Rollout Deployment

The Rollout Deployment chart deploys an advanced version of deployment that supports Blue/Green and Canary deployments. For functioning, it requires a rollout controller to run inside the cluster.

You can define application behavior by providing information in the following sections:

Key
Descriptions

Chart version

Select the Chart Version using which you want to deploy the application. Refer Chart Version section for more detail.

Basic (GUI)

You can perform a basic deployment configuration for your application in the Basic (GUI) section instead of configuring the YAML file. Refer Basic Configuration section for more detail.

Advanced (YAML)

If you want to do additional configurations, then click Advanced (YAML) for modifications. Refer Advanced (YAML) section for more detail.

Show application metrics

You can enable Show application metrics to see your application's metrics-CPU Service Monitor usage, Memory Usage, Status, Throughput and Latency. Refer Application Metrics for more detail.

Super-admins can lock keys in rollout deployment template to prevent non-super-admins from modifying those locked keys. Refer Lock Deployment Configuration to know more.


Advanced (YAML)

Container Ports

This defines the ports on which application services will be exposed to other services.

ContainerPort:
  - envoyPort: 8799
    envoyTimeout: 15s
    idleTimeout:
    name: app
    port: 8080
    servicePort: 80
    supportStreaming: true
    useHTTP2: true
Key
Description

envoyPort

envoy port for the container.

envoyTimeout

envoy Timeout for the container,envoy supports a wide range of timeouts that may need to be configured depending on the deployment.By default the envoytimeout is 15s.

idleTimeout

the duration of time that a connection is idle before the connection is terminated.

name

name of the port.

port

port for the container.

servicePort

port of the corresponding kubernetes service.

supportStreaming

Used for high performance protocols like grpc where timeout needs to be disabled.

useHTTP2

Envoy container can accept HTTP2 requests.

EnvVariables

EnvVariables: []

EnvVariables provide run-time information to containers and allow to customize how the application works and the behavior of the applications on the system.

Here we can pass the list of env variables , every record is an object which contain the name of variable along with value.

To set environment variables for the containers that run in the Pod.

Example of EnvVariables

IMP Docker image should have env variables, whatever we want to set.

EnvVariables: 
  - name: HOSTNAME
    value: www.xyz.com
  - name: DB_NAME
    value: mydb
  - name: USER_NAME
    value: xyz

But ConfigMap and Secret are the preferred way to inject env variables. You can create this in App Configuration Section.

ConfigMap

It is a centralized storage, specific to k8s namespace where key-value pairs are stored in plain text.

Secret

It is a centralized storage, specific to k8s namespace where we can store the key-value pairs in plain text as well as in encrypted(Base64) form.

IMP All key-values of Secret and CofigMap will reflect to your application.

Liveness Probe

If this check fails, kubernetes restarts the pod. This should return error code in case of non-recoverable error.

LivenessProbe:
  Path: ""
  port: 8080
  initialDelaySeconds: 20
  periodSeconds: 10
  successThreshold: 1
  timeoutSeconds: 5
  failureThreshold: 3
  command:
    - python
    - /etc/app/healthcheck.py
  httpHeaders:
    - name: Custom-Header
      value: abc
  scheme: ""
  tcp: true
Key
Description

Path

It define the path where the liveness needs to be checked.

initialDelaySeconds

It defines the time to wait before a given container is checked for liveliness.

periodSeconds

It defines how often (in seconds) to perform the liveness probe.

successThreshold

It defines the number of successes required before a given container is said to fulfil the liveness probe.

timeoutSeconds

The maximum time (in seconds) for the probe to complete.

failureThreshold

The number of consecutive failures required to consider the probe as failed.

command

The mentioned command is executed to perform the livenessProbe. If the command returns a non-zero value, it's equivalent to a failed probe.

httpHeaders

Custom headers to set in the request. HTTP allows repeated headers,You can override the default headers by defining .httpHeaders for the probe.

scheme

Scheme to use for connecting to the host (HTTP or HTTPS). Defaults to HTTP.

tcp

The kubelet will attempt to open a socket to your container on the specified port. If it can establish a connection, the container is considered healthy.

MaxUnavailable

  MaxUnavailable: 0

The maximum number of pods that can be unavailable during the update process. The value of "MaxUnavailable: " can be an absolute number or percentage of the replicas count. The default value of "MaxUnavailable: " is 25%.

MaxSurge

MaxSurge: 1

The maximum number of pods that can be created over the desired number of pods. For "MaxSurge: " also, the value can be an absolute number or percentage of the replicas count. The default value of "MaxSurge: " is 25%.

