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Data Science & Development

Solution	Description
JupyterHub Server	JupyterHub platform supporting multiple programming languages and collaborative development
RStudio Server	Simplify your R development workflow with a pre-configured RStudio Server environment for remote access
RShiny Server	Production-ready environment for hosting and managing Shiny applications

Security & Infrastructure

Solution	Description
VPN Server	VPN solution with Web GUI for secure network access
Linux with GUI Desktop	User-friendly desktop environment for cloud-based Linux systems
Linux SFTP Server	Facilitates secure file transfers with a pre-configured SFTP server environment
ClamAV Antivirus API	Secure your cloud data with our integrated virus scanning solution

AI & Machine Learning

Solution	Description
Stable Diffusion UI	State-of-the-art image generation and manipulation platform with intuitive web interface

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We're here to help you succeed! Our dedicated support team is ready to assist with:

• Technical implementation
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• General inquiries
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📧 Contact us: support@elmcomputing.io

---

ClamAV AntiVirus

Running ECS Task with Fargate

This guide provides step-by-step instructions to run the virus scan API server using Amazon ECS Fargate. If not mentioned, please use the default configurations.

---

Step 1: Create an ECS Task Definition

1. Log into the Amazon ECS Console.

2. Select Task Definitions and click Create new Task Definition.

3. Under Task definition configuration:

   • Task definition family: Set a name (e.g., elm-clamav-virus-scan-api).

4. Under Infrastructure requirements:

   • Launch Type: Fargate
   • Operating System/Architecture: Linux/X86_64
   • Task size: Set 1 vCPU and 3GB memory (initial settings, adjustable as needed for handling larger or more files).
   • Task role and Task execution role: Ensure the following IAM policies are attached to the roles:
     • AmazonECSTaskExecutionRolePolicy
     • AmazonS3ReadOnlyAccess
     • AWSMarketplaceMeteringRegisterUsage

5. Under Container - 1:

   • Container Name: Set a name (e.g., clamav-virus-scan-api).

   • Image URI:

     709825985650.dkr.ecr.us-east-1.amazonaws.com/elm-computing/clamav-virus-scan-api:1.2.1.2
     

     where 1.2.1.2 is the version number and can be replaced for other versions.

   • Port Mappings:

     • Container Port: 8080
     • Protocol: TCP
     • Port Name: virus-scan-api
     • App Protocol: http

   • Health Check: Command:

     CMD-SHELL, curl -f http://localhost:8080/api/healthcheck || exit 1
     

     • Interval: 30 seconds
     • Timeout: 5 seconds
     • Start period: 30 seconds
     • Retries: 3

6. Click Create to finalize the task definition.

---

Step 2: Run the Task

1. In the Amazon ECS Console, select Clusters from the left-hand side and choose an existing cluster or create a new one.

2. Click on the Tasks tab, then click Run new Task.

3. Under Compute configuration (advanced):

   • Compute options: Launch type
   • Launch Type: Fargate.

4. Under Deployment configuration:

   • Application type: Task
   • Family: Select the task definition created in Step 1.

5. Under Networking:

   • VPC and Subnet: Choose the appropriate VPC and subnet.

6. For Security Group, ensure the inbound port 8080 is open to all IPs or to a specific range:

   • Type: Custom TCP Rule.
   • Port: 8080.
   • Source: 0.0.0.0/0 (or restrict the IP range for secure access).
   • Public IP: Turned On (for security concerns, this can be turned off if the API server is only accessible from within the same subnet).

7. Click Create.

---

Step 3: Monitor the Task

1. Go to the Tasks tab to check the Health status. It usually takes around 2-3 minutes for the task to reach the "Healthy" status.

2. Check the task logs via Amazon CloudWatch Logs to ensure there are no errors reported and that the task is functioning correctly.

---

By following these steps, you will successfully run your ClamAV Virus Scan API container image with an initial task size of 1 vCPU and 3GB memory, adjustable as needed for handling larger or more files for scanning.

Scan S3 objects

After starting the EC2 instance, you can access the API Server using its IP address and the port 8080. For instance, if the IP address is 172.31.39.37, you can perform file scans on the S3 bucket by making requests to http://172.31.39.37:8080/api/clamav/scan/s3/object.

curl -d '{"stream": true, "bucket": "elm-bucket-virus-scan", "key": "test/virus_test.txt"}' -H 'Content-Type: application/json' http://172.31.39.37:8080/api/clamav/scan/s3/object 

The three parameters have the following meanings:

• stream: This parameter determines how the server should handle the file download. When set to false, it means that the server will download the whole file into memory first before saving it to disk. When set to true, the server will stream the file directly to disk in smaller chunks. Using streaming can be advantageous when dealing with large files as it reduces the memory footprint required for the download process. It allows for more efficient resource utilization and enables the server to handle files that might otherwise exceed available memory capacity.

• bucket: This parameter specifies the name of the S3 bucket from which the file should be retrieved.

• key: This parameter represents the key of the file within the S3 bucket. It specifies the specific file that should be downloaded and scanned.

Response

A json format string will be returned. The possible return codes are 0, 1, 2, and 99.

