Configuring Backup in Tanzu SQL with MySQL for Kubernetes

Backup & Restore

Prerequisite: A reachable S3 endpoint. Can be local or remote, but the pods must be able to resolve its name or IP. Create or select and existing bucket for your database backups. In this case, I have a minio instance running on-prem with a bucket named backup-mysql.

Create a secret for the S3 endpoint credentials. This account will need to be able to write to the database backup bucket. Here’s an example:

---
apiVersion: v1
kind: Secret
metadata:
  name: minio-creds
stringData:
  # S3 Credentials
  accessKeyId: "MYACCESSKEY"
  secretAccessKey: "MYSECRETKEY"

Create a TanzuMySQLBackupLocation. In the example below, we’re not using SSL with the minio endpoint, so I’m explicitly using port 80. More examples and details are found here. I like to keep the backups organized, so I’ll create a backup location for each instance and specify an bucketPath for each.

---
apiVersion: with.sql.tanzu.vmware.com/v1
kind: MySQLBackupLocation
metadata:
  name: backuplocation-mysql-ha
spec:
  storage:
    # For S3 or Minio:
    s3:
      bucket: "backup-mysql-ha"
      bucketPath: "/mysql-ha/"
      # region: "us-east-1"
      endpoint:  "http://minio.ragazzilab.com:80" # optional, default to AWS
      forcePathStyle: true
      secret:
        name: minio-creds

Test with a one-off backup. Create and apply a yaml like the following to request a backup without a schedule. Here’s an example yaml for a one-off backup for the mysql-ha instance to its corresponding backup location:

---
apiVersion: with.sql.tanzu.vmware.com/v1
kind: MySQLBackup
metadata:
  name: backup-mysql-ha-1off
spec:
  location:
    name: backuplocation-mysql-ha
  instance:
    name: mysql-ha

We can get the MySQLBackups to see that it has completed successfully:

Create a backup Schedule

Now that we’ve confirmed that the backup location and credentials work as expected, we should add a backup schedule. Here’s an example:

---
apiVersion: with.sql.tanzu.vmware.com/v1
kind: MySQLBackupSchedule
metadata:
  name: mysql-ha-daily
spec:
  backupTemplate:
    spec:
      location:
        name: backuplocation-mysql-ha
      instance:
        name:  mysql-ha
  schedule: "@daily"

Apply this kubectl apply -n mysql-instances -f backupschedule-mysql-ha-daily.yaml

I found that (unlike Velero), when applying the MySQLBackupSchedule, a backup does not immediately begin. At the scheduled time however, a pod for the backup schedule will be created to run the backup job. This pod will remain intact to run subsequent backup jobs.

Backup Pods and created Backup objects

Lastly, regarding backups, keep in mind that the backup data on the S3 endpoint never expires, the backups will remain there until removed manually. This may be important if you have limited capacity.

Restore/Recover

From the docs:

MySQLRestores always restores to a new MySQL instance to avoid overwriting any data on an existing MySQL instance. The MySQL instance is created automatically when the restore is triggered. Tanzu MySQL for Kubernetes does not allow you to restore a backup to an existing MySQL instance. Although you can perform this manually by copying the MySQL data from the backup artifact onto an existing MySQL instance, VMware strongly discourages you from doing this because you might overwrite existing data on the MySQL instance.

So, we should not expect to restore directly to a running database instance. If we need to recover, we’ll create a new instance and restore the backup to it.

To create a restore, we’ll need the name of the MySQLBackup object to restore from and a name of a database to create from that backup as part of the restore. We’ll put that into a yaml like the one below. Notice that we provide a spec for a new database, I wanted a loadbalancer for it although we are able to repoint the existing loadbalancer to the new proxy nodes (for ha) or the new database node (for standalone)

---
apiVersion: with.sql.tanzu.vmware.com/v1
kind: MySQLRestore
metadata:
  name: restore-ha
spec:
  backup:
    name: mysql-ha-daily-20210708-000005
  instanceTemplate:
    metadata:
      name: restored-mysql-database
    spec:
      storageSize: 2Gi
      imagePullSecret: harbor
      serviceType: LoadBalancer
      highAvailability:
        enabled: true

Apply the yaml to create the restore kubectl apply -n mysql-instances -f ./restore-ha.yamlYou should see a new database pending and a MySQLRestore object running:

Job is running and instance is pending
Restore job succeeded and there is a new mysql instance

Now, the choice if yours to copy data from the restored database back to the original or to point the applications to the new database or to point the loadbalancer at the new database.

If you choose to repoint the existing load-balancer to the new database, here’s an example how to do that:

kubectl patch service -n mysql-instances mysql-ha -p '{"spec":{"selector":{"app.kubernetes.io/instance": "restored-mysql-database"}}}'

Configuring VMware Tanzu SQL with MySQL for Kubernetes for High Availability

As a follow up to the getting started post, let’s touch on what it takes to configure a MySQL instance for High Availability in Tanzu SQL/MySQL

Why this is important

In kubernetes, pods are generally treated as transient and ephemeral, they can be restarted quickly and are often stateless. This is certainly not the case with databases. We need to make sure our databases remain online and usable. MySQL itself provides a means to do High Availability with multiple instances and synchronization; we’ll be leveraging this capability today.

High Availability Architecture

Blatantly ripped off from the official docs

Unlike our stand-alone instance when create an instance with HA enabled, the operator creates FIVE pods and two services for us.

Pods created for HA instance
Services created for HA instance

You’ll notice that the mysql-ha LoadBalancer uses the proxy pods as its endpoints and the mysql-ha-members uses the database pods themselves.

Create an HA instance

In this example, I’m going to reuse the “harbor” docker-registry secret we created originally, but we’ll want a new tls certificate for this instance.

Create the TLS certificate

Just like previously, save the following as cert-ha.yaml and apply it with kubectl -n mysql-instances -f cert-ha.yaml to create a certificate for our instance. Adjust the names to match your environment of course. Notice the issuerRef.name is ca-issuer

apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
  name: mysql-ha-secret
spec:
  # Secret names are always required.
  secretName: mysql-ha-secret
  duration: 2160h # 90d
  renewBefore: 360h # 15d
  subject:
    organizations:
    - ragazzilab.com
  # The use of the common name field has been deprecated since 2000 and is
  # discouraged from being used.
  commonName: mysql-ha.ragazzilab.com
  dnsNames:
  - mysql-ha.ragazzilab.com
  - mysql-ha
  - mysql-ha.mysql-instances.svc.cluster.local
  # Issuer references are always required.
  issuerRef:
    name: ca-issuer
    # We can reference ClusterIssuers by changing the kind here.
    # The default value is Issuer (i.e. a locally namespaced Issuer)
    kind: Issuer
    # This is optional since cert-manager will default to this value however
    # if you are using an external issuer, change this to that issuer group.
    group: cert-manager.io

Create the instance

The only differences are highAvailability.enabled:true and the name of the certificate secret

apiVersion: with.sql.tanzu.vmware.com/v1
kind: MySQL
metadata:
  name: mysql-ha
spec:
  storageSize: 2Gi
  imagePullSecret: harbor
#### Set highAvailability.enabled:true to create three pods; one primary and two standby, plus two proxy pods
  highAvailability:
    enabled: true

#### Set the storage class name to change storage class of the PVC associated with this resource
  storageClassName: tanzu

#### Set the type of Service used to provide access to the MySQL database.
  serviceType: LoadBalancer # Defaults to ClusterIP

### Set the name of the Secret used for TLS
  tls:
    secret:
      name: mysql-ha-secret

Apply this as usual: kubectl apply -n mysql-instances -f ./mysql-ha.yaml

Create a database user

The steps to create the database user in an HA instance are just like those for the standalone instance once we determine which Pod is the primary/active and writable one. I was unable to make the one-liner method in the official docs work, so here’s what I did instead.

