Project Setup Guide

This document provides comprehensive step-by-step instructions to deploy Infosys Agentic Foundry in Amazon Elastic Kubernetes Service (EKS).

Prerequisites

Before setting up the project, ensure you have the following requirements and access permissions:

Ensure users have access to the following:

Python 3.12+ - Required Python version
React - Frontend framework
Infosys GitHub Repo: Infosys-Agentic-Foundry
Ensure users have their AWS Bedrock / Amazon Comprehend / Amazon Transcribe (Speech-to-Text) Keys and Endpoints as required.
Ensure AWS resources are created, and you have access/connectivity to push and pull from these resources:
- Amazon Elastic Container Registry (ECR)
- Amazon Elastic Kubernetes Service (EKS)
- Amazon RDS for PostgreSQL (Instance equivalent: db.t3.small – 2 vCPUs, 4 GiB memory, 32 GiB storage or as per requirement)
- Amazon EC2 Linux Virtual Machine
Install Docker, AWS CLI, and kubectl on your EC2 instance
Create a namespace in the EKS cluster as per your requirement (Optional)

kubectl create namespace <namespace>

AWS Deployment

ARIZE PHOENIX

STEPS FOR DEPLOYING ARIZE PHOENIX IN EKS

Create a YAML file for deploying Arize Phoenix as a container. You can use the Arize Phoenix image in the YAML file.

nano filename1.yaml

Info

You can get the image from Docker - Phoenix or any other trusted source which your organization allows

Now you need to use this command for creating deployment and service:
```
kubectl apply -f filename1.yaml
```
You can check the pods deployed using the command below
```
kubectl get pods -n namespace
```
You can check the services deployed using the command below
```
kubectl get svc -n namespace
```
Note down the load balancer IP for the container. You need to update it in the .env of your backend and frontend folders before creating the respective docker images.

REDIS

STEPS FOR DEPLOYING REDIS IN EKS

Create a YAML file for deploying Redis as a container. You can use the Redis image in the YAML file.

nano filename2.yaml

Info

You can get the image from Image Layer Details - redis:8.2.1 or any other trusted source which your organization allows

Now you need to use this command for creating deployment and service:
```
kubectl apply -f filename2.yaml
```
You can check the pods deployed using the command below
```
kubectl get pods -n namespace
```
You can check the services deployed using the command below
```
kubectl get svc -n namespace
```
Note down the load balancer IP for the container. You need to update it in the .env of your backend folder before creating the respective docker image.

GRAFANA

STEPS FOR DEPLOYING GRAFANA IN EKS

Create a YAML file for deploying Grafana as a container. You can use the Grafana image in the YAML file.

nano filename3.yaml

Info

You can get the image from Image Layer Details - grafana/grafana:11.2.0 or any other trusted source which your organization allows

Now you need to use this command for creating deployment and service:
```
kubectl apply -f filename3.yaml
```
You can check the pods deployed using the command below
```
kubectl get pods -n namespace
```
You can check the services deployed using the command below
```
kubectl get svc -n namespace
```
Note down the load balancer IP for the container. You need to update it in the .env of your backend and frontend folders before creating the respective docker images.

ELASTIC SEARCH

STEPS FOR DEPLOYING ELASTIC SEARCH IN EKS

Create a YAML file for deploying Elasticsearch as a container. You can use the Elasticsearch image in the YAML file.

nano filename4.yaml

Info

You can get the image from elasticsearch - Official Image | Docker Hub or any other trusted source which your organization allows

Now you need to use this command for creating deployment and service:
```
kubectl apply -f filename4.yaml
```
You can check the pods deployed using the command below
```
kubectl get pods -n namespace
```
You can check the services deployed using the command below
```
kubectl get svc -n namespace
```
Note down the load balancer IP for the container and update it in the OpenTelemetry YAML script.