Clean

{"code":0,"message":"OK"}

Infected

For example, when Eicar-Signature is identified, the response would be

{"code":1,"message":"Eicar-Signature FOUND"}

Scan Errors

For example, when having file access error, the response would be

{"code":2,"message":"Can't access file /tmp/test/file"}

Other Errors

For example, when the IAM role is not properly set, the response would be

{"code":99,"message":"no credentials in the property bag"}

Scan local files

You can perform file scans on local files by making requests to http://172.31.39.37:8080/api/clamav/scan/file.

curl -d '{"file": "/tmp/test.txt"}' -H 'Content-Type: application/json' http://172.31.39.37:8080/api/clamav/scan/file

Code Examples

Shell

curl -d '{"stream": true, "bucket": "elm-bucket-virus-scan", "key": "test/virus_test.txt"}' -H 'Content-Type: application/json' http://172.31.39.37:8080/api/clamav/scan/s3/object 

Python

import requests
import json

def elm_scan_object(url, stream, bucket, key):
    # Define the payload as a dictionary
    payload = {
		"stream": stream,
        "bucket": bucket,
        "key": key
    }

    # Set the headers
    headers = {
        "Content-Type": "application/json"
    }

    # Send a POST request to the API endpoint
    response = requests.post(url, data=json.dumps(payload), headers=headers)

    # Check the response status code
    if response.status_code == 200:
        # Request was successful
        data = response.json()  # Extract the JSON data from the response
        return data
    else:
        # Request was not successful
        print(f"Request failed with status code: {response.status_code}")
        return None

if __name__ == '__main__':        
    result = elm_scan_object(
        url = "http://172.31.39.37:8080/api/clamav/scan/s3/object", \
		stream = True, \
        bucket = 'elm-bucket-virus-scan', \
        key = 'virus_test.txt')
    
    if result:
        print(result)
        print(result['code'])
        print(result['message'])

JavaScript

const axios = require('axios');

async function elmScanObject(url, stream, bucket, key) {
  try {
    const payload = {
	  stream,
      bucket,
      key,
    };

    const headers = {
      'Content-Type': 'application/json',
    };

    const response = await axios.post(url, payload, { headers });

    if (response.status === 200) {
      return response.data;
    } else {
      console.log(`Request failed with status code: ${response.status}`);
      return null;
    }
  } catch (error) {
    console.error('An error occurred:', error.message);
    return null;
  }
}

async function main() {
  const url = 'http://172.31.39.37:8080/api/clamav/scan/s3/object';
  const stream = true;
  const bucket = 'elm-bucket-virus-scan';
  const key = 'virus_test.txt';

  const result = await elmScanObject(url, stream, bucket, key);

  if (result) {
    console.log(result);
    console.log(result.code);
    console.log(result.message);
  }
}

main();

Dart

import 'dart:convert';
import 'package:http/http.dart' as http;

Future<Map<String, dynamic>?> elmScanObject(String url, bool stream, String bucket, String key) async {
  try {
    final payload = {
      'stream': stream,
      'bucket': bucket,
      'key': key,
    };

    final headers = {
      'Content-Type': 'application/json',
    };

    final response = await http.post(Uri.parse(url), headers: headers, body: jsonEncode(payload));

    if (response.statusCode == 200) {
      return jsonDecode(response.body);
    } else {
      print('Request failed with status code: ${response.statusCode}');
      return null;
    }
  } catch (error) {
    print('An error occurred: $error');
    return null;
  }
}

void main() async {
  final url = 'http://172.31.39.37:8080/api/clamav/scan/s3/object';
  final stream = true;
  final bucket = 'elm-bucket-virus-scan';
  final key = 'virus_test.txt';

  final result = await elmScanObject(url, stream, bucket, key);

  if (result != null) {
    print(result);
    print(result['code']);
    print(result['message']);
  }
}

Go

package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"io/ioutil"
	"net/http"
)

func elmScanObject(url string, stream bool, bucket string, key string) (map[string]interface{}, error) {
	payload := map[string]interface{}{
		"stream": stream,
		"bucket": bucket,
		"key":    key,
	}

	payloadBytes, err := json.Marshal(payload)
	if err != nil {
		return nil, err
	}

	req, err := http.NewRequest("POST", url, bytes.NewBuffer(payloadBytes))
	if err != nil {
		return nil, err
	}

	req.Header.Set("Content-Type", "application/json")

	client := &http.Client{}
	resp, err := client.Do(req)
	if err != nil {
		return nil, err
	}
	defer resp.Body.Close()

	respBody, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		return nil, err
	}

	if resp.StatusCode == http.StatusOK {
		var data map[string]interface{}
		err = json.Unmarshal(respBody, &data)
		if err != nil {
			return nil, err
		}
		return data, nil
	} else {
		return nil, fmt.Errorf("Request failed with status code: %d", resp.StatusCode)
	}
}

func main() {
	url := "http://172.31.39.37:8080/api/clamav/scan/s3/object"
	stream := true
	bucket := "elm-bucket-virus-scan"
	key := "virus_test.txt"

	result, err := elmScanObject(url, stream, bucket, key)
	if err != nil {
		fmt.Println("An error occurred:", err)
		return
	}

	if result != nil {
		fmt.Println(result)
		fmt.Println(result["code"])
		fmt.Println(result["message"])
	}
}

Version 1.2.1.2

• ClamAV: 1.2.1

• Enabled detecting OLE2 files containing VBA macros, which were not detected by signatures will be marked as "Heuristics.OLE2.ContainsMacros".

• Enabled AlertExceedsMax.

