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Monitor your Kubernetes Cluster
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======
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This article originally appeared on [Kevin Monroe's blog][1]
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Keeping an eye on logs and metrics is a necessary evil for cluster admins. The benefits are clear: metrics help you set reasonable performance goals, while log analysis can uncover issues that impact your workloads. The hard part, however, is getting a slew of applications to work together in a useful monitoring solution.
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In this post, I'll cover monitoring a Kubernetes cluster with [Graylog][2] (for logging) and [Prometheus][3] (for metrics). Of course that's not just wiring 3 things together. In fact, it'll end up looking like this:
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![][4]
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As you know, Kubernetes isn't just one thing -- it's a system of masters, workers, networking bits, etc(d). Similarly, Graylog comes with a supporting cast (apache2, mongodb, etc), as does Prometheus (telegraf, grafana, etc). Connecting the dots in a deployment like this may seem daunting, but the right tools can make all the difference.
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I'll walk through this using [conjure-up][5] and the [Canonical Distribution of Kubernetes][6] (CDK). I find the conjure-up interface really helpful for deploying big software, but I know some of you hate GUIs and TUIs and probably other UIs too. For those folks, I'll do the same deployment again from the command line.
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Before we jump in, note that Graylog and Prometheus will be deployed alongside Kubernetes and not in the cluster itself. Things like the Kubernetes Dashboard and Heapster are excellent sources of information from within a running cluster, but my objective is to provide a mechanism for log/metric analysis whether the cluster is running or not.
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### The Walk Through
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First things first, install conjure-up if you don't already have it. On Linux, that's simply:
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```
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sudo snap install conjure-up --classic
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```
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There's also a brew package for macOS users:
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```
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brew install conjure-up
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```
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You'll need at least version 2.5.2 to take advantage of the recent CDK spell additions, so be sure to `sudo snap refresh conjure-up` or `brew update && brew upgrade conjure-up` if you have an older version installed.
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Once installed, run it:
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```
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conjure-up
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```
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![][7]
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You'll be presented with a list of various spells. Select CDK and press `Enter`.
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![][8]
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At this point, you'll see additional components that are available for the CDK spell. We're interested in Graylog and Prometheus, so check both of those and hit `Continue`.
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You'll be guided through various cloud choices to determine where you want your cluster to live. After that, you'll see options for post-deployment steps, followed by a review screen that lets you see what is about to be deployed:
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![][9]
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In addition to the typical K8s-related applications (etcd, flannel, load-balancer, master, and workers), you'll see additional applications related to our logging and metric selections.
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The Graylog stack includes the following:
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* apache2: reverse proxy for the graylog web interface
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* elasticsearch: document database for the logs
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* filebeat: forwards logs from K8s master/workers to graylog
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* graylog: provides an api for log collection and an interface for analysis
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* mongodb: database for graylog metadata
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The Prometheus stack includes the following:
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* grafana: web interface for metric-related dashboards
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* prometheus: metric collector and time series database
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* telegraf: sends host metrics to prometheus
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You can fine tune the deployment from this review screen, but the defaults will suite our needs. Click `Deploy all Remaining Applications` to get things going.
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The deployment will take a few minutes to settle as machines are brought online and applications are configured in your cloud. Once complete, conjure-up will show a summary screen that includes links to various interesting endpoints for you to browse:
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![][10]
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#### Exploring Logs
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Now that Graylog has been deployed and configured, let's take a look at some of the data we're gathering. By default, the filebeat application will send both syslog and container log events to graylog (that's `/var/log/*.log` and `/var/log/containers/*.log` from the kubernetes master and workers).
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Grab the apache2 address and graylog admin password as follows:
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```
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juju status --format yaml apache2/0 | grep public-address
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public-address: <your-apache2-ip>
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juju run-action --wait graylog/0 show-admin-password
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admin-password: <your-graylog-password>
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```
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Browse to `http://<your-apache2-ip>` and login with admin as the username and <your-graylog-password> as the password. **Note:** if the interface is not immediately available, please wait as the reverse proxy configuration may take up to 5 minutes to complete.
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Once logged in, head to the `Sources` tab to get an overview of the logs collected from our K8s master and workers:
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![][11]
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Drill into those logs by clicking the `System / Inputs` tab and selecting `Show received messages` for the filebeat input:
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![][12]
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From here, you may want to play around with various filters or setup Graylog dashboards to help identify the events that are most important to you. Check out the [Graylog Dashboard][13] docs for details on customizing your view.