Min Ready Seconds

MinReadySeconds: 60

This specifies the minimum number of seconds for which a newly created Pod should be ready without any of its containers crashing, for it to be considered available. This defaults to 0 (the Pod will be considered available as soon as it is ready).

Readiness Probe

If this check fails, kubernetes stops sending traffic to the application. This should return error code in case of errors which can be recovered from if traffic is stopped.

ReadinessProbe:
  Path: ""
  port: 8080
  initialDelaySeconds: 20
  periodSeconds: 10
  successThreshold: 1
  timeoutSeconds: 5
  failureThreshold: 3
  command:
    - python
    - /etc/app/healthcheck.py
  httpHeaders:
    - name: Custom-Header
      value: abc
  scheme: ""
  tcp: true
Key
Description

Path

It define the path where the readiness needs to be checked.

initialDelaySeconds

It defines the time to wait before a given container is checked for readiness.

periodSeconds

It defines how often (in seconds) to perform the readiness probe.

successThreshold

It defines the number of successes required before a given container is said to fulfill the readiness probe.

timeoutSeconds

The maximum time (in seconds) for the probe to complete.

failureThreshold

The number of consecutive failures required to consider the probe as failed.

command

The mentioned command is executed to perform the readinessProbe. If the command returns a non-zero value, it's equivalent to a failed probe.

httpHeaders

Custom headers to set in the request. HTTP allows repeated headers,You can override the default headers by defining .httpHeaders for the probe.

scheme

Scheme to use for connecting to the host (HTTP or HTTPS). Defaults to HTTP.

tcp

The kubelet will attempt to open a socket to your container on the specified port. If it can establish a connection, the container is considered healthy.

Startup Probe

Startup Probe in Kubernetes is a type of probe used to determine when a container within a pod is ready to start accepting traffic. It is specifically designed for applications that have a longer startup time.

StartupProbe:
  Path: ""
  port: 8080
  initialDelaySeconds: 20
  periodSeconds: 10
  successThreshold: 1
  timeoutSeconds: 5
  failureThreshold: 3
  httpHeaders:
    - name: Custom-Header
      value: abc
  command:
    - python
    - /etc/app/healthcheck.py
  tcp: false
Key
Description

Path

It define the path where the startup needs to be checked.

initialDelaySeconds

It defines the time to wait before a given container is checked for startup.

periodSeconds

It defines how often (in seconds) to perform the startup probe.

successThreshold

The number of consecutive successful probe results required to mark the container as ready.

timeoutSeconds

The maximum time (in seconds) for the probe to complete.

failureThreshold

The number of consecutive failures required to consider the probe as failed.

command

The mentioned command is executed to perform the startup probe. If the command returns a non-zero value, it's equivalent to a failed probe.

httpHeaders

Custom headers to set in the request. HTTP allows repeated headers,You can override the default headers by defining .httpHeaders for the probe.

tcp

The kubelet will attempt to open a socket to your container on the specified port. If it can establish a connection, the container is considered healthy.

Autoscaling

This is connected to HPA and controls scaling up and down in response to request load.

autoscaling:
  enabled: false
  MinReplicas: 1
  MaxReplicas: 2
  TargetCPUUtilizationPercentage: 90
  TargetMemoryUtilizationPercentage: 80
  extraMetrics: []
Key
Description

enabled

Set true to enable autoscaling else set false.

MinReplicas

Minimum number of replicas allowed for scaling.

MaxReplicas

Maximum number of replicas allowed for scaling.

TargetCPUUtilizationPercentage

The target CPU utilization that is expected for a container.

TargetMemoryUtilizationPercentage

The target memory utilization that is expected for a container.

extraMetrics

Used to give external metrics for autoscaling.

Fullname Override

fullnameOverride: app-name

fullnameOverride replaces the release fullname created by default by devtron, which is used to construct Kubernetes object names. By default, devtron uses {app-name}-{environment-name} as release fullname.

Image

image:
  pullPolicy: IfNotPresent

Image is used to access images in kubernetes, pullpolicy is used to define the instances calling the image, here the image is pulled when the image is not present,it can also be set as "Always".

serviceAccount

serviceAccount:
  create: false
  name: ""
  annotations: {}
Key
Description

enabled

Determines whether to create a ServiceAccount for pods or not. If set to true, a ServiceAccount will be created.

name

Specifies the name of the ServiceAccount to use.

annotations

Specify annotations for the ServiceAccount.

imagePullSecrets

imagePullSecrets contains the docker credentials that are used for accessing a registry.

imagePullSecrets:
  - regcred

regcred is the secret that contains the docker credentials that are used for accessing a registry. Devtron will not create this secret automatically, you'll have to create this secret using dt-secrets helm chart in the App store or create one using kubectl. You can follow this documentation Pull an Image from a Private Registry https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/ .

