Once logged in, check out the cluster metric dashboard by clicking the Home drop-down box and selecting Kubernetes Metrics (via Prometheus):Īs alluded to in the intro, I prefer the wizard-y feel of conjure-up to guide me through complex software deployments like Kubernetes. Juju run-action -wait grafana/0 get-admin-passwordīrowse to login with admin as the username and as the password. Grab the grafana address and admin password as follows: juju status -format yaml grafana/0 | grep public-address 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. Check out the Graylog Dashboard docs for details on customizing your view. Once complete, conjure-up will show a summary screen that includes links to various interesting endpoints for you to browse:įrom 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. The deployment will take a few minutes to settle as machines are brought online and applications are configured in your cloud. Click Deploy all Remaining Applications to get things going. You can fine tune the deployment from this review screen, but the defaults will suite our needs. telegraf: sends host metrics to prometheus.prometheus: metric collector and time series database.grafana: web interface for metric-related dashboards. The Prometheus stack includes the following: graylog: provides an api for log collection and an interface for analysis.filebeat: forwards logs from K8s master/workers to graylog.elasticsearch: document database for the logs.apache2: reverse proxy for the graylog web interface.The Graylog stack includes the following: 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. 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. There’s also a brew package for macOS users: brew install conjure-up On Linux, that’s simply: sudo snap install conjure-up -classic The Walk Throughįirst things first, install conjure-up if you don’t already have it. 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. For those folks, I’ll do the same deployment again from the command line.īefore we jump in, note that Graylog and Prometheus will be deployed alongside Kubernetes and not in the cluster itself. 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. I’ll walk through this using conjure-up and the Canonical Distribution of Kubernetes (CDK). Connecting the dots in a deployment like this may seem daunting, but the right tools can make all the difference. Similarly, Graylog comes with a supporting cast (apache2, mongodb, etc), as does Prometheus (telegraf, grafana, etc). As you know, Kubernetes isn’t just one thing - it’s a system of masters, workers, networking bits, etc(d).
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