Monitoring your container-based infrastructure is crucial to ensure good performance, identify issues early and gain the insight necessary to maximize its efficiency. When you are dealing with a large number of often short-lived containers spread over multiple hosts and even data centers, understanding the operational health of your infrastructure implies the need to aggregate performance data from both physical hosts as well as the container cluster running on top of it. Ideally, you want to capture and correlate application performance with the underlying infrastructure to troubleshoot and identify bottlenecks. Implementing a monitoring system that satisfies these requirements can be a complex endeavor. A previous blog post compared a number of monitoring options that integrate with Docker. One of those evaluated is the SaaS-based monitoring platform from Datadog (www.datadoghq.com). Datadog works with an agent-based deploy that allows you to capture system resource metrics as well as key Docker metrics and visualize them in highly customizable graphs and dashboards. The agent is available as a Docker image, which is a huge win in terms of ease of deployment. The recent release of the Datadog Agent introduced the Service Discovery feature, which facilitates polling of application-level metrics in dynamic, container-based environments. In this article, I will walk you through the steps of setting up environment-wide monitoring across all layers of your stack (ie. host, Docker engine and application) using the Datadog template from Rancher’s application catalog. In the process, I’ll show you how adopting a policy of consistent labeling of hosts and services in Rancher will help you gain maximum visibility into your applications and infrastructure. I will also give a short insight into how Rancher Catalog templates work.
Step 1: Label your hosts and service
Tags assigned to servers and metrics play a crucial role in subsetting and querying the collected data throughout the Datadog application. Similarly, Rancher adopts the concept of labels, that is key/value pairs attached to hosts and services. Rancher not only uses labels to manage various features when starting services (see labels documentation), but also supports user-defined labels conveying metadata about your hosts and services. To provide better integration between Rancher and Datadog, the catalog template allows you to specify a list of host and service labels to convert to Datadog tags. This makes it possible to leverage an existing labeling scheme for subsetting metrics in Datadog, instead of having to refer to individual host names or (short-lived) container and image identifiers. If you aren’t already adopting a labeling scheme for your hosts and services, this might be a good occasion to start doing just that. You can use labels to encode any amount of metadata about hosts and services. Here is a set of labels that provides a basic amount of metadata about hosts:
- region (e.g. us-east-1)
- zone (e.g. us-east-1b)
- flavor (e.g. t2.medium)
- env (e.g. dev|staging|production)
- tier (e.g. frontend|backend)
- app (e.g. web|database|message-queue)
The more meaningful metadata you encode in host and service labels, the easier it will be to aggregate relevant information in Datadog and create custom dashboards providing not only the big picture but also a view into the smallest detail. And as an added benefit, a consistent labeling scheme will also help you to create narrowly scoped container scheduling rules. Note: Host labels can not only be assigned at the time of creation of the host but also later via the Edit option in the host’s drop down menu.
2: Grab your Datadog API key
Datadog has a free account tier allowing you to use their service indefinitely with up to 5 hosts. To get started, first sign up for the free trial on their website. Once you are signed into your account, you will need to grab your API key which can be found under Integrations => APIs. Also make sure to activate the Docker integration for your account.
Step 3: Configure the Catalog stack
In your Rancher server UI, navigate to Catalog => Library and locate the entry for the Datadog stack. Click on View Details to open the configuration view and enter a name for the stack. Next, let’s have a look at the available configuration options:
Export Host Labels
Here you can specify which of the labels assigned to your hosts in Rancher should be used for tagging your hosts in Datadog. Doing so will allow you to easily track system metrics for groups of hosts that share a specific attribute (e.g. availability zone) instead of having to refer to each host individually.
Export Service Labels
When the Datadog agent captures metrics from the Docker engine, it will by default turn the Docker \“image name\“? and \“image tag\” attributes as well as the Rancher stack and service names into tags?. You may enter one or more user-defined service labels in this field to also be used as tags. This will later allow you to track metrics matching specific services or labels in aggregate.
Global Service means that a Datadog agent container will be scheduled to run on every host in your current environment. You will normally want this enabled to monitor system, Docker and application performance environment-wide. Global Service will also make sure that any instances added later on will automatically be monitored by Datadog as well.