HostAliases

the hostAliases field is used in a Pod specification to associate additional hostnames with the Pod's IP address. This can be helpful in scenarios where you need to resolve specific hostnames to the Pod's IP within the Pod itself.

  hostAliases:
  - ip: "192.168.1.10"
    hostnames:
    - "hostname1.example.com"
    - "hostname2.example.com"
  - ip: "192.168.1.11"
    hostnames:
    - "hostname3.example.com"

Ingress

This allows public access to the url. Please ensure you are using the right nginx annotation for nginx class. The default value is nginx.

ingress:
  enabled: false
  # For K8s 1.19 and above use ingressClassName instead of annotation kubernetes.io/ingress.class:
  className: nginx
  annotations: {}
  hosts:
      - host: example1.com
        pathType: "ImplementationSpecific"
        paths:
            - /example
      - host: example2.com
        pathType: "ImplementationSpecific"
        paths:
            - /example2
            - /example2/healthz
  tls: []

Legacy deployment-template ingress format

ingress:
  enabled: false
  # For K8s 1.19 and above use ingressClassName instead of annotation kubernetes.io/ingress.class:
  ingressClassName: nginx-internal
  annotations: {}
  path: ""
  host: ""
  tls: []
Key
Description

enabled

Enable or disable ingress

annotations

To configure some options depending on the Ingress controller

host

Host name

pathType

Path in an Ingress is required to have a corresponding path type. Supported path types are ImplementationSpecific, Exact and Prefix.

path

Path name

tls

It contains security details

Ingress Internal

This allows private access to the url, please ensure you are using right nginx annotation for nginx class, its default value is nginx

ingressInternal:
  enabled: false
  # For K8s 1.19 and above use ingressClassName instead of annotation kubernetes.io/ingress.class:
  ingressClassName: nginx-internal
  annotations: {}
  hosts:
      - host: example1.com
        pathType: "ImplementationSpecific"
        paths:
            - /example
      - host: example2.com
        pathType: "ImplementationSpecific"
        paths:
            - /example2
            - /example2/healthz
  tls: []
Key
Description

enabled

Enable or disable ingress

annotations

To configure some options depending on the Ingress controller

host

Host name

pathType

Path in an Ingress is required to have a corresponding path type. Supported path types are ImplementationSpecific, Exact and Prefix.

path

Path name

pathType

Supported path types are ImplementationSpecific, Exact and Prefix.

tls

It contains security details

Init Containers

initContainers: 
  - reuseContainerImage: true
    securityContext:
      runAsUser: 1000
      runAsGroup: 3000
      fsGroup: 2000
    volumeMounts:
     - mountPath: /etc/ls-oms
       name: ls-oms-cm-vol
   command:
     - flyway
     - -configFiles=/etc/ls-oms/flyway.conf
     - migrate

  - name: nginx
    image: nginx:1.14.2
    securityContext:
      privileged: true
    ports:
    - containerPort: 80
    command: ["/usr/local/bin/nginx"]
    args: ["-g", "daemon off;"]

Specialized containers that run before app containers in a Pod. Init containers can contain utilities or setup scripts not present in an app image. One can use base image inside initContainer by setting the reuseContainerImage flag to true.

Pause For Seconds Before Switch Active

pauseForSecondsBeforeSwitchActive: 30

To wait for given period of time before switch active the container.

Resources

These define minimum and maximum RAM and CPU available to the application.

resources:
  limits:
    cpu: "1"
    memory: "200Mi"
  requests:
    cpu: "0.10"
    memory: "100Mi"

Resources are required to set CPU and memory usage.

Limits

Limits make sure a container never goes above a certain value. The container is only allowed to go up to the limit, and then it is restricted.

Requests

Requests are what the container is guaranteed to get.

Service

This defines annotations and the type of service, optionally can define name also.

  service:
    type: ClusterIP
    annotations: {}
Key
Description

type

Select the type of service, default ClusterIP

annotations

Annotations are widely used to attach metadata and configs in Kubernetes.

name

Optional field to assign name to service

loadBalancerSourceRanges

If service type is LoadBalancer, Provide a list of whitelisted IPs CIDR that will be allowed to use the Load Balancer.

Note - If loadBalancerSourceRanges is not set, Kubernetes allows traffic from 0.0.0.0/0 to the LoadBalancer / Node Security Group(s).

Volumes

volumes:
  - name: log-volume
    emptyDir: {}
  - name: logpv
    persistentVolumeClaim:
      claimName: logpvc

It is required when some values need to be read from or written to an external disk.

