gcp-token-broker | GCP Token Broker enables end-to-end Kerberos security | GCP library

 by   GoogleCloudPlatform Java Version: Current License: Apache-2.0

kandi X-RAY | gcp-token-broker Summary

kandi X-RAY | gcp-token-broker Summary

gcp-token-broker is a Java library typically used in Cloud, GCP, Hadoop applications. gcp-token-broker has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub, Maven.

The GCP Token Broker enables end-to-end Kerberos security and Cloud IAM integration for Hadoop workloads on Google Cloud Platform (GCP).

            kandi-support Support

              gcp-token-broker has a low active ecosystem.
              It has 27 star(s) with 27 fork(s). There are 9 watchers for this library.
              It had no major release in the last 6 months.
              There are 5 open issues and 10 have been closed. On average issues are closed in 98 days. There are 5 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of gcp-token-broker is current.

            kandi-Quality Quality

              gcp-token-broker has 0 bugs and 0 code smells.

            kandi-Security Security

              gcp-token-broker has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              gcp-token-broker code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              gcp-token-broker is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              gcp-token-broker releases are not available. You will need to build from source code and install.
              Deployable package is available in Maven.
              Build file is available. You can build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed gcp-token-broker and discovered the below as its top functions. This is intended to give you an instant insight into gcp-token-broker implemented functionality, and help decide if they suit your requirements.
            • Run the request
            • Send a request to the bucket
            • Authenticate session
            • Attempts to retrieve a value from the cache
            • Runs the command
            • Send a request to the bucket
            • Authenticate session
            • Attempts to retrieve a value from the cache
            • Save model
            • Format the value
            • Returns an UPDATE statement for the given dialect
            • Simple test for testing
            • Retrieves a model by its ID
            • Authenticate user
            • Runs the session token
            • Entry point for the KMS API
            • Entry point for the refresh token
            • Creates a gRPC channel
            • Delete a model by id
            • Retrieve an OAuth access token from the database
            • Load mapping rules
            • Return this object as a map
            • Deletes the items that have been expired
            • Loads the settings
            • Serialize this logging event to JSON
            • Initialize the database
            • Runs the renew session
            • Gets all models from the database
            • Deletes all items for a given model class
            Get all kandi verified functions for this library.

            gcp-token-broker Key Features

            No Key Features are available at this moment for gcp-token-broker.

            gcp-token-broker Examples and Code Snippets

            No Code Snippets are available at this moment for gcp-token-broker.

            Community Discussions


            Submit command line arguments to a pyspark job on airflow
            Asked 2022-Mar-29 at 10:37

            I have a pyspark job available on GCP Dataproc to be triggered on airflow as shown below:



            Answered 2022-Mar-28 at 08:18

            You have to pass a Sequence[str]. If you check DataprocSubmitJobOperator you will see that the params job implements a class google.cloud.dataproc_v1.types.Job.

            Source https://stackoverflow.com/questions/71616491


            Skip first line in import statement using gc.open_by_url from gspread (i.e. add header=0)
            Asked 2022-Mar-16 at 08:12

            What is the equivalent of header=0 in pandas, which recognises the first line as a heading in gspread?

            pandas import statement (correct)



            Answered 2022-Mar-16 at 08:12

            Looking at the API documentation, you probably want to use:

            Source https://stackoverflow.com/questions/71418682


            Automatically Grab Latest Google Cloud Platform Secret Version
            Asked 2022-Mar-01 at 03:01

            I'm trying to grab the latest secret version. Is there a way to do that without specifying the version number? Such as using the keyword "latest". I'm trying to avoid having to iterate through all the secret versions with a for loop as GCP documentation shows:



