def fetch_results(statement_id, redshift_client):
    """
    Fetches question outcomes from the Redshift Knowledge API.

    Args:
        statement_id (str): The execution ID of the assertion.
        redshift_client (boto3.shopper): The Redshift Knowledge API shopper.

    Returns:
        record: An inventory of data from the question outcome.
    """
    attempt:
        response = redshift_client.get_statement_result(Id=statement_id)
        return response.get("Information", [])
    
    besides ClientError as e:
        logging.error(f"Error fetching question outcomes: {e}")
        increase

Conclusion

On this put up, we confirmed find out how to create a third-party software backed by analytics insights arriving from Amazon Redshift securely utilizing OIDC. With Redshift Knowledge API help of IAM Id Heart integration, you possibly can hook up with Amazon Redshift utilizing SSO from the IdP of your selection. You possibly can lengthen this methodology to authenticate different AWS companies that help trusted identification propagation, corresponding to Amazon Athena and Amazon QuickSight, enabling fine-grained entry management for IAM Id Heart customers and teams throughout your AWS ecosystem. We encourage you to arrange your software utilizing IAM Id Heart integration and unify your entry management instantly out of your IdP throughout all IAM Id Heart supported AWS companies.

For extra data on AWS companies and functions that help trusted identification propagation, discuss with Trusted identification propagation overview.

In regards to the Authors

Songzhi Liu is a Principal Large Knowledge Architect with the AWS Id Options workforce. On this position, he collaborates intently with AWS prospects and cross-functional groups to design and implement scalable information architectures, specializing in integrating huge information and machine studying options to boost identification consciousness inside the AWS ecosystem.

Rohit Vashishtha is a Senior Analytics Specialist Options Architect at AWS based mostly in Dallas, Texas. He has over 19 years of expertise architecting, constructing, main, and sustaining huge information platforms. Rohit helps prospects modernize their analytic workloads utilizing the breadth of AWS companies and ensures that prospects get one of the best value/efficiency with utmost safety and information governance.

Fei Peng is a Senior Software program Growth Engineer working within the Amazon Redshift workforce, the place he leads the event of Redshift Knowledge API, enabling seamless and scalable entry to cloud information warehouses.

Yanzhu Ji is a Product Supervisor within the Amazon Redshift workforce. She has expertise in product imaginative and prescient and technique in industry-leading information merchandise and platforms. She has excellent ability in constructing substantial software program merchandise utilizing net growth, system design, database, and distributed programming methods. In her private life, Yanzhu likes portray, pictures, and taking part in tennis.