  Files exceeding the MaxFileSize (100M), MaxScanSize (400M), or MaxRecursion (10) limit will be flagged with the virus name starting with "Heuristics.Limits.Exceeded".

  If your scan is expected to trigger the alert, please contact us at support@elmcomputing.io

API endpoints

• http://ip-address:8080/api/clamav/scan/s3/object

• http://ip-address:8080/api/clamav/scan/file

• http://ip-address:8080/api/healthcheck

This AMI offers two ways to set up and use:

1. RStudio IDE with AI Assistant within Linux GUI Desktop
2. Regular RStudio Server access

---

1. RStudio IDE with AI Assistant within Linux GUI Desktop

To connect to the Linux GUI Desktop on your EC2 instance using an RDP client:

1. Use the public IP address of the instance as the PC name.
2. The default username is ruser.
3. The password is the EC2 instance ID, which follows the format i-0c7xxxxxxxxxxxxxx. Replace this with your actual instance ID found in the AWS Management Console under the Instances section.
4. Proceed to connect. You may receive a security warning about the certificate; you can safely choose to continue.

RDP Client Downloads:

• For Mac: Windows App
• For Windows: Windows App

This setup allows you to remotely access your instance using the Remote Desktop Protocol (RDP) with the provided credentials.

Connection Steps

Detailed steps for connecting to the Linux GUI Desktop are available here.

Launch RStudio IDE

Once connected, start the RStudio IDE with AI Assistant:

1. Navigate to:

Applications -> Development -> RStudio

2. This will launch the RStudio IDE within your Linux environment.

Steps to Start the gptstudio RShiny App in the Viewer Panel

1. Load the gptstudio Library

   library(gptstudio)
   

2. Set the OpenAI API Key

   You need an API key from OpenAI to use the gptstudio OpenAI features. You can obtain your key by signing up or logging into your account on the OpenAI website. After obtaining the key, set it using the following command:

   Sys.setenv(OPENAI_API_KEY = "your_openai_api_key")
   

3. Launch the Chat App

   gptstudio_chat()
   

4. Check the Port Number in the Error Message:

   If an error occurs, note the port number shown in the error message. For example, the error message might indicate:

   Failed to connect to 127.0.0.1 port 3570 after 0 ms: Connection refused
   

   In this case, the port is 3570.

5. Open the App in the Viewer Pane

   Replace the port number accordingly:

   rstudioapi::viewer("http://127.0.0.1:<port_number>")
   

   For example, if the port is 3570, use:

   rstudioapi::viewer("http://127.0.0.1:3570")
   

These steps will launch the gptstudio RShiny app and display it in RStudio’s Viewer panel.

---

2. Regular RStudio Server Access

After the EC2 instance is started, you can access RStudio Server via the public IP address.

For example, if the IP address is 10.11.12.13, enter the following URL in your browser

http://10.11.12.13

to access the login page as below:

Login Credentials

• Username: ruser
• Password: The EC2 instance ID (format: i-0c7xxxxxxxxxxxxxx)

Automatic Redirect from HTTP to HTTPS

All HTTP traffic is automatically redirected to HTTPS to ensure encrypted and secure communication.

Self-Signed Certificate

• The HTTPS connection uses a self-signed certificate.
• The first time you access the site, you may need to accept the self-signed certificate in your browser.
• This step is necessary to establish a secure connection.

IP Address Changes

• If the IP address changes, a new self-signed certificate will be generated.
• You may need to accept the new certificate in your browser to re-establish a secure connection.

Additional Information

• SSH Username: ubuntu
• SSH Port: 22

RStudio Server

    R: 4.4.2

    rstudio-server: 2024.04.2-764

Release Notes

Integrated RStudio Server with Xfce GUI Desktop, featuring an AI Assistant for the RStudio IDE.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4303)

After the EC2 instance is started, you can access the RStudio Server with its public IP address. For example, if the IP address is 10.11.12.13, typing http://10.11.12.13 in the browser will bring you to the following startup page:

The default username is ruser and the password is the EC2 instance ID that has the form of i-0c7fadc4dc193eca7.

RStudio Server AMI on AWS Marketplace

Subscribe to the AMI

Continue to configure the EC2 instance

Choose a region close to your location

Choose an instance type

t2.micro is a good starting point for testing. Once everything is confirmed to work, you can switch to other instance types (more CPUs, high memory) that fit your need.

Create security group

If you do not already have an SSH key pair, please generate a new one to use when logging into the RStudio Server.

Create SSH key pair with default values

Choose "allow" to download your SSH key pair

Launch your EC2 instance

Go to EC2 console

Select the new EC2 instance

Public IP address and Instance ID

Access the login page

Enter RStudio IDE

Change instance type

To change the instance type once the server is tested, please go to "Actions", "Instance settings", and then "Change instance type".

