I'm running hortonworks 2.3 and currently hooking into the REST API through ambari to start/stop the flume service and also submit configurations.
This is all working fine, My issue is how do I get the metrics?
Previously I used to run an agent with the parameters to produce the metrics to a http port and then read them in from there using this:
-Dflume.root.logger=INFO,console
-Dflume.monitoring.type=http
-Dflume.monitoring.port=XXXXX
However now that Ambari kicks off the agent I no longer have control over this.
Any assistance appreciated :-)
Using Ambari 2.6.2.0,
http://{ipadress}:8080/api/v1/clusters/{your_cluster_name}/components/?ServiceComponentInfo/component_name=FLUME_HANDLER&fields=host_components/metrics/flume/flume
gives flume metrics breakdown by components.
Found the answer by giving a shot (and doing some cropping) to the API call provided to this JIRA issue (which complains about how slow fetching flume metrics is) https://issues.apache.org/jira/browse/AMBARI-9914?attachmentOrder=asc
Hope this helps.
I don't know if you still need the answer. That happens because Hortonworks, by default, disable JSON monitoring, they use their own metric class to send the metrics to Ambari Metrics. While you can't retrieve it from Flume directly, you still can retrieve it from Ambari REST API: https://github.com/apache/ambari/blob/trunk/ambari-server/docs/api/v1/index.md.
Good luck,
Related
Is there any other way to deploy connector config rather than POSTing connector config to kafka connect REST api? https://docs.confluent.io/platform/current/connect/references/restapi.html#tasks
I am thinking of any form of persistent approach like a volume or s3, where connect during bootstrap would grap those configs would be great. Don't know/can't find if thats anywhere available.
regards
The REST API is the only way.
You can use abstractions like Terraform or Kubernetes resources, however, which wrap an HTTP client.
If you use other storage, that'll require you to write extra code to download files and call the REST API.
I am trying to implement a Rest client for Flink to send jobs via Restful Flink services. And also I want to integrate Flink and Kubernetes natively. I have decided to use “Application Mode” as deployment mode according to Flink documentation .
I have already implemented a job and packaged it as jar. And I have tested it on Standalone Flink. But my aim is to move on Kubernetes and deploy my application in Application mode via Rest API of Flink.
I have already investigated the samples at Flink documentation - Native Kubernetes. But I cannot find a sample for executing same samples via Restful services (esp. how to set --target kubernetes-application/kubernetes-session or other parameters).
In addition to samples, I checked out the Flink sources from GitHub and tried to find some sample implementation or get some clue.
I think the below ones are related with my case.
org.apache.flink.client.program.rest. RestClusterClient
org.apache.flink.kubernetes. KubernetesClusterDescriptorTest. testDeployApplicationCluster
But they are all so complicated for me to understand below points.
For application mode, are there any need to initialize a container to serve Flink Rest services before submitting job? If so, is it JobManager?
For application mode, how can I set the same command line parameters via Rest services?
For session mode, in command line samples, kubernetes-session.sh is executed before job submission to initialize a JobManager container. How sould I do this step via Rest client?
For session mode, how can I set the same command line parameters via Rest services? Although the command line samples send .jar job as parameter, should I upload jar before submitting job?
Could you please provide me some clue/sample to continue my implementation?
Best regards,
Burcu
I suspect that if you study the implementation of the Apache Flink Kubernetes Operator you'll find some clues.
I see many docs and posts about how to send logs to Stackdriver but almost no information about how to do the opposite - send logs from the Stackdriver to Kafka.
In my case, our Ops want to collect the logs from our web servers using Google's stackdriver agents and pushing them to stackdriver ... However, for my stream processing needs I want to get the logs into Kafka to use it's unparalleled abilities to retain and reprocess data by any number of consumers, something that I cannot do with PubSub.
So, what are the options for doing this? I only saw a couple of possible avenues - neither sounds too good:
based on this post: (https://powerspace.tech/how-to-stream-data-from-google-pubsub-to-kafka-with-kafka-connect-dbef1c340a76) push data into PubSub first, and then read from it using either Kafka connector or write my own Kafka consumer. I hate the thought of adding yet another hop (serialize/deserialize/ack/etc.) between the source of data and Kafka ....