  1. Get the MySQL root password: kubectl get secret -n mysql-instances mysql-ha-credentials -o jsonpath='{.data.rootPassword}' | base64 -D
  2. Get a shell on the mysql-ha-0 pod: kubectl -n mysql-instances exec --stdin --tty pod/mysql-ha-0 -c mysql -- /bin/bash
  3. Get into the mysql cli: mysql -uroot -p<root password>
  4. Identify the Primary member: SELECT MEMBER_HOST, MEMBER_ROLE FROM performance_schema.replication_group_members;
  5. If the primary node is mysql-ha-0 (the one we’re on), proceed to the next step. If it is not, go back to step step 2 to get a shell on the pod that is primary.
  6. Now, we should be on the mysql cli on the primary pod/member. Just like with the standalone instance, let’s create a user:
CREATE USER 'admin'@'%' IDENTIFIED BY 'password';
  GRANT ALL PRIVILEGES ON * . * TO 'admin'@'%';
  FLUSH PRIVILEGES;

Type exit twice to get out of mysql and the pod.

Ok, so now, we have a running instance of mysql and we’ve created a user account that can manage it (cannot login remotely as root). We can connect phpMyAdmin to the instance using the admin credentials:

Showing the three members of the instance

Getting Started with VMware Tanzu SQL with MySQL for Kubernetes

Let’s deploy Tanzu SQL with MySQL on Kubernetes and use phpMyAdmin to interact with our
database secured with TLS

VMware Tanzu SQL with MySQL for Kubernetes is quite a mouthful. For this post, I’ll refer to the product as Tanzu SQL/MySQL. We’re going to deploy it onto an existing Tanzu Kubernetes Grid cluster.

Objectives:

  • Deploy Tanzu SQL with MySQL on Kubernetes
  • Use phpMyAdmin to interact with our databases
  • Secure database instances with TLS

Cluster Setup

Tanzu SQL/MySQL can run on any conformant kubernetes cluster, if you already have one running, you can skip ahead. If, like me, you want to provision a new TKG cluster for Tanzu SQL/MySQL, you’ll want settings like this:

  • K8s version 1.18 or 1.19 or 1.20.7
  • Additional volume on /var/lib/containerd for the images
  • For a test cluster, best-effort small control-plane nodes (3) and best-effort-medium worker nodes (2) is sufficient to start, YMMV.
  • Install metrics-server and add appropriate PSPs

Get the images and chart

You’ll need to login to pivnet and registry.pivotal.io, accept the EULA for VMware Tanzu SQL with MySQL for Kubernetes.

At a command-line, run:docker login registry.pivotal.io then, provide your credentials. This is so that docker can pull down the images from VMware. Login to your local container registry as well – you’ll need permissions to push images into your project.

In the following commands, replace “{local repo}” with the FQDN for your local registry and “{project}” with the project name in that repo that you can push images to.

docker pull registry.pivotal.io/tanzu-mysql-for-kubernetes/tanzu-mysql-instance:1.0.0
docker pull registry.pivotal.io/tanzu-mysql-for-kubernetes/tanzu-mysql-operator:1.0.0
docker tag registry.pivotal.io/tanzu-mysql-for-kubernetes/tanzu-mysql-instance:1.0.0 {local repo}/{project}/tanzu-mysql-instance:1.0.0
docker tag registry.pivotal.io/tanzu-mysql-for-kubernetes/tanzu-mysql-operator:1.0.0 {local repo}/{project}/tanzu-mysql-operator:1.0.0
docker push {local repo}/{project}/tanzu-mysql-instance:1.0.0
docker push {local repo}/{project}/tanzu-mysql-operator:1.0.0

Retrieve the helm chart:

export HELM_EXPERIMENTAL_OCI=1
helm chart pull registry.pivotal.io/tanzu-mysql-for-kubernetes/tanzu-mysql-operator-chart:1.0.0
helm chart export registry.pivotal.io/tanzu-mysql-for-kubernetes/tanzu-mysql-operator-chart:1.0.0

In the tanzu-sql-with-mysql-operator folder created by the helm export, copy values.yaml to values-override.yaml. Edit the keys with the correct values (we haven’t created the harbor secret yet, but we’ll name it the value you provide here). Here’s an example:


imagePullSecret: harbor
operatorImage: {local repo}/{project}/tanzu-mysql-operator:1.0.0"
instanceImage: {local repo}/{project}/tanzu-mysql-instance:1.0.0"
resources:
  limits:
    cpu: 100m
    memory: 128Mi
  requests:
    cpu: 100m
    memory: 128Mi

Deploy Operator

We’ll want to create namespace, a docker-registry secret (named harbor in the example below) and then install the chart.

kubectl create namespace tanzu-mysql
kubectl --namespace tanzu-mysql create secret docker-registry harbor --docker-server=https://{local repo} --docker-username=MYUSERNAME --docker-password=MYPASSWORD
helm install --namespace tanzu-mysql --values=./tanzu-sql-with-mysql-operator/values-override.yaml tanzu-mysql-operator ./tanzu-sql-with-mysql-operator/

Let’s check that the pods are running by running kubectl get po -n tanzu-mysql

Before Creating an Instance…

We’ll need to create a namespace to put our mysql instances, a secret in that namespace in order to pull the images from our local repo, and a way to create TLS certificates and phpMyAdmin. These commands will create the namespace, create the docker-registry secret and install cert-manager:

kubectl create namespace cert-manager helm repo add jetstack https://charts.jetstack.io helm repo update helm install cert-manager jetstack/cert-manager --namespace cert-manager --version v1.0.2 --set installCRDs=true kubectl create namespace tanzu-mysql kubectl --namespace mysql-instances create secret docker-registry harbor --docker-server=https://<local repo> --docker-username=<username> --docker-password=<password>

Working with cert-manager

Cert-manager uses issuers to create certificates from cert-requests. There are a variety of issuers supported, but we must have the ca certificate included in the resulting certificate secret – something not all issuers do. For example, self-signed and ACME are not suitable as they do not appear to include the ca certificate in the cert secret. Luckily, the CA issuer works fine and can use a self-signed issuer as its own signer. Save the following as a yaml file to create a self-signed issuer, root cert and a CA issuer and apply it with kubectl -n mysql-instances -f cabootstrap.yaml