RStudio Server

    R: 4.5.0

    rstudio-server: 2024.12.1-563

Release Notes

Update R to version 4.5.0, upgrade all R packages to their latest versions, update RStudio Server to version 2024.12.1-563, and apply security patches.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4319)

RStudio Server

    R: 4.4.3

    rstudio-server: 2024.04.2-764

Release Notes

There was an issue in version 4.4.3.0 where R was mistakenly left at version 4.4.2 instead of being upgraded to 4.4.3. This has now been corrected, and R has been upgraded to version 4.4.3, with all R packages remaining the same as in version 4.4.3.0.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4317)

RStudio Server

    R: 4.4.2

    rstudio-server: 2024.04.2-764

Release Notes

Upgraded R to version 4.4.3 and updated all R packages to their latest versions; applied security patches. (There was a mistake and R was still 4.4.2 in this version)

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4317)

RStudio Server

    R: 4.4.2

    rstudio-server: 2024.04.2-764

Release Notes

Upgraded R packages to their latest versions.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4310)

RStudio Server

    R: 4.4.2

    rstudio-server: 2024.04.2-764

Release Notes

Upgraded R to version 4.4.2, and all R packages to their latest versions.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4302)

RStudio Server

R: 4.4.1

rstudio-server: 2024.04.2-764

Release Notes

Since RStudio v1.3, the default authentication timeout configuration was changed to address security concerns about session hijacking, as users could remain signed in for extended periods. The new default automatically signs users out after 60 minutes of inactivity (no interaction with the IDE). This change impacts long-running code that is not started as a background job. To accommodate user preferences, the legacy behavior has been restored, allowing users to stay signed in for several days without being forced to log in again after going idle.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4293)

RStudio Server

R: 4.4.1

rstudio-server: 2024.04.2-764

Release Notes

Upgraded the operating system from Ubuntu 20.04 to Ubuntu 22.04, and all R packages to their latest versions.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4293)

RStudio Server

R: 4.4.1

rstudio-server: 2024.04.2-764

Release Notes

Upgraded R to version 4.4.1, rstudio-server to version 2024.04.2-764, and all R packages to their latest versions; removed GPU support that will be integrated into a separate AMI product.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4410)

RStudio Server

R: 4.4.0

rstudio-server: 2023.12.0+369

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

• Enabled HTTPS to Improve Security: HTTPS has been enabled to ensure that all data between your browser and our servers is encrypted.

• Automatic Redirect from HTTP to HTTPS: All HTTP traffic is now automatically redirected to HTTPS, ensuring that all communications between your browser and our servers are encrypted and secure.

• Self-Signed Certificate: Please note that the HTTPS connection uses a self-signed certificate. When accessing the site for the first time, you may need to accept the self-signed certificate in your browser to proceed. This step is necessary to establish a secure connection.

• IP Address Changes: If the IP address changes, a new self-signed certificate will be generated. You may need to accept the new certificate in your browser to re-establish a secure connection.

R: 4.4.0; rstudio-server: 2023.12.0+369; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4170)

RStudio Server

R: 4.4.0

rstudio-server: 2023.12.0+369

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Upgraded R to version 4.4.0 and all R packages to their latest versions.

R: 4.4.0; rstudio-server: 2023.12.0+369; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4170)

RStudio Server

R: 4.3.3

rstudio-server: 2023.12.0+369

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Added GPU support for tensorflow.

R: 4.3.3; rstudio-server: 2023.12.0+369; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4161)

RStudio Server

R: 4.3.3

rstudio-server: 2023.12.0+369

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Installed tensorflow CPU version.

R: 4.3.3; rstudio-server: 2023.12.0+369; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4161)

RStudio Server

R: 4.3.3

rstudio-server: 2023.12.0+369

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Upgraded R to version 4.3.3 and all R packages to their latest versions.

R: 4.3.3; rstudio-server: 2023.12.0+369; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4161)

RStudio Server

R: 4.3.2

rstudio-server: 2023.12.0+369

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Applied security patching and updated all R packages to their latest versions. Additionally, included essential R packages for Actuarial Science, Optimization, Genomics, Proteomics, Metabolomics, Transcriptomics, and other Omics.

R: 4.3.2; rstudio-server: 2023.12.0+369; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4156)

RStudio Server

R: 4.3.2

rstudio-server: 2023.12.0+369

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Upgraded rstudio-server to version 2023.12.0+369, and all R packages to their latest versions. Additionally, included essential R packages for Econometrics.

R: 4.3.2; rstudio-server: 2023.12.0+369; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics and natural language processing.

R packages (3638)

RStudio Server

R: 4.3.2

rstudio-server: 2023.09.01-494

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Upgraded R to version 4.3.2, rstudio-server to version 2023.09.01-494, and all R packages to their latest versions. Additionally, included essential R packages for Reproducible Research, Phylogenetics, Web Technologies, Hydrology, and Sports Analytics.

R: 4.3.2; rstudio-server: 2023.09.1-494; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics and natural language processing.

R packages (3518)

RStudio Server

R: 4.3.1

rstudio-server: 2023.06.2+561

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Added package flock

R: 4.3.1; rstudio-server: 2023.06.2+561; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, and natural language processing.

R packages (2904)

RStudio Server

R: 4.3.1

rstudio-server: 2023.06.2+561

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Added packages argparse, lpSolveAPI and telegram.bot

R: 4.3.1; rstudio-server: 2023.06.2+561; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, and natural language processing.

R packages (2903)

RStudio Server

R: 4.3.1

rstudio-server: 2023.06.2+561

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Applied security patching; Updated R packages to newer versions; Added R packages for spatial and spatiotemporal analysis; Updated rstudio-server to 2023.06.2+561

R: 4.3.1; rstudio-server: 2023.06.2+561; CUDA Version: 11.7; GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, and natural language processing.

