webb.ai
Generated on 13 Nov 2023 from the webb.ai catalog page
Webb.ai is a continuous automated root cause analysis(RCA) platform for Kubernetes. It empowers SREs, devops and engineers to debug application and infrastructure issues in Kubernetes much more efficiently. The Webb.ai RCA functionality includes the following:
- track changes made in the Kubernetes cluster
- understand the potential impact of changes
- establish causality between changes and low level Kubernetes events and changes made by Kubernetes controllers(e.g., HPA, VPA, Keda)
- establish relevance between changes and issues through webb.ai’s LLM-based debugging agent
The Webb.ai RCA solution includes:
- resource collector: agent running in your Kubernetes cluster as a single pod to collect changes, K8s metadata, and events.
- traffic collector: agent running in your Kubernetes cluster as a DaemonSet that automatically collects telemetry data based on eBPF.
- web console: web interface that includes the full functionality of webb.ai.
Notes:
- Webb.ai is currently in early access. After installing the helm chart in your Kubernetes cluster, please sign up at https://app.webb.ai/ to get access to Webb’s web console to get full functionality.
- DigitalOcean is using Helm v3 to deploy webb.ai to your DOKS cluster.
Please follow the official documentation to read and learn more about webb.ai.
Software Included
Package | Version | License |
---|
Creating an App using the Control Panel
Click the Deploy to DigitalOcean button to install a Kubernetes 1-Click Application. If you aren’t logged in, this link will prompt you to log in with your DigitalOcean account.
Creating an App using the API
In addition to creating webb.ai using the control panel, you can also use the DigitalOcean API. As an example, to create a 3 node DigitalOcean Kubernetes cluster made up of Basic Droplets in the SFO2 region, you can use the following doctl
command. You need to authenticate with doctl
with your API access token) and replace the $CLUSTER_NAME
variable with the chosen name for your cluster in the command below.
doctl kubernetes clusters create --size s-4vcpu-8gb $CLUSTER_NAME --1-clicks webb.ai
Getting Started After Deploying webb.ai
How to Connect to Your Cluster
Follow these instructions to connect to your cluster with kubectl
and doctl
.
Confirming that Webb.ai is Running
First, check if the Helm installation was successful by running the command below:
helm ls -n webbai
The output should look similar to the following:
NAME NAMESPACE REVISION UPDATED STATUS CHART APP VERSION
webbai-agent webbai 1 2023-10-13 15:52:17.259511 -0700 PDT deployed webbai-agent-0.1.5 v0.4.8
The STATUS
column value should be deployed
.
Next, verify if webb.ai pods are up and running:
kubectl get pods -n webbai
The output should look similar to the following:
NAME READY STATUS RESTARTS AGE
webbai-resource-collector-854bc5b745-r2k74 1/1 Running 0 4d20h
webbai-traffic-collector-fkn9t 1/1 Running 0 4d20h
All pods should be in a READY
state with a STATUS
of Running
.
Tweaking Helm Chart Values
The webb.ai stack provides some custom values to start with. See the values file from the main GitHub repository for more information.
You can inspect all the available options, as well as the default values for the webb.ai Helm chart by running the following command:
helm show values webb.ai/webbai-agent
After customizing the Helm values file (values.yml
), you can apply the changes via the helm upgrade
command, as shown below:
helm upgrade webbai-agent webb.ai/webbai-agent \
--namespace webbai \
--values values.yml
Exploring the webb.ai web console
Please refer to https://github.com/digitalocean/marketplace-kubernetes/blob/master/stacks/webb.ai/README.md#exploring-the-webbai-web-console