Volume Mounts

volumeMounts:
  - mountPath: /var/log/nginx/
    name: log-volume 
  - mountPath: /mnt/logs
    name: logpvc
    subPath: employee  

It is used to provide mounts to the volume.

Affinity and anti-affinity

Spec:
  Affinity:
    Key:
    Values:

Spec is used to define the desire state of the given container.

Node Affinity allows you to constrain which nodes your pod is eligible to schedule on, based on labels of the node.

Inter-pod affinity allow you to constrain which nodes your pod is eligible to be scheduled based on labels on pods.

Key

Key part of the label for node selection, this should be same as that on node. Please confirm with devops team.

Values

Value part of the label for node selection, this should be same as that on node. Please confirm with devops team.

Tolerations

tolerations:
 - key: "key"
   operator: "Equal"
   value: "value"
   effect: "NoSchedule|PreferNoSchedule|NoExecute(1.6 only)"

Taints are the opposite, they allow a node to repel a set of pods.

A given pod can access the given node and avoid the given taint only if the given pod satisfies a given taint.

Taints and tolerations are a mechanism which work together that allows you to ensure that pods are not placed on inappropriate nodes. Taints are added to nodes, while tolerations are defined in the pod specification. When you taint a node, it will repel all the pods except those that have a toleration for that taint. A node can have one or many taints associated with it.

Arguments

args:
  enabled: false
  value: []

This is used to give arguments to command.

Command

command:
  enabled: false
  value: []
  workingDir: {}

It contains the commands to run inside the container.

Key
Description

enabled

To enable or disable the command.

value

It contains the commands.

workingDir

It is used to specify the working directory where commands will be executed.

Containers

Containers section can be used to run side-car containers along with your main container within same pod. Containers running within same pod can share volumes and IP Address and can address each other @localhost. We can use base image inside container by setting the reuseContainerImage flag to true.

    containers:
      - name: nginx
        image: nginx:1.14.2
        ports:
        - containerPort: 80
        command: ["/usr/local/bin/nginx"]
        args: ["-g", "daemon off;"]
      - reuseContainerImage: true
        securityContext:
          runAsUser: 1000
          runAsGroup: 3000
          fsGroup: 2000
        volumeMounts:
        - mountPath: /etc/ls-oms
          name: ls-oms-cm-vol
        command:
          - flyway
          - -configFiles=/etc/ls-oms/flyway.conf
          - migrate

Prometheus

  prometheus:
    release: monitoring

It is a kubernetes monitoring tool and the name of the file to be monitored as monitoring in the given case.It describes the state of the prometheus.

rawYaml

rawYaml: 
  - apiVersion: v1
    kind: Service
    metadata:
      name: my-service
    spec:
      selector:
        app: MyApp
      ports:
        - protocol: TCP
          port: 80
          targetPort: 9376
      type: ClusterIP

Accepts an array of Kubernetes objects. You can specify any kubernetes yaml here and it will be applied when your app gets deployed.

Grace Period

GracePeriod: 30

Kubernetes waits for the specified time called the termination grace period before terminating the pods. By default, this is 30 seconds. If your pod usually takes longer than 30 seconds to shut down gracefully, make sure you increase the GracePeriod.

A Graceful termination in practice means that your application needs to handle the SIGTERM message and begin shutting down when it receives it. This means saving all data that needs to be saved, closing down network connections, finishing any work that is left, and other similar tasks.

There are many reasons why Kubernetes might terminate a perfectly healthy container. If you update your deployment with a rolling update, Kubernetes slowly terminates old pods while spinning up new ones. If you drain a node, Kubernetes terminates all pods on that node. If a node runs out of resources, Kubernetes terminates pods to free those resources. It’s important that your application handle termination gracefully so that there is minimal impact on the end user and the time-to-recovery is as fast as possible.

Server

server:
  deployment:
    image_tag: 1-95a53
    image: ""

It is used for providing server configurations.

Deployment

It gives the details for deployment.

Key
Description

image_tag

It is the image tag

image

It is the URL of the image

Service Monitor

servicemonitor:
      enabled: true
      path: /abc
      scheme: 'http'
      interval: 30s
      scrapeTimeout: 20s
      metricRelabelings:
        - sourceLabels: [namespace]
          regex: '(.*)'
          replacement: myapp
          targetLabel: target_namespace

It gives the set of targets to be monitored.

Db Migration Config

dbMigrationConfig:
  enabled: false

It is used to configure database migration.

Istio

These Istio configurations collectively provide a comprehensive set of tools for controlling access, authenticating requests, enforcing security policies, and configuring traffic behavior within a microservices architecture. The specific settings you choose would depend on your security and traffic management requirements.

