Nessie on Kubernetes¶

The easiest and recommended way to get started with Nessie on Kubernetes is to use the Helm chart described below.

For more information on Helm and Helm charts, see the Helm docs.

Installing the Helm chart¶

Add the Nessie Helm repo:

helm repo add nessie-helm https://charts.projectnessie.org
helm repo update

Install the Helm chart in the nessie-ns namespace (create the namespace first if it doesn’t exist), and name the release nessie:

helm install -n nessie-ns nessie nessie-helm/nessie

Additional docs (incl. all configuration settings) can be found in the Nessie Helm chart docs hosted in Nessie’s GitHub repository.

Customizing the Helm chart¶

For example, to install the Helm chart with a predefined image, simply do this:

helm install -n nessie-ns nessie nessie-helm/nessie \
    --set image.repository=ghcr.io/projectnessie/nessie \
    --set image.tag=0.100.2

It’s also useful to create more than one replica of the Nessie server. To do this, simply set the replicaCount value:

helm install -n nessie-ns nessie nessie-helm/nessie --set replicaCount=3

Configuring database authentication¶

Nessie supports a variety of version stores, each of which requires different configuration. For example, the JDBC version store requires a JDBC URL, username and password, while the DynamoDB version store requires AWS credentials.

All database authentication options must be provided as Kubernetes secrets, and these must be created before installing the Helm chart.

Providing secrets for JDBC datastores¶

• Make sure you have a Secret in the following form (assuming PostgreSQL, but the same applies to other JDBC datastores):

> cat $PWD/postgres-creds
postgres_username=YOUR_USERNAME
postgres_password=YOUR_PASSWORD

• Create the secret from the given file:

kubectl create secret generic postgres-creds --from-env-file="$PWD/postgres-creds"

• The postgres-creds secret will now be picked up when you use JDBC as the version store when installing Nessie (see below).

Providing secrets for MongoDB¶

• Providing secrets for MongoDB is strongly recommended, but not enforced.
• Make sure you have a Secret in the following form:

> cat $PWD/mongodb-creds
mongodb_username=YOUR_USERNAME
mongodb_password=YOUR_PASSWORD

• Create the secret from the given file:

kubectl create secret generic mongodb-creds --from-env-file="$PWD/mongodb-creds"

• The mongodb-creds secret will now be picked up when you use MONGODB as the version store when installing Nessie (see below).

Providing secrets for Cassandra¶

• Providing secrets for Cassandra is strongly recommended, but not enforced.
• Make sure you have a Secret in the following form:

> cat $PWD/cassandra-creds
cassandra_username=YOUR_USERNAME
cassandra_password=YOUR_PASSWORD

• Create the secret from the given file:

kubectl create secret generic cassandra-creds --from-env-file="$PWD/cassandra-creds"

• The cassandra-creds secret will now be picked up when you use CASSANDRA as the version store when installing Nessie (see below).

Providing secrets for DynamoDB¶

• Make sure you have a Secret in the following form:

> cat $PWD/awscreds
aws_access_key_id=YOURACCESSKEYDATA
aws_secret_access_key=YOURSECRETKEYDATA

• Create the secret from the given file:

kubectl create secret generic awscreds --from-env-file="$PWD/awscreds"

• The awscreds secret will now be picked up when you use DYNAMODB as the version store when installing Nessie (see below).

Providing secrets for Bigtable¶

A secret is not required for Bigtable. If one is present, it is assumed that authentication will use a service account JSON key. See this page for details on how to create a service account key.

If no secret is used, then Workload Identity usage is assumed instead; in this case, make sure that the pod’s service account has been granted access to BigTable. See this page for details on how to create a suitable service account.

Important: when using Workload Identity, unless the cluster is in Autopilot mode, it is also required to add the following nodeSelector label:

iam.gke.io/gke-metadata-server-enabled: "true"

This is not done automatically by the chart because this selector would be invalid for Autopilot clusters.

• Make sure you have a Secret in the following form:

> cat $PWD/bigtable-creds
sa_json=YOUR_SA_JSON_KEY

• Create the secret from the given file:

kubectl create secret generic bigtable-creds --from-env-file="$PWD/bigtable-creds"

• The bigtable-creds secret will now be picked up when you use BIGTABLE as the version store when installing Nessie (see below).

Configuring the version store¶

Configuring JDBC version stores¶

Let’s assume that we want to use a PostgreSQL service, that the database is called nessiedb and the schema nessie. The PostgreSQL service is running at postgres:5432 in the same namespace.

