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values.yaml
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# Default values for medifor-ui-helm-chart
# Declare variables to be passed into your templates.
###############################################################
# The namespace that will contain the medifor resources
#
namespace: medifor
############################################################################################
# Flag whethere or not the system is being deployed on remote instance without internet access
# Affects how containers are pulled for pods
#
remotedeploy: false
###################################
# Flag to enable/disable Prometheus
# If enable then helm will create template for analytic services and service monitors
#
prometheus:
enabled: false
###################################
# Replica counts for various pods
#
replicas:
ui: 1
fusion: 1
analytic: 1
###################################################
# The list of analytics to create deployments for
#
# id - ID of the analytic
# name - Name of the analytic
# description - Description of the analytic's function
# container - URL to the docker image for this analytic
# version - Version of the analytic
# media - The type or types of media that the analytic r*uns on. Must follow the given format
# resource - The resource requests and limits to be used by the analytic in the cluster
#
analytics:
- id: ela-base
name: Error Level Analysis
description: Identifying areas within an image that are at different compression levels
container: docker.pkg.github.com/mediaforensics/packages/ela:latest
version: prod2020-03
media: ["IMAGE", "VIDEO"]
resources:
requests:
cpu: .125
mem: 100Mi
gpu: 0
limits:
cpu: .25
mem: 200Mi
gpu: 0
- id: exif
name: Baseline Analytic Exif
description: Baseline Analytic Exif Description
container: docker.pkg.github.com/mediaforensics/packages/exif:latest
version: prod2020-03
media: ["IMAGE"]
resources:
requests:
cpu: .125
mem: 100Mi
gpu: 0
limits:
cpu: .25
mem: 200Mi
gpu: 0
##########################################################
# The list of fusion analytics to create deployments for
#
# id - ID of the fusion analytic
# name - Name of the fusion analytic
# description - Description of the fusion analytic's function
# container - URL to the docker image for this fusion analytic
# version - Version of the fusion analytic
# media - The type or types of media that the fusion analytic runs on. Must follow the given format
# resource - The resource requests and limits to be used by the fusion analytic in the cluster
#
fusers:
- id: ta2avg
name: Image Averaging Fusion
description: Averages all analytic input scores available to calculate score
container: docker.pkg.github.com/mediaforensics/packages/ta2avg:latest
version: prod2020-03
media: ["FUSION_IMAGE", "FUSION_VIDEO"]
resources:
requests:
cpu: .1
mem: 100Mi
gpu: 0
limits:
cpu: .2
mem: 200Mi
gpu: 0
##################################################################
# The volume mount paths for the data from the analytic containers
#
analyticmounts:
input:
external: /medifor/input
internal: /mnt/medifor/input
output:
external: /medifor/output
internal: /mnt/medifor/output
####################################################################################
# The analytic worker that will be use for all analytic and analytic workflow pods
#
# id - ID for the analytic worker
# version - Version for the analytic worker which also serves as the docker image tag
# config_mount - Location in the analyticworker container where the analytic configuration file will be mounted
# container - URL to the docker image for the analytic worker
# ports - Ports the analytic worker container will listen on
#
analyticworker:
id: analyticworkflow
version: develop
config_mount: /mnt/config/analytic_config.json
container: docker.pkg.github.com/mediaforensics/packages/analyticworker:latest
ports:
grpc:
port_number: 50051
http:
port_number: 50052
prometheus:
port_number: 2112
###################################################################
# The values and environment variables for the medifor-ui container
#
# name - Name for the UI resource
# container - URL for the docker image for the UI container
# port - Port that the UI container will expose inside the pod
# env.CONTAINER_ROOT - Directory where the UI container stores static upload media and output from analytics
# env.WORKFLOW_HOST - Name of the analytic workflow host
# env.WORKFLOW_PORT - Port that the analyticworkflow resource will listen on
# env.CACHE_TTL_SECONDS - Number of seconds that the UI will cache the analytic list response from the pipeline
# env.UI_ENABLE_GROUPS - Flag to turn on/off the grouping feature within the UI
# env.UI.DEFAULT_FUSER_ID - ID for the default fusion model to be used in the UI, if left empty then first fuser in the list will be chosen
# env.UI_UNKNOWN_USERS - 'deny/allow' flag on how to handle unknown system users when grouping is enabled
# env.UI_GROUP_PREFIX - Prefix used to denote user groups in the headers
# env.UI_USER_TAG_PREFIX - Prefix for user tags
# env.UI_GROUP_TAG_PREFIX - Prefix from group tags
# env.UI_TAG_PREFIX_FLAG - Prefix appended to all user and group tags - '__user' '__group'
ui:
name: medifor-ui
container: docker.pkg.github.com/mediaforensics/packages/medifor-ui:latest
port: 3000
service:
type: NodePort
nodePort: 30000
env:
CONTAINER_ROOT: "/medifor"
WORKFLOW_HOST: "analyticworkflow"
WORKFLOW_PORT: "50051"
PORT: "3000"
CACHE_TTL_SECONDS: 600
UI_ENABLE_GROUPS: false
UI_ENABLE_DELETE: true
UI_DEFAULT_FUSER_ID: ""
UI_UNKNOWN_USERS: "deny"
UI_GROUP_PREFIX: "medifor-uigrp-"
UI_USER_TAG_PREFIX: "user"
UI_GROUP_TAG_PREFIX: "group"
UI_TAG_PREFIX_FLAG: "__"
#################################
# Values for the postgres resource
#
postgres:
database: postgres
username: postgres
password: postgres
address: pgmedifor
port: 5432
################################
# Values for the Entroq resource
#
entroq:
ports:
grpc: 37706
metrics: 8080
##################################################
# Configurable condition for the autoscaler templates
#
autoscaler:
enabled: false
###################################
# Default Persistence Configuration
# The medifor-data-pvc and the postgres-pvc will use the cluster's default storage class if
# `storageClass:` is undefined
#
# Otherwise you can create your own custom storage class and define it as
# `storageClass: <customStorageClassName>`
#
persistence:
medifor:
# storageClass:
accessMode: ReadWriteMany
size: 2Gi
postgres:
# storageClass:
accessMode: ReadWriteOnce
size: 5Gi