Istio

These Istio configurations collectively provide a comprehensive set of tools for controlling access, authenticating requests, enforcing security policies, and configuring traffic behavior within a microservices architecture. The specific settings you choose would depend on your security and traffic management requirements.

istio:
  enable: true

  gateway:
    enabled: true
    labels:
      app: my-gateway
    annotations:
      description: "Istio Gateway for external traffic"
    host: "example.com"
    tls:
      enabled: true
      secretName: my-tls-secret

  virtualService:
    enabled: true
    labels:
      app: my-service
    annotations:
      description: "Istio VirtualService for routing"
    gateways:
      - my-gateway
    hosts:
      - "example.com"
    http:
      - match:
          - uri:
              prefix: /v1
        route:
          - destination:
              host: my-service-v1
              subset: version-1
      - match:
          - uri:
              prefix: /v2
        route:
          - destination:
              host: my-service-v2
              subset: version-2

  destinationRule:
    enabled: true
    labels:
      app: my-service
    annotations:
      description: "Istio DestinationRule for traffic policies"
    subsets:
      - name: version-1
        labels:
          version: "v1"
      - name: version-2
        labels:
          version: "v2"
    trafficPolicy:
      connectionPool:
        tcp:
          maxConnections: 100
      outlierDetection:
        consecutiveErrors: 5
        interval: 30s
        baseEjectionTime: 60s

  peerAuthentication:
    enabled: true
    labels:
      app: my-service
    annotations:
      description: "Istio PeerAuthentication for mutual TLS"
    selector:
      matchLabels:
        version: "v1"
    mtls:
      mode: STRICT
    portLevelMtls:
      8080:
        mode: DISABLE

  requestAuthentication:
    enabled: true
    labels:
      app: my-service
    annotations:
      description: "Istio RequestAuthentication for JWT validation"
    selector:
      matchLabels:
        version: "v1"
    jwtRules:
      - issuer: "issuer-1"
        jwksUri: "https://issuer-1/.well-known/jwks.json"

  authorizationPolicy:
    enabled: true
    labels:
      app: my-service
    annotations:
      description: "Istio AuthorizationPolicy for access control"
    action: ALLOW
    provider:
      name: jwt
      kind: Authorization
    rules:
      - from:
          - source:
              requestPrincipals: ["*"]
        to:
          - operation:
              methods: ["GET"]
Key
Description

istio

Istio enablement. When istio.enable set to true, Istio would be enabled for the specified configurations

authorizationPolicy

It allows you to define access control policies for service-to-service communication.

action

Determines whether to ALLOW or DENY the request based on the defined rules.

provider

Authorization providers are external systems or mechanisms used to make access control decisions.

rules

List of rules defining the authorization policy. Each rule can specify conditions and requirements for allowing or denying access.

destinationRule

It allows for the fine-tuning of traffic policies and load balancing for specific services. You can define subsets of a service and apply different traffic policies to each subset.

subsets

Specifies subsets within the service for routing and load balancing.

trafficPolicy

Policies related to connection pool size, outlier detection, and load balancing.

gateway

Allowing external traffic to enter the service mesh through the specified configurations.

host

The external domain through which traffic will be routed into the service mesh.

tls

Traffic to and from the gateway should be encrypted using TLS.

secretName

Specifies the name of the Kubernetes secret that contains the TLS certificate and private key. The TLS certificate is used for securing the communication between clients and the Istio gateway.

peerAuthentication

It allows you to enforce mutual TLS and control the authentication between services.

mtls

Mutual TLS. Mutual TLS is a security protocol that requires both client and server, to authenticate each other using digital certificates for secure communication.

mode

Mutual TLS mode, specifying how mutual TLS should be applied. Modes include STRICT, PERMISSIVE, and DISABLE.

portLevelMtls

Configures port-specific mTLS settings. Allows for fine-grained control over the application of mutual TLS on specific ports.

selector

Configuration for selecting workloads to apply PeerAuthentication.

requestAuthentication

Defines rules for authenticating incoming requests.

jwtRules

Rules for validating JWTs (JSON Web Tokens). It defines how incoming JWTs should be validated for authentication purposes.

selector

Specifies the conditions under which the RequestAuthentication rules should be applied.

virtualService

Enables the definition of rules for how traffic should be routed to different services within the service mesh.

gateways

Specifies the gateways to which the rules defined in the VirtualService apply.

hosts

List of hosts (domains) to which this VirtualService is applied.

http

Configuration for HTTP routes within the VirtualService. It define routing rules based on HTTP attributes such as URI prefixes, headers, timeouts, and retry policies.