---
apiVersion: cert-manager.io/v1
kind: ClusterIssuer
metadata:
  name: selfsigned-issuer
spec:
  selfSigned: {}
---
apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
  name: my-selfsigned-ca
spec:
  isCA: true
  commonName: my-selfsigned-ca
  secretName: root-secret
  privateKey:
    algorithm: ECDSA
    size: 256
  issuerRef:
    name: selfsigned-issuer
    kind: ClusterIssuer
    group: cert-manager.io
---
apiVersion: cert-manager.io/v1
kind: Issuer
metadata:
  name: ca-issuer
spec:
  ca:
    secretName: root-secret

Save the following as cert.yaml and apply it with kubectl -n mysql-instances -f cert.yaml to create a certificate for our instance. Adjust the names to match your environment of course. Notice the issuerRef.name is ca-issuer

apiVersion: cert-manager.io/v1
kind: Certificate
metadata:
  name: mysql-tls-secret
spec:
  # Secret names are always required.
  secretName: mysql-tls-secret
  duration: 2160h # 90d
  renewBefore: 360h # 15d
  subject:
    organizations:
    - ragazzilab.com
  # The use of the common name field has been deprecated since 2000 and is
  # discouraged from being used.
  commonName: mysql-tls.mydomain.local
  dnsNames:
  - mysql-tls.mydomain.local
  - mysql-tls
  - mysql-tls.mysql-instances.svc.cluster.local
  # Issuer references are always required.
  issuerRef:
    name: ca-issuer
    # We can reference ClusterIssuers by changing the kind here.
    # The default value is Issuer (i.e. a locally namespaced Issuer)
    kind: Issuer
    # This is optional since cert-manager will default to this value however
    # if you are using an external issuer, change this to that issuer group.
    group: cert-manager.io

Confirm that the corresponding secret contains three files: ca.crt, tls.crt, tls.key by using kubectl describe secret -n mysql-instances mysql-tls-secret

Create an instance and add a user

Here is an example yaml for a MySQL instance. This will create an instance name mysql-tls, using the docker-registry secret named harbor we created earlier and the certificate secret we created above named mysql-tls-secret and use a LoadBalancer IP so we can access it from outside of the cluster.

apiVersion: with.sql.tanzu.vmware.com/v1
kind: MySQL
metadata:
  name: mysql-tls
spec:
  storageSize: 2Gi
  imagePullSecret: harbor

#### Set the storage class name to change storage class of the PVC associated with this resource
  storageClassName: tanzu

#### Set the type of Service used to provide access to the MySQL database.
  serviceType: LoadBalancer # Defaults to ClusterIP

### Set the name of the Secret used for TLS
  tls:
    secret:
      name: mysql-tls-secret

Apply this yaml to the mysql-instances namespace to create the instance: kubectl apply -n mysql-instances -f ./mysqlexample.yaml

Watch for two containers in the pod to be ready

Watch for the mysql-tls-0 pod to be running with 2 containers. When the instance is created, the operator also creates a secret containing the root password. Retrieve the root password with this command: kubectl get secret -n mysql-instances mysql-tls-credentials -o jsonpath='{.data.rootPassword}' | base64 -D
Retrieve the load-balancer address for the MySQL instance with this command: kubectl get svc -n mysql-instances mysql-tls

LoadBalancer address for our instance

Login to Pod and run mysql commands

Logging into the pod, then into mysql

Run this to get into a command prompt on the mysql pod: kubectl -n mysql-instances exec --stdin --tty pod/mysql-tls-0 -c mysql -- /bin/bash
Once in the pod and at a prompt, run this to get into the mysql cli as root: mysql -uroot -p<root password>
Once at the mysql prompt, run this to create a user named “admin” with a password set to “password” (PLEASE use a different password!)

  CREATE USER 'admin'@'%' IDENTIFIED BY 'password';
  GRANT ALL PRIVILEGES ON * . * TO 'admin'@'%';
  FLUSH PRIVILEGES;

Type exit twice to get out of mysql and the pod.

Ok, so now, we have a running instance of mysql and we’ve created a user account that can manage it (cannot login remotely as root).

Deploy, Configure and use phpMyAdmin

There are several ways to do this, but I’m going to go with kubeapps to deploy phpMyAdmin. Run this to install kubeapps with a loadbalancer front-end:

helm repo add bitnami https://charts.bitnami.com/bitnami
kubectl create namespace kubeapps
helm install kubeapps --namespace kubeapps bitnami/kubeapps --set frontend.service.type=LoadBalancer

Find the External IP address for kubeapps and point a browser at it: kubectl get svc -n kubeapps kubeapps. Get the token from your .kube/config file to paste into the token field in kubeapps and click submit. Once in kubeapps, be sure to select the kubeapps namespace – you should see kubeapps itself under Applications.

logged into kubeapps in the kubeapps namespace

Click “Catalog” and type “phpmyadmin” into the search field. Click on the phpmyadmin box that results. On the next page, describing phpmyadmin, click the Blue deploy button.

Now, you should be looking at a configuration yaml for phpmyadmin. First, set the Name up top to something meaningful, like phpmyadmin, the scroll down to line 256, you should see the service type currently set to ClusterIP, replace ClusterIP with LoadBalancer.

Set the name and service type

Then scroll the rest of the way to click the blue “Deploy X.Y.Z” button and hang tight. After it deploys, the Access URLs will show the IP address for phpMyAdmin.

Access URLs for phpmyadmin after deployment

Click the Access URL to get to the Login page for phpMyAdmin and supply the IP Address of the mysql instance as well as the admin username and password we created above, then click Go.

Login to instance IP with the account we made earlier

Now you should be able to manage the databases and objects in the mysql instance!

phpmyadmin connected to our instance!

Notes

  • Kubernetes v1.20. There are filesystem permissions set on Tanzu Kubernetes Grid image 1.20.2 that prevent the MySQL instance pods from running. On TKG or vSphere with Tanzu, use v1.20.7 instead.
  • You don’t have to use cert-manager if you have another source for TLS certificates, just put the leaf cert, private key and ca cert into the secret referenced by the mysql instance yaml.
  • Looks like you can reuse the TLS cert for multiple databases, just keep in mind that if you connect using a name/fqdn that is not in the cert’s dnsNames, you may be a cert error.
  • This example uses Tanzu Kubernetes Grid Service in vSphere with Tanzu on vSphere 7 Update 2 using NSX-ALB.

Configure Tanzu Kubernetes Grid to use Active Directory

Tanzu Kubernetes Grid includes and supports packages for dex and Gangway.  These are used to extend authentication to LDAP and OIDC endpoints.  Recall that Kubernetes does not do user-management or traditional authentication.  As a K8s cluster admin, you can create service accounts of course, but those are not meant to be used by developers.

