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May 17, 2021 20:24
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| Simple Python applications for demonstrating the features of [Amazon CodeGuru Profiler](https://aws.amazon.com/codeguru/) using the Python agent that is open-sourced at [aws/amazon-codeguru-profiler-python-agent](https://github.com/aws/amazon-codeguru-profiler-python-agent). | ||
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| Check the individual folders for each specific demo application. | ||
| ## How it works | ||
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| The application does some basic image processing, with some CPU-heavy | ||
| operations alongside some IO-heavy operations. | ||
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| It consists chiefly of two components which run in parallel, the task publisher | ||
| and the image processor. | ||
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| CodeGuru Profiler Python agent runs inside the application, in the same way any real application | ||
| would use it. It collects and reports profiling data about the application, ready to | ||
| be viewed in the AWS console. | ||
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| ##### [`TaskPublisher`](aws_python_sample_application/task_publisher.py) | ||
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| ## License | ||
| Checks the S3 bucket for available images, and submits the name of some of these images | ||
| to the SQS queue. | ||
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| This code is licensed under the Apache-2.0 License. See the [LICENSE](LICENSE) file. | ||
| ##### [`ImageProcessor`](aws_python_sample_application/image_processor.py) | ||
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| Polls SQS for names of images to process. Processing an image involves downloading | ||
| it from S3, applying some image transforms (e.g. converting to monochrome), and | ||
| uploading the result back to S3. | ||
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| ## Setup | ||
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| Here is the summary of the steps that follow. | ||
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| 1. Make sure you have installed the latest version of [AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-welcome.html). | ||
| Use an IAM entity for the AWS CLI that has permissions to access CodeGuru Profiler, S3 and SQS to create all the required components for the demo application to run. | ||
| 2. Create a profiling group in CodeGuru Profiler, named `PythonDemoApplication`. | ||
| 3. Create a S3 bucket, e.g. `s3://python-demo-application-test-bucket`. Note, the bucket name must be unique across all of Amazon S3. | ||
| See [here](https://docs.aws.amazon.com/cli/latest/reference/s3/mb.html) for more details. | ||
| 4. Create an SQS queue, e.g. `DemoApplicationQueue`. See [here](https://docs.aws.amazon.com/cli/latest/reference/sqs/create-queue.html) | ||
| for more details. | ||
| 5. Create virtual environment with venv, e.g. `python3 -m venv ./venv`. | ||
| 6. Activate the virtual environment, e.g. `source venv/bin/activate`. | ||
| 7. Install dependency `boto3` and `skimage` through pip3 that are used for the demo application. | ||
| 8. Install the Python agent `codeguru_profiler_agent` through pip3. | ||
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| Here are the commands to run on your machine. | ||
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| ```bash | ||
| aws configure # Set up your AWS credentials and region as usual. | ||
| ``` | ||
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| ```bash | ||
| aws codeguruprofiler create-profiling-group --profiling-group-name PythonDemoApplication | ||
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| # It is required to set the DEMO_APP_BUCKET_NAME and DEMO_APP_SQS_URL environment applications for later running the demo application. | ||
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| # Make sure you update `YOUR-BUCKET-NAME-REPLACE-ME`with a bucket name that is unique across all of Amazon S3. | ||
| export DEMO_APP_BUCKET_NAME=YOUR-BUCKET-NAME-REPLACE-ME | ||
| aws s3 mb s3://${DEMO_APP_BUCKET_NAME} | ||
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| # Make sure you update `YOUR-AWS-REGION-REPLACE-ME` and `YOUR-ACCOUNT-ID-REPLACE-ME`. | ||
| aws sqs create-queue --queue-name DemoApplicationQueue | ||
| export DEMO_APP_SQS_URL=https://sqs.${YOUR-AWS-REGION-REPLACE-ME}.amazonaws.com/YOUR-ACCOUNT-ID-REPLACE-ME/DemoApplicationQueue | ||
| ``` | ||
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| ```bash | ||
| python3 -m venv ./venv | ||
| source venv/bin/activate | ||
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| pip3 install boto3 scikit-image | ||
| pip3 install codeguru_profiler_agent | ||
| ``` | ||
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| For Python 3.9, installing `scikit-image` may cause failures; this is a known issue, discussed in https://github.com/scikit-image/scikit-image/issues/5060. | ||
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| ## How to run | ||
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| The main entry point of this application is in the ``aws_python_sample_application/main.py`` in the ``SampleDemoApp`` class. | ||
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| ```bash | ||
| # Run the demo application with the CodeGuru Profiler Python Agent. | ||
| python3 -m codeguru_profiler_agent -p PythonDemoApplication aws_python_sample_application/main.py | ||
| ``` | ||
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| Let it run for at least 15 to 20 minutes to get plenty of data shown for the PythonDemoApplication profiling group. | ||
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| **Note**: When running the demo application for the first time, it is expected to see the error message such as | ||
| `No messages exists in SQS queue at the moment, retry later.` and | ||
| `Failed to list images in demo-application-test-bucket-1092734-YOUR-BUCKET-REPLACE-ME under input-images/` | ||
| printing to the terminal. Our demo application would handle the upload of the image and the publish of SQS message | ||
| after a few seconds. | ||
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| ## How to see the results | ||
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| Go to the [AWS CodeGuru Profiler console](https://console.aws.amazon.com/codeguru/profiler) to check the results. Choose the region you picked and your profiling group. |
There was a problem hiding this comment.
Why did you move this here? This was intentionally moved inside each folder as this repository contains multiple sample applications.
| serviceAccountName: codeguru-profiler | ||
| containers: | ||
| - name: codeguru-python-app-deployment | ||
| image: 338918620411.dkr.ecr.eu-west-1.amazonaws.com/codeguru-python-app-deployment:latest |
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