To monitor an Imply cluster, you can use:
In cloud deployments, you can further enable monitoring of the metadata store (Amazon RDS, by default) using CloudWatch. See Monitoring the metadata store with CloudWatch for more information.
On Imply Cloud, you can access Clarity from the Manager console. To do so, from the cluster overview page, click Monitor from the left menu.
By default, Clarity opens in the Visuals pane:
From the Clarity home page, you can access various views, including:
It's a good practice to open the Clarity UI regularly to inspect the performance of your Imply cluster. In addition,
by configuring alerts, you can have Clarity notify you when a condition is met. You can configure conditions to evaluate
query times, exception counts, and more.
You can configure alerts from the Alerts tab:
You can control the way Druid emits metrics by adding the following properties to the Druid properties file, common.runtime.properties, of the metrics emitting cluster.
druid.emitter.clarity. as a prefix to the field names shown, for example,
||String||HTTP endpoint events will be posted to, e.g.
||String||Kafka "bootstrap.servers" configuration (a list of brokers)||[required]||yes|
||String||Can be used to specify any other Kafka producer property.||empty||no|
||String||Cluster name used to tag events||null||no|
||Boolean||Should hostnames be scrubbed from events?||false||no|
||Integer||Maximum size of event buffer||min(250MB, 10% of heap)||no|
||Integer||For sampled metrics, what percentage of metrics will be emitted||100||no|
||List||Which event types are sampled||["query/wait/time", "query/segment/time", "query/segmentAndCache/time"]||no|
||List||Which node types are sampled||["druid/historical", "druid/peon", "druid/realtime"]||no|
The following connection settings are optional, or required only as necessitated by your metrics collection Druid configuration.
The settings are equivalent to those in the Pivot configuration. However, those settings are separate from Clarity's.
||The timeout for the metric queries. Default is 40000.|
||The connection protocol, one of
||If connecting via TLS, a trusted certificate of the certificate authority if using self-signed certificates. Should be PEM formatted text.|
||If connecting via TLS, the client side certificate to present. Should be PEM-formatted text.|
||If connecting via TLS, the private key file name. The key should be PEM-formatted text.|
||If connecting via TLS, a passphrase for the private key, if needed.|
||If Druid authentication is enabled, the default token that will be used to authenticate against this connection.|
||If Clarity needs to connect to Druid via a SOCKS5 proxy, the hostname of the proxy host.|
||The user for the Socks proxy, if needed.|
||The password for proxy authentication, if needed.|
Druid includes status APIs that return metrics that help you gauge the health of the system. The following APIs are especially useful for monitoring.
Unavailable segments: On the Coordinator, check
verify each datasource registers "0". This is the number of unavailable segments. It may briefly be
non-zero when new segments are added, but if this value is high for a prolonged period of time, it
indicates a problem with segment availability in your cluster. In this case, check your data nodes
to confirm they are healthy, have spare disk space to load data, and have access to your S3 bucket
where data is stored.
Data freshness: Run a "dataSourceMetadata" query to get the "maxIngestedEventTime" and verify that it's recent enough for your needs. For example, alert if it's more than a few minutes old. This is an inexpensive Druid query, since it only hits the most recent segments and it only looks at the last row of data. In addition to verifying ingestion time, this also verifies that Druid is responsive to queries. If this value is staler than you expect, it can indicate that real-time data is not being loaded properly. In this case, use the Imply Manager to verify that your data ingestion is healthy, that there have not been any errors loading data, and that you have enough capacity to load the amount of data that you're trying to load.
See Druid API reference for more information.
Amazon CloudWatch RDS monitoring can help you identify and avoid capacity or other issues with the metadata store for the cluster. With the Amazon CloudWatch integration, enabling metadata store monitoring for your cluster allows Imply support to track the health of your clusters and get notifications of potential issues. Specifically, alerts are triggered for these conditions:
Note that using Amazon CloudWatch with Imply may entail additional costs, which are not included in the Imply subscription. See CloudWatch pricing for details.
Metadata monitoring is enabled by default for new clusters created after the availability of Imply version 3.4 (July, 2020).
For clusters that existed prior to that time, metadata store monitoring is disabled by default to avoid the possibility of interfering with existing settings or validated configurations.
You can enable metadata store monitoring as follows.
As the Imply role in the AWS account needs permission to interact with Amazon CloudWatch, in the IAM settings, create a policy for Imply that enables the following permissions for the CloudWatch service:
Enable metadata store monitoring as follows: