If you have any questions as you go through this guide please don’t hesitate to reach out.
Select your cloud provider below to view links and instructions for how to launch Philter in that cloud. Philter is currently available on the AWS, Azure, and GCP marketplaces.
Philter on AWS is a virtual machine-based product. It runs in EC2 on its own EC2 instance. A free trial period may be available during which there is no charge for the Philter software but there may be charges for the underlying AWS infrastructure.
Launch Philter in AWS
Go to Philter in the AWS Marketplace. On this page you can see the Philter overview, the pricing, and the supported EC2 instance types.
Select an instance type. We recommend
m5.large. The smaller instance types are intended only for testing and are not well-suited for production usage.
Click the “Continue to Subscribe” button.
View and accept Philter’s license agreement. Then click “Accept Terms.”
The subscription will now be created and you will be notified when it is ready! This usually only takes less than a minute.
Click the “Continue to Configuration” button to select the AMI, the version, and the region. We recommend using the newest version if multiple are available.
Click the “Continue to Launch” button to launch Philter in your AWS account!
Here’s a brief screen cast showing how to launch Philter in AWS.
Congratulations! You have deployed Philter in AWS. You are now ready to filter text!
Philter on Microsoft Azure is a virtual machine-based product. A free trial period may be available during which there is no charge for the Philter software but there may be charges for the underlying Azure infrastructure.
Click the “Get It Now” button.
Review the information that is shown on the popup and click “Continue” when ready.
You will now be asked to log in to your Microsoft Azure account if you were not already logged in.
Click the “Create” button to begin making a Philter virtual machine.
Enter the required details of the virtual machine and click the “Review + create” button.
Review the virtual machine details and click “Create” when ready!
Your Philter virtual machine will now be launching.
Congratulations! You have deployed Philter in Azure. You are now ready to filter text!
Philter on Google Cloud is a virtual machine-based product. A free trial period may be available during which there is no charge for the Philter software but there may be charges for the underlying Google Cloud infrastructure.
Launch Philter in Google Cloud
Click the "Launch on Compute Engine" button.
The general purpose machine type is n2-standard-2 and this machine type should be adequate for most use-cases. We recommend 8 vCPUs and 8-16 GB of RAM for a production deployment.
Congratulations! You have deployed Philter in Google Cloud. You are now ready to filter text!
Philter can be launched using docker-compose. Download the docker-compose.yml file and then edit it to set your Philter license key. If you do not have a Philter license key you can request a free license key.
curl -O https://raw.githubusercontent.com/mtnfog/philter/master/docker-compose.ymldocker-compose up
Now that the containers are running you are ready to continue below with Step 2! If you are running the containers on your local computer just use
localhost as the target of the curl requests.
With Philter now running we can take it for a spin. We will send some text to Philter and inspect at the response we get back. The Philter virtual machine running in your cloud account should have a public IP address (unless you customized the deployment). We will use that public IP address to interact with Philter.
In the command below, replace
<PUBLIC_IP> with the virtual machine’s public IP address or the host name or IP address of the Docker host.
curl -k -X POST https://<PUBLIC_IP>:8080/api/filter --data "George Washington was a patient and his SSN is 123-45-6789." -H "Content-type: text/plain"
With this command we are sending the text in the command to Philter for filtering. Philter will identify the patient name (George Washington) and the SSN (123-45-6789) and redact those values in the response. You can always use
curl to send text to Philter as in these examples but there are also SDKs you can use, too, to integrate Philter with your applications.
The types of sensitive information that Philter identifies and removes is controlled by filter profiles. By default, Philter includes a filter profile that includes many of the types of sensitive information, such as names and social security numbers. We can send text to filter to Philter for filtering using this default filter profile with the following command:
curl -k -X POST https://localhost:8080/api/filter -d @file.txt -H "Content-Type: text/plain"
This command sends the contents of the file
file.txt to Philter. Philter will apply the enabled filters and return a plain-text response consisting of the filtered text. (Replace
localhost with the IP address or host name of Philter if you are not running the command where Philter is running.) You can also send text directly in the request instead of sending it as a file:
curl -k -X POST https://localhost:8080/api/filter --data "Your text goes here..." -H "Content-type: text/plain"
Now that you have Philter running and know how to send text to it you are ready to integrate Philter into your existing workflow and systems. Philter’s API details how to send files to Philter. Clients for some languages for Philter’s API are available on GitHub.
Be sure to check out Filter Profiles to see how you can customize the types of sensitive information Philter finds!
Here's a few examples showing how to use Philter with some common big-data and streaming applications.
Remove sensitive information from text in an Apache NiFi dataflow.
Remove sensitive information from text using AWS Lambda in an Amazon Kinesis Firehose pipeline.
Amazon Kinesis. AWS Lambda
Remove sensitive information from text using a custom Apache Flink
Remove sensitive information from text using a custom Apache Pulsar Function.