I noticed a brief mentioning in passing on adding a plugin to Google's version of Fluentd (which is what stackdriver log collection agent is based on) here: https://powerspace.tech/how-to-stream-data-from-google-pubsub-to-kafka-with-kafka-connect-dbef1c340a76 . Not many details - so hard to tell how involved this approach is ...
Any other options?
Thank you!
Enter in to the Kafka console and add certain elements in the console. Once you have added the elements in the Kafka console you need to check if these elements are reflected successfully in the cloud shell. For this you will run the command > $ gcloud pubsub subscriptions pull from-kafka — auto-ack — limit=10 < . Once you run this command it will take some time to sync with the Kafka console. You will get the results after running this command a couple of times.
You will run the commands in the Cloud Shell and see the output in the Kafka VM SSH.
***Image1
Now you will be verifying the exact opposite procedure where in you will be running the command in the Kafka VM and seeing the output in the Cloud Shell. It will take some time for the output to be reflected and you may have to run the command > $ gcloud pubsub subscriptions pull from-kafka — auto-ack — limit=10 < a couple of times to see the output. Your output will look like this
*** image2
The Kafka plugin is deprecated. For more information, refer to https://cloud.google.com/stackdriver/docs/deprecations
Note: This functionality is only available for agents running on Linux. It is not available on Windows.
Kafka is monitored via JMX. Monitoring supports monitoring Kafka version 0.8.2 and higher.
On your VM instance, download kafka-082.conf from the GitHub configuration repository and place it in the directory /etc/stackdriver/collectd.d/:
(cd /etc/stackdriver/collectd.d/ && sudo curl -O https://raw.githubusercontent.com/Stackdriver/stackdriver-agent-service-configs/master/etc/collectd.d/kafka-082.conf)
The downloaded plugin configuration file assumes that your Kafka server is configured to accept JMX connections on port 9999. If you have configured Kafka with a different JMX port, as root, edit the file and follow the instructions to change the JMX port settings.
After adding the configuration file, restart the Monitoring agent by running the following command:
sudo service stackdriver-agent restart
What is monitored:
https://cloud.google.com/monitoring/api/metrics_agent#agent-kafka
We are using Kafka Connectors (JDBC and others), and configuring them using the REST API (using curl in shell scripts). Right now, when testing/developing, we are including secrets (for the JDBC connect - database user/pw) directly in the request. This is obviously bad, as those are then readily available for everybody to see when reading them out using the GET request.
Is there a good way to give secrets to the connectors? We can bring them in safely using environment variables or config files (injected fom OpenShift) - but is there a syntax available when starting a connector via the REST API for that?
EDIT: This is for the distributed mode of connectors; i.e., configuration by REST API, not connector config files...
A pluggable interface for this was implemented in Apache Kafka 2.0 through KIP-297. You can see more details in the documented example here.
Is there any documentation out there on sending logs from containers in K8s to an external ELK cluster running on EC2 instances?
We're in the process of trying to Kubernetes set up and I'm trying to figure out how to get the logging to work correctly. We already have an ELK stack setup on EC2 for current versions of the application but most of the documentation out there seems to be referring to ELK as it's deployed to the K8s cluster.
I am also working on the same cause.
First you should know what driver is being used by your docker containers to manage the logs (json driver/ journald etc - read here).
After that you should use some log collector in your architecture to send the logs to the Logstash endpoint. You can use filebeat/fluent bit. They are light weight alternatives to logstash/fluentd respectively. You must use one of them and not directly send your logs to logstash via syslog since these log shippers have a special functionality of enriching your logs with kubernetes metadata of the respective containers.
There might be lot of challenges after that. Parsing log data (multiline logs for example) etc. For an efficient pipeline, it’s better to do most of the work (i.e. extracting the date object from the logs etc) at the log sender side, than using the common logstash for this purpose that might be a bottle-neck.
Note that in case the container logs are not sent to stdout/stderr but written else-where, you might need to run filebeat/fluent-bit as side-car with your containers.
As for the links for documentation are concerned, I myself didn’t find anything documented in a single place on this, but the keywords that I mentioned over, reading about them I got to know many things.
Hope this helps.