            Answered 2021-Sep-12 at 18:54
            import com.google.cloud.secretmanager.v1.AccessSecretVersionResponse;
            import com.google.cloud.secretmanager.v1.SecretManagerServiceClient;
            import com.google.cloud.secretmanager.v1.SecretVersionName;
            import java.io.IOException;
            public class AccessSecretVersion {
              public static void accessSecretVersion() throws IOException {
                // TODO(developer): Replace these variables before running the sample.
                String projectId = "your-project-id";
                String secretId = "your-secret-id";
                String versionId = "latest"; //<-- specify version
                accessSecretVersion(projectId, secretId, versionId);
              // Access the payload for the given secret version if one exists. The version
              // can be a version number as a string (e.g. "5") or an alias (e.g. "latest").
              public static void accessSecretVersion(String projectId, String secretId, String versionId)
                  throws IOException {
                // Initialize client that will be used to send requests. This client only needs to be created
                // once, and can be reused for multiple requests. After completing all of your requests, call
                // the "close" method on the client to safely clean up any remaining background resources.
                try (SecretManagerServiceClient client = SecretManagerServiceClient.create()) {
                  SecretVersionName secretVersionName = SecretVersionName.of(projectId, secretId, versionId);
                  // Access the secret version.
                  AccessSecretVersionResponse response = client.accessSecretVersion(secretVersionName);
                  // Print the secret payload.
                  // WARNING: Do not print the secret in a production environment - this
                  // snippet is showing how to access the secret material.
                  String payload = response.getPayload().getData().toStringUtf8();
                  System.out.printf("Plaintext: %s\n", payload);

            Source https://stackoverflow.com/questions/68805240


            Programmatically Connecting a GitHub repo to a Google Cloud Project
            Asked 2022-Feb-12 at 16:16

            I'm working on a Terraform project that will set up all the GCP resources needed for a large project spanning multiple GitHub repos. My goal is to be able to recreate the cloud infrastructure from scratch completely with Terraform.

            The issue I'm running into is in order to setup build triggers with Terraform within GCP, the GitHub repo that is setting off the trigger first needs to be connected. Currently, I've only been able to do that manually via the Google Cloud Build dashboard. I'm not sure if this is possible via Terraform or with a script but I'm looking for any solution I can automate this with. Once the projects are connected updating everything with Terraform is working fine.

            TLDR; How can I programmatically connect a GitHub project with a GCP project instead of using the dashboard?



            Answered 2022-Feb-12 at 16:16

            Currently there is no way to programmatically connect a GitHub repo to a Google Cloud Project. This must be done manually via Google Cloud.

            My workaround is to manually connect an "admin" project, build containers and save them to that project's artifact registry, and then deploy the containers from the registry in the programmatically generated project.

            Source https://stackoverflow.com/questions/69834735


            Unable to create a new Cloud Function - cloud-client-api-gae
            Asked 2022-Feb-11 at 18:49

            I'm unable to create a Cloud Function in my GCP project using GUI, but have admin roles for GCF, SA and IAM.

            Here is the error message:

            Missing necessary permission iam.serviceAccounts.actAs for cloud-client-api-gae on the service account serviceaccountname@DOMAIN.iam.gserviceaccount.com. Grant the role 'roles/iam.serviceAccountUser' to cloud-client-api-gae on the service account serviceaccountname@DOMAIN.iam.gserviceaccount.com.

            cloud-client-api-gae is not an SA nor User on my IAM list. It must be a creature living underneath Graphical User Interfrace.

            I have Enabled API for GCF, AppEngine and I have Service Account Admin role.

            I had literally 0 search results when googling for cloud-client-api-gae.



            Answered 2022-Jan-18 at 13:53

            I contacted GCP support and it seems I was missing a single permission for my user: Service Account User - that's it.

            PS: Person from support didn't know what this thing called "cloud-client-api-gae" is.

            Source https://stackoverflow.com/questions/70756708


            TypeScript project failing to deploy to App Engine targeting Node 12 or 14, but works with Node 10
            Asked 2022-Jan-16 at 14:32

            I have a TypeScript project that has been deployed several times without any problems to Google App Engine, Standard environment, running Node 10. However, when I try to update the App Engine project to either Node 12 or 14 (by editing the engines.node value in package.json and the runtime value in app.yaml), the deploy fails, printing the following to the console:



            Answered 2022-Jan-16 at 14:32

            I encountered the exact same problem and just put typescript in dependencies, not devDependencies.