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#### Exploring Metrics
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Our deployment exposes two types of metrics through our grafana dashboards: system metrics include things like cpu/memory/disk utilization for the K8s master and worker machines, and cluster metrics include container-level data scraped from the K8s cAdvisor endpoints.
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Grab the grafana address and admin password as follows:
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```
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juju status --format yaml grafana/0 | grep public-address
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public-address: <your-grafana-ip>
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juju run-action --wait grafana/0 get-admin-password
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password: <your-grafana-password>
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```
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Browse to `http://<your-grafana-ip>:3000` and login with admin as the username and <your-grafana-password> as the password. Once logged in, check out the cluster metric dashboard by clicking the `Home` drop-down box and selecting `Kubernetes Metrics (via Prometheus)`:
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![][14]
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We can also check out the system metrics of our K8s host machines by switching the drop-down box to `Node Metrics (via Telegraf) `
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![][15]
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### The Other Way
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As alluded to in the intro, I prefer the wizard-y feel of conjure-up to guide me through complex software deployments like Kubernetes. Now that we've seen the conjure-up way, some of you may want to see a command line approach to achieve the same results. Still others may have deployed CDK previously and want to extend it with the Graylog/Prometheus components described above. Regardless of why you've read this far, I've got you covered.
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The tool that underpins conjure-up is [Juju][16]. Everything that the CDK spell did behind the scenes can be done on the command line with Juju. Let's step through how that works.
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**Starting From Scratch**
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If you're on Linux, install Juju like this:
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```
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sudo snap install juju --classic
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```
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For macOS, Juju is available from brew:
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```
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brew install juju
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```
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Now setup a controller for your preferred cloud. You may be prompted for any required cloud credentials:
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```
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juju bootstrap
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```
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We then need to deploy the base CDK bundle:
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```
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juju deploy canonical-kubernetes
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```
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**Starting From CDK**
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With our Kubernetes cluster deployed, we need to add all the applications required for Graylog and Prometheus:
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```
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## deploy graylog-related applications
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juju deploy xenial/apache2
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juju deploy xenial/elasticsearch
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juju deploy xenial/filebeat
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juju deploy xenial/graylog
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juju deploy xenial/mongodb
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```
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```
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## deploy prometheus-related applications
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juju deploy xenial/grafana
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juju deploy xenial/prometheus
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juju deploy xenial/telegraf
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```
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Now that the software is deployed, connect them together so they can communicate:
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```
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## relate graylog applications
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juju relate apache2:reverseproxy graylog:website
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juju relate graylog:elasticsearch elasticsearch:client
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juju relate graylog:mongodb mongodb:database
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juju relate filebeat:beats-host kubernetes-master:juju-info
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juju relate filebeat:beats-host kubernetes-worker:jujuu-info
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```
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```
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## relate prometheus applications
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juju relate prometheus:grafana-source grafana:grafana-source
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juju relate telegraf:prometheus-client prometheus:target
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juju relate kubernetes-master:juju-info telegraf:juju-info
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juju relate kubernetes-worker:juju-info telegraf:juju-info
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```
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At this point, all the applications can communicate with each other, but we have a bit more configuration to do (e.g., setting up the apache2 reverse proxy, telling prometheus how to scrape k8s, importing our grafana dashboards, etc):
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```
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## configure graylog applications
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juju config apache2 enable_modules="headers proxy_html proxy_http"
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juju config apache2 vhost_http_template="$(base64 <vhost-tmpl>)"
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juju config elasticsearch firewall_enabled="false"
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juju config filebeat \
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logpath="/var/log/*.log /var/log/containers/*.log"
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juju config filebeat logstash_hosts="<graylog-ip>:5044"
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juju config graylog elasticsearch_cluster_name="<es-cluster>"
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```
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```
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## configure prometheus applications
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juju config prometheus scrape-jobs="<scraper-yaml>"
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juju run-action --wait grafana/0 import-dashboard \
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dashboard="$(base64 <dashboard-json>)"
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```
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Some of the above steps need values specific to your deployment. You can get these in the same way that conjure-up does:
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* <vhost-tmpl>: fetch our sample [template][17] from github
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* <graylog-ip>: `juju run --unit graylog/0 'unit-get private-address'`
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* <es-cluster>: `juju config elasticsearch cluster-name`
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* <scraper-yaml>: fetch our sample [scraper][18] from github; [substitute][19]appropriate values for `[K8S_PASSWORD][20]` and `[K8S_API_ENDPOINT][21]`
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* <dashboard-json>: fetch our [host][22] and [k8s][23] dashboards from github
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Finally, you'll want to expose the apache2 and grafana applications to make their web interfaces accessible:
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```
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## expose relevant endpoints
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juju expose apache2
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juju expose grafana
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```
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Now that we have everything deployed, related, configured, and exposed, you can login and poke around using the same steps from the **Exploring Logs** and **Exploring Metrics** sections above.
