Big Data

Construct a safe knowledge visualization software utilizing the Amazon Redshift Information API with AWS IAM Identification Heart

março 7, 2025
techhdesign


In at present’s data-driven world, securely accessing, visualizing, and analyzing knowledge is crucial for making knowledgeable enterprise choices. Tens of hundreds of consumers use Amazon Redshift for contemporary knowledge analytics at scale, delivering as much as thrice higher price-performance and 7 occasions higher throughput than different cloud knowledge warehouses.

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

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

As an example, a worldwide sports activities gear firm promoting merchandise throughout a number of areas wants to visualise its gross sales knowledge, which incorporates country-level particulars. To take care of the proper degree of entry, the corporate needs to limit knowledge visibility based mostly on the person’s function and area. Regional gross sales managers ought to solely see gross sales knowledge for his or her particular area, resembling North America or Europe. Conversely, the worldwide gross sales executives require full entry to the whole dataset, overlaying all international locations.

On this submit, we dive into the newly launched function of Amazon Redshift Information API assist for SSO, Amazon Redshift RBAC for row-level safety (RLS) and column-level safety (CLS), and trusted identification propagation with AWS IAM Identification Heart to let company identities connect with AWS providers securely. We exhibit combine these providers to create an information visualization software utilizing Streamlit, offering safe, role-based entry that simplifies person administration whereas ensuring that your group could make data-driven choices with enhanced safety and ease.

Resolution overview

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

  • IAM Identification Heart and trusted identification propagation – IAM Identification Heart can simplify person administration by enabling SSO throughout AWS providers. This permits customers to authenticate with their company credentials managed of their company identification supplier (IdP) like Okta, offering seamless entry to the applying. We discover how trusted identification propagation permits managing application-level entry management at scale and exercise logging throughout AWS providers, like Amazon Redshift, by propagating and sustaining identification context all through the workflow.
  • Exterior IdP – We use Okta as an exterior IdP to handle person authentication. Okta connects to IAM Identification Heart, permitting customers to authenticate from exterior programs whereas sustaining centralized identification administration inside AWS. This makes positive that person entry and roles are persistently maintained throughout each AWS providers and exterior instruments.
  • Amazon Redshift Serverless workgroup, Amazon Redshift Information API, and Amazon Redshift RBAC – Amazon Redshift is a completely managed knowledge warehouse service that enables for quick querying and evaluation of huge datasets. On this answer, we use the Redshift Information API, which provides a easy and safe HTTP-based connection to Amazon Redshift, eliminating the necessity for JDBC or ODBC driver-based connections. The Redshift Information API is the beneficial methodology to attach with Amazon Redshift for internet functions. We additionally use RBAC in Amazon Redshift to exhibit entry restrictions on gross sales knowledge based mostly on the area column, ensuring that regional gross sales managers solely see knowledge for his or her assigned areas, whereas world gross sales managers have full entry.
  • Streamlit software – Streamlit is a broadly used open supply instrument that permits the creation of interactive knowledge 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 knowledge in a visible, accessible format. The applying 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 Information API utilizing IAM Identification Heart.

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

  1. The person (whether or not a regional gross sales supervisor or world gross sales supervisor) accesses the Streamlit software, which is built-in with SSO to supply a seamless authentication expertise.
  2. The applying redirects the person to authenticate by Okta, the exterior IdP. Okta verifies the person’s credentials and returns an ID token to the applying.
  3. The applying makes use of the token issued by Okta to imagine a job and non permanent AWS Identification and Entry Administration (IAM) session credentials to name the IAM Identification Heart AssumeRoleWithWebIdentity API and IAM AssumeRole API in later steps.
  4. The applying exchanges the Okta ID token for a token issued by IAM Identification Heart by calling the IAM Identification Heart CreateTokenWithIAM API utilizing the non permanent IAM credentials from the earlier step. This token makes positive that the person is authenticated with AWS providers and is tied to the IAM Identification Heart person profile.
  5. The applying requests an identity-enhanced IAM function session utilizing the IAM Identification Heart token by calling the AssumeRole
  6. The applying makes use of the identity-enhanced IAM function session credentials to securely question Amazon Redshift for gross sales knowledge. The credentials make it possible for solely approved customers can work together with the Redshift knowledge.
  7. Because the question is processed, Amazon Redshift checks the identification context offered by IAM Identification Heart. It verifies the person’s function and group membership, resembling being part of the North American area or the worldwide gross sales supervisor group.
  8. Primarily based on the person’s identification and group membership, and utilizing Amazon Redshift RBAC and row-level safety, Amazon Redshift makes an authorization choice. The teams for the illustration will be broadly categorized into the next classes:
    1. Regional gross sales managers can be granted entry to view gross sales knowledge just for the particular nation or area they handle. As an example, the AMER North American Gross sales Supervisor will solely see gross sales knowledge 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 can be granted full entry to all areas, enabling them to view the whole world dataset.

