Bufstream

Deploy Bufstream to Google Cloud

Enterprise

This product is in beta. For more information about using Bufstream in production, contact us.

This page walks you through installing Bufstream into your Google Cloud Platform (GCP) deployment by setting your Helm values and installing the provided Helm chart. See the GCP configuration page for defaults and recommendations about resources, replicas, storage, and scaling.

Data from your Bufstream cluster will never leave your network or report back to Buf.

Prerequisites

To deploy Bufstream on GCP, you need the following capabilities before you start:

  • A Kubernetes cluster (v1.27 or newer)
  • A Google Cloud Storage bucket
  • Helm (v3.12.0 or newer)

Deploy Bufstream

1. Authenticate helm

To get started, authenticate helm with the Bufstream OCI registry using the keyfile that was sent alongside this documentation. The keyfile should contain a base64 encoded string.

$ cat keyfile | helm registry login -u _json_key_base64 --password-stdin \
  https://us-docker.pkg.dev/buf-images-1/bufstream

2. Create a namespace

Create a Kubernetes namespace in the k8s cluster for the bufstream Helm chart to use:

$ kubectl create namespace bufstream

3. Configure Bufstream's Helm values

Bufstream is configured using Helm values that are passed to the bufstream Helm chart. To configure the values:

  1. Create a Helm values file named bufstream-values.yaml, which is required by the helm install command in step 5. This file can be in any location, but we recommend creating it in the same directory where you run the helm commands.

  2. Put the values from the steps below in the bufstream-values.yaml file. Skip to Install the Helm chart for a full example chart.

Configure object storage

Bufstream requires GCS object storage.

Bufstream attempts to acquire credentials from the environment using GKE Workload Identity Federation. To configure storage, set the following Helm values, filling in your GCS variables and service account annotations for the service account binding:

bufstream-values.yaml
storage:
  use: gcs
  gcs:
    bucket: "my-bucket-name"
bufstream:
  serviceAccount:
    annotations:
      iam.gke.io/gcp-service-account: my-gcp-service-account@my-gcp-project.iam.gserviceaccount.com

The k8s service account to be bound to the GCP service account is named bufstream-service-account.

Alternatively, you can use service account credentials.

  1. Create a k8s secret containing the service account credentials:
$ kubectl create secret --namespace bufstream generic bufstream-service-account-credentials \
  --from-file=credentials.json=<credentials.json>
  1. Set the secretName in the configuration:
bufstream-values.yaml
storage:
  use: gcs
  gcs:
    bucket: "my-bucket-name"
    secretName: "bufstream-service-account-credentials"

Configure etcd

Bufstream requires an etcd cluster. To set up an example deployment of etcd on Kubernetes, use the Bitnami etcd Helm chart with the following values:

$ helm install \
  --namespace bufstream \
  bufstream-etcd \
  oci://registry-1.docker.io/bitnamicharts/etcd \
  --version 10.2.4 \
  -f - <<EOF
replicaCount: 3
persistence:
  enabled: true
  size: 10Gi
  storageClass: "premium-rwo"
autoCompactionMode: periodic
autoCompactionRetention: 30s
removeMemberOnContainerTermination: false
resources:
  requests:
    cpu: 1
    memory: 1024Mi
  limits:
    memory: 1024Mi
auth:
  rbac:
    create: false
    enabled: false
  token:
    enabled: false
EOF

etcd is sensitive to disk performance, so we recommend using SSD-backed disks, such as the premium-rwo in the example above.

Then, configure Bufstream to connect to the etcd cluster:

bufstream-values.yaml
metadata:
  use: etcd
  etcd:
    # etcd addresses to connect to
    addresses:
      - host: "bufstream-etcd.bufstream.svc.cluster.local"
        port: 2379

Configure observability

The observability block is used to configure the collection and exporting of metrics and traces from your application, using Prometheus or OTLP:

bufstream-values.yaml
observability:
  # Optional, set the log level
  # logLevel: INFO
  # otlpEndpoint: "" # Optional, OTLP endpoint to send traces and metrics to..
  metrics:
    # Optional, can be either "NONE", "STDOUT", "HTTP", "HTTPS" or "PROMETHEUS"
    # When set to HTTP or HTTPS, will send OTLP metrics
    # When set to PROMETHEUS, will expose prometheus metrics for scraping on port 9090 under /metrics
    exporter: "NONE"
  tracing:
    # Optional, can be either "NONE", STDOUT", "HTTP", or "HTTPS"
    # When set to HTTP or HTTPS, will send OTLP metrics
    exporter: "NONE"
    # Optional, trace sampling ratio, defaults to 0.1
    # traceRatio: 0.1

4. Install the Helm chart

After following the steps above, the set of Helm values should be similar to the example below:

bufstream-values.yaml
storage:
  use: gcs
  gcs:
    bucket: "my-bucket-name"
bufstream:
  serviceAccount:
    annotations:
      iam.gke.io/gcp-service-account: my-gcp-service-account@my-gcp-project.iam.gserviceaccount.com
metadata:
  use: etcd
  etcd:
    # etcd addresses to connect to
    addresses:
      - host: "bufstream-etcd.bufstream.svc.cluster.local"
        port: 2379
observability:
  metrics:
    exporter: "PROMETHEUS"

Using the bufstream-values.yaml Helm values file, install the Helm chart for the cluster and set the correct Bufstream version:

$ helm install bufstream oci://us-docker.pkg.dev/buf-images-1/bufstream/charts/bufstream \
  --version "0.x.x" \
  --namespace=bufstream \
  --values bufstream-values.yaml

If you change any configurations in the bufstream-values.yaml file, re-run the command.