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### The Wrap Up
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My goal here was to show you how to deploy a Kubernetes cluster with rich monitoring capabilities for logs and metrics. Whether you prefer a guided approach or command line steps, I hope it's clear that monitoring complex deployments doesn't have to be a pipe dream. The trick is to figure out how all the moving parts work, make them work together repeatably, and then break/fix/repeat for a while until everyone can use it.
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This is where tools like conjure-up and Juju really shine. Leveraging the expertise of contributors to this ecosystem makes it easy to manage big software. Start with a solid set of apps, customize as needed, and get back to work!
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Give these bits a try and let me know how it goes. You can find enthusiasts like me on Freenode IRC in **#conjure-up** and **#juju**. Thanks for reading!
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### About the author
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Kevin joined Canonical in 2014 with his focus set on modeling complex software. He found his niche on the Juju Big Software team where his mission is to capture operational knowledge of Big Data and Machine Learning applications into repeatable (and reliable!) solutions.
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--------------------------------------------------------------------------------
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via: https://insights.ubuntu.com/2018/01/16/monitor-your-kubernetes-cluster/
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作者：[Kevin Monroe][a]
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译者：[译者ID](https://github.com/译者ID)
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校对：[校对者ID](https://github.com/校对者ID)
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本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
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[a]:https://insights.ubuntu.com/author/kwmonroe/
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[1]:https://medium.com/@kwmonroe/monitor-your-kubernetes-cluster-a856d2603ec3
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[2]:https://www.graylog.org/
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[3]:https://prometheus.io/
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[4]:https://insights.ubuntu.com/wp-content/uploads/706b/1_TAA57DGVDpe9KHIzOirrBA.png
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[5]:https://conjure-up.io/
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[6]:https://jujucharms.com/canonical-kubernetes
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[7]:https://insights.ubuntu.com/wp-content/uploads/98fd/1_o0UmYzYkFiHIs2sBgj7G9A.png
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[8]:https://insights.ubuntu.com/wp-content/uploads/0351/1_pgVaO_ZlalrjvYd5pOMJMA.png
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[9]:https://insights.ubuntu.com/wp-content/uploads/9977/1_WXKxMlml2DWA5Kj6wW9oXQ.png
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[10]:https://insights.ubuntu.com/wp-content/uploads/8588/1_NWq7u6g6UAzyFxtbM-ipqg.png
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[11]:https://insights.ubuntu.com/wp-content/uploads/a1c3/1_hHK5mSrRJQi6A6u0yPSGOA.png
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[12]:https://insights.ubuntu.com/wp-content/uploads/937f/1_cP36lpmSwlsPXJyDUpFluQ.png
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[13]:http://docs.graylog.org/en/2.3/pages/dashboards.html