Think of dex as a transition layer, it uses ‘connectors’ for upstream Identity providers (IdP) like Active Directory for LDAP or Okta for SAML and presents an OpenID Connect (OIDC) endpoint for k8s to use.

TKG provides not only the packages mentioned above, but also a collection of yaml files and documentation for implementation.  The current version (as of May 12, 2020) documentation for configuring authentication is pretty general, the default values in the config files are suitable for OpenLDAP.  So, I thought I’d share the specific settings for connecting dex to Active Directory.

Assumptions:

    1. TKG Management cluster is deployed
    2. Following the VMware documentation
    3. Using the TKG-provided tkg-extensions
    4. dex will be deployed to management cluster or to a specific workload cluster

Edits to authentication/dex/vsphere/ldap/03-cm.yaml – from Docs

  1. Replace <MGMT_CLUSTER_IP> with the IP address of one of the control plane nodes of your management cluster.  This is one of the control plane nodes where we’re putting dex
  2. If the LDAP server is listening on the default port 636, which is the secured configuration, replace <LDAP_HOST> with the IP or DNS address of your LDAP server. If the LDAP server is listening on any other port, replace <LDAP_HOST> with the address and port of the LDAP server, for example 192.168.10.22:389 or ldap.mydomain.com:389.  Never, never, never use unencrypted LDAP.  You’ll need to specify port 636 unless your targeted AD controller is also a Global Catalog server in which case you’ll specify port 3269.  Check with the AD team if you’re unsure.
  3. If your LDAP server is configured to listen on an unsecured connection, uncomment insecureNoSSL: true. Note that such connections are not recommended as they send credentials in plain text over the network. Never, never, never use unencrypted LDAP.
  4. Update the userSearch and groupSearch parameters with your LDAP server configuration.  This need much more detail – see steps below

Edits to authentication/dex/vsphere/ldap/03-cm.yaml – AD specific

  1. Obtain the root CA public certificate for your AD controller. Save a base64-encoded version of the certificate: echo root64.cer | base64 > rootcer.b64 for example will write the data from the PEM-encoded root64.cer file into a base64-encoded file named rootcer.b64
  2. Add the base64-encoded certificate content to the rootCAData key.  Be sure to remove the leading “#”.  This is an alternative to using the rootCA key, where we’ll have to place the file on each Control Plane node
  3. Update the userSearch values as follows:
    key default set to notes
    baseDN ou=people,

    dc=vmware,dc=com

    DN of OU in AD under

    which user accounts are found

    Example: ou=User Accounts,DC=ragazzilab,DC=com
    filter “(objectClass=

    posixAccount)”

    “(objectClass=person)”
    username uid userPrincipalName
    idAttr uid DN Case-sensitive
    emailAttr mail userPrincipalName
    nameAttr givenName cn
  4. Update the groupSearch values as follows:
    key default set to notes
    baseDN ou=people,

    dc=vmware,dc=com

    DN of OU in AD under

    which security Groups are found

    Example: DC=ragazzilab,DC=com
    filter “(objectClass=

    posixGroup)”

    “(objectClass=group)”
    userAttr uid DN Case-Sensitive
    groupAttr memberUid “member:1.2.840.113556.1.4.1941:” This is necessary to search within nested groups in AD
    nameAttr cn cn

Other important Notes
When you create the oidc secret in the workload clusters running Gangway, the clientSecret value is base64-encoded, but the corresponding secret for the workload cluster in the staticClients section of the dex configmMap is decoded. This can be confusing since the decoded value is also randomly-generated.

Replicating images from DockerHub to Harbor

Harbor LogoI found the documentation for actually replicating images from DockerHub to a local Harbor instance to be missing.  So here’s what I’ve found:

Objective: Replicate the images for the Yelb sample application to local Harbor repo

Set-up and Prereqs

  1. A local Harbor instance – I’ll be using an Enterprise PKS foundation with Harbor 1.10
  2. An account for DockerHub

Steps

      1. Login to Harbor Web GUI as an administrator. Navigate to Administration/Registries
      2. Add Endpoint for local Harbor by clicking ‘New Endpoint’ and entering the following:
        • Provider: harbor
        • Name: local (or FQDN or whatever)
        • Description: optional
        • Endpoint URL: the actual URL for your harbor instance beginning with https and ending with :443
        • Access ID: username for an admin or user that at least has Project Admin permission to the target Projects/namespaces
        • Access Secret: Password for the account above
        • Verify Remote Cert: typically checked
      3. Add Endpoint for Docker Hub by clicking ‘New Endpoint’ and entering the following:
        • Provider: docker-hub
        • Name: dockerhub (or something equally profound)
        • Description: optional
        • Endpoint URL: pre-populated/li>
        • Access ID: username for your account at dockerhub
        • Access Secret: Password for the account above
        • Verify Remote Cert: typically checked

        Notice that this is for general dockerhub, not targeting a particular repo.

      4. Configure Replications for the Yelb Images
        You may create replications for several images at once using a variety of filters, but I’m going to create a replication rule for each image we need. I think this makes it easier to identify a problem, removes the risk of replicating too much and makes administration easier. Click ‘New Replication Rule‘ enter the following to create our first rule:

        • Name: yelb-db-0.5
        • Description: optional
        • Replication Mode: Pull-based (because we’re pulling the image from DockerHub)
        • Source registry: dockerhub
        • Source Registry Filter – Name: mreferre/yelb-db
        • Source Registry Filter – Tag: 0.5
        • Source Registry Filter – Resource: pre-populated
        • Destination Namespace: yelb (or whatever Project you want the images saved to)
        • Trigger Mode: Select ‘Manual’ for a one-time sync or select ‘Scheduled’ if you want to ensure the image is replicated periodically. Note that the schedule format is cron with seconds, so 0 0 23 * * 5 would trigger the replication to run every Friday at 23:00:00. Scheduled replication makes sense when the tag filter is ‘latest’ for example
        • Override: leave checked to overwrite the image if it already exists
        • Enable rule: leave checked to keep the rule enabled
      5. Add the remaining Replication Rules:
        Name Name Filter Tag Filter Dest Namespace
        yelb-ui-latest mreferre/yelb-ui latest yelb
        yelb-appserver-latest mreferre/yelb-appserver latest yelb
        redis-4.0.2 library/redis 4.0.2 yelb

        Note that redis is an official image, so we have to include library/

Logging into a Kubernetes cluster with an OIDC LDAP account

I confess, most of my experience with Kubernetes is with Pivotal Container Service (PKS) Enterprise.  PKS makes it rather easy to get started and I found that I took some tasks for granted.

In PKS Enterprise, one can use the pks cli to not only life-cycle clusters, but to obtain the credentials to the cluster and automatically update the kubeconfig with the account information.  So, administrative/operations users can run the command “pks get-credentials my-cluster” to have a kubeconfig updated with the authentication tokens and parameters to connect to my-cluster.