The setup consists of two foremost steps:

  1. Provision the assets for IAM Identification Heart, Amazon Redshift and Okta:
    1. Allow IAM Identification Heart and configure Okta because the IdP to handle person authentication and group provisioning.
    2. Create an Okta software to authenticate customers accessing the Streamlit software.
    3. Arrange an Amazon Redshift IAM Identification 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 Identification Heart federated roles, mapped to IAM Identification Heart teams.
  2. Obtain, configure, and run the Streamlit software:
    1. Create a buyer managed software in IAM Identification Heart for the Redshift Information 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

You must have the next stipulations:

Provision the assets for IAM Identification Heart, Amazon Redshift, and Okta

On this part, we stroll by the steps to provision the assets for IAM Identification Heart, Amazon Redshift, and Okta.

Allow IAM Identification Heart and configure Okta because the IdP

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

  1. Create the next customers and teams in Okta:
    1. Ethan World 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

  1. Create an IAM Identification Heart occasion within the AWS Area the place Amazon Redshift goes to be deployed. A company occasion sort is beneficial.
  2. Configure Okta because the identification supply and allow automated person and group provisioning. The customers and teams can be pushed to IAM Identification Heart utilizing SCIM protocol.

The next screenshot reveals the customers synced in IAM Identification 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 Identification Heart software to attach utilizing the Redshift Information 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 regionally on port 8501).
    3. Underneath 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 Identification Heart connection software

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

  1. On the Amazon Redshift console, select IAM Identification Heart connection within the navigation pane.
  2. Select Create software.
  3. Identify the applying redshift-data-api-okta-app.
  4. Word down the IdP namespace. The default worth AWSIDC is used for this submit.
  5. Within the IAM function for IAM Identification Heart entry part, it is advisable to present an IAM function. You’ll be able to go to the IAM console and create an IAM function known as RedshiftOktaRole with the next coverage and belief relationship. RedshiftOktaRole is utilized by the Amazon Redshift IAM Identification Heart connection software to handle and work together with IAM Identification Heart.
    1. The coverage hooked up to the function 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 function 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"
      ]
    }
  ]
}

  1. Depart Trusted Identification 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 instances 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.
  2. Within the Configure shopper connections that use third-party IdPs part, select No.
  3. Assessment and select Create software.
  4. When the applying is created, navigate to your IAM Identification Heart connection redshift-data-api-okta-app and select Assign so as to add the teams that have been synced in IAM Identification 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 Information API in a later step as a substitute of configuring it within the Amazon Redshift connection software.

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

The next screenshot reveals teams assigned to the Amazon Redshift IAM Identification 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 in your workgroup (for instance, redshift-tip-enabled).
  4. Change the Base capability to eight RPU within the Efficiency and price management
  5. You’ll be able to 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 in your workgroup. (For instance, redshift-tip-enabled-namespace).
  7. Within the Database identify and password part, choose Customise admin person credentials and set the admin person identify and create a password. Word them down to make use of in a later step to configure RBAC in Amazon Redshift.
  8. Within the Identification Heart connections part, select Allow for the cluster choice and choose the Amazon Redshift IAM Identification Heart software created within the earlier step (redshift-data-api-okta-app).
  9. Affiliate an IAM function with the workgroup that has the next insurance policies hooked up. Make it the default function to make use of.
    1. AmazonS3ReadOnlyAccess
    2. AmazonRedshiftDataFullAccess
    3. AmazonRedshiftQueryEditorV2ReadSharing
  10. Depart different settings as default and select Subsequent.
  11. Assessment the settings and create the workgroup.

