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rancher/opni: Observability + AIOps for Kubernetes

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

rancher/opni

开源软件地址(OpenSource Url):

https://github.com/rancher/opni

开源编程语言(OpenSource Language):

Go 96.6%

开源软件介绍(OpenSource Introduction):

Opni = AIOps for Kubernetes + Observability Tools

Opni currently features log anomaly detection for Kubernetes.

What does Opni give me?
  • AI generated insights on your cluster's log messages
    • Control Plane & etcd insights
      • Pretrained models maintained by Rancher Labs
  • Every log message sent to Opni will be marked as:
    • Normal
    • Suspicious - Operators may want to investigate
    • Anomalous - Operators definitely should investigate
  • Opensearch + Opensearch Dashboards
    • Opni dashboard to consume log insights & explore logs

alt text


Deprecation Notice

  • GPU Learning is temporarily disabled in the v0.4.0 release as Opni moves to a multicluster architecture. This will be returning in a future release
  • The v1beta1 API has been deprecated in this release. Please migrate to v1beta2.
  • The UI and Insights services, which were experimental, have been removed

Getting started with Opni

Full Install Opni in your Kubernetes cluster:

Manifests install (recommended):

Prerequisites:

  • Cert manager installed. This can be installed with the following command:
    kubectl apply -f https://github.com/cert-manager/cert-manager/releases/download/v1.7.2/cert-manager.yaml
  • Opni Gateway installed - see the Main Cluster docs for Opni Monitoring

Installation:

  1. All clusters (both the main cluster and clusters to collect logs from) the manifests in deploy/manifests in order from 00 - 10.
  2. Deploy an Opensearch cluster e.g (node this cluster will need to be exposed via a LoadBalancer or Ingress to allow logs to be indexed)
    apiVersion: opensearch.opster.io/v1
    kind: OpenSearchCluster
    metadata:
      name: opni
      namespace: opni-cluster-system
    spec:
      # Add fields here
      general:
        httpPort: 9200
        vendor: opensearch
        version: 1.2.3
        serviceName: os-svc
        setVMMaxMapCount: true
      confMgmt:
        autoScaler: false
        monitoring: false
      dashboards:
        enable: true
        version: 1.2.0
        replicas: 1
      nodePools:
      - component: master
        replicas: 3
        diskSize: 32
        resources:
          requests:
            cpu: 500m
            memory: 1Gi
          limits:
            memory: 1Gi
        roles:
        - master
        persistence:
          emptyDir: {}
      - component: nodes
        replicas: 2
        diskSize: 32
        resources:
          requests:
            cpu: 500m
            memory: 2Gi
          limits:
            memory: 2Gi
        jvm: "-Xmx1G -Xms1G"
        roles:
        - data
        persistence:
          emptyDir: {}
  3. Bind Opni to the Opensearch cluster:
    apiVersion: opni.io/v1beta2
    kind: MulticlusterRoleBinding
    metadata:
      name: opni-logging
      namespace: opni-cluster-system
    spec:
      opensearch:
        name: opni
        namespace: opni-cluster-system
      opensearchExternalURL: https://external.opensearch.url
  4. Deploy the Opni pretrained Kubernetes model
    apiVersion: opni.io/v1beta2
    kind: PretrainedModel
    metadata:
      name: control-plane
      namespace: opni-cluster-system
    spec:
      source:
        http:
          url: "https://opni-public.s3.us-east-2.amazonaws.com/pretrain-models/control-plane-model-v0.4.0.zip"
      hyperparameters:
        modelThreshold: "0.6"
        minLogTokens: 1
        isControlPlane: "true"
  5. Deploy Opni AI services
    apiVersion: opni.io/v1beta2
    kind: OpniCluster
    metadata:
      name: demo
      namespace: opni-cluster-system
    spec:
      version: v0.4.0
      deployLogCollector: false
      services:
        gpuController:
          enabled: false
        inference:
          pretrainedModels:
          - name: control-plane
      opensearch:
        externalOpensearch:
          name: opni
          namespace: opni-cluster-system
        enableLogIndexManagement: false
      s3:
        internal: {}
      nats:
        authMethod: nkey
  6. Add additional Logging clusters from the Opni Gateway UI

Consume insights from the Opni Dashboard in Opensearch Dashboards. You will need to expose the Dashboards service or port forward to do this.


Watch a demo of Opni:


What's next?

  • v0.1.1 (Released) allows you to view Opni's log anomaly insights only on a demo environment created on a VM
  • v0.1.2 (Released) allows you install Opni into your existing Kubernetes cluster and consume log insights from it
  • v0.1.3 (August 2021) - only 1 GPU required, changes to the Opni operator, log anomaly optimizations
  • v0.2.0 (Fall 2021) will introduce a custom UI, AI applied to metrics, kubernetes events, audit logs, and more!

alt text


License

Copyright (c) 2014-2020 Rancher Labs, Inc.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.


Build codecov Go Report Card Maintainability


Opni Monitoring is an open-source multi-cluster monitoring system. It ingests Prometheus metrics from any number of Kubernetes clusters and provides a centralized observability plane for your infrastructure. Use Opni Monitoring to visualize metrics from all your clusters at once, and give every user their own customized view using granular access control.

Powered by Open-Source

Opni Monitoring is completely free Apache-licensed open-source software. It builds upon existing, ubiquitous open-source systems - Prometheus, Grafana, and Cortex - and extends them with a number of powerful enterprise features typically only found in SaaS platforms and other proprietery solutions.


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