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[14]:https://insights.ubuntu.com/wp-content/uploads/9256/1_kskust3AOImIh18QxQPgRw.png
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[15]:https://insights.ubuntu.com/wp-content/uploads/2037/1_qJpjPOTGMQbjFY5-cZsYrQ.png
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[16]:https://jujucharms.com/
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[17]:https://raw.githubusercontent.com/conjure-up/spells/master/canonical-kubernetes/addons/graylog/steps/01_install-graylog/graylog-vhost.tmpl
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[18]:https://raw.githubusercontent.com/conjure-up/spells/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/prometheus-scrape-k8s.yaml
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[19]:https://github.com/conjure-up/spells/blob/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/after-deploy#L25
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[20]:https://github.com/conjure-up/spells/blob/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/after-deploy#L10
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[21]:https://github.com/conjure-up/spells/blob/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/after-deploy#L11
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[22]:https://raw.githubusercontent.com/conjure-up/spells/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/grafana-telegraf.json
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[23]:https://raw.githubusercontent.com/conjure-up/spells/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/grafana-k8s.json
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266
translated/tech/20180116 Monitor your Kubernetes Cluster.md
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@ -0,0 +1,266 @@
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监视 Kubernetes 集群
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======
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这篇文章最初发表在 [Kevin Monroe 的博客][1] 上
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监视日志和指标状态是集群管理员的重点工作。它的好处很明显：指标能帮你设置一个合理的性能目标，而日志分析可以发现影响你工作负载的问题。然而，困难的是如何找到一个与大量运行的应用程序一起工作的监视解决方案。
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在本文中，我将使用 [Graylog][2] （用于日志）和 [Prometheus][3] （用于指标）去打造一个Kubernetes 集群的监视解决方案。当然了，这不仅是将三个东西连接起来那么简单，实现上，最终结果看起来应该如下图所示：
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![][4]
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正如你所了解的，Kubernetes 不仅做一件事情 —— 它是 master、workers、networking bit 等等。同样，Graylog 是一个配角（apache2、mongodb、等等），Prometheus 也一样（telegraf、grafana 等等）。在部署中连接这些点看起来似乎有些让人恐惧，但是使用合适的工具将不会那么困难。
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我将使用 [conjure-up][5] 和 [Canonical Distribution of Kubernetes][6] (CDK) 去探索 Kubernetes。我发现 conjure-up 接口对部署大型软件很有帮助，但是我知道一些人可能不喜欢 GUIs、TUIs 以及其它 UIs。对于这些人，我将用命令行再去部署一遍。
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在开始之前需要注意的一点是，Graylog 和 Prometheus 是部署在 Kubernetes 侧而不是集群上。像 Kubernetes 仪表盘和 Heapster 是运行的集群中非常好的信息来源，但是我的目标是为日志/指标提供一个分析机制，而不管集群运行与否。
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### 开始探索
|
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如果你的系统上没有 conjure-up，首先要做的第一件事情是，请先安装它，在 Linux 上，这很简单：
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```
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sudo snap install conjure-up --classic
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```
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对于 macOS 用户也提供了 brew 包：
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```
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brew install conjure-up
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||||