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

Create the tables and configure RBAC inside the Redshift Serverless workgroup

Subsequent, you utilize the Amazon Redshift Question Editor V2 on the Amazon Redshift console to hook up 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 Identification Heart and use the RBAC coverage to grant customers privileges to view knowledge 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 identify and select Edit connection.
  3. Choose Different methods to attach and use the database person identify 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 knowledge 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 function 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 Identification Heart will map the teams into the Redshift roles within the format of Namespace:IDCGroupName. Due to this fact, create the function identify as AWSIDC:emea-sales and so forth to match them with Okta group names synced in IAM Identification Heart. The customers can be created routinely 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 the steps to obtain, configure, and run the Streamlit software.

Create a buyer managed software in IAM Identification Heart for the Redshift Information API shopper

In an effort to begin a trusted identification propagation workflow and permit Amazon Redshift to make authorization choices based mostly on the customers and teams from IAM Identification Heart (provisioned from the exterior IdP), you want an identity-enhanced IAM function session.

This requires a few IAM roles and a buyer managed software in IAM Identification Heart to deal with the belief relationship between the exterior IdP and IAM Identification Heart and management entry for the Redshift Information 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 short lived IAM function (we named it IDCBridgeRole) to trade the token with IAM Identification Heart (assuming you don’t have an current IAM identification to make use of). This function can be assumed by the Streamlit software with AssumeRoleWithWebIdentity to get a short lived set of function credentials to name the CreateTokenWithIAM and AssumeRole APIs to get the identity-enhanced function session.
    1. Connect the next coverage the function: 
      {
    "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"
        }
    ]
}

  1. Create an IAM function with permissions to entry the Redshift Information API (we named it RedshiftDataAPIClientRole). This function can be assumed by the Streamlit software with the improved identities from IAM Identification Heart after which used to authenticate requests to the Redshift Information 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.

  1. On the IAM Identification Heart console, select Purposes within the navigation pane.
  2. Select Add software.
  3. Select I’ve an software I need to setup, choose the OAuth 2.0 software sort, and select Subsequent.
  4. Enter a reputation for the applying, for instance, RedshiftStreamlitDemo.
  5. In Person and group task methodology, select Don’t require task. This implies all of the customers provisioned in IAM Identification Heart from Okta can use their Okta credentials to sign up to the Streamlit software. You’ll be able to alternatively choose the Require assignments choice and decide the customers and teams you need to permit entry to the applying.
  6. Within the AWS entry portal part, select Not seen, then select Subsequent.
  7. 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.
  8. Within the map attribute, use the default e-mail to e-mail mapping between the exterior IdP attribute and IAM Identification Heart attribute, then create the trusted token issuer.
  9. Choose the trusted token issuer you simply created.
  10. Within the Aud declare part, use the shopper ID of the Okta software you famous earlier, then select Subsequent.
  11. Within the Specify software credentials part, select Edit the applying coverage and use the next coverage: 
    {
  "Model": "2012-10-17",
  "Assertion": [
    {
      "Effect": "Allow",
      "Principal": {
        "Service": "redshift-data.amazonaws.com"
      },
      "Action": "sso-oauth:*",
      "Resource": "*"
    }
  ]
}

  12. Select Submit.

After the applying is created, you possibly can view it in on the IAM Identification Heart.

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

  1. Select the applying to navigate to the applying particulars web page.
  2. 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.
  3. Select Amazon Redshift because the service, then select Subsequent.
  4. Within the Utility that may obtain requests part, select the Amazon Redshift IAM Identification Heart software you created, then select Subsequent.
  5. Within the Entry Scopes to use part, verify the redshift:join
  6. Assessment after which select Belief software.