K8s OIDC using UAA on PKS

The PKS controller includes the User Account and Authentication (UAA) component, which is used to authenticate users into PKS Enterprise.  UAA can also be easily configured to connect to an existing LDAP service – this is the desired configuration in most organizations so that users account exist in one place (Active Directory in my example).

So, I found myself wondering “I don’t want to provide the PKS CLI to developers, so how can they connect kubectl to the cluster?”

Assumptions:

  • PKS Enterprise on vSphere (with or without NSX-T)
  • Active Directory
  • Developer user account belongs to the k8s-devs security group in AD

Prerequisite configuration:

  1. UAA on PKS configured a with UAA User Account Store: LDAP Server.  This links UAA to LDAP/Active Directory
  2. User Search Filter: userPrincipalName={0}  This means that users can login as user@domain.tld
  3. Group Search Filter: member={0} This ensures that AD groups may be used rather than specifying individual users
  4. Configure created clusters to use UAA as the OIDC provider: Enabled  This pre-configures the kubernetes API to use OpenID Connect with UAA. If not using PKS Enterprise, you’ll need to provide another OpenID Connect-Compliant endpoint (like Dex), link it to Active Directory and update the kubernetes cluster api manually to use the OpenID Authentication.

 

Operator: Create Role and RoleBinding:

While authentication is handled by OIDC/UAA/LDAP, Authorization must be configured on the cluster to provide access to resources via RBAC.  This is done by defining a Role (or clusterRole) that indicates what actions may be taken on what resources and a RoleBinding which links the Role to one or more “subjects”.

  1.  Authenticate to kubernetes cluster with an administrative account (for example, using PKS cli to connect)
  2.  Create yaml file for our Role and RoleBinding:
    kind: Role
    apiVersion: rbac.authorization.k8s.io/v1
    metadata:
      name: developers
    rules:
    - apiGroups: ["", "extensions", "apps"]
      resources: ["deployments", "replicasets", "pods"]
      verbs: ["get", "list", "watch", "create", "update", "patch", "delete"] 
      # You can also use ["*"]
    ---
    kind: RoleBinding
    apiVersion: rbac.authorization.k8s.io/v1beta1
    metadata:
      name: developer-dev-binding
    subjects:
    - kind: Group
      name: k8s-devs
      apiGroup: rbac.authorization.k8s.io
    roleRef:
      kind: Role
      name: developers
      apiGroup: rbac.authorization.k8s.io
    

    In the example above, we’re creating a Role named “developers”, granting access to the core, extensions and apps API groups and several actions against deployments, replicaSets and pods. Notice that developers in this role would have have access to secrets (for example)
    The example RoleBinding binds a group named “k8s-devs” to the developers role. Notice that we have not created the k8s-devs group in Kubernetes or UAA; it exists in Active Directory

  3. Use Kubectl to apply the yaml, creating the Role and Rolebinding in the targeted namespace

 

Creating the kubeconfig – the hard way

To get our developer connected with kubectl, they’ll need a kubeconfig with the authentication and connection details.  The Hard way steps are:

  1. Operator obtains the cluster’s certificate authority data.  This can be done via curl or by copying the value from the existing kubeconfig.
  2. Operator creates a template kubeconfig, replacing the value specified, then sends it to the developer user
    apiVersion: v1
    clusters:
    - cluster:
      certificate-authority-data: <OBTAINED IN STEP 1 >
      server: < FQDN to Master Node. >
      name: PROVIDED-BY-ADMIN
    contexts:
    - context:
        cluster: PROVIDED-BY-ADMIN
        user: PROVIDED-BY-USER
      name:  PROVIDED-BY-ADMIN
    current-context: PROVIDED-BY-ADMIN
    kind: Config
    preferences: {}
    users:
    - name: PROVIDED-BY-USER
      user:
        auth-provider:
          config:
            client-id: pks_cluster_client
            cluster_client_secret: ""
            id-token: PROVIDED-BY-USER
            idp-issuer-url: https://PROVIDED-BY-ADMIN:8443/oauth/token
            refresh-token:  PROVIDED-BY-USER
          name: oidc
  3. The developer user obtains the id_token and refresh_token from UAA, via a curl command
    curl 'https://PKS-API:8443/oauth/token' -k -XPOST -H
    'Accept: application/json' -d "client_id=pks_cluster_client&client_secret=""&grant_type=password&username=UAA-USERNAME&response_type=id_token" --data-urlencode password=UAA-PASSWORD
  4. The developer user updates the kubeconfig with the id_token and refresh token in the kubeconfig

 

Creating the kubeconfig – the easy way

Assuming the developer is using Mac or Linux…

  1. Install jq on developer workstation
  2. Download the get-pks-k8s-config.sh script, make it executable (chmod +x get-pks.k8s.config.sh)
  3. Execute the script (replace the params with your own)
    ./get-pks-k8s-config.sh --API=api.pks.mydomain.com \
    --CLUSTER=cl1.pks.mydomain.com \
    --USER=dev1@mydomain.com \
    --NS=scratch
    • API – FQDN to PKS Controller, for UAA
    • CLUSTER – FQDN to master node of k8s cluster
    • USER – userPrincipalName for the user
    • NS – Namespace to target; optional
  4. After entering the user’s password, the script will set the params in the kubeconfig and switch context automatically

Try it out
Our developer user should able to “see” pods but not namespaces for example:

dev1 can see pods but not namespaces

 

Creating the kubeconfig – the easiest way

  1. Provide the developer with the PKS CLI tool, remember we have not added them to any group or role with PKS admin permissions.
  2. Provide the developer with the PKS API endpoint FQDN and the cluster name
  3. The developer may run this command to generate the updated kubeconfig and set the current context
    pks get-kubeconfig CLUSTERNAME -a API -u USER -k

    • CLUSTERNAME is the name of the cluster
    • API – FQDN to PKS Controller
    • USER – userPrincipalName for the user
  4. You’ll be prompted for the account password. Once entered, the tool will fetch the user-specific kubeconfig.

Use PKS CLI to get the kubeconfig

 

Getting Started with CredHub in Concourse

First, some background – I promise to keep it short.  You should never have credentials in a public github repo.  Probably not good to have them in a private repo either.  At Pivotal, the github client is configured with credalert which complains when I try to push credentials to github.  I maintain compliance, I needed a way to update the stuff in the repo and have my credentials too.  Concourse supports a couple of AWS credential managers, Vault and Credhub.  Since CredHub is built-in to ops-manager-deployed BOSH director, we don’t have to spin anything else up.

The simplified diagram shows how this will work.  CredHub is on the BOSH director, so it’ll need to be reachable from the Concourse Web ATS service and anywhere the credhub cli will be used. If your BOSH director is behind a NAT, you may want to configure a DNAT, so it can be reached.

In this case, we’re using a “management/infrastructure” Operations Manager and BOSH director to deploy and manage concourse and minio.  The pipelines on concourse will be used to deploy and maintain other foundations in the environment.

