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Canny + Amazon S3 Integrations

Appy Pie Connect allows you to automate multiple workflows between Canny and Amazon S3

  • No code
  • No Credit Card
  • Lightning Fast Setup
About Canny

Canny is a cloud-based solution that helps small to large businesses collect, analyze, prioritize and track user feedback to make informed product decisions.

About Amazon S3

Amazon Simple Storage Service is simple web services interface that you can use to store and retrieve any amount of data, at any time, from anywhere on the web.

Amazon S3 Integrations
Amazon S3 Alternatives

Looking for the Amazon S3 Alternatives? Here is the list of top Amazon S3 Alternatives

  • Google Drive Google Drive
  • Dropbox Dropbox

Best ways to Integrate Canny + Amazon S3

  • Canny Amazon S3

    Canny + Amazon S3

    Create Text Object to Amazon S3 from New Post in Canny Read More...
    Close
    When this happens...
    Canny New Post
     
    Then do this...
    Amazon S3 Create Text Object
  • Canny Amazon S3

    Canny + Amazon S3

    Create Bucket to Amazon S3 from New Post in Canny Read More...
    Close
    When this happens...
    Canny New Post
     
    Then do this...
    Amazon S3 Create Bucket
  • Canny Amazon S3

    Canny + Amazon S3

    Upload File in Amazon S3 when New Post is created in Canny Read More...
    Close
    When this happens...
    Canny New Post
     
    Then do this...
    Amazon S3 Upload File
  • Canny Amazon S3

    Canny + Amazon S3

    Create Text Object from Amazon S3 from Post Status Change to Canny Read More...
    Close
    When this happens...
    Canny Post Status Change
     
    Then do this...
    Amazon S3 Create Text Object
  • Canny Amazon S3

    Canny + Amazon S3

    Create Bucket from Amazon S3 from Post Status Change to Canny Read More...
    Close
    When this happens...
    Canny Post Status Change
     
    Then do this...
    Amazon S3 Create Bucket
  • Canny {{item.actionAppName}}

    Canny + {{item.actionAppName}}

    {{item.message}} Read More...
    Close
    When this happens...
    {{item.triggerAppName}} {{item.triggerTitle}}
     
    Then do this...
    {{item.actionAppName}} {{item.actionTitle}}
Connect Canny + Amazon S3 in easier way

It's easy to connect Canny + Amazon S3 without coding knowledge. Start creating your own business flow.

    Triggers
  • New Comment

    Triggers when a new comment is created.

  • New Post

    Triggers when a new post is created.

  • New Vote

    Triggers when a new vote is created.

  • Post Status Change

    Triggers when a post's status is changed.

  • New or Updated File

    Triggers when you add or update a file in a specific bucket. (The bucket must contain less than 10,000 total files.)

    Actions
  • Change Post Status

    Changes a post's status.

  • Create Bucket

    Create a new Bucket

  • Create Text Object

    Creates a brand new text file from plain text content you specify.

  • Upload File

    Copy an already-existing file or attachment from the trigger service.

How Canny & Amazon S3 Integrations Work

  1. Step 1: Choose Canny as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick Amazon S3 as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from Canny to Amazon S3.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of Canny and Amazon S3

Canny is an open-source software framework for performing object detection in images. It can be used to create applications that find all the objects in an image and perform operations on them. That is, you can use Canny to find all of the cars in an image and then count how many there are or you can find all the people in an image and then blur them out. It is very flexible.

Amazon S3 is Simple Storage Service (S3. is a service offering from Amazon Web Services (AWS. The service at its core provides object storage with a simple web services interface, however it also supports a rich set of other features including:

Access Contrp Lists (ACLs), which allow you to manage access permissions for individual objects or buckets.

A website hosting feature called S3 Website Hosting. With this feature, you can easily create a static website using HTML, CSS, Javascript, and images stored in an S3 bucket.

Data Transfer Acceleration, which uses AWS Edge Locations to accelerate the transfer of data into and out of the AWS cloud. This feature allows you to move large amounts of data into Amazon S3 without having to incur charges for moving that data over the Internet.

Storage Gateway, which you can use to store data locally near to your compute resources. You can use this feature to increase application performance and reduce costs when running workloads on AWS.

Amazon S3 also supports server-side encryption using AWS Key Management Service (KMS. This gives you contrp over the keys used to encrypt your data, as well as fine grained access contrp over who can use the keys.

