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‎.ci/run-elasticsearch.sh

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#!/usr/bin/env bash
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#
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environment=($(cat <<-END
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--env ELASTIC_PASSWORD=changeme
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--env node.name=elasticsearch-serverless
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--env cluster.name=elasticsearch-serverless
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--env cluster.initial_master_nodes=elasticsearch-serverless
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--env discovery.seed_hosts=instance
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--env cluster.routing.allocation.disk.threshold_enabled=false
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--env bootstrap.memory_lock=true
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--env node.attr.testattr=test
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--env path.repo=/tmp
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--env repositories.url.allowed_urls=http://snapshot.test*
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--env action.destructive_requires_name=false
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--env ingest.geoip.downloader.enabled=false
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--env cluster.deprecation_indexing.enabled=false
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--env xpack.security.enabled=false
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--env xpack.security.http.ssl.enabled=false
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END
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))
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export DETACH=${DETACH-false}
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docker run \
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--name elasticsearch-serverless \
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--network elastic \
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--env "ES_JAVA_OPTS=-Des.serverless=true -Xms1g -Xmx1g -da:org.elasticsearch.xpack.ccr.index.engine.FollowingEngineAssertions" \
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"${environment[@]}" \
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--volume serverless-data:/usr/share/elasticsearch/data \
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--publish 9200:9200 \
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--ulimit nofile=65536:65536 \
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--ulimit memlock=-1:-1 \
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--detach=$DETACH \
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--rm \
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docker.elastic.co/elasticsearch/elasticsearch:$STACK_VERSION;

‎.github/workflows/tests.yml

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name: main
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on: [push]
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jobs:
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rspec:
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strategy:
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matrix:
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<<[lang]>>: [ ]
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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- uses: <<[lang]>>/setup-<<[lang]>>@v1
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with:
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<<[lang]>>-version: ${{ matrix.<<[lang]>> }}
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- name: Build and test with
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run: |

‎.gitignore

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*.gem
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.bundle
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Gemfile.lock
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.DS_Store
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tmp
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*.log

‎CONTRIBUTING.md

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Describe how to install the library for development purposes.
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### Run Tests
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### Run Elasticsearch Serverless Docker container
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### Contributing Code Changes
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1. Please make sure you have signed the [Contributor License
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Agreement](http://www.elastic.co/contributor-agreement/). We are not
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asking you to assign copyright to us, but to give us the right to distribute
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your code without restriction. We ask this of all contributors in order to
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assure our users of the origin and continuing existence of the code. You only
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need to sign the CLA once.
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2. Rebase your changes. Update your local repository with the most recent code
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from the main `elasticsearch-serverless-<<[lang]>>` repository and rebase your branch
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on top of the latest `main` branch.
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3. Submit a pull request. Push your local changes to your forked repository
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and [submit a pull request](https://github.com/elastic/elasticsearch-serverless/pulls)
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and mention the issue number if any (`Closes #123`) Make sure that you
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add or modify tests related to your changes so that CI will pass.
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4. Sit back and wait. There may be some discussion on your pull request and
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if changes are needed we would love to work with you to get your pull request
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merged into `elasticsearch-serverless-<<[lang]>>`.

‎LICENSE

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Copyright 2022 Elasticsearch B.V (https://www.elastic.co)
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in
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all copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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THE SOFTWARE.

‎README.md

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# How to use this template
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This is the template structure for an Elasticsearch Serverless Client.
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It can be used to start a new repository for a specific client (e.g. elasticsearch-serverless-php).
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## Parameters
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When you create a new repository using this template you have to customize the
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contents according to the programming language of the client.
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We offered an automatic tool to search and replace occurrences of `<<[lang]>>` and
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`<<[LANG]>>` in all the files.
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The `<<[lang]>>` is the placeholder for the repository name `elasticsearch-serverless-<<[lang]>>`.
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For instance, if `<<[lang]>> = "php"` then the repository will be `elasticsearch-serverless-php`.
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The `<<[LANG]>>` is the placeholder for the language name. For instance, `<<[LANG]>> = "PHP"`.
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This is typically used in README or documentation files.
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## How to customize the files
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You can customize the files replacing the parameters using the following command:
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```bash
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customize.sh <<[lang]>>
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```
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where `<<[lang]>>` is the language specific client to use (e.g. `customize.sh php`).
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This will search & replace all the occurrencies of `<<[lang]>>` and `<<[LANG]>>` in some files
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(e.g. README, CONTRIBUTING, etc).
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## Choose the correct LICENSE
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You need to choose the LICENSE for your custom client. Remember to change the `LICENSE` file.