R packages (2900)

RStudio Server

R: 4.3.1

rstudio-server: 2023.06.0+421

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Applied patching, updated R packages, and added R packages used in finance, official statistics, and survey statistics.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, and natural language processing.

R packages (2659)

RStudio Server

R: 4.3.1

rstudio-server: 2023.06.0+421

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Installed R packages used for interacting with databases.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, databases, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, and natural language processing.

R packages (2349)

RStudio Server

R: 4.3.1

rstudio-server: 2023.06.0+421

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Updated R from 4.3.0 to 4.3.1 and R packages to newer versions.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, and natural language processing.

R packages (2295)

RStudio Server

R: 4.3.0

rstudio-server: 2023.06.0+421

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Set cairo as the default graphics backend; Installed flexdashboard and rticles to provide versatile R Markdown templates; Updated rstudio-server to 2023.06.0+421

This AMI provides thousands of R packages covering various domains such as data science, machine learning, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, and natural language processing.

R packages (2291)

RStudio Server

R: 4.3.0

rstudio-server: 2023.03.0

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Installed additional R packages covering various domains such as Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, and natural language processing.

R packages (2289)

RStudio Server

R: 4.3.0

rstudio-server: 2023.03.0

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Updated R to 4.3.0, rstudio-server to 2023.03.0, and R packages to newer versions.

R packages

RStudio Server

R: 4.2.3

rstudio-server: 2022.12.0-353

CUDA Version: 12.0

GPU Driver Version: 525.85.12

Release Notes

Increased the maximum number of open connections to 1024, with three of them allocated for stdin, stdout, and stderr.

R packages

RStudio Server

R: 4.2.3

rstudio-server: 2022.12.0-353

CUDA Version: 12.0

GPU Driver Version: 525.85.12

Release Notes

Applied system patches.

Enabled automatic compression and extraction for exporting and uploading.

Removed the file size limit for uploads, allowing users to upload larger files.

R packages

RStudio Server

R: 4.2.3

rstudio-server: 2022.12.0-353

CUDA Version: 12.0

GPU Driver Version: 525.85.12

R packages

RStudio Server

R: 4.2.2

rstudio-server: 2022.12.0-353

CUDA Version: 12.0

GPU Driver Version: 525.85.12

R packages

RStudio Server

R: 4.2.2

rstudio-server: 2022.12.0-353

CUDA Version: 12.0

GPU Driver Version: 525.85.12

R packages

RStudio Server

R: 4.2.2

rstudio-server: 2022.12.0-353

R packages

After the EC2 instance is started, you can access the RShiny Server with its public IP address. For example, if the IP address is 10.11.12.13, typing http://10.11.12.13 in the browser will bring you to the following startup page:

The RShiny applications are served from the directory /srv/shiny-server.

RShiny Server

    R: 4.5.0

    rshiny-server: 1.5.23.1030

Release Notes

Update R to version 4.5.0, upgrade all R packages to their latest versions, update RShiny Server to version 1.5.23.1030, and apply security patches.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4319)

RShiny Server

    R: 4.4.3

    rshiny-server: 1.5.22.1017

Release Notes

Upgraded R to version 4.4.3 and updated all R packages to their latest versions; applied security patches.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4317)

RShiny Server

    R: 4.4.2

    rshiny-server: 1.5.22.1017

Release Notes

Upgraded R to version 4.4.2, and all R packages to their latest versions.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4302)

RShiny Server

R: 4.4.1

rshiny-server: 1.5.22.1017

Release Notes

Upgraded the operating system from Ubuntu 20.04 to Ubuntu 22.04, and all R packages to their latest versions.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4293)

RShiny Server

R: 4.4.0

rshiny-server: 1.5.22.1017

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Upgraded R to version 4.4.0 and all R packages to their latest versions.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4170)

RShiny Server

R: 4.3.3

rshiny-server: 1.5.21.1012

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Upgraded R to version 4.3.3 and all R packages to their latest versions.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics, natural language processing, actuarial science, optimization, genomics, proteomics, metabolomics, transcriptomics, and other omics.

R packages (4161)

RShiny Server

R: 4.3.2

rshiny-server: 1.5.21.1012

CUDA Version: 11.7

GPU Driver Version: 515.43.04

Release Notes

Upgraded R to 4.3.2 and shiny-server to version shiny-server-1.5.21.1012, and all R packages to their latest versions.

This AMI provides thousands of R packages covering various domains such as data science, machine learning, economitrics, database, finance, official statistics, survey statistics, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, analysis of spatial and spatiotemporal data, reproducible research, phylogenetics, web technologies, hydrology, sports analytics and natural language processing.

R packages (3638)

RShiny Server

R: 4.3.0

rshiny-server: 1.5.20.1002

CUDA Version: 11.7

GPU Driver Version: 515.43.04

This AMI provides thousands of R packages covering various domains such as data science, machine learning, Bayesian statistics, clinical trials, epidemiology, experimental design, psychometric methodology, analysis of pharmacokinetic data, medical image processing, teaching statistics, time series analysis, and natural language processing.

R packages (2291)

RShiny Server

R: 4.2.3

rshiny-server: 1.5.20.1002

CUDA Version: 12.0

GPU Driver Version: 525.85.12

R packages

ClamAV AntiVirus

IAM Role Configuration

To facilitate the server's access to S3 data, it is essential to assign an IAM role with the AmazonS3ReadOnlyAccess policy attached. This role should be created and linked to the EC2 instance, ensuring the necessary permissions for data retrieval.