Configure UAA

  1. Logon to the ops manager and navigate to status to record the IP address of the BOSH director.  If your BOSH director is behind a NAT, locate it’s DNAT instead.
  2. Navigate to the credentials tab.  We’re going to need the uaa_login_client_credentials password and the uaa_admin_client_credentials password.
  3. While here, save the ops manager root ca to your computer.  From the installation dashboard, click on your name in the upper right, select Settings.  Then click Advanced and Download Root CA.
  4. SSH into your ops manager:  ubuntu@<ops manager name or IP>
  5. Set uaac target

    uaac target https://<IP of BOSH director>:8443 –ca-cert /var/tempest/workspaces/default/root_ca_certificate

  6. Login to uaac – ok, this gets awkward

    uaac token owner get login -s <uaa_login_client_credentials>

    • Replace <uaa_login_client_credentials> with the value you saved
    • When prompted for a username enter admin
    • For password enter the uaa_admin_client_password value you saved
    • You should see “Successfully fetched token…”
  7. Create a uaac client for concourse to use with credhub

    uaac client add –name concourse-to-credhub –authorized-grant-types client_credentials –authorities credhub.read,credhub.write –access-token-validity 30 –secret MySecretPassword

    Please replace MySecretPassword with something else

  8. Create a uaac user for use with the CredHub cli

    uaac user add credhub –email credhub@whatever.com -p MySecretPassword

Try out Credhub cli

    1. Download and install the credhub cli.  On mac, you can use brew install credhub
    2. From a terminal/command line run this to point the cli to the credhub instance on the BOSH director:

      credhub api -s <IP of BOSH director>:8844 –ca-cert ./root_ca_certificate

      • Replace <IP of BOSH director> with the name or reachable IP of the director
      • root_ca_certificate is the root CA from ops manager you downloaded earlier
    3. Login to credhub:

      credhub login -u credhub -p MySecretPassword

      User and pass are from the User we added to uaa earlier

    4. Set a test value:

      credhub –type:value –name=/testval –value=hello

      Here’s we’re setting a key (aka credential) with the name /testval to the value “hello”. Note that all the things stored in credhub start with a slash and that there are several types of credentials that can be stored, the simplest being “value”

    5. Get our value:

      credhub –name /testval

      This will return the metadata for our key/credential

Configuring Concourse to use CredHub

Concourse TSA must be configured to look to credhub as a credential manager. I’m using BOSH-deployed concourse, so I’ll simply update the deployment manifest with the new params. if you’re using concourse via docker-compose, you’ll want to update the yml with the additional params as described here.

For concourse deployed via BOSH and using concouse-bosh-deployment, we’ll include the /operations/credhub.yml file and the additional params.  For me this looks like

bosh -e core deploy -d concourse concourse.yml \
-l ../versions.yml \
–vars-store cluster-creds.yml \
-o operations/static-web.yml \
-o operations/basic-auth.yml \
-o operations/scale.yml \
-o operations/privileged-http.yml \
-o operations/credhub.yml \
–var web_ip=192.168.100.205 \
–var external_url=http://concourse.ragazzilab.com \
–var network_name=INFRA \
–var web_vm_type=small.disk \
–var db_vm_type=small.disk \
–var azs=[BOSH] \
–var db_persistent_disk_type=10240 \
–var worker_vm_type=concourse.worker \
–var deployment_name=concourse \
–var local_user.username=myuser \
–var local_user.password=mypass \
–var web_instances=1 \
–var worker_instances=1 \
–var syslog_address=syslog.ragazzilab.com \
–var syslog_port=514 \
–var syslog_permitted_peer=syslog.ragazzilab.com \
–var credhub_url=”https://192.168.100.200:8844 ” \
–var credhub_client_id=concourse-to-credhub \
–var credhub_client_secret=MySecretPassword \
–var credhub_ca_cert=”$(cat root_ca_certificate)”

Test a pipeline

    1. Use credhub cli to create a value

      credhub set –name /concourse/main/hello-credhub/hello –value World

      Concourse has a default pattern for looking up interpolation values. It’s /concourse/<team name>/<pipeline name>/<key>

    2. Get the test pipeline from here.

      jobs:
      – name: hello-credhub
      plan:
      – do:
      – task: hello-credhub
      config:
      platform: linux
      image_resource:
      type: docker-image
      source:
      repository: ubuntu
      run:
      path: sh
      args:
      – -exc
      – |
      echo “Hello $WORLD_PARAM”
      params:
      WORLD_PARAM: ((hello))

    3. Use fly to set the test pipeline

      fly -t concourse login -c http://concourse -u myuser -p mypass -n main
      fly -t core sp -p hello-credhub -c hello-credhub.yml

    4. Run the test pipeline in concourse. If all goes well, it should say Hello World”

Using Helm and Dynamic PersistentVolumes with Multi-AZ PKS on vSphere

So, you’ve installed PKS and created a PKS cluster.  Excellent!  Now what?

We want to use helm charts to deploy applications.  Many of the charts use PersistentVolumes, so getting PVs set up is our first step.

There are a couple of complicating factors to be aware of when it comes to PVs in a multi-AZ/multi-vSphere-Cluster environment.  First, you probably have cluster-specific datastores – particularly if you are using Pivotal Ready Architecture and VSAN.  These datastores are not suitable for PersistentVolumes consumed by applications deployed to our Kubernetes cluster.  To work-around this, we’ll need to provide some shared block storage to each host in each cluster.  Probably the simplest way to do this is with an NFS share.

Prerequisites:

Common datastore; NFS share or iSCSI

In production, you’ll want a production-quality fault-tolerant solution for NFS or iSCSI, like Dell EMC Isilon. For this proof-of-concept, I’m going to use an existing NFS server, create a volume and share it to the hosts in the three vSphere clusters where the PKS workload VMs will run.  In this case, the NFS datastore is named “sharednfs” ’cause I’m creative like that.  Make sure that your hosts have adequate permissions to the share.  Using VMFS on iSCSI is supported, just be aware that you may need to cable-up additional NICs if yours are already consumed by N-VDS and/or VSAN.

Workstation Prep

We’ll need a handful of command-line tools, so make sure your workstation has the PKS CLI and Kubectl CLI from Pivotal and you’ve downloaded and extracted Helm.

PKS Cluster
We’ll want to provision a cluster using the PKS CLI tool.  This document assumes that your cluster was provisioned successfully, but nothing else has been done to it.  For my environment, I configured the “medium” plan to use 3 Masters and 3 Workers in all three AZs, then created the cluster with the command

pks create-cluster pks1cl1 --external-hostname cl1.pks1.lab13.myenv.lab --plan "medium" --num-nodes "3"


Logged-in
Make sure you’re logged into the Kubernetes cluster. In PKS, the easiest way to do this is via the PKS cli:

pks login -a api.pks1.lab13.myenv.lab -u pksadmin -p my_password --skip-ssl-validation
pks cluster pks1cl1
pks get-credentials pks1cl1
kubectl config use-context pks1cl1
kubectl get nodes -o wide

Where “pks1cl1″ is replaced by your cluster’s name,”api.pks1.lab13.myenv.lab” is replaced by the FQDN to your PKS API server, “pksadmin” is replaced by the username with admin rights to PKS and “my_password” is replaced with that account’s password.