```
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||||
|
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你需要最新的 2.5.2 版，它的好处是添加了 CDK spell，因此，如果你的系统上已经安装了旧的版本，请使用 `sudo snap refresh conjure-up` 或者 `brew update && brew upgrade conjure-up` 去更新它。
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安装完成后，运行它：
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```
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conjure-up
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```
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|
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![][7]
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你将发现有一个 spell 列表。选择 CDK 然后按下 `Enter`。
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||||
|
||||
![][8]
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||||
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||||
这个时候，你将看到 CDK spell 可用的附加组件。我们感兴趣的是 Graylog 和 Prometheus，因此选择这两个，然后点击 `Continue`。
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它将引导你选择各种云，以决定你的集群部署的地方。之后，你将看到一些部署的后续步骤，接下来是回顾屏幕，让你再次确认部署内容：
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![][9]
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除了典型的 K8s 相关的应用程序（etcd、flannel、load-balancer、master、以及 workers）之外，你将看到我们选择的日志和指标相关的额外应用程序。
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Graylog 栈包含如下：
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* apache2：graylog web 接口的反向代理
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* elasticsearch：日志使用的文档数据库
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* filebeat：从 K8s master/workers 转发日志到 graylog
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* graylog：为日志收集器提供一个 api，以及提供一个日志分析界面
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* mongodb：保存 graylog 元数据的数据库
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Prometheus 栈包含如下：
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* grafana：指标相关的仪表板的 web 界面
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* prometheus：指标收集器以及时序数据库
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* telegraf：发送主机的指标到 prometheus 中
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||||
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||||
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||||
你可以在回顾屏幕上微调部署，但是默认组件是必选 的。点击 `Deploy all Remaining Applications` 继续。
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||||
部署工作将花费一些时间，它将部署你的机器和配置你的云。完成后，conjure-up 将展示一个摘要屏幕，它包含一些链连，你可以用你的终端去浏览各种感兴趣的内容：
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||||
|
||||
![][10]
|
||||
|
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#### 浏览日志
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||||
现在，Graylog 已经部署和配置完成，我们可以看一下采集到的一些数据。默认情况下，filebeat 应用程序将从 Kubernetes 的 master 和 workers 中转发系统日志（ `/var/log/*.log` ）和容器日志（`/var/log/containers/*.log`）到 graylog 中。
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|
||||
记住如下的 apache2 的地址和 graylog 的 admin 密码：
|
||||
```
|
||||
juju status --format yaml apache2/0 | grep public-address
|
||||
public-address: <your-apache2-ip>
|
||||
juju run-action --wait graylog/0 show-admin-password
|
||||
admin-password: <your-graylog-password>
|
||||
```
|
||||
|
||||
在浏览器中输入 `http://<your-apache2-ip>` ，然后以管理员用户名（admin）和密码（<your-graylog-password>）登入。
|
||||
|
||||
**注意：** 如果这个界面不可用，请等待大约 5 分钟时间，以便于配置的反向代理生效。
|
||||
|
||||
登入后，顶部的 `Sources` 选项卡可以看到从 K8s 的 master 和 workers 中收集日志的概述：
|
||||
|
||||
![][11]
|
||||
|
||||
通过点击 `System / Inputs` 选项卡深入这些日志，选择 `Show received messages` 查看 filebeat 的输入：
|
||||
|
||||
![][12]
|
||||
|
||||
在这里，你可以应用各种过滤或者设置 Graylog 仪表板去帮助识别大多数比较重要的事件。查看 [Graylog Dashboard][13] 文档，可以了解如何定制你的视图的详细资料。
|
||||
|
