• Table of contents
  • Description
  • Why Mordo Image Service
  • Supported Opearations
  • Platforms
  • Usage
    • Routes
    • Query Strings
  • Service Configuration
  • Service Setup
  • Local Testing
    • Config
    • Run

Mordo image service is designed with serverless im mind. This service is exposed as HTTP endpoint and used TBD

Mordo Image Service is designed with serverless in the soul. Main advantage of serverless applications is mintenance costs. Serverless services require zero infrastructure maintenance and configuration. Second big advantage is running costs. With serverless "you pay as you go", you pay only for time that service works (invocation time) which generally much cheaper than traditional "VM running service".

Next image operations are supported:

1. Resize (with preserving aspect ratio)
2. DPR (Dual Pixel Ratio)
3. Crop
4. Watermark
5. Sharpen

Supported:

1. AWS (AWS Lambda)

Future:

1. GCP
2. Standalone server

Mordo API has only one endpoint /{image path} exposed via:

• CloudFront for AWS

For testing purposes /process AWS Api Gateway endpoint is available. This endpoint won't cache resulting image at the edge locations.

Image operations are defined by query string passed to endpoint.

1. width/height Resize - use one to define new size of the image. For example:

   Usage examples:

   • https://demo.mordo.io/origin_2k.jpg?width=1000
   • https://demo.mordo.io/origin_2k.jpg?height=1000

2. dpr - set Dual Pixel Ratio, number. It is kind of resize, but act like scale factor. Vaules: 0 - infinity.

   Usage examples:

   • https://demo.mordo.io/origin_2k.jpg?dpr=1.5 - DPR (scale) factor 1.5, which means image will be 150% size of original

   Note: Please avoid using with Resize operation, cause under the hood DPR and Resize is almost same operation and modifies image in same way

   Note: If dpr > 1 image will be enlarged. Enlarging is heavy operation

3. w_x, w_y, w_s Watermark - use to define watermark position and watermark scale.

   w_x - position by X axis, string, required parameter. Available values:

   • right
   • left
   • center

   w_y - position by Y axis, string, required parameter. Available values:

   • top

   • bottom

   • center

     w_s - watermark scale factor, number, optional parameter. Values: 0 - infinity.

     Note: setting w_s value more than 1 will have severe impact on performance.

   Usage examples:

   • https://demo.mordo.io/origin_2k.jpg?w_x=left&w_y=bottom - watermark to left bottom corner
   • https://demo.mordo.io/origin_2k.jpg?w_x=right&w_y=center&w_s=0.5 - watermark to right by X, center by Y
   • https://demo.mordo.io/origin_2k.jpg?width=1000&w_x=right&w_y=center - resize image to 1000 px by width watermark to right by X, center by Y, scale watermark to 50% of original size.

4. sharpen - Sharpen operation - use to apply sharpening to image. Vaules: t - apply sharpening.

   Predefined sharpening params:

   • radius: 1 - Gaussian Blur radius for high-frequency signal
   • X1: 2 - flat/jaggy threshold
   • Y2: 5 - maximum amount of brightening
   • Y3: 10 - maximum amount of darkening
   • M1: 0 - slope for flat areas
   • M2: 3 - slope for jaggy areas

   Usage examples:

   • https://demo.mordo.io/origin_2k.jpg?sharpen=t - apply sharpening.

Mordo Image service is configured via environment variables.

• "DEBUG": "true" - Mordo Debug mode. More logging, no S3 cache, CloudFront caching still applies.
• "PLATFORM": "AWS"
• "AWS_S3_BUCKET_PROCESSED": "foo-bar"
• "WATERMARK": "true"
• "WATERMARK_PATH": "foo/bar/baz/watermark"
• "WATERMARK_SCALE": "0.15"
• "IMAGE_QUALITY": "90"
• "IMAGE_LOSSLESS": "true"
• "IMAGE_COMPRESSION": "0"
• "IMAGE_ENLARGE": "TRUE"

The best way to setup Mordo is Terraform

Terraform install resources is located at ./terraform.

• AWS

In order to run locally you need to create S3 bucket for resulting images and set AWS_S3_BUCKET_PROCESSED in .env.

Also You need to fill .envlocal.sample with AWS_ACCESS_KEY and AWS_SECRET_KEY. This user must have next permissions:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "1",
            "Effect": "Allow",
            "Action": [
                "s3:PutObjectTagging",
                "s3:PutObject",
                "s3:PutObjectAcl",
                "s3:GetObject",
                "s3:ListBucket",
                "s3:ListAllMyBuckets",
                "s3:GetBucketLocation"
            ],
            "Resource": [
                "arn:aws:s3:::AWS_S3_BUCKET_PROCESSED/*",
                "arn:aws:s3:::AWS_S3_BUCKET_PROCESSED"
            ]
        },
        {
            "Sid": "2",
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket",
                "s3:ListAllMyBuckets",
                "s3:GetBucketLocation"
            ],
            "Resource": [
                "arn:aws:s3:::AWS_S3_BUCKET_WITH_IMAGES/*",
                "arn:aws:s3:::AWS_S3_BUCKET_WITH_IMAGES"
            ]
        },
        {
            "Sid": "3",
            "Effect": "Allow",
            "Action": [
                "s3:ListAllMyBuckets",
                "s3:GetBucketLocation"
            ],
            "Resource": "*"
        }
    ]
}

Modify next blocks of doc/apigw_event/blank.json

Note: You can doc/apigw_event/* are events that AWS API Gateway passes to AWS Lambda. Thay are passed to local container which emulates AWS Lambda behaviour.

  "queryStringParameters": {
    "width": "1000"
  },

and

  "stageVariables": {
    "baz": "qux",
    "s3_bucket": "AWS_S3_BUCKET_WITH_IMAGES",
    "s3_bucket_region": "us-west-1"
  },

# sh scripts/build_linux.sh aws 1>/dev/null

# cat doc/apigw_event/blank.json |  docker run --rm -i -v "$PWD"/pkg:/var/task --env-file=.envlocal --env-file=.env lambci/lambda:go1.x mordo 2>&1

or

sh scripts/run_aws_local.sh