Application Metrics

Application metrics can be enabled to see your application's metrics-CPU Service Monitor usage, Memory Usage, Status, Throughput and Latency.

Deployment Metrics

It gives the realtime metrics of the deployed applications

Key
Description

Deployment Frequency

It shows how often this app is deployed to production

Change Failure Rate

It shows how often the respective pipeline fails.

Mean Lead Time

It shows the average time taken to deliver a change to production.

Mean Time to Recovery

It shows the average time taken to fix a failed pipeline.

Addon features in Deployment Template Chart version 3.9.0

Service Account

serviceAccountName: orchestrator

A service account provides an identity for the processes that run in a Pod.

When you access the cluster, you are authenticated by the API server as a particular User Account. Processes in containers inside pod can also contact the API server. When you are authenticated as a particular Service Account.

When you create a pod, if you do not create a service account, it is automatically assigned the default service account in the namespace.

Pod Disruption Budget

You can create PodDisruptionBudget for each application. A PDB limits the number of pods of a replicated application that are down simultaneously from voluntary disruptions. For example, an application would like to ensure the number of replicas running is never brought below the certain number.

podDisruptionBudget: 
     minAvailable: 1

or

podDisruptionBudget: 
     maxUnavailable: 50%

You can specify either maxUnavailable or minAvailable in a PodDisruptionBudget and it can be expressed as integers or as a percentage.

Key
Description

minAvailable

Evictions are allowed as long as they leave behind 1 or more healthy pods of the total number of desired replicas.

maxUnavailable

Evictions are allowed as long as at most 1 unhealthy replica among the total number of desired replicas.

Application metrics Envoy Configurations

envoyproxy:
  image: envoyproxy/envoy:v1.14.1
  configMapName: ""
  resources:
    limits:
      cpu: "50m"
      memory: "50Mi"
    requests:
      cpu: "50m"
      memory: "50Mi"

Envoy is attached as a sidecar to the application container to collect metrics like 4XX, 5XX, Throughput and latency. You can now configure the envoy settings such as idleTimeout, resources etc.

Prometheus Rule

prometheusRule:
  enabled: true
  additionalLabels: {}
  namespace: ""
  rules:
    - alert: TooMany500s
      expr: 100 * ( sum( nginx_ingress_controller_requests{status=~"5.+"} ) / sum(nginx_ingress_controller_requests) ) > 5
      for: 1m
      labels:
        severity: critical
      annotations:
        description: Too many 5XXs
        summary: More than 5% of the all requests did return 5XX, this require your attention

Alerting rules allow you to define alert conditions based on Prometheus expressions and to send notifications about firing alerts to an external service.

In this case, Prometheus will check that the alert continues to be active during each evaluation for 1 minute before firing the alert. Elements that are active, but not firing yet, are in the pending state.

Pod Labels

Labels are key/value pairs that are attached to pods. Labels are intended to be used to specify identifying attributes of objects that are meaningful and relevant to users, but do not directly imply semantics to the core system. Labels can be used to organize and to select subsets of objects.

podLabels:
  severity: critical

Pod Annotations

Pod Annotations are widely used to attach metadata and configs in Kubernetes.

podAnnotations:
  fluentbit.io/exclude: "true"

Custom Metrics in HPA

autoscaling:
  enabled: true
  MinReplicas: 1
  MaxReplicas: 2
  TargetCPUUtilizationPercentage: 90
  TargetMemoryUtilizationPercentage: 80
  behavior:
    scaleDown:
      stabilizationWindowSeconds: 300
      policies:
      - type: Percent
        value: 100
        periodSeconds: 15
    scaleUp:
      stabilizationWindowSeconds: 0
      policies:
      - type: Percent
        value: 100
        periodSeconds: 15
      - type: Pods
        value: 4
        periodSeconds: 15
      selectPolicy: Max

HPA, by default is configured to work with CPU and Memory metrics. These metrics are useful for internal cluster sizing, but you might want to configure wider set of metrics like service latency, I/O load etc. The custom metrics in HPA can help you to achieve this.

Wait For Seconds Before Scaling Down

waitForSecondsBeforeScalingDown: 30

Wait for given period of time before scaling down the container.

4. Show Application Metrics

If you want to see application metrics like different HTTP status codes metrics, application throughput, latency, response time. Enable the Application metrics from below the deployment template Save button. After enabling it, you should be able to see all metrics on App detail page. By default it remains disabled.

Once all the Deployment template configurations are done, click on Save to save your deployment configuration. Now you are ready to create Workflow to do CI/CD.

Helm Chart Json Schema Table

Helm Chart json schema is used to validate the deployment template values.

