Page Comparison

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Dependency with Knowlg BB:

1. Currently, all common modules are part of knowlg BB and are tightly coupled with knowlg/inQuiry services/jobs.

2. inQuiry uses the below api’s

• category definition api’s, framework api’s - taxonomy-service

• search api - search-service

• asset api’s, content api’s, channel api - content-service

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Deployment Structure:

• inQuiry is dependent on the below services and jobs from Knowlg BB:

  • search-service

  • taxonomy-service

  • content-service

  • search-indexer flink job

• inQuiry will install all dependent services/jobs in its own infra.

inQuiry & Knowlg using Same DB:

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inQuiry portal will use Knowlg channel, category definition, asset & search APIs.

inQuiry & Knowlg using Different DB:

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inQuiry portal will use Knowlg channel, category definition, asset & search api's.

quml-service:

configuration change:

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• all common modules listed in the Current Code Structure section will be pushed to either a common repo or different repo for each module - Need to decide by considering maven central movement for each component?

• For resolving common module dependency, we have the below options:

  • option 1:

    • Check out all dependent repos along with the main repo and do a sequential build (dependent module first. e.g: platform-core then graph-engine) and then build the main repo.

    • A custom Jenkins build script with the parameterised branch will be written for the same. so that inQuiry can point to a specific branch/tag for the dependent component.

    • We need to have a similar build script for local checkout and development.

  • option 2:

    • Add all dependent modules as submodules.

    • Modify the Jenkins build script to checkout the main repo along with all submodules.

    • For all submodules, a specific branch (e.g: 4.9.0) will be configured.

• For service level code movement, we have the below option:

  • option 1:

    • only assessment-service related code will be committed manually in the proposed structure because we need to take the code out from knowledge-platform/assessment-api folder.

  • option 2:

    • the entire knowledge-platform repo can be moved and then we can delete the unused code and modify the current service folder structure.

• the graph-engine module needs to be enhanced to either use a DB connection or API call for fetching category definition. the default option would be DB call unless it is configured for API call. - for now, we can deploy taxonomy-service under inQuiry BB and use the DB call or can directly point to Knowlg keyspace. this enhancement can be taken up in the next release.

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2. inQuiry will deploy search-indexer job, if graph db is going to be different for assessment-service.

quml-jobs:

• Two Jobs (questionset-publish & auto-creator-v2) will be moved to the inQuiry Github repo.

• For the above two jobs, two dependent components jobs-core and publish-core are required.

• These two common components should be present in the separate repo and should be pulled during the build of inQuiry specific jobs.

• Three other common jobs (search-indexer, audit-event-generator, audit-history-indexer) can be build and deployed under inQuiry infra from Knowlg BB.

• the inQuiry will maintain only the build & deployment script and BB Specific configuration for other jobs. the codebase will remain under Knowlg BB.

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• quml-player code is already independent. So just we need to move from project-sunbird to inQuiry Github repo.

Deployment Structure:

• inQuiry is dependent on the below services and jobs from Knowlg BB:

  • search-service

  • taxonomy-service

  • content-service

  • search-indexer flink job

• inQuiry will install all dependent services/jobs in its own infra.

inQuiry & Knowlg using Same DB:

...

inQuiry portal will use Knowlg channel, category definition, asset & search APIs.

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Micro Services

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assessment-service:

• assessment-service will be deployed with its own configuration.

• assessment-service will be configured to make db calls for category definitions.

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flink jobs

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• questionset-publish:

  • It will be installed with inQuiry specific configuration.

• auto-creator-v2:

  • the job makes 2 api call (get hierarchy & add to hierarchy).

  • the api calls will be made using internal content-service url and end points (url & endpoint will be a configuration)

• search-indexer:

  • No need to install search-indexer job for inQuiry, as graph db is same.

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DB’s

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• Neo4j:

  • inQuiry doesn't need to install db extension, if graph db is same.

• Logstash:

  • No need to install for inQuiry

• Kafka:

  • assessment-service will use its own kafka topic for publishing question/questionset.

• Cassandra:

  • inQuiry will have its own keyspace names.

• Redis:

  • inQuiry will use db number assigned to BB.

• ES:

  • inQuiry will use Knowlg search-indexer job and will write data to Knowlg Index (e.g: compositesearch)

  • inQuiry will use Knowlg search-service and consume data

inQuiry & Knowlg using Different DB:

...

inQuiry portal will use Knowlg channel, category definition, asset & search api's.

...

Micro Services

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assessment-service:

• assessment-service will be configured to make db calls to get the category definition as taxonomy-service will be installed.

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flink jobs

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• questionset-publish:

  • It will be installed with inQuiry specific configuration.

• auto-creator-v2:

  • the job makes 2 api call (get hierarchy & add to hierarchy).

  • the api calls will be made using internal content-service url and end points (url & endpoint will be a configuration)

• search-indexer:

  • inQuiry will install search-indexer job with inQuiry specific configuration.

  • The job will write data to inQuiry Index (e.g: inquiry_searchindex)

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DB’s

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Neo4j:

• inQuiry need to install db extension, because graph db server is different.

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Logstash:

• Need to install for inQuiry

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Kafka:

• a inQuiry specific topic need to create for search-indexer job also.

• assessment-service will use its own kafka topic for publishing question/questionset.

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Cassandra:

• inQuiry will have its own keyspace names.

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Redis:

• inQuiry will use db number assigned to BB.

ES:

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inQuiry will use its own search-indexer job and will write data to own Index (e.g: inquiry_searchindex)

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