Page Comparison

...

• AuthNAuth Backend: This container handles the backend services for authentication and authorization, integrating with your company's SAML for secure user verification.

• AuthNAuth UI: This container provides the user interface for authentication and authorization, allowing users to interact with the login and access control features seamlessly.

• Postgres: This container is for the PostgreSQL database, which stores user credentials, permissions, and other related authentication data securely.

NOTE: Based on specific requirements, you can bring up these respective containers as needed.

...

Make sure to pass all the environmental key values and configuration details needed for your pods to function correctly.

NOTE: Refer Environmental variable document for in detail explanation check here

...

When installing Knohow in a Kubernetes (K8s) environment, it is recommended to use cloud-provided services for MongoDB like MongoDB Atlas, Azure Cosmos DB to ensure reliability, scalability, and ease of management. However, for testing or non-production environments, you can also deploy MongoDB as a Kubernetes pod.

NOTE: Bellow Cloud provider is not supported for KNOWHOH

1. AWS DocumentDB

To create the MongoDB pod, Download the attached YAML file

...

The YAML file specifies the name of the Deployment, the container image to use, the container port 8080 to expose, and the Environmental variable for MongoDB host to connect to.

Note: Please provide the latest image tag version in the image place holders . Latest image version number can be found here : Docker hub repo

...

Note: Please provide the latest image tag version in the image place holders . Latest image version number can be found here docker hub Repo

...

Attaching the list of all the processor you may run

Jira-Processor

Note: Please provide the latest image tag version in the image place holders . Latest image version number can be found here Dockerhub repo

...

kubectl apply -f jira-processor.yaml

Devops-processor

Note: Please provide the latest image tag version in the image place holders . Latest image version number can be found here Dockerhub repo

...

Note: Please provide the latest image tag version in the image place holders . Latest image version number can be found here Dockerhub repo

...

Note: Please provide the latest image tag version in the image place holders . Latest image version number can be found here Dockerhub repo

...

Step 6 : Installing Authentication and Authorization App

NOTE: If you want to authenticate and authorize users of Knowhow with your company's SAML, install the bellow central login containers. Otherwise, you can skip this step, and your installation is complete.

...

1. If you are upgrading PSknowhow from 7.0.0 to 7.x.x please execute the bellow step else execute step 2

   Code Block
   kubectl exec -it <Mongodb Pod name> sh mongo admin --username="${MONGODB_ADMIN_USER}" --password="${MONGODB_ADMIN_PASS}" --eval "db.shutdownServer()"

2. Edit the deployment in following order
   mongodb
   customapi
   ui
   jira-processor
   devops-processor
   azure-pipeline-repo
   azure-board-processor
   by

   Code Block
   kubectl edit deploy <Deploy name> -o yaml

3. Replace the tag version with the latest version in image section

4. Check for environmental variable section and add if any new variables are required in current manifest file Refer this docs . And save it.

Base Image

1. customapi with amazoncorretto:17 as base image which handles api request, which runs on 8080 port.

2. ui with nginx:1.22.1-alpine-slim base image, which proxy-pass to customapi and ui components, which runs on port 80 & 443.

3. mongodb with mongo:5.0.18 as base image, which stores data and runs on port 27017.

4. Jira-processor with amazoncorretto:17 base image which is a jira collector.

5. devops-processor with amazoncorretto:17 base image which collects jenkins, github, gitlab, bamboo, bitbucket, zephyr, sonar, teamcity.

6. azure-board-processorwith amazoncorretto:17 base image and which collects azure board.

7. azure-pipeline-repo with amazoncorretto:17 as base image which collects azure pipeline and azure repo.

8. scm-processor-api Its python:3.8 application to calculate KPI metrics of different SCM tools like github, gitlab & Bitbucket.

9. scm-processor-core Its a python:3.8 application which collects raw data from SCM tools like github, gitlab & Bitbucket and saves it.

10. scm-processor-postgres: Version 11.1 is used to store repotool related data(Only required when repotool is installed)

11. scm-processor-rabbitmq Version 3.8-management is a job scheduler user by repotool-knowhow application (Only required when repotool is installed)

...