Next, we need to configure the Helm chart to use the JDBC version store type and to pull the database credentials from the secret that was created previously. We can do this by creating a values.yaml file with the following content:

versionStoreType: JDBC
jdbc:
  jdbcUrl: jdbc:postgresql://postgres:5432/nessiedb?currentSchema=nessie
  secret:
    name: postgres-creds
    username: postgres_username
    password: postgres_password

Let’s now assume that we are using MariaDB or MySQL instead of PostgreSQL. These backends do not support schemas, thus only the database name needs to be provided. MariaDB and MySQL share the same JDBC driver (the MariaDB one), so the JDBC URL is roughly the same for both; a minimal JDBC URL for these backends would look like this:

For MariaDB:

jdbcUrl: jdbc:mariadb://mariadb:3306/nessiedb

For MySQL:

jdbcUrl: jdbc:mysql://mysql:3306/nessiedb

In the above examples, mariadb and mysql are the service names of the MariaDB and MySQL services, respectively. The database name is nessiedb.

Then, we can install the Helm chart with the following values:

helm install -n nessie-ns nessie nessie-helm/nessie -f values.yaml

Configuring MongoDB version stores¶

Let’s assume that we want to use a MongoDB database. The database must be created beforehand, as the Helm chart will not create it for you. Let’s assume that the database is called nessie. The MongoDB service is running at mongodb:27017 in the same namespace.

Then, we need to configure the Helm chart to use the MONGODB version store type and to pull the database credentials from the secret that was created previously. We can do this by creating a values.yaml file with the following content:

versionStoreType: MONGODB
mongodb:
  database: nessie
  connectionString: mongodb://mongodb:27017
  secret:
    name: mongodb-creds
    username: mongodb_username
    password: mongodb_password

Configuring DynamoDB version stores¶

Let’s assume that we want to use a DynamoDB database in the us-west-2 region. The tables will be created automatically by Nessie if they don’t exist.

Then, we need to configure the Helm chart to use the DYNAMODB version store type and to pull the AWS credentials from the secret that was created previously. We can do this by creating a values.yaml file with the following content:

versionStoreType: DYNAMODB
dynamodb:
  region: us-west-2
  secret:
    name: awscreds
    awsAccessKeyId: aws_access_key_id
    awsSecretAccessKey: aws_secret_access_key

Configuring Bigtable version stores¶

Let’s assume that we want to use a Bigtable instance named nessie-bigtable in the prod-us project, using the default profile id. The tables will be created automatically by Nessie if they don’t exist, but the instance must be created and configured beforehand.

Then, we need to configure the Helm chart to use the BIGTABLE version store type and to pull the Bigtable credentials from the secret that was created previously. We can do this by creating a values.yaml file with the following content:

versionStoreType: BIGTABLE
bigtable:
  projectId: prod-us
  instanceId: nessie-bigtable
  appProfileId: default

The above will use Workload Identity. If you are using instead a service account JSON key as described above, you can also specify it in the values.yaml file:

versionStoreType: BIGTABLE
bigtable:
  projectId: prod-us
  instanceId: nessie-bigtable
  appProfileId: default
  secret:
    name: bigtable-creds
    key: sa_json

Configuring other datasource types¶

Other datasource types are supported, and most of them have mandatory and optional configuration options. Again, check the Nessie Helm chart docs for more information.

Uninstalling the Helm chart¶

To uninstall the Helm chart and delete the nessie release from the nessie-ns namespace:

helm uninstall -n nessie-ns nessie

Troubleshooting¶

The first step in troubleshooting a Nessie Kubernetes deployment is to check the logs of the Nessie server pod. You can do this by running:

kubectl logs -n <namespace> <pod>

You can also check the status of the pod:

kubectl describe pod -n <namespace> <pod>

It’s also possible to get a terminal into the Nessie pod’s main container:

kubectl exec -it -n <namespace> <pod> -- /bin/bash

But beware that the container does not have some tools installed, e.g. curl, wget, etc. are not present.

Troubleshooting connectivity¶

Connectivity issues require more powerful tools. One useful technique is to run an ephemeral container in the same pod as the Nessie server, which shares the same network namespace and can access the Nessie server as localhost. This can be done with the kubectl debug command:

kubectl debug -it -n <namespace> <pod> --image=nicolaka/netshoot --target=nessie --share-processes

The above example uses the nicolaka/netshoot image, which contains a lot of useful tools for debugging. See the nicolaka/netshoot Docker Hub page for more information. The command should give you a shell in the Nessie pod, where you can use curl, wget, netstat, dig, tcpdump, etc.