Configure and run the Streamlit software

Now that you’ve the roles and the shopper managed software in IAM Identification Heart, you possibly can create an identity-enhanced IAM function session, which is probably the most crucial step to allow trusted identification propagation. Following steps present an summary of Streamlit software code to create the identity-enhanced IAM function 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 Identification Heart issued id_token.
  3. Use AssumeRoleWithWebIdentity to acquire non permanent IAM credentials (by assuming IDCBridgeRole, defined later).
  4. Extract the sts:identity_context from the IAM Identification Heart issued id_token.
  5. Assume the function RedshiftDataAPIClientRole with the AssumeRole API and insert the sts:identity_context to acquire the identity-enhanced IAM function session credentials.

Now you need to use these credentials to make requests to the Redshift Information API, and Amazon Redshift will have the ability to use the identification context for authorization choices.

At this level, it is best to have all of the required assets 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 assets provisioned earlier:
# TIP Token trade 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" # fastened worth, please do not change
TEMP_ROLE_ARN = "" # The function created on this step for customers to imagine with AssumeRoleWithWebIdentity(IDCBridgeRole)
ENHANCED_ROLE_ARN = "" # The function created on this step for customers to imagine for the Identification-enhanced function session with IAM Identification Heart(RedshiftDataAPIClientRole)
IDENHANCED_ROLE_SESSION_NAME = "rs-idc-tip-session" # Use any identify for the session 
ROLE_DURATION_SECS = 3600  # 1 hour

# Okta OAuth configuration, exchange 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/take a look at goal solely
SCOPE = "openid profile e-mail" # Please don't change
WORKGROUP_NAME = "" #The identify 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 instances, and utilizing AWS Secrets and techniques Supervisor for delicate data just like the CLIENT_ID and CLIENT_SECRET offered as configuration parameters within the code for simplicity.

For this instance, we use the Okta group URL (/oauth2/v1/). You should use the shopper authorization servers as effectively, for instance, the default authorization server, however ensure all URLs are utilizing the identical authorization server. Consult 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.

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

You could 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
  1. You’ll be able to set up these libraries straight 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

  2. Check the Streamlit software within the Python digital atmosphere with the next command: 
    streamlit run /path/to/st_app.py

  3. Log in with the person ming@instance.com from the apac-sales group.

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

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

  1. Log off and log again in with the worldwide government person, ethan@instance.com from the exec-global

You must see the info in all areas.

You’ll be able to strive different regional customers’ logins and it is best to see solely the info within the area they belong to.

Trusted identification propagation deep dive

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

foremost()

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

def foremost():
    # 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")
        end result = oauth2.authorize_button("Login with Okta", REDIRECT_URI, SCOPE)
        if end result and "token" in end result:
            # Save the token in session state and mark the person as authenticated
            st.session_state.token = end result.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 knowledge visualizetion omitted

We use the Streamlit st.session_state offered by Streamlit to retailer vital session states, together with the authentication standing in addition to further data like person data and the AWS identity-enhanced function session credentials.

get_id_enhanced_session()

The get_id_enhanced_session() operate code has three steps:

  1. We use the id_token (variable identify: jwt_token) from Okta in JWT format to name the AssumeRoleWithWebIdentity API to imagine the function IDCBridgeRole. It is because the person doesn’t have any AWS credentials to work together with the IAM Identification Heart API. If you happen to plan to host this software in an AWS atmosphere with an IAM function accessible, for instance, on an EC2 occasion, you need to use the function related to Amazon EC2 to make the decision to the IAM Identification Heart APIs with out creating IDCBridgeRole, however ensure the EC2 function has the required permissions we specified for IDCBridgeRole.
  2. After we have now the credentials of the non permanent function, we use them to make a name to the CreateTokenWithIAM API of IAM Identification Heart. This API handles the trade of tokens by taking within the id_token from Okta and returning an IAM Identification Heart issued token, which can be used later to get the identity-enhanced function session. For extra data, discuss with the CreateTokenWithIAM API reference.
  3. Lastly, we extract the sts:identity_context from the IAM Identification Heart issued id_token and cross it to the AWS Safety Token Service (AWS STS) AssumeRole That is finished 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 short lived IAM function,
    making a token with IAM, and assuming an enhanced function 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 short lived IAM function with the offered JWT token
    temp_credentials = assume_role_with_web_identity(jwt_token)
    if not temp_credentials:
        logging.error("Did not assume function with internet identification.")
        return None

    # Step 2: Use the non permanent 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 function session
    enhanced_creds = assume_enhanced_role_session(id_token, temp_credentials)
    if not enhanced_creds:
        logging.error("Did not assume enhanced function 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 function with the net identification.

def assume_role_with_web_identity(jwt_token):
    """
    Assumes an IAM function utilizing an online identification token and returns the non permanent credentials.