Besides monitoring system and Docker resources, the Datadog agent can also poll metrics from applications running in your Docker containers. When Service Discovery is enabled, the agent watches for container events, identifies which service a specific container provides and dynamically reconfigures the checks to capture the metrics exposed by the application. Enabling the Service Discovery feature is all that is required in order to monitor the following applications: Apache, Consul, Couch, Couchbase, Elasticsearch, etcd, Kyoto Tycoon, Memcached, Redis and Riak. To monitor any of the other 100+ supported applications you will need to provide configuration templates for the specific images in an etcd or Consul store. To do so, first setup the configuration templates as documented hereand then fill in the information required to connect to the chosen key-value store in the various Config Backend fields.
The Datadog image provides a StatsD daemon which can aggregate and forward application metrics to Datadog. With this option enabled only the DogStatsD service without the full agent will run in the container. That is, host or Docker metrics will not be captured at all, but you will be able to send StatsD metrics to the service from any application in your environment. You will also want to disable the Global Service option when this option is enabled. For the purpose of this article we’ll enable just the Service Discovery option, enter our host and service labels as well as API key and leave the other options at their defaults.
Reviewing the Catalog template
Before we deploy the Datadog service, let’s take a brief look at the containers that make up the stack. When you click the Preview label located above the Launch button you will see a docker-compose.yml and rancher-compose.yml file. These files are the foundation of any template in the Rancher Catalog. Here is a snippet showing the relevant parts of the docker-compose.yml:
datadog-init: image: janeczku/datadog-rancher-init:v1.1 ... volumes: - /opt/rancher ... datadog-agent: image: datadog/docker-dd-agent:11.1.580 ... volumes_from: - datadog-init labels: io.rancher.sidekicks: 'datadog-init'
As you can see, this stack comprises two containers. The \“datadog-agent\” container runs the official Datadog agent image and mounts a configuration volume exposed by the sidekick container named \“datadog-init\“. The purpose of the sidekick container is to configure the agent for the Rancher environment. In a nutshell, the sidekick retrieves the name of the host and the host labels from Rancher’s metadata service and generates a configuration file using the information provided in the UI. To learn more about creating Rancher Catalog templates check out this article. Let’s go ahead with launching the stack. After clicking the Launch button, confirm that the status of the Datadog stack has become Active, meaning that the containers have been started on all hosts.
Leveraging Rancher metadata in Datadog
Once the stack is deployed to your Rancher environment, you should already see events and metrics flowing into Datadog. Let me show you how you are now able to refer to Rancher metadata when visualizing performance of our hosts, containers and applications. When you open the Infrastructure List in Datadog, notice that the names of the hosts and their tags correspond to the designated names and host labels in Rancher. We can now easily scope host performance data using label attributes or click on individual hosts for a detailed look. The example below shows how we can now filter and group hosts by region, zone and instance flavor. Next, navigate to the Docker integration dashboard, which provides an overview into the status and resource usage of all Docker containers. Using the Scope drop down you can change the scope of the view based on stack and service names, host and service labels or Docker image tags. Let’s see how we can use Rancher metadata within Datadog to create custom views into our performance data. In the example below, we query the CPU usage of all Docker containers that are part of the service \“gitlab\” in the stack \“ci\” grouped by the host’s availability region: Now let us put the Service Discovery feature to test by launching a Redis service in Rancher. You can see in the screenshot that I used the official Redis image from Docker Hub and assigned labels according to the labeling scheme discussed above. Once the service has started, the Datadog agent should automatically begin to capture application metrics from the Redis container. We can verify this by opening the Redis integration dashboard in Datadog which should provide a pre-configured look at the key metrics. And finally, here is an example for a custom graph correlating Redis requests per second with the CPU usage of the host it is running on: This should provide you with enough inspiration to start creating your own custom dashboards in Datadog using Rancher metadata provided by tags. I hope this article gives you an idea about how the Datadog template in Rancher’s Catalog can help you implement monitoring of your Rancher environment across all layers of your stack in a matter of minutes. If you have any questions, please reach out to me (firstname.lastname@example.org), or contact us on Twitter @Rancher_Labs.