‎README_TEMPLATE.md

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# Elasticsearch Serverless Client
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[![main](https://github.com/elastic/elasticsearch-serverless-<<[lang]>>/actions/workflows/tests.yml/badge.svg?branch=main)](https://github.com/elastic/elasticsearch-serverless-<<[lang]>>/actions/workflows/tests.yml)
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This is the official Elastic client for the **Elasticsearch Serverless** service. If you're looking to develop your <<[LANG]>> application with the Elasticsearch Stack, you should look at the [Elasticsearch Client](https://github.com/elastic/elasticsearch-<<[lang]>>) instead. If you're looking to develop your {LANG} application with Elastic Enterprise Search, you should look at the [Enterprise Search Client](https://github.com/elastic/enterprise-search-<<[lang]>>/).
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## Installation
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### Instantiate a Client
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### Using the API
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Once you've instantiated a client with your API key and Elasticsearch endpoint, you can start ingesting documents into Elasticsearch Service. You can use the **Bulk API** for this. This API allows you to index, update and delete several documents in one request. You call the `bulk` API on the client with a body parameter, an Array of hashes that define the action and a document. Here's an example of indexing some classic books into the `books` index:
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```<<[lang]>>
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# First we build our data:
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body = [
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{ index: { _index: 'books', data: {name: "Snow Crash", "author": "Neal Stephenson", "release_date": "1992-06-01", "page_count": 470} } },
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{ index: { _index: 'books', data: {name: "Revelation Space", "author": "Alastair Reynolds", "release_date": "2000-03-15", "page_count": 585} } },
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{ index: { _index: 'books', data: {name: "1984", "author": "George Orwell", "release_date": "1985-06-01", "page_count": 328} } },
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{ index: { _index: 'books', data: {name: "Fahrenheit 451", "author": "Ray Bradbury", "release_date": "1953-10-15", "page_count": 227} } },
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{ index: { _index: 'books', data: {name: "Brave New World", "author": "Aldous Huxley", "release_date": "1932-06-01", "page_count": 268} } },
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{ index: { _index: 'books', data: {name: "The Handmaid's Tale", "author": "Margaret Atwood", "release_date": "1985-06-01", "page_count": 311} } }
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]
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# Then we send the data via the bulk api:
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> response = client.bulk(body: body)
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# And we can check that the items were indexed and given an id in the response:
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> response['items']
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=>
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[{"index"=>{"_index"=>"books", "_id"=>"Pdink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>0, "_primary_term"=>1, "status"=>201}},
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{"index"=>{"_index"=>"books", "_id"=>"Ptink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>1, "_primary_term"=>1, "status"=>201}},
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{"index"=>{"_index"=>"books", "_id"=>"P9ink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>2, "_primary_term"=>1, "status"=>201}},
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{"index"=>{"_index"=>"books", "_id"=>"QNink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>3, "_primary_term"=>1, "status"=>201}},
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{"index"=>{"_index"=>"books", "_id"=>"Qdink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>4, "_primary_term"=>1, "status"=>201}},
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{"index"=>{"_index"=>"books", "_id"=>"Qtink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>5, "_primary_term"=>1, "status"=>201}}]
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```
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When you use the client to make a request to Elasticsearch, it will return an API Response object. You can see the HTTP return code by calling `status` and the HTTP headers by calling `headers` on the response object. The Response object behaves as a Hash too, so you can access the body values directly as seen on the previous example with `response['items']`.
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Now that some data is available, you can search your documents using the **Search API**:
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```<<[lang]>>
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> response = client.search(index: 'books', q: 'snow')
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> response['hits']['hits']
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=> [{"_index"=>"books", "_id"=>"Pdink4cBmDx329iqhzM2", "_score"=>1.5904956, "_source"=>{"name"=>"Snow Crash", "author"=>"Neal Stephenson", "release_date"=>"1992-06-01", "page_count"=>470}}]
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```
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## Development
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See [CONTRIBUTING](./CONTRIBUTING.md).
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### Docs
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Some questions, assumptions and general notes about this project can be found in [the docs directory](./docs/questions-and-assumptions.md).