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

    Returns:
        dict: Momentary IAM credentials (Entry Key, Secret Key, Session Token) or None if an error happens.
    """
    strive:
        # 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 non permanent credentials from the response
        temp_credentials = assume_role_response['Credentials']
        logging.data("Momentary credentials efficiently obtained.")
        
        # Return the non permanent 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 known as to get the id_token from IAM Identification Heart. The jwt_token is the id_token in JWT format issued by Okta; the id_token is the IAM Identification Heart issued id_token.

def create_token_with_iam(jwt_token, temp_credentials):
    """
    Creates an IAM token utilizing the offered JWT token and non permanent credentials.

    Args:
        jwt_token (str): The JWT token to trade for an IAM token.
        temp_credentials (dict): Momentary AWS credentials for assuming the function.
    
    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 non permanent credentials
    strive:
        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
    strive:
        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 discipline in response: {e}")
        return None

Within the CreateTokenWithIAM name, we cross the next parameters:

  • clientId – The ARN of the IAM Identification Heart software for the Redshift Information 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 Identification Heart is returned.

assume_enhanced_role_session()

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

def assume_enhanced_role_session(id_token, temp_credentials):
    """
    Assumes an identity-enhanced IAM function session utilizing the offered ID token and non permanent credentials.

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

    Returns:
        dict or None: The credentials for the identity-enhanced IAM function 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

    strive:
        # Initialize STS shopper with non permanent 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 function.")
        
        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 accessible, in any other case None.
    """
    logging.data("Decoding ID token to extract identification context.")

    strive:
        # 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’ve gotten the identity-enhanced function session credentials to name the Amazon Redshift Information API.

execute_statement() and fetch_results()

The execute_statement() and fetch_results() features exhibit 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 offered Redshift Information API shopper.

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

    Returns:
        str: The execution ID of the assertion.

    Raises:
        ClientError: If an error happens throughout execution.
    """
    strive:
        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}")
            elevate
            
def fetch_results(statement_id, redshift_client):
    """
    Fetches question outcomes from the Redshift Information API.

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

    Returns:
        listing: A listing of data from the question end result.
    """
    strive:
        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}")
        elevate

Conclusion

On this submit, we confirmed create a third-party software backed by analytics insights arriving from Amazon Redshift securely utilizing OIDC. With Redshift Information API assist of IAM Identification Heart integration, you possibly can connect with Amazon Redshift utilizing SSO from the IdP of your selection. You’ll be able to lengthen this methodology to authenticate different AWS providers that assist trusted identification propagation, resembling Amazon Athena and Amazon QuickSight, enabling fine-grained entry management for IAM Identification Heart customers and teams throughout your AWS ecosystem. We encourage you to arrange your software utilizing IAM Identification Heart integration and unify your entry management straight out of your IdP throughout all IAM Identification Heart supported AWS providers.

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

In regards to the Authors

Songzhi Liu is a Principal Massive Information Architect with the AWS Identification Options staff. On this function, he collaborates carefully with AWS clients and cross-functional groups to design and implement scalable knowledge architectures, specializing in integrating large knowledge 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 large knowledge platforms. Rohit helps clients modernize their analytic workloads utilizing the breadth of AWS providers and ensures that clients get the perfect worth/efficiency with utmost safety and knowledge governance.

Fei Peng is a Senior Software program Improvement Engineer working within the Amazon Redshift staff, the place he leads the event of Redshift Information API, enabling seamless and scalable entry to cloud knowledge warehouses.

Yanzhu Ji is a Product Supervisor within the Amazon Redshift staff. She has expertise in product imaginative and prescient and technique in industry-leading knowledge merchandise and platforms. She has excellent ability in constructing substantial software program merchandise utilizing internet growth, system design, database, and distributed programming strategies. In her private life, Yanzhu likes portray, images, and enjoying tennis.