Enhancing Security

For enhanced security, it is strongly advised to disable the public IP address associated with the instance. This precautionary measure limits access to the API Server, thereby reducing potential security risks.

Optimizing Network Deployment

To minimize data transfer costs, it is recommended to deploy the server within the same availability zone as your existing infrastructure. By colocating the virus scan server and your other resources in the same availability zone, you can take advantage of the low-cost or free data transfer within the same zone. This setup also ensures that the virus scan API server operates within the same network environment as your infrastructure, enabling faster and more efficient communication while minimizing data transfer costs.

Cross-Machine File Scanning

To scan files located on different machines, you can leverage the NFS server enabled on the API server. Follow these steps:

• On your local machine, create a directory to store the data you want to scan. For example:

  mkdir /tmp/data-to-scan

• Use the following command to mount the NFS shared directory from your Virus Scan Server AMI to your local machine:

  sudo mount -t nfs api-server-ip-address:/elm/shared /tmp/data-to-scan

• Files stored in /tmp/data-to-scan on your local machine can be accessed and scanned by the Virus Scan Server AMI via http://api-server-ip-address:8080/api/clamav/scan/file

To install the NFS client, use the following commands for ubuntu-like and amazon-linux-like operating systems, respectively:

sudo apt install nfs-common

sudo yum install nfs-utils

Scan S3 objects

After starting the EC2 instance, you can access the API Server using its IP address and the port 8080. For instance, if the IP address is 172.31.39.37, you can perform file scans on the S3 bucket by making requests to http://172.31.39.37:8080/api/clamav/scan/s3/object.

The virus scan API Server is configured to listen on the local address 127.0.0.1:3000. To initiate a virus scan, you can send an HTTP request to http://127.0.0.1:3000/api/clamav/scan/s3/object if the request originates from within the virus scan API server.

curl -d '{"stream": true, "bucket": "elm-bucket-virus-scan", "key": "test/virus_test.txt"}' -H 'Content-Type: application/json' http://172.31.39.37:8080/api/clamav/scan/s3/object 

Parameter Meanings

The following parameters are used in the request:

stream

This parameter controls how the server handles the file download process. When set to false, the server downloads the entire file into memory before saving it to disk. Conversely, when set to true, the server streams the file directly to disk in smaller chunks. Streaming is particularly beneficial when dealing with large files, as it reduces the memory required for the download process. This approach enables more efficient resource utilization and allows the server to handle files that might otherwise exceed available memory capacity.

bucket

This parameter specifies the name of the S3 bucket from which the file should be retrieved.

key

This parameter represents the key of the file within the S3 bucket. It identifies the specific file that should be downloaded and scanned.

Response

A json format string will be returned. The possible return codes are 0, 1, 2, and 99.

Clean

{"code":0,"message":"OK"}

Infected

For example, when Eicar-Signature is identified, the response would be

{"code":1,"message":"Eicar-Signature FOUND"}

Scan Errors

For example, when having file access error, the response would be

{"code":2,"message":"Can't access file /tmp/test/file"}

Other Errors

For example, when the IAM role is not properly set, the response would be

{"code":99,"message":"no credentials in the property bag"}

Scan local files

You can perform file scans on local files by making requests to http://172.31.39.37:8080/api/clamav/scan/file.

curl -d '{"file": "/tmp/test.txt"}' -H 'Content-Type: application/json' http://172.31.39.37:8080/api/clamav/scan/file

Shell

curl -d '{"stream": true, "bucket": "elm-bucket-virus-scan", "key": "test/virus_test.txt"}' -H 'Content-Type: application/json' http://172.31.39.37:8080/api/clamav/scan/s3/object 

Python

import requests
import json

def elm_scan_object(url, stream, bucket, key):
    # Define the payload as a dictionary
    payload = {
		"stream": stream,
        "bucket": bucket,
        "key": key
    }

    # Set the headers
    headers = {
        "Content-Type": "application/json"
    }

    # Send a POST request to the API endpoint
    response = requests.post(url, data=json.dumps(payload), headers=headers)

    # Check the response status code
    if response.status_code == 200:
        # Request was successful
        data = response.json()  # Extract the JSON data from the response
        return data
    else:
        # Request was not successful
        print(f"Request failed with status code: {response.status_code}")
        return None

if __name__ == '__main__':        
    result = elm_scan_object(
        url = "http://172.31.39.37:8080/api/clamav/scan/s3/object", \
		stream = True, \
        bucket = 'elm-bucket-virus-scan', \
        key = 'virus_test.txt')
    
    if result:
        print(result)
        print(result['code'])
        print(result['message'])

JavaScript

const axios = require('axios');

async function elmScanObject(url, stream, bucket, key) {
  try {
    const payload = {
	  stream,
      bucket,
      key,
    };

    const headers = {
      'Content-Type': 'application/json',
    };

    const response = await axios.post(url, payload, { headers });

    if (response.status === 200) {
      return response.data;
    } else {
      console.log(`Request failed with status code: ${response.status}`);
      return null;
    }
  } catch (error) {
    console.error('An error occurred:', error.message);
    return null;
  }
}

async function main() {
  const url = 'http://172.31.39.37:8080/api/clamav/scan/s3/object';
  const stream = true;
  const bucket = 'elm-bucket-virus-scan';
  const key = 'virus_test.txt';

  const result = await elmScanObject(url, stream, bucket, key);

  if (result) {
    console.log(result);
    console.log(result.code);
    console.log(result.message);
  }
}

main();