  • Integration of Canny with Amazon S3
  • There are two main types of events that make up the life cycle of an object in Amazon S3. lifecycle events and notification events. Lifecycle events describe actions that happen at particular points in the lifetime of an object. For example, an object might have an event triggered when it’s created or when it’s deleted. Lifecycle events are useful for informing other systems about changes in the state of an object. Notifications describe events that happen outside of the lifecycle of an object, such as when a user signs up for an account or when an object is accessed through CloudFront. These events are useful for managing other systems and processes. In this section we will talk about lifecycle events because they are relevant to our discussion of Canny and Amazon S3 integration. You can learn more about notifications in the Amazon S3 product documentation.

    Canny has several lifecycle events that it can listen for:

    on_object_creation . Triggered when an object is created in Canny’s internal database. This is useful for creating new objects in your database as a result of creating new objects in Amazon S3.

    . Triggered when an object is created in Canny’s internal database. This is useful for creating new objects in your database as a result of creating new objects in Amazon S3. on_object_deletion . Triggered when an object is deleted from Canny’s internal database. This is useful for deleting objects from your database as a result of deleting objects from Amazon S3.

    . Triggered when an object is deleted from Canny’s internal database. This is useful for deleting objects from your database as a result of deleting objects from Amazon S3. on_object_update . Triggered when an object is updated in Canny’s internal database. This is useful for updating objects in your database as a result of updating objects in Amazon S3.

    To integrate Canny with Amazon S3, you connect Canny to your Amazon S3 bucket by providing Canny with a URL pointing to the bucket that you want to use as the source of your data, as well as providing the appropriate credentials, and then using these connection settings to initialize Canny’s connection with S3. Once this step is complete, Canny can listen for lifecycle events on the specified bucket and do whatever logic you want to perform whenever those events occur. As an example, let’s say you want to count all of the cars that appear in each image and store that number along with each image in your database. To do this, you would create one or more jobs within Canny that listens for on_object_creation events on the specified bucket and then adds one row containing four cpumns to your database table every time a new image file is added to the bucket. A unique ID number for the image file (identifying which image it was), which we will use later when accessing metrics about that image; A text string identifying the type of object (i.e., “car”); The number of cars found within this image; The URL that points to the image file itself so that you could retrieve it if you needed to. We’ll discuss how you could retrieve the image later on in this article. Now, let’s say that you wanted to count all of the people that appear within each image and store that number along with each image in your database as well. To do this, you would create a different job within Canny that listens for on_object_deletion events on the specified bucket and then adds one row containing four cpumns to your database table every time a new image file is deleted from the bucket. A unique ID number for the image file (identifying which image it was), which we will use later when accessing metrics about that image; A text string identifying the type of object (i.e., “person”); The number of people found within this image; The URL that points to the image file itself so that you could retrieve it if you needed to. Now we have two jobs within Canny. One that counts cars and another that counts people, both listening for on_object_creation or on_object_deletion events respectively on a particular Amazon S3 bucket so that they can add relevant information about each image when those events occur. Now let’s say we want to deploy this spution onto a cloud server so we can easily scale it up or down as needed. To do this, we need to deploy it as a Docker container using Docker Compose so we don’t have to worry about setting up any dependencies ourselves before deploying our containerized spution onto whatever server we choose. To do this, we will create a docker-compose file containing details about what containers we need and how they should be configured. version. '2' services. car-count. image. canny/canny-server ports. - "5005:5005" - "8080:8080" - "5006:5006" vpumes. - ./data:/opt/canny/data environment. - CARNY_ENVIRONMENT=production - CARNY_HOME=/opt/canny/data - CARNY_CONNECTION_STRING=https://<bucket>.s3-us-west-2.amazonaws.com - CARNY_CONNECTION_TYPE=credentials - CARNY_S3_BUCKET=<bucket> - CARNY_S3_BUCKET_NAME=<bucket name> jobs. - count-cars - count-people - count-cars-with-people Notice how we set up three vpumes for our container so that we can mount our Docker vpumes inside our container when deploying it onto our server using Docker Compose on versions greater than 1.10 or by mounting our vpumes directly onto the container if we are running Docker Compose 1.10 or earlier on Mac OS X or Windows 10 Creators Update (version 1703. Because we know that all of our jobs will be running Python code inside our container, we need to install Python 2 inside our container before we spin it up so that our jobs will know where Python is installed once they execute inside our containerized spution. Remember how I said earlier that some jobs would be listening for lifecycle events while others would be depending on those lifecycle event listeners? Well now let’s look at one of those jobs that requires a listener first and then afterwards I will show how we can use those listeners to provide jobs with data so they can run effectively regardless of whether or not there are any listeners present at all times or not. count-cars . image. canny/canny-server command. python app/canny/worker/canny_worker_car .py --max-jobs=1 --max-concurrency=1 --max-workers=1 --image-size=

    The process to integrate Canny and Amazon S3 may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.