OPEN-TELEMETRY

STEPS FOR DEPLOYING OPEN-TELEMETRY IN EKS

Create a YAML file for deploying OpenTelemetry as a container, and use the OpenTelemetry Collector image in the YAML file.

nano filename5.yaml

Info

You can get the image from otel/OpenTelemetry-collector-contrib - Docker Image or any other trusted source your organization allows

Now you need to use this command for creating deployment and service:
```
kubectl apply -f filename5.yaml
```
You can check the pods deployed using the command below
```
kubectl get pods -n namespace
```
You can check the services deployed using the command below
```
kubectl get svc -n namespace
```
Note down the load balancer IP for the container. You need to update it in the .env of your backend folder before creating the respective docker image.

MODEL SERVER

STEPS TO SET UP MODEL SERVER

For detailed instructions on deploying and configuring your model server, refer to the Model Server Deployment guide.

Note

You need to update the URL for the model server in the .env of the backend folder

BACKEND

STEPS TO SET UP BACKEND

Download Backend code from GitHub. For detailed instructions, see Download the Backend Project Code.

Log in to AWS EC2 Linux OS (AWS VM).
Download Backend source code folder into AWS VM.
Before starting backend image creation make sure that Arize Phoenix, OpenTelemetry, Grafana, Elasticsearch, Redis, and Model server are set up as per instructions provided above. Update the respective URLs of all these services in .env file.
Update the remaining values for the variables in the .env file.
Change working directory to the Backend Folder:
```
cd `<BE foldername>`
```
Create a Dockerfile inside the Backend folder to create docker image for Backend code.

Create backend image:

    docker build -f `<dockerfile-name>` -t `<tag-name>`

Retag the created image to ECR name:

docker tag localhost/<imagename>:<tag> <ecr login server>/<imagename>:<tag>

Log in to ECR:
```
docker login <ecr login server>
```

Push the retagged image to ECR:

docker push <ecr login server>/<imagename>:<tag>

Create backend deployment file:
```
nano <deployment filename.yaml>
```
Log in to EKS

Execute the deployment file:

kubectl apply -f <deployment filename.yaml>

Check if the pods are deployed successfully:
```
kubectl get pods -n <namespace>
```
Check if the service is up & running successfully:
```
kubectl get svc -n <namespace>
```

FRONTEND

STEPS TO SET UP FRONTEND

Download Frontend code from GitHub. For detailed instructions, see Download the Frontend Project Code.

Log in to AWS VM
Download Frontend source code folder into AWS VM
Before starting frontend image creation make sure that Arize Phoenix and Grafana are set up as per instructions provided above. Update the respective URLs of all these services in .env file.
Change working directory to the Frontend Folder:
```
    cd <Frontend foldername>
```
Create a Dockerfile inside the Frontend folder to create docker image from Frontend code.
In .env file of Frontend, update the following service load balancer URLs, which were generated after deployment of the backend server in Amazon Elastic Kubernetes Service (EKS).
- REACT_APP_BASE_URL (use Backend URL),
- REACT_APP_MKDOCS_BASE_URL (use mkdocs URL),
- REACT_APP_LIVE_TRACKING_URL (use Arize Phoenix URL),
- REACT_APP_GRAFANA_DASHBOARD_URL (use Grafana URL)

Create Frontend image:

    docker build -f <dockerfile-name> -t <tag-name>

Retag the created image to ECR name:

docker tag localhost/<imagename>:<tag> <ecr login server>/<imagename>:<tag>

Log in to ECR:
```
docker login <ecr login server>
```

Push the retagged image to ECR:

docker push <ecr login server>/<imagename>:<tag>

Create Frontend deployment file:
```
nano <deployment filename.yaml>
```
Log in to Amazon Elastic Kubernetes Service (EKS)

Execute the deployment file:

kubectl apply -f <deployment filename.yaml>

Check if the pods are deployed successfully:
```
kubectl get pods -n <namespace>
```
Check if the service is up & running successfully:
```
kubectl get svc -n <namespace>
```

Troubleshooting

Virtual Environment Activation Fails

Permissions Error: Try running command prompt as administrator

Dependency Installation Errors

Update pip to the latest version:

python -m pip install --upgrade pip

Check for typos in commands or file names

To troubleshoot, check pod logs in Kubernetes using the following commands:

kubectl describe pods <pod_name> -n <namespace>
kubectl logs <pod_name> -n <namespace>