For example, once you get a shell in the debug container, you can:

• Check which processes are running in the Nessie pod with ps aux;
• Check Nessie’s management API on port 9000 to see if the server is healthy:

  curl http://127.0.0.1:9000/q/health
  

• Check the Nessie server’s API endpoint on port 19120:

  curl http://127.0.0.1:19120/api/v2/config
  

Advanced Nessie JVM troubleshooting¶

JVM issues such as memory leaks, high CPU usage, etc. can be debugged using JVM tools.

The Nessie container ships with few utilities, but it does have jcmd, a command-line utility for interacting with the JVM, installed.

First, get a shell in the Nessie container:

kubectl exec -it -n <namespace> <pod> -c nessie -- /bin/bash

Then, you can use jcmd to capture a thread dump, heap dump, etc.:

jcmd 1 Thread.print
jcmd 1 GC.heap_dump /tmp/heapdump.hprof

If you need other JVM tools, such as jfr or async-profiler, a more complex setup is required.

First, restart the Nessie pod with some extra JVM options. The most useful option to add is the --XX:+StartAttachListener JVM option; without it, the JVM will not allow attaching to it and tools like jcmd will fail.

This can be done by modifying the pod template spec in the deployment spec, and adding/updating the JAVA_OPTS_APPEND environment variable:

java_opts_append=$(kubectl get deployment -n <namespace> <deployment> -o jsonpath='{.spec.template.spec.containers[0].env[?(@.name=="JAVA_OPTS_APPEND")].value}')
kubectl set env -n <namespace> deployment <deployment> JAVA_OPTS_APPEND="$java_opts_append -XX:+StartAttachListener"

Once the target pod is ready to be attached, you will need an image with the required tools. One example is the lightrun-platform/koolkits/koolkit-jvm image, which contains a JVM-based toolset for debugging Java applications:

kubectl debug -it -n <namespace> <pod> --image=lightruncom/koolkits:jvm --target=nessie --share-processes

See the JVM KoolKits page for more information. Beware that the image is quite large, so it may take some time to download.

A few preliminary commands may need to be executed prior to be able to use the tools, for example if users and groups don’t match: the Nessie process runs as UID 10000 and GID 10001 by default, while in many debug containers, the running user is root (UID 0). If that is the case, you won’t be able to attach to the Nessie JVM. You can solve the problem by creating a new user with the same UID and GID as the Nessie process. In the case of JVM KoolKits, you also need to copy a few files before switching to the new user; here is the whole snippet to run:

addgroup --gid 10001 debug
adduser --home /home/debug --uid 10000 --gid 10001 --disabled-password --gecos "" debug
cp -Rf /root/.sdkman/ /home/debug/ && chown -R 10000:10001 /home/debug/.sdkman
cp /root/.bashrc /home/debug/ && chown 10000:10001 /home/debug/.bashrc 
su - debug

After running the above commands, you should be able to use jps, jcmd, jmap, etc. as well as other tools like jfr (Java Flight Recorder), etc. For example, you can use JFR to record a profile for 30 seconds:

jcmd 1 JFR.start duration=30s filename=/tmp/profile.jfr

Note that the profile will be saved in the Nessie container, not the debug container. You can copy it to your local machine with kubectl cp:

kubectl cp -n <namespace> <pod>:/tmp/profile.jfr profile.jfr

Remote debugging¶

If the above doesn’t help, you can also enable remote debugging, by attaching to the Nessie pod with a remote debugger.

Again, this will require restarting the Nessie pod with some extra JVM options. The most useful option to add is the -agentlib:jdwp JVM option, which enables the Java Debug Wire Protocol (JDWP).

This can be done more easily done by simply setting the JAVA_DEBUG and JAVA_DEBUG_PORT environment variables in the deployment spec:

kubectl set env -n <namespace> deployment <deployment> JAVA_DEBUG="true" JAVA_DEBUG_PORT="*:5005"

Once the pod is ready to be debugged, you must forward the 5005 port to your local machine:

kubectl port-forward -n <namespace> <pod> 5005:5005

Then you can attach to the Nessie server with your favorite IDE or command-line debugger.