[README] Add contribution guide reference to README opensearch-projec…

…t#293 (opensearch-project#299)

* Official Contribution guide from https://opensearch.org/docs/latest/benchmark/user-guide/contributing-workloads/#testing-the-workload added to the readme.
Signed-off-by: safimuhammad <safiwahid38@gmail.com>

* Official contribution guide added to main Readme

Signed-off-by: safimuhammad <safiwahid38@gmail.com>

* Official Contribution guide from https://opensearch.org/docs/latest/b
enchmark/user-guide/contributing-workloads/#testing-the-workload added to the readme.

Signed-off-by: safimuhammad <safiwahid38@gmail.com>

* 1. added a line to consider steps.
2. Added link to offical contribution guide.

Signed-off-by: safimuhammad <safiwahid38@gmail.com>

---------

Signed-off-by: safimuhammad <safiwahid38@gmail.com>

README.md

@@ -14,6 +14,47 @@ After making changes to a workload, it's recommended for developers to run a sim
 
 See all details in the [contributor guidelines](https://github.com/opensearch-project/opensearch-benchmark/blob/main/CONTRIBUTING.md).
 
+**Following are the steps to consider when contributing.**
+### Create a README.md
+
+- The purpose of the workload. When creating a description for the workload, consider its specific use and how the that use case differs from others in the repository.
+- An example document from the dataset that helps users understand the data’s structure.
+- The workload parameters that can be used to customize the workload.
+- A list of default test procedures included in the workload as well as other test procedures that the workload can run.
+- An output sample produced by the workload after a test is run.
+- A copy of the open-source license that gives the user and OpenSearch Benchmark permission to use the dataset.
+
+For an example workload README file, go to the [http_logs](https://github.com/opensearch-project/opensearch-benchmark-workloads/blob/main/http_logs/README.md).
+
+### Verify the workload’s structure
+
+The workload must include the following files:
+- `workload.json`
+- `index.json`
+- `files.txt`
+- `test_procedures/default.json`
+- `operations/default.json`
+
+Both default.json file names can be customized to have a descriptive name. The workload can include an optional workload.py file to add more dynamic functionality. For more information about a file’s contents, go to [Anatomy of a workload](https://opensearch.org/docs/latest/benchmark/user-guide/understanding-workloads/anatomy-of-a-workload/).
+
+### Testing the workload
+
+- All tests run to explore and produce an example from the workload must target an OpenSearch cluster.
+- The workload must pass all integration tests. Follow these steps to ensure that the workload passes the integration tests:
+  1. Add the workload to your forked copy of the [workloads repository](https://github.com/opensearch-project/opensearch-benchmark-workloads/). Make sure that you’ve forked both the opensearch-benchmark-workloads repository and the OpenSearch Benchmark repository.
+  2. In your forked OpenSearch Benchmark repository, update the `benchmark-os-it.ini` and `benchmark-in-memory.ini` files in the `/osbenchmark/it/resources` directory to point to the forked workloads repository containing your workload.
+  3. After you’ve modified the `.ini` files, commit your changes to a branch for testing.
+  4. Run your integration tests using GitHub actions by selecting the branch for which you committed your changes. Verify that the tests have run as expected.
+  5. If your integration tests run as expected, go to your forked workloads repository and merge your workload changes into branches 1 and 2. This allows for your workload to appear in both major versions of OpenSearch Benchmark.
+
+### Create a PR
+
+After testing the workload, create a pull request (PR) from your fork to the opensearch-project [workloads repository](https://github.com/opensearch-project/opensearch-benchmark-workloads/). Add a sample output and summary result to the PR description. The OpenSearch Benchmark maintainers will review the PR.
+
+Once the PR is approved, you must share the data corpora of your dataset. The OpenSearch Benchmark team can then add the dataset to a shared S3 bucket. If your data corpora is stored in an S3 bucket, you can use [AWS DataSync](https://docs.aws.amazon.com/datasync/latest/userguide/create-s3-location.html) to share the data corpora. Otherwise, you must inform the maintainers of where the data corpora resides.
+
+For more details, see this [guide](https://opensearch.org/docs/latest/benchmark/user-guide/contributing-workloads/)
+
 Backporting changes
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