@ovotech/backstage-plugin-confluence-backend
v0.0.15
Published
This plugin integrates Confluence documents to Backstage' search engine.
Downloads
520
Maintainers
Keywords
Readme
Confluence search plugin backend
This plugin integrates Confluence documents to Backstage' search engine.
It is used in combination with its frontend counter-part.
Installation
Add the plugin to your backend app:
cd packages/backend && yarn add @k-phoen/backstage-plugin-confluence-backend
Configure the plugin in app-config.yaml
:
# app-config.yaml
confluence:
# Confluence base URL for wiki API
# Typically: https://{org-name}.atlassian.net/wiki
wikiUrl: https://org-name.atlassian.net/wiki
# List of spaces to index
# See https://confluence.atlassian.com/conf59/spaces-792498593.html
spaces: [ENG]
# Authentication credentials towards Confluence API
auth:
username: ${CONFLUENCE_USERNAME}
# While Confluence supports BASIC authentication, using an API token is preferred.
# See: https://support.atlassian.com/atlassian-account/docs/manage-api-tokens-for-your-atlassian-account/
password: ${CONFLUENCE_PASSWORD}
It is also possible to use a Resource
in the catalog to specify the spaces
to index.
The Resource
should like like this:
apiVersion: backstage.io/v1alpha1
kind: Resource
metadata:
name: company-confluence-spaces
description: List of all company Confluence spaces to index
annotations:
atlassian.net/confluence-spaces: 'Eng, Sales, Marketing, BizDev'
spec:
type: confluence-spaces
owner: my-team
Enable Confluence documents indexing in the search engine:
// packages/backend/src/plugins/search.ts
import { ConfluenceCollatorFactory } from '@k-phoen/backstage-plugin-confluence-backend';
export default async function createPlugin({
logger,
permissions,
discovery,
config,
tokenManager,
}: PluginEnvironment) {
// Initialize a connection to a search engine.
const searchEngine = await ElasticSearchSearchEngine.fromConfig({
logger,
config,
});
const indexBuilder = new IndexBuilder({ logger, searchEngine });
// …
// Confluence indexing
const halfHourSchedule = env.scheduler.createScheduledTaskRunner({
frequency: Duration.fromObject({ minutes: 30 }),
timeout: Duration.fromObject({ minutes: 15 }),
// A 3 second delay gives the backend server a chance to initialize before
// any collators are executed, which may attempt requests against the API.
initialDelay: Duration.fromObject({ seconds: 3 }),
});
indexBuilder.addCollator({
schedule: halfHourSchedule,
factory: ConfluenceCollatorFactory.fromConfig(env.config, {
logger: env.logger,
}),
});
// …
// The scheduler controls when documents are gathered from collators and sent
// to the search engine for indexing.
const { scheduler } = await indexBuilder.build();
// A 3 second delay gives the backend server a chance to initialize before
// any collators are executed, which may attempt requests against the API.
setTimeout(() => scheduler.start(), 3000);
useHotCleanup(module, () => scheduler.stop());
return await createRouter({
engine: indexBuilder.getSearchEngine(),
types: indexBuilder.getDocumentTypes(),
permissions,
config,
logger,
});
}
If you have decided to use the Catalog (Resource
) to define the spaces to index then there is a small change to the
initialisation code:
...
indexBuilder.addCollator({
schedule: halfHourSchedule,
factory: ConfluenceCollatorFactory.fromConfig(env.config, {
logger: env.logger,
catalogClient: new CatalogClient({ discoveryApi: env.discovery }),
}),
});
...
This will ensure the Catalog Client is specified - and it can then get the Resources
of the specified type.
License
This library is under the MIT license.