Chart Version
Link

reference-chart_3-12-0

reference-chart_3-11-0

reference-chart_3-10-0

reference-chart_3-9-0

Other Validations in Json Schema

The values of CPU and Memory in limits must be greater than or equal to in requests respectively. Similarly, In case of envoyproxy, the values of limits are greater than or equal to requests as mentioned below.

resources.limits.cpu >= resources.requests.cpu
resources.limits.memory >= resources.requests.memory
envoyproxy.resources.limits.cpu >= envoyproxy.resources.requests.cpu
envoyproxy.resources.limits.memory >= envoyproxy.resources.requests.memory

Addon features in Deployment Template Chart version 4.11.0

KEDA Autoscaling

Prerequisite: KEDA controller should be installed in the cluster. To install KEDA controller using Helm, navigate to chart store and search for keda chart and deploy it. You can follow this documentation for deploying a Helm chart on Devtron.

KEDA Helm repo : https://kedacore.github.io/charts

KEDA is a Kubernetes-based Event Driven Autoscaler. With KEDA, you can drive the scaling of any container in Kubernetes based on the number of events needing to be processed. KEDA can be installed into any Kubernetes cluster and can work alongside standard Kubernetes components like the Horizontal Pod Autoscaler(HPA).

Example for autoscaling with KEDA using Prometheus metrics is given below:

kedaAutoscaling:
  enabled: true
  minReplicaCount: 1
  maxReplicaCount: 2
  idleReplicaCount: 0
  pollingInterval: 30
  advanced:
    restoreToOriginalReplicaCount: true
    horizontalPodAutoscalerConfig:
      behavior:
        scaleDown:
          stabilizationWindowSeconds: 300
          policies:
          - type: Percent
            value: 100
            periodSeconds: 15
  triggers: 
    - type: prometheus
      metadata:
        serverAddress:  http://<prometheus-host>:9090
        metricName: http_request_total
        query: envoy_cluster_upstream_rq{appId="300", cluster_name="300-0", container="envoy",}
        threshold: "50"
  triggerAuthentication:
    enabled: false
    name:
    spec: {}
  authenticationRef: {}

Example for autosccaling with KEDA based on kafka is given below :

kedaAutoscaling:
  enabled: true
  minReplicaCount: 1
  maxReplicaCount: 2
  idleReplicaCount: 0
  pollingInterval: 30
  advanced: {}
  triggers: 
    - type: kafka
      metadata:
        bootstrapServers: b-2.kafka-msk-dev.example.c2.kafka.ap-southeast-1.amazonaws.com:9092,b-3.kafka-msk-dev.example.c2.kafka.ap-southeast-1.amazonaws.com:9092,b-1.kafka-msk-dev.example.c2.kafka.ap-southeast-1.amazonaws.com:9092
        topic: Orders-Service-ESP.info
        lagThreshold: "100"
        consumerGroup: oders-remove-delivered-packages
        allowIdleConsumers: "true"
  triggerAuthentication:
    enabled: true
    name: keda-trigger-auth-kafka-credential
    spec:
      secretTargetRef:
        - parameter: sasl
          name: keda-kafka-secrets
          key: sasl
        - parameter: username
          name: keda-kafka-secrets
          key: username
  authenticationRef: 
    name: keda-trigger-auth-kafka-credential

NetworkPolicy

Kubernetes NetworkPolicies control pod communication by defining rules for incoming and outgoing traffic.

networkPolicy:
  enabled: false
  annotations: {}
  labels: {}
  podSelector:
    matchLabels:
      role: db
  policyTypes:
    - Ingress
    - Egress
  ingress:
    - from:
        - ipBlock:
            cidr: 172.17.0.0/16
            except:
              - 172.17.1.0/24
        - namespaceSelector:
            matchLabels:
              project: myproject
        - podSelector:
            matchLabels:
              role: frontend
      ports:
        - protocol: TCP
          port: 6379
  egress:
    - to:
        - ipBlock:
            cidr: 10.0.0.0/24
      ports:
        - protocol: TCP
          port: 5978
Key
Description

enabled

Enable or disable NetworkPolicy.

annotations

Additional metadata or information associated with the NetworkPolicy.

labels

Labels to apply to the NetworkPolicy.

podSelector

Each NetworkPolicy includes a podSelector which selects the grouping of pods to which the policy applies. The example policy selects pods with the label "role=db". An empty podSelector selects all pods in the namespace.

policyTypes

Each NetworkPolicy includes a policyTypes list which may include either Ingress, Egress, or both.

Ingress

Controls incoming traffic to pods.

Egress

Controls outgoing traffic from pods.