Dart

import 'dart:convert';
import 'package:http/http.dart' as http;

Future<Map<String, dynamic>?> elmScanObject(String url, bool stream, String bucket, String key) async {
  try {
    final payload = {
      'stream': stream,
      'bucket': bucket,
      'key': key,
    };

    final headers = {
      'Content-Type': 'application/json',
    };

    final response = await http.post(Uri.parse(url), headers: headers, body: jsonEncode(payload));

    if (response.statusCode == 200) {
      return jsonDecode(response.body);
    } else {
      print('Request failed with status code: ${response.statusCode}');
      return null;
    }
  } catch (error) {
    print('An error occurred: $error');
    return null;
  }
}

void main() async {
  final url = 'http://172.31.39.37:8080/api/clamav/scan/s3/object';
  final stream = true;
  final bucket = 'elm-bucket-virus-scan';
  final key = 'virus_test.txt';

  final result = await elmScanObject(url, stream, bucket, key);

  if (result != null) {
    print(result);
    print(result['code']);
    print(result['message']);
  }
}

Go

package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"io/ioutil"
	"net/http"
)

func elmScanObject(url string, stream bool, bucket string, key string) (map[string]interface{}, error) {
	payload := map[string]interface{}{
		"stream": stream,
		"bucket": bucket,
		"key":    key,
	}

	payloadBytes, err := json.Marshal(payload)
	if err != nil {
		return nil, err
	}

	req, err := http.NewRequest("POST", url, bytes.NewBuffer(payloadBytes))
	if err != nil {
		return nil, err
	}

	req.Header.Set("Content-Type", "application/json")

	client := &http.Client{}
	resp, err := client.Do(req)
	if err != nil {
		return nil, err
	}
	defer resp.Body.Close()

	respBody, err := ioutil.ReadAll(resp.Body)
	if err != nil {
		return nil, err
	}

	if resp.StatusCode == http.StatusOK {
		var data map[string]interface{}
		err = json.Unmarshal(respBody, &data)
		if err != nil {
			return nil, err
		}
		return data, nil
	} else {
		return nil, fmt.Errorf("Request failed with status code: %d", resp.StatusCode)
	}
}

func main() {
	url := "http://172.31.39.37:8080/api/clamav/scan/s3/object"
	stream := true
	bucket := "elm-bucket-virus-scan"
	key := "virus_test.txt"

	result, err := elmScanObject(url, stream, bucket, key)
	if err != nil {
		fmt.Println("An error occurred:", err)
		return
	}

	if result != nil {
		fmt.Println(result)
		fmt.Println(result["code"])
		fmt.Println(result["message"])
	}
}

Version 1.2.1.1

Enabled AlertExceedsMax.

Files exceeding the MaxFileSize (100M), MaxScanSize (400M), or MaxRecursion (10) limit will be flagged with the virus name starting with "Heuristics.Limits.Exceeded".

If your scan is expected to trigger the alert, please contact us at support@elmcomputing.io

API endpoints

• http://ip-address:8080/api/clamav/scan/s3/object

• http://ip-address:8080/api/clamav/scan/file

Version 1.2.1.0

Updated clamav to 1.2.1 and ubuntu to 22.04.

API endpoints

• http://ip-address:8080/api/clamav/scan/s3/object

• http://ip-address:8080/api/clamav/scan/file

Version 1.1.0.1

Applied security patching and Enabled NSF Server such that the API server can be used to scan the files on other machines.

With this new feature, implementing it into your existing application is straightforward. Here's how you can do it:

• Install the NFS client on your existing EC2 instance.

• Mount the shared folder, /elm/shared, located on the API Server, to your existing EC2 instance. You can choose a destination directory for this, for example, /tmp/data-to-scan.

• Once the folder is mounted, any files placed into /tmp/data-to-scan can be seamlessly scanned using the API Server, as if these files were stored locally in the /elm/shared folder on the API Server.

API endpoints

• http://ip-address:8080/api/clamav/scan/s3/object

• http://ip-address:8080/api/clamav/scan/file

Version 1.1.0.0

• Updated ClamAV to 1.1.0

• Enabled detecting OLE2 files containing VBA macros, which were not detected by signatures will be marked as "Heuristics.OLE2.ContainsMacros".

• The AMI version naming convention has been changed to refer to the ClamAV version.

API endpoints

• http://ip-address:8080/api/clamav/scan/s3/object

• http://ip-address:8080/api/clamav/scan/file

After the EC2 instance is started, you can access the Bayesian Workbench RStudio Server with its public IP address. For example, if the IP address is 10.11.12.13, typing http://10.11.12.13 in the browser will bring you to the following startup page:

The default username is ruser and the password is the EC2 instance ID that has the form of i-0c7fadc4dc193eca7.

Bayesian Statistics Workbench for R on AWS Marketplace

The steps of starting this workbench is the same with the procedure of spinning up an instance of our RStudio Server product.

Subscribe to the AMI

Continue to configure the EC2 instance

Choose a region close to your location

Choose an instance type

t3.xlarge is a good starting point for testing. Once everything is confirmed to work, you can switch to other instance types (more CPUs, high memory) that fit your need.