Procedure:

  1. Create storageclass
    • Create storageclass spec yaml. Note that the file is named storageclass-nfs.yml and we’re naming the storage class itself “nfs”:
      kind: StorageClass
      apiVersion: storage.k8s.io/v1
      metadata:
        name: nfs
        annotations:
          storageclass.kubernetes.io/is-default-class: "true"
      provisioner: kubernetes.io/vsphere-volume
      parameters:
        diskformat: thin
        datastore: sharednfs
        fstype: ext3
      

    • Apply the yml with kubectl

      kubectl create -f storageclass-nfs.yml

    • Create a sample PVC (Persistent Volume Claim). Note that the file is names pvc-sample.yml, the PVC name is “pvc-sample” and uses the “nfs” storageclass we created above. This step is not absolutely necessary, but will help confirm we can use the storage.
      kind: PersistentVolumeClaim
      apiVersion: v1
      metadata:
        name: pvc-sample
        annotations:
          volume.beta.kubernetes.io/storage-class: nfs
      spec:
        accessModes:
          - ReadWriteOnce
        resources:
          requests:
            storage: 1Gi
        storageClassName: nfs
      
    • Apply the yml with kubectl

      kubectl create -f pvc-sample.yml


      If you’re watching vSphere closely, you’ll see a VMDK created in the kubevols folder of the NFS datastore

    • Check that the PVC was created with

      kubectl get pvc

      and

      kubectl describe pvc pvc-sample

    • Remove sample PVC with

      kubectl delete -f pvc-sample

  2. Configure Helm and Tiller
    • Create Service Account for tiller with
      apiVersion: v1
      kind: ServiceAccount
      metadata:
        name: tiller
        namespace: kube-system
      ---
      apiVersion: rbac.authorization.k8s.io/v1beta1
      kind: ClusterRoleBinding
      metadata:
        name: tiller
      roleRef:
        apiGroup: rbac.authorization.k8s.io
        kind: ClusterRole
        name: cluster-admin
      subjects:
        - kind: ServiceAccount
          name: tiller
          namespace: kube-system
      
    • Apply the service account yml with Kubectl

      kubectl create -f rbac-config.yml

    • Initialize helm and tiller with

      helm init --service-account tiller

    • Check that tiller is ready

      helm version


      Look for a version number for the version; note that it might take a few seconds for tiller in the cluster to get ready.

  3. Deploy sample helm chart
    • Update helm local chart repository. We do this so that we can be sure that helm can reach the public repo and to cache teh latest information to our local repo.

      helm repo update


      If this step results in a certificate error, you may have to add the cert to the trusted certificates on the workstation.

    • Install helm chart with ingress enabled. Here, I’ve selected the Dokuwiki app. The command below will enable ingress, so we can access it via routable IP and it will use the default storageclass we configured earlier.

      helm install --name dokuwiki \
      --set ingress.enabled="true",dokuwikiUsername=admin,dokuwikiPassword=password \
      stable/dokuwiki

      Edit – April 23 2019 – Passing the credentials in here makes connecting easier later.

    • Confirm that the app was deployed
      helm list
      kubectl get pods -n default
      kubectl get services -n default


      From the get services results, make a note of the external IP address – in the example above, it’s 192.13.6.73

    • Point a browser at the external address from the previous step and marvel at your success in deploying Dokuwiki via helm to Kubernetes!
      If you want to actually login to your Dokuwiki instance, first obtain the password for the user account with this command:

      kubectl get secret -n default dokuwiki-dokuwiki \
      -o jsonpath="{.data.dockuwiki-password}" | base64 --decode

      Then login with username “user” and that password.

       

      Edit – 04/23/19 – Login with the username and password you included in the helm install command

  4. Additional info
    • View Persistent Volume Claims with

      kubectl get pvc -n default


      This will list the PVCs and the volumes in the “default” namespace. Note the volume corresponds to the name of the VMDK on the datastore.

    • Load-Balancer
      Notice that since we are leveraging the NSX-T Container Networking Interface and enabled the ingress when we installed dokuwiki, a load-balancer in NSX-T was automatically created for us to point to the application.

This took me some time to figure out; had to weed through a lot of documentation – some of which contradicted itself and quite a bit of trial-and-error. I hope this helps save someone time later!

Automating PKS Upgrades

Last night, Pivotal announced new versions of PKS and Harbor, so I thought it’s time to simplify the upgrade process. Here is a concourse pipeline that essentially aggregates the upgrade-tile pipeline so that PKS and Harbor are upgraded in one go.

What it does:

  1. Runs on a schedule – you set the time and days it may run
  2. Downloads the latest version of PKS and Harbor from Pivnet- you set the major.minor version range
  3. Uploads the PKS and Harbor releases to your BOSH director
  4. Determines whether the new release is missing a stemcell, downloads it from PivNet and uploads it to BOSH director
  5. Stages the tiles/releases
  6. Applies changes

What you need:

  1. A working Concourse instance that is able to reach the Internet to pull down the binaries and repo
  2. The fly cli and credentials for your Concourse.
  3. A token from your PivNet account
  4. An instance of PKS 1.0.2 or 1.0.3 AND Harbor 1.4.x deployed on Ops Manager
  5. Credentials for your Ops Manager
  6. (optional) A token from your GitHub account

How to use the pipeline:

  1. Download params.yml and pipeline.yml from here.
  2. Edit the params.yml by replacing the values in double-parentheses with the actual value. Each line has a bit explaining what it’s expecting.  For example, ((ops_mgr_host)) becomes opsmgr.pcf1.domain.local
    • Remove the parens
    • If you have a GitHub Token, pop that value in, otherwise remove ((github_token))
    • The current pks_major_minor_version regex will get the latest 1.0.x.  If you want to pin it to a specific version, or when PKS 1.1.x is available, you can make those changes here.
    • The ops_mgr_usr and ops_mgr_pwd credentials are those you use to logon to Ops Manager itself.  Typically set when the Ops Manager OVA is deployed.
    • The schedule params should be adjusted to a convenient time to apply the upgrade.  Remember that in addition to the PKS Service being offline (it’s a singleton) during the upgrade, your Kubernetes clusters may be affected if you have the “Upgrade all Clusters” errand set to run in the PKS configuration, so schedule wisely!