Winter-Soldier

Winter Soldier can be used to

  • cleans up (delete) Kubernetes resources

  • reduce workload pods to 0

NOTE: After deploying this we can create the Hibernator object and provide the custom configuration by which workloads going to delete, sleep and many more. for more information check the main repo

Given below is template values you can give in winter-soldier:

winterSoldier:
  enabled: false
  apiVersion: pincher.devtron.ai/v1alpha1
  action: sleep
  timeRangesWithZone:
    timeZone: "Asia/Kolkata"
    timeRanges: []
  targetReplicas: []
  fieldSelector: []
Key
values
Description

enabled

false,true

decide the enabling factor

apiVersion

pincher.devtron.ai/v1beta1, pincher.devtron.ai/v1alpha1

specific api version

action

sleep,delete, scale

This specify the action need to perform.

timeRangesWithZone:timeZone

eg:- "Asia/Kolkata","US/Pacific"

It use to specify the timeZone used. (It uses standard format. please refer this)

timeRangesWithZone:timeRanges

array of [ timeFrom, timeTo, weekdayFrom, weekdayTo]

It use to define time period/range on which the user need to perform the specified action. you can have multiple timeRanges. These settings will take action on Sat and Sun from 00:00 to 23:59:59,

targetReplicas

[n] : n - number of replicas to scale.

These is mandatory field when the action is scale Default value is [].

fieldSelector

- AfterTime(AddTime( ParseTime({{metadata.creationTimestamp}}, '2006-01-02T15:04:05Z'), '5m'), Now())

These value will take a list of methods to select the resources on which we perform specified action .

here is an example,

winterSoldier:
  apiVersion: pincher.devtron.ai/v1alpha1 
  enabled: true
  annotations: {}
  labels: {}
  timeRangesWithZone:
    timeZone: "Asia/Kolkata"
    timeRanges: 
      - timeFrom: 00:00
        timeTo: 23:59:59
        weekdayFrom: Sat
        weekdayTo: Sun
      - timeFrom: 00:00
        timeTo: 08:00
        weekdayFrom: Mon
        weekdayTo: Fri
      - timeFrom: 20:00
        timeTo: 23:59:59
        weekdayFrom: Mon
        weekdayTo: Fri
  action: scale
  targetReplicas: [1,1,1]
  fieldSelector: 
    - AfterTime(AddTime( ParseTime({{metadata.creationTimestamp}}, '2006-01-02T15:04:05Z'), '10h'), Now())

Above settings will take action on Sat and Sun from 00:00 to 23:59:59, and on Mon-Fri from 00:00 to 08:00 and 20:00 to 23:59:59. If action:sleep then runs hibernate at timeFrom and unhibernate at timeTo. If action: delete then it will delete workloads at timeFrom and timeTo. Here the action:scale thus it scale the number of resource replicas to targetReplicas: [1,1,1]. Here each element of targetReplicas array is mapped with the corresponding elements of array timeRangesWithZone/timeRanges. Thus make sure the length of both array is equal, otherwise the cnages cannot be observed.

The above example will select the application objects which have been created 10 hours ago across all namespaces excluding application's namespace. Winter soldier exposes following functions to handle time, cpu and memory.

  • ParseTime - This function can be used to parse time. For eg to parse creationTimestamp use ParseTime({{metadata.creationTimestamp}}, '2006-01-02T15:04:05Z')

  • AddTime - This can be used to add time. For eg AddTime(ParseTime({{metadata.creationTimestamp}}, '2006-01-02T15:04:05Z'), '-10h') ll add 10h to the time. Use d for day, h for hour, m for minutes and s for seconds. Use negative number to get earlier time.

  • Now - This can be used to get current time.

  • CpuToNumber - This can be used to compare CPU. For eg any({{spec.containers.#.resources.requests}}, { MemoryToNumber(.memory) < MemoryToNumber('60Mi')}) will check if any resource.requests is less than 60Mi.

Security Context

A security context defines privilege and access control settings for a Pod or Container.

To add a security context for main container:

containerSecurityContext:
  allowPrivilegeEscalation: false

To add a security context on pod level:

podSecurityContext:
  runAsUser: 1000
  runAsGroup: 3000
  fsGroup: 2000

Topology Spread Constraints

You can use topology spread constraints to control how Pods are spread across your cluster among failure-domains such as regions, zones, nodes, and other user-defined topology domains. This can help to achieve high availability as well as efficient resource utilization.

topologySpreadConstraints:
  - maxSkew: 1
    topologyKey: zone
    whenUnsatisfiable: DoNotSchedule
    autoLabelSelector: true
    customLabelSelector: {}

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