Create security group

If you do not already have an SSH key pair, please generate a new one to use when logging into the RStudio Server.

Create SSH key pair with default values

Choose "allow" to download your SSH key pair

Launch your EC2 instance

Go to EC2 console

Select the new EC2 instance

Public IP address and Instance ID

Access the login page

Enter RStudio IDE

Change instance type

To change the instance type once the server is tested, please go to "Launch instances", "Instance settings", and then "Change instance type".

RStudio Server

R: 4.3.2

rstudio-server: 2023.09.01-494

Intel MKL for blas and lapack

Release Notes

Install R, rstudio-server, Intel MKL and Bayesian statistics packages.

R: 4.3.2; rstudio-server: 2023.09.1-494

R packages (672)

After the EC2 instance is started, you can access the Bioconductor Workbench RStudio Server with its public IP address. For example, if the IP address is 10.11.12.13, typing http://10.11.12.13 in the browser will bring you to the following startup page:

The default username is ruser and the password is the EC2 instance ID that has the form of i-0c7fadc4dc193eca7.

Bioconductor Workbench for R on AWS Marketplace

The steps of starting this workbench is the same with the procedure of spinning up an instance of our RStudio Server product.

Subscribe to the AMI

Continue to configure the EC2 instance

Choose a region close to your location

Choose an instance type

t3.xlarge is a good starting point for testing. Once everything is confirmed to work, you can switch to other instance types (more CPUs, high memory) that fit your need.

Create security group for the Rstudio Server

If you do not already have an SSH key pair, please generate a new one to use when logging into the RStudio Server.

Create SSH key pair with default values

Choose "allow" to download your SSH key pair

Launch your EC2 instance

Go to EC2 console

Select the new EC2 instance

Public IP address and Instance ID

Access the login page

Enter RStudio IDE

Change instance type

To change the instance type once the server is tested, please go to "Launch instances", "Instance settings", and then "Change instance type".

RStudio Server

    R: 4.4.3

    rstudio-server: 2023.12.1-402

Release Notes

Added Bioconductor 3.20 packages, updated R to version 4.4.3, and enabled SSL for secure HTTPS connections.

R packages (3890)

RStudio Server

R: 4.3.0

rstudio-server: 2023.12.1-402

Release Notes

Install popular Bioconductor packages.

R: 4.3.0; rstudio-server: 2023.12.1-402

R packages (3829)

Python version: 3.10.12

Python packages

JupyterHub Server with GPU Support + PyTorch

This JupyterHub Server is specifically designed to support GPU acceleration and comes pre-installed with PyTorch, making it an ideal environment for data science projects that require intense computational power. It allows multiple users to access Jupyter notebooks simultaneously through their web browsers, facilitating collaboration and independent work on projects that leverage GPU capabilities and PyTorch. The server can be deployed on a single server for small teams or scaled up to handle large numbers of users.

Set up JupyterHub Server

Default user: jhub-admin

Please sign up and set your password for jhub-admin when you start the server for the first time. Different from regular users, jhub-admin is automatically authorized to log in after the password is created.

http is supported out of box.

If https is desired, please send your request to support@elmcomputing.io

Startup page

After the EC2 instance is started, you can access the JupyterHub Server with its public IP address. For example, if the IP address is 10.11.12.13, typing http://10.11.12.13 in the browser will bring you to the following startup page:

Sign-up page

When the JupyterHub Server is activated, a default user "jhub-admin" is created. The first time you access the server, a password need to be set for "jhub-admin".

jupyterlab

Authorize page

When creating new users, an authorization step is needed at "http://10.11.12.13/hub/authorize"

Change password

The password can be changed at "http://10.11.12.13/hub/change-password"

PyTorch Workbench Ver 2.5.1.0

PyTorch: 2.5.1

Python version: 3.11

Python packages

JupyterHub Server

JupyterHub is a multi-user server for Jupyter notebooks and allows multiple users to access Jupyter notebooks simultaneously through their web browsers, making it ideal for environments where multiple users need to collaborate or work independently on data science projects. It can be deployed on a single server for small teams or scaled up to handle large numbers of users.

Set up JupyterHub Server on EC2

Default user: jhub-admin

Please sign up and set your password for jhub-admin when you start the server for the first time. Different from regular users, jhub-admin is automatically authorized to log in after the password is created.

http is supported out of box.

If https is desired, please send your request to support@elmcomputing.io

Startup page

After the EC2 instance is started, you can access the JupyterHub Server with its public IP address. For example, if the IP address is 10.11.12.13, typing http://10.11.12.13 in the browser will bring you to the following startup page:

Sign-up page

When the JupyterHub Server is activated, a default user "jhub-admin" is created. The first time you access the server, a password need to be set for "jhub-admin".

jupyterlab

Authorize page

When creating new users, an authorization step is needed at "http://10.11.12.13/hub/authorize"

Change password

The password can be changed at "http://10.11.12.13/hub/change-password"

Release Notes

Added Python 3.9, 3.10, and 3.11; For each Python version, the data science packages such as tensorflow, torch, datascience, mlpack, mlflow and xgboost are installed.

SageMath: 9.0

GPU Support

Python version: 3.8.10

Python packages

Python version: 3.9

Python packages

Python version: 3.10

Python packages

Python version: 3.11

Python packages

SageMath: 9.0

Data science packages

GPU Support

Python version: 3.8.10

Python packages