||||
#### 浏览指标
|
||||
|
||||
我们的部署通过 grafana 仪表板提供了两种类型的指标：系统指标，包括像 K8s master 和 workers 的 cpu/内存/磁盘使用情况，以及集群指标，包括像从 K8s cAdvisor 端点上收集的容器级指标。
|
||||
|
||||
记住如下的 grafana 的地址和 admin 密码：
|
||||
```
|
||||
juju status --format yaml grafana/0 | grep public-address
|
||||
public-address: <your-grafana-ip>
|
||||
juju run-action --wait grafana/0 get-admin-password
|
||||
password: <your-grafana-password>
|
||||
```
|
||||
|
||||
在浏览器中输入 `http://<your-grafana-ip>:3000`，输入管理员用户（admin）和密码（<your-grafana-password>）登入。成功登入后，点击 `Home` 下拉框，选取 `Kubernetes Metrics (via Prometheus)` 去查看集群指标仪表板：
|
||||
|
||||
![][14]
|
||||
|
||||
我们也可以通过下拉框切换到 `Node Metrics (via Telegraf) ` 去查看 K8s 主机的系统指标。
|
||||
|
||||
![][15]
|
||||
|
||||
|
||||
### 另一种方法
|
||||
|
||||
正如在文章开始的介绍中提到的，我喜欢 conjure-up 的 “魔法之杖” 去指导我完成像 Kubernetes 这种复杂软件的部署。现在，我们来看一下 conjure-up 的另一种方法，你可能希望去看到实现相同结果的一些命令行的方法。还有其它的可能已经部署了前面的 CDK，想去扩展使用上述的 Graylog/Prometheus 组件。不管什么原因你既然看到这了，既来之则安之，继续向下看吧。
|
||||
|
||||
支持 conjure-up 的工具是 [Juju][16]。CDK spell 所做的一切，都可以使用 juju 命令行来完成。我们来看一下，如何一步步完成这些工作。
|
||||
|
||||
**从 Scratch 中启动**
|
||||
|
||||
如果你使用的是 Linux，安装 Juju 很简单，命令如下：
|
||||
```
|
||||
sudo snap install juju --classic
|
||||
```
|
||||
|
||||
对于 macOS，Juju 也可以从 brew 中安装：
|
||||
```
|
||||
brew install juju
|
||||
```
|
||||
|
||||
现在为你选择的云配置一个控制器。你或许会被提示请求一个凭据（用户名密码）：
|
||||
```
|
||||
juju bootstrap
|
||||
```
|
||||
|
||||
我们接下来需要基于 CDK 捆绑部署：
|
||||
```
|
||||
juju deploy canonical-kubernetes
|
||||
```
|
||||
|
||||
**从 CDK 开始**
|
||||
|
||||
使用我们部署的 Kubernetes 集群，我们需要去添加 Graylog 和 Prometheus 所需要的全部应用程序：
|
||||
```
|
||||
## deploy graylog-related applications
|
||||
juju deploy xenial/apache2
|
||||
juju deploy xenial/elasticsearch
|
||||
juju deploy xenial/filebeat
|
||||
juju deploy xenial/graylog
|
||||
juju deploy xenial/mongodb
|
||||
```
|
||||
```
|
||||
## deploy prometheus-related applications
|
||||
juju deploy xenial/grafana
|
||||
juju deploy xenial/prometheus
|
||||
juju deploy xenial/telegraf
|
||||
```
|
||||
|
||||
现在软件已经部署完毕，将它们连接到一起，以便于它们之间可以相互通讯：
|
||||
```
|
||||
## relate graylog applications
|
||||
juju relate apache2:reverseproxy graylog:website
|
||||
juju relate graylog:elasticsearch elasticsearch:client
|
||||
juju relate graylog:mongodb mongodb:database
|
||||
juju relate filebeat:beats-host kubernetes-master:juju-info
|
||||
juju relate filebeat:beats-host kubernetes-worker:jujuu-info
|
||||
```
|
||||
```
|
||||
## relate prometheus applications
|
||||
juju relate prometheus:grafana-source grafana:grafana-source
|
||||
juju relate telegraf:prometheus-client prometheus:target
|
||||
juju relate kubernetes-master:juju-info telegraf:juju-info
|
||||
juju relate kubernetes-worker:juju-info telegraf:juju-info
|
||||
```
|
||||
|
||||
这个时候，所有的应用程序已经可以相互之间进行通讯了，但是我们还需要多做一点配置（比如，配置 apache2 反向代理、告诉 prometheus 如何从 K8s 中取数、导入到 grafana 仪表板等等）：
|
||||
```
|
||||
## configure graylog applications
|
||||
juju config apache2 enable_modules="headers proxy_html proxy_http"
|
||||
juju config apache2 vhost_http_template="$(base64 <vhost-tmpl>)"
|
||||
juju config elasticsearch firewall_enabled="false"
|
||||
juju config filebeat \
|
||||
logpath="/var/log/*.log /var/log/containers/*.log"
|
||||
juju config filebeat logstash_hosts="<graylog-ip>:5044"
|
||||
juju config graylog elasticsearch_cluster_name="<es-cluster>"
|
||||
```
|
||||
```
|
||||
## configure prometheus applications
|
||||
juju config prometheus scrape-jobs="<scraper-yaml>"
|
||||
juju run-action --wait grafana/0 import-dashboard \
|
||||
dashboard="$(base64 <dashboard-json>)"
|
||||
```
|
||||
|
||||
以上的步骤需要根据你的部署来指定一些值。你可以用与 conjure-up 相同的方法得到这些：
|
||||
|
||||
* <vhost-tmpl>: 从 github 获取我们的示例 [模板][17]
|
||||