‎customize.sh

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#!/usr/bin/env bash
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dir=$(dirname "$(realpath -s "$0")")
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lang=$1
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LANG="${lang^}"
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# Update README.md
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sed -i "s/<<\[lang\]>>/$lang/" $dir/README_TEMPLATE.md
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sed -i "s/<<\[LANG\]>>/$LANG/" $dir/README_TEMPLATE.md
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# CONTRIBUTING.md
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sed -i "s/<<\[lang\]>>/$lang/" $dir/CONTRIBUTING.md
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sed -i "s/<<\[LANG\]>>/$LANG/" $dir/CONTRIBUTING.md
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# docs/getting-started.MDX
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sed -i "s/<<\[lang\]>>/$lang/" $dir/docs/getting-started.MDX
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sed -i "s/<<\[LANG\]>>/$LANG/" $dir/docs/getting-started.MDX
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# docs/landing-page.MDX
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sed -i "s/<<\[lang\]>>/$lang/" $dir/docs/landing-page.MDX
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sed -i "s/<<\[LANG\]>>/$LANG/" $dir/docs/landing-page.MDX
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# .github/workflows/test.yml
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sed -i "s/<<\[lang\]>>/$lang/" $dir/.github/workflows/test.yml
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sed -i "s/<<\[LANG\]>>/$LANG/" $dir/.github/workflows/test.yml
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# Clean up
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rm README.md
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mv README_TEMPLATE.md README.md
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rm customize

‎docs/getting-started.MDX

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---
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id: gettingStarted
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slug: /serverless-<<[lang]>>/docs/getting-started
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title: Getting started with the Serverless <<[LANG]>> client
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description: This page contains quickstart information about the Serverless <<[LANG]>> client.
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date: 2023-04-27
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tags: ['serverless','<<[LANG]>> client','docs', 'getting started']
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---
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This page guides you through the installation process of the Serverless <<[LANG]>>
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client, shows you how to instantiate the client, and how to perform basic
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Elasticsearch operations with it.
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## Requirements
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* <<[LANG]>> x or higher installed on your system.
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## Installation
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### Using the command line
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You can install the Elasticsearch Serverless <<[LANG]>> client with the following
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commands:
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```bash
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```
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## Instantiate a client
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You can instantiate a client by running the following command:
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```<<[lang]>>
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```
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You can find the Elasticsearch endpoint on the Cloud deployment management page.
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<DocImage url="images/copy-endpoint.gif" alt="Copy the endpoint for Elasticsearch"/>
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You can create a new API Key under **Stack Management** > **Security**:
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<DocImage url="images/setup-api-key.gif" alt="Create and copy Apy Key"/>
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## Using the API
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After you instantiated a client with your API key and Elasticsearch endpoint,
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you can start ingesting documents into the Elasticsearch Service. You can use
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the Bulk API for this. This API enables you to index, update, and delete several
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documents in one request.
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### Creating an index and ingesting documents
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You can call the `bulk` API with a body parameter, an array of hashes that
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define the action, and a document.
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The following is an example of indexing some classic books into the `books`
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index:
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```<<[lang]>>
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```
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When you use the client to make a request to Elasticsearch, it returns an API
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response object. You can check the HTTP return code by calling `status` and the
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HTTP headers by calling `headers` on the response object. The response object
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also behaves as a Hash, so you can access the body values directly as seen on
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the previous example with ``.
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### Searching
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Now that some data is available, you can search your documents using the
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**Search API**:
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```<<[lang]>>
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```

‎docs/images/copy-endpoint.gif

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