  3. Open your cli and login to concourse with fly

    fly -t concourse login -c http://concourse.domain.local:8080 -u username -p password

  4. Set the new pipeline. Here, I’m naming the pipeline “PKS_Upgrade”. You’ll pass the pipeline.yml with the “-c” param and your edited params.yml with the “-l” param

    fly -t concourse sp -p PKS_Upgrade -c pipeline.yml -l params.yml

    Answer “y” to “Apply Configuration”…

  5. Unpause the pipeline so it can run when in the scheduled window

    fly -t concourse up -p PKS_Upgrade

  6. Login to the Concourse web to see our shiny new pipeline!

    If you don’t want to deal with the schedule and simply want it to upgrade on-demand, use the pipeline-nosched.yml instead of pipeline.yml, just be aware that when you unpause the pipeline, it’ll start doing its thing.  YMMV, but for me, it took about 8 minutes to complete the upgrade.

Behind the scenes
It’s not immediately obvious how the pipeline does what it does. When I first started out, I found it frustrating that there just isn’t much to the pipeline itself. To that end, I tried making pipelines that were entirely self-contained. This was good in that you can read the pipeline and see everything it’s doing; plus it can be made to run in an air-gapped environment. The downside is that there is no separation, one error in any task and you’ll have to edit the whole pipeline file.
As I learned a little more and poked around in what others were doing, it made sense to split the “tasks” out, keep them in a GitHub public repo and pull it down to run on-demand.

Pipelines generally have two main sections; resources and jobs.
Resources are objects that are used by jobs. In this case, the binary installation files, a zip of the GitHub repo and the schedule are resources.
Jobs are (essentially) made up of plans and plans have tasks.
Each task in most pipelines uses another source yml. This task.yml will indicate which image concourse should build a container from and what it should do on that container (typically, run a script). All of these task components are in the GitHub repo, so when the pipeline job runs, it clones the repo and runs the appropriate task script in a container built on an image pulled from dockerhub.

More info
I’ve got a several pipelines in the repo.   Some of them do what they’re supposed to. 🙂 Most of them are derived from others’ work, so many thanks to Pivotal Services and Sabha Parameswaran

PKS and NSX-T: I did everything wrong

I’ve fought with PKS and NSX-T for a month or so now. I’ll admit it: I did everything wrong, several times. One thing for certain, I know how NOT to configure it. So, now that I’ve finally gotten past my configuration issues, it makes sense to share the pain lessons learned.

  1. Set your expectations correctly. PKS is literally a 1.0 product right now. It’s getting a lot of attention and will make fantastic strides very quickly, but for now, it can be cumbersome and confusing. The documentation is still pretty raw. Similarly, NSX-T is very young. The docs are constantly referring you to the REST API instead of the GUI – this is fine of course, but is a turn-off for many. The GUI has many weird quirks. (when entering a tag, you’ll have to tab off of the value field after entering a value, since it is only checked onBlur)
  2. Use Chrome Incognito  NSX-T does not work in Firefox on Windows. It works in Chrome, but I had issues where the cache would problems (the web GUI would indicate that backup is not configured until I closed Chrome, cleared cache and logged in again)
  3. Do not use exclamation point in the NSX-T admin password Yep, learned that the hard way. Supposedly, this is resolved in PKS 1.0.3, but I’m not convinced as my environment did not wholly cooperate until I reset the admin password to something without an exclamation point in it
  4. Tag only one IP Pool with ncp/external I needed to build out several foundations on this environment and wanted to keep them in discrete IP space by created multiple “external IP Pools” and assigning each to its own foundation. Currently the nsx-cli.sh script that accompanies PKS with NSX-T only looks for the “ncp/external” tag on IP Pools, if more than one is found, it quits. I suppose you could work around this by forking the script and passing an additional “cluster” param, but I’m certain that the NSBU is working on something similar
  5. Do not take a snapshot of the NSX Manager This applies to NSX for vSphere and NSX-T, but I have made this mistake and it was costly. If your backup solution relies on snapshots (pretty much all of them do), be sure to exclude the NSX Manager and…
  6. Configure scheduled backups of NSX Manager I found the docs for this to be rather obtuse. Spent a while trying to configure a FileZilla SFTP or even IIS-FTP server until it finally dawned on me that it really is just FTP over SSH. So, the missing detail for me was that you’ll just need a linux machine with plenty of space that the NSX Manager can connect to – over SSH – and dump files to. I started with this procedure, but found that the permissions were too restrictive.
  7. Use concourse pipelines This was an opportunity for me to really dig into concourse pipelines and embrace what can be done. One moment of frustration came when PKS 1.0.3 was released and I discovered that the parameters for vSphere authentication had changed. In PKS 1.0 through 1.0.2, there was a single set of credentials to be used by PKS to communicate with vCenter Server. As of 1.0.3, this was split into credentials for master and credentials for workers. So, the pipeline needed a tweak in order to complete the install. I ended up putting in a conditional to check the release version, so the right params are populated. If interested, my pipelines can be found at https://github.com/BrianRagazzi/concourse-pipelines
  8. Count your Load-Balancers In NSX-T, the load-balancers can be considered a sort of empty appliance that Virtual Servers are attached to and can itself attach to a Logical Router. The load-balancers in-effect require pre-allocated resources that must come from an Edge Cluster. The “small” load-balancer consumes 2 CPU and 4GB RAM and the “Large” edge VM provides 8 CPU and 16GB RAM. So, a 2-node Edge Cluster can support up to FOUR active/standby Load-Balancers. This quickly becomes relevant when you realize that PKS creates a new load-balancer when a new K8s cluster is created. If you get errors in the diego databse with the ncp job when creating your fifth k8s cluster, you might need to add a few more edge nodes to the edge cluster.
  9. Configure your NAT rules as narrow as you can. I wasted a lot of time due to mis-configured NAT rules. The log data from provisioning failures did not point to NAT mis-configuration, so wild geese were chased.  Here’s what finally worked for me:
    Router Priority Action Source Destination Translated Description
    Tier1 PKS Management 512 No NAT [PKS Management CIDR] [PKS Service CIDR] Any No NAT between management and services
    [PKS Service CIDR] [PKS Management CIDR]
    1024 DNAT Any [External IP for Ops Manager] [Internal IP for Ops Manager] So Ops Manager is reachable
    [External IP for PKS Service] [Internal IP for PKS Service] (obtain from Status tab of PKS in Ops Manager) So PKS Service (and UAA) is reachable
    SNAT [Internal IP for PKS Service] Any [External IP for PKS Service] Return Traffic for PKS Service
    2048 [PKS Management CIDR] [Infrastructure CIDR] (vCenter Server, NSX Manager, DNS Servers) [External IP for Ops Manager] So PKS Management can reach infrastructure
    [PKS Management CIDR] [Additional Infrastructure] (NTP in this case) [External IP for Ops Manager]
    Tier1 PKS Services 512 No NAT [PKS Service CIDR] [PKS Management CIDR] Any No NAT between management and services
    [PKS Management CIDR] [PKS Service CIDR]
    1024 SNAT [PKS Service CIDR] [Infrastructure CIDR] (vCenter Server, NSX Manager, DNS Servers) [External IP] (not the same as Ops Manager and PKS Service, but in the same L3 network) So PKS Services can reach infrastructure
    [PKS Service CIDR] [Additional Infrastructure] (NTP in this case) [External IP]