* <graylog-ip>: `juju run --unit graylog/0 'unit-get private-address'`
|
||||
* <es-cluster>: `juju config elasticsearch cluster-name`
|
||||
* <scraper-yaml>: 从 github 获取我们的示例 [scraper][18] ；`[K8S_PASSWORD][20]` 和 `[K8S_API_ENDPOINT][21]` [substitute][19] 的正确值
|
||||
* <dashboard-json>: 从 github 获取我们的 [主机][22] 和 [k8s][23] 仪表板
|
||||
|
||||
|
||||
|
||||
最后，发布 apache2 和 grafana 应用程序，以便于可以通过它们的 web 界面访问：
|
||||
```
|
||||
## expose relevant endpoints
|
||||
juju expose apache2
|
||||
juju expose grafana
|
||||
```
|
||||
|
||||
现在我们已经完成了所有的部署、配置、和发布工作，你可以使用与上面的**浏览日志**和**浏览指标**部分相同的方法去查看它们。
|
||||
|
||||
### 总结
|
||||
|
||||
我的目标是向你展示如何去部署一个 Kubernetes 集群，很方便地去监视它的日志和指标。无论你是喜欢向导的方式还是命令行的方式，我希望你清楚地看到部署一个监视系统并不复杂。关键是要搞清楚所有部分是如何工作的，并将它们连接到一起工作，通过断开/修复/重复的方式，直到它们每一个都能正常工作。
|
||||
|
||||
这里有一些非常好的工具像 conjure-up 和 Juju。充分发挥这个生态系统贡献者的专长让管理大型软件变得更容易。从一套可靠的应用程序开始，按需定制，然后投入到工作中！
|
||||
|
||||
大胆去尝试吧，然后告诉我你用的如何。你可以在 Freenode IRC 的 **#conjure-up** 和 **#juju** 中找到像我这样的爱好者。感谢阅读！
|
||||
|
||||
### 关于作者
|
||||
|
||||
Kevin 在 2014 年加入 Canonical 公司，他专注于复杂软件建模。他在 Juju 大型软件团队中找到了自己的位置，他的任务是将大数据和机器学习应用程序转化成可重复的（可靠的）解决方案。
|
||||
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
via: https://insights.ubuntu.com/2018/01/16/monitor-your-kubernetes-cluster/
|
||||
|
||||
作者：[Kevin Monroe][a]
|
||||
译者：[qhwdw](https://github.com/qhwdw)
|
||||
校对：[校对者ID](https://github.com/校对者ID)
|
||||
|
||||
本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
|
||||
|
||||
[a]:https://insights.ubuntu.com/author/kwmonroe/
|
||||
[1]:https://medium.com/@kwmonroe/monitor-your-kubernetes-cluster-a856d2603ec3
|
||||
[2]:https://www.graylog.org/
|
||||
[3]:https://prometheus.io/
|
||||
[4]:https://insights.ubuntu.com/wp-content/uploads/706b/1_TAA57DGVDpe9KHIzOirrBA.png
|
||||
[5]:https://conjure-up.io/
|
||||
[6]:https://jujucharms.com/canonical-kubernetes
|
||||
[7]:https://insights.ubuntu.com/wp-content/uploads/98fd/1_o0UmYzYkFiHIs2sBgj7G9A.png
|
||||
[8]:https://insights.ubuntu.com/wp-content/uploads/0351/1_pgVaO_ZlalrjvYd5pOMJMA.png
|
||||
[9]:https://insights.ubuntu.com/wp-content/uploads/9977/1_WXKxMlml2DWA5Kj6wW9oXQ.png
|
||||
[10]:https://insights.ubuntu.com/wp-content/uploads/8588/1_NWq7u6g6UAzyFxtbM-ipqg.png
|
||||
[11]:https://insights.ubuntu.com/wp-content/uploads/a1c3/1_hHK5mSrRJQi6A6u0yPSGOA.png
|
||||
[12]:https://insights.ubuntu.com/wp-content/uploads/937f/1_cP36lpmSwlsPXJyDUpFluQ.png
|
||||
[13]:http://docs.graylog.org/en/2.3/pages/dashboards.html
|
||||
[14]:https://insights.ubuntu.com/wp-content/uploads/9256/1_kskust3AOImIh18QxQPgRw.png
|
||||
[15]:https://insights.ubuntu.com/wp-content/uploads/2037/1_qJpjPOTGMQbjFY5-cZsYrQ.png
|
||||
[16]:https://jujucharms.com/
|
||||
[17]:https://raw.githubusercontent.com/conjure-up/spells/master/canonical-kubernetes/addons/graylog/steps/01_install-graylog/graylog-vhost.tmpl
|
||||
[18]:https://raw.githubusercontent.com/conjure-up/spells/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/prometheus-scrape-k8s.yaml
|
||||
[19]:https://github.com/conjure-up/spells/blob/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/after-deploy#L25
|
||||
[20]:https://github.com/conjure-up/spells/blob/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/after-deploy#L10
|
||||
[21]:https://github.com/conjure-up/spells/blob/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/after-deploy#L11
|
||||
[22]:https://raw.githubusercontent.com/conjure-up/spells/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/grafana-telegraf.json
|
||||
[23]:https://raw.githubusercontent.com/conjure-up/spells/master/canonical-kubernetes/addons/prometheus/steps/01_install-prometheus/grafana-k8s.json
|
||||
Loading…
Reference in New Issue
Block a user