Search Engines
Backstage supports 3 search engines by default, an in-memory engine called Lunr, Postgres and Elasticsearch.
Lunr
Lunr search engine is enabled by default for your Backstage instance if you have not done additional changes to the scaffolded app.
As Lunr is built into the Search backend plugin it can be added like this:
yarn --cwd packages/backend add @backstage/plugin-search-backend
Then add the following line:
const backend = createBackend();
// Other plugins...
backend.add(import('@backstage/plugin-search-backend'));
backend.start();
Lunr is appropriate as a zero-config search engine when developing other parts of Backstage locally, however its use is highly discouraged when running Backstage in production. When deploying Backstage, use one of the other search engines instead.
Postgres
The Postgres based search engine only requires that Postgres being configured as the database engine for Backstage. Therefore it targets setups that want to avoid maintaining another external service like Elasticsearch. The search provides decent results and performs well with ten thousands of indexed documents. The connection to Postgres is established via the database manager also used by other plugins.
Important: The search plugin requires at least Postgres 12!
First we need to add the plugin:
yarn --cwd packages/backend add @backstage/plugin-search-backend-module-pg
Then add the following line:
const backend = createBackend();
// Other plugins...
// search plugin
backend.add(import('@backstage/plugin-search-backend'));
backend.add(import('@backstage/plugin-search-backend-module-pg'));
backend.start();
Optional Configuration
The following is an example of the optional configuration that can be applied when using Postgres as the search backend. Currently this is mostly for just the highlight feature:
search:
pg:
highlightOptions:
useHighlight: true # Used to enable to disable the highlight feature. The default value is true
maxWord: 35 # Used to set the longest headlines to output. The default value is 35.
minWord: 15 # Used to set the shortest headlines to output. The default value is 15.
shortWord: 3 # Words of this length or less will be dropped at the start and end of a headline, unless they are query terms. The default value of three (3) eliminates common English articles.
highlightAll: false # If true the whole document will be used as the headline, ignoring the preceding three parameters. The default is false.
maxFragments: 0 # Maximum number of text fragments to display. The default value of zero selects a non-fragment-based headline generation method. A value greater than zero selects fragment-based headline generation (see the linked documentation above for more details).
fragmentDelimiter: ' ... ' # Delimiter string used to concatenate fragments. Defaults to " ... ".
Note: the highlight search term feature uses ts_headline which has been known to potentially impact performance. You only need this minimal config to disable it should you have issues:
search:
pg:
highlightOptions:
useHighlight: false
The Postgres documentation on Highlighting Results has more details.
Elasticsearch
Backstage supports Elasticsearch (and OpenSearch) search engine connections, indexing and querying out of the box. Available configuration options enable usage of either AWS or Elastic.co hosted solutions, or a custom self-hosted solution.
Similarly to Postgres above, Elasticsearch can be set up as follows.
First we need to add the plugin:
yarn --cwd packages/backend add @backstage/plugin-search-backend-module-elasticsearch
Then add the following line:
const backend = createBackend();
// Other plugins...
// search plugin
backend.add(import('@backstage/plugin-search-backend'));
backend.add(import('@backstage/plugin-search-backend-module-elasticsearch'));
backend.start();
Elasticsearch needs some additional configuration before it is ready to use within your instance. The configuration options are documented in the configuration schema definition file.
The underlying functionality uses either the official Elasticsearch client
version 7.x (meaning that Elasticsearch version 7 is the only one confirmed to
be supported), or the OpenSearch client, when the aws or opensearch provider
is configured.
Example configurations
AWS
Using AWS hosted Elasticsearch the only configuration option needed is the URL to the Elasticsearch service. The implementation assumes that environment variables for AWS access key id and secret access key are defined in accordance to the default AWS credential chain..
search:
elasticsearch:
provider: aws
node: https://my-backstage-search-asdfqwerty.eu-west-1.es.amazonaws.com
Elastic.co
Elastic Cloud hosted Elasticsearch uses a Cloud ID to determine the instance of hosted Elasticsearch to connect to. Additionally, username and password needs to be provided either directly or using environment variables like defined in Backstage documentation.
search:
elasticsearch:
provider: elastic
cloudId: backstage-elastic:asdfqwertyasdfqwertyasdfqwertyasdfqwerty==
auth:
username: elastic
password: changeme
OpenSearch
OpenSearch can be self hosted for example with the official docker image. The configuration requires only the node and authentication.
search:
elasticsearch:
provider: opensearch
node: http://0.0.0.0:9200
auth:
username: opensearch
password: changeme
Others
Other Elasticsearch instances can be connected to by using standard Elasticsearch authentication methods and exposed URL, provided that the cluster supports that. The configuration options needed are the URL to the node and authentication information. Authentication can be handled by either providing username/password or an API key. For more information how to create an API key, see Elastic documentation on API keys.
With username and password
search:
elasticsearch:
node: http://localhost:9200
auth:
username: elastic
password: changeme
With API key
search:
elasticsearch:
node: http://localhost:9200
auth:
apiKey: base64EncodedKey
Elasticsearch batch size
Default batch size of the Elasticsearch engine is set to 1000. If you are using a lower spec computing resources (like AWS small instance),
you may get an error caused by limited thread_pool configuration. ( 429 Too Many Requests /_bulk )
In this case you need to decrease the batch size to index the resources to prevent this kind of error. You can easily decrease
or increase the batch size in your app-config.yaml using the batchSize option provided for Elasticsearch configuration.
Set batch size to 100
search:
elasticsearch:
batchSize: 100
You can also increase the batch size if you are using a large ES instance.