            It worked after that, but cannot assure that it is due to this change (since I have no proof of that).

            Source https://stackoverflow.com/questions/69153522


            Dataproc Java client throws NoSuchMethodError setUseJwtAccessWithScope
            Asked 2022-Jan-14 at 19:24

            I am following this article ,for submit a job to an existing Dataproc cluster via a Dataproc API

            For the following line of code :



            Answered 2022-Jan-14 at 19:22

            The method com.google.api.gax.core.GoogleCredentialsProvider$Builder com.google.api.gax.core.GoogleCredentialsProvider$Builder.setUseJwtAccessWithScope(boolean) was introduced in com.google.api:gax in version 2.3.0.

            Can you

            1. run mvn dependency:tree and confirm that your version of com.google.api:gax is above version 2.3.0?

            2. upgrade all Google libraries to the latest version?

            Here is a similar issue found on the internet.

            Source https://stackoverflow.com/questions/70640346


            Apache Beam Cloud Dataflow Streaming Stuck Side Input
            Asked 2022-Jan-12 at 13:12

            I'm currently building PoC Apache Beam pipeline in GCP Dataflow. In this case, I want to create streaming pipeline with main input from PubSub and side input from BigQuery and store processed data back to BigQuery.

            Side pipeline code



            Answered 2022-Jan-12 at 13:12

            Here you have a working example:

            Source https://stackoverflow.com/questions/70561769


            BIG Query command using BAT file
            Asked 2022-Jan-09 at 15:24
            echo Give yearmonth "yyyyMM"
            setlocal enabledelayedexpansion
            SET /p yearmonth= 
            SET ClientName[0]=abc
            SET ClientName[1]=def
            SET i = 0
            if defined ClientName[%i%] (
                call bq query --use_legacy_sql=false "CREATE EXTERNAL TABLE `test.!ClientName[%%i]!.%yearmonth%` OPTIONS (format = 'CSV',skip_leading_rows = 1 uris = ['gs://test/!ClientName[%%i]!/AWS/%yearmonth%/Metrics/data/*.csv'])"
                set /a "i+=1"
                GOTO :myLoop


            Answered 2022-Jan-09 at 11:04
            1. It is bad practice to set variables as standalone alphabetical characters like i. One reason is exactly as you have experienced, you have confused for metavariable %%i with a set variable %i%.

            2. You are expanding in the loop, but have not enabledelayedexpansion so there are 2 ways, which we will get to in a second.

            3. setting variables should not have spaces before or after = excluding the likes of set /a

            So, Method 1, without delayedexpansion (note how the variables are used with double %% in the loop with the call command).

            Source https://stackoverflow.com/questions/70640411


            Vertex AI Model Batch prediction, issue with referencing existing model and input file on Cloud Storage
            Asked 2021-Dec-21 at 14:35

            I'm struggling to correctly set Vertex AI pipeline which does the following:

            1. read data from API and store to GCS and as as input for batch prediction.
            2. get an existing model (Video classification on Vertex AI)
            3. create Batch prediction job with input from point 1.
              As it will be seen, I don't have much experience with Vertex Pipelines/Kubeflow thus I'm asking for help/advice, hope it's just some beginner mistake. this is the gist of the code I'm using as pipeline


            Answered 2021-Dec-21 at 14:35

            I'm glad you solved most of your main issues and found a workaround for model declaration.

            For your input.output observation on gcs_source_uris, the reason behind it is because the way the function/class returns the value. If you dig inside the class/methods of google_cloud_pipeline_components you will find that it implements a structure that will allow you to use .outputs from the returned value of the function called.

            If you go to the implementation of one of the components of the pipeline you will find that it returns an output array from convert_method_to_component function. So, in order to have that implemented in your custom class/function your function should return a value which can be called as an attribute. Below is a basic implementation of it.

            Source https://stackoverflow.com/questions/70356856

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install gcp-token-broker

            You can download it from GitHub, Maven.
            You can use gcp-token-broker like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the gcp-token-broker component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .


            See the full documentation here.
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