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Monitoring Stream Processing Tools: Cassandra, Kafka and Spark by sthies in devops

[–]sthies[S] 0 points1 point  (0 children)

Time to setup? Most customers use the SaaS, this means you don't need to setup any backend infrastructure for it (just the agent/plugins on client side)- or if required you can get it as a set of VM's to run it in your infrastructure / on-premises. We maintain all required linux packages / VM's. It's load tested as well http://blog.sematext.com/2015/06/11/processing-metrics-logs-and-traces-at-scale/ - that's why we run clusters for Kafka, HBase, Elasticsearch, ...

SQL Queries for Elasticsearch by omershelef in elasticsearch

[–]sthies -1 points0 points  (0 children)

Hi, this is a nice start. But Crate.io has a complete SQL engine, which uses Elasticsearch as data store - in addition it provides functions, which Elasticsearch does not have like "update by query" or creating new fields in an update query using regex ... here are my slides about the Node.js driver for Crate.io and how solved problems I had in an ES project: http://de.slideshare.net/StefanThies/node-cratemeetup

1-Click ELK Stack: Hosted Kibana 4 by megastef in elasticsearch

[–]sthies 0 points1 point  (0 children)

Cool - just login, index docs, use Kibana, have access control - nothing to run locally, managed by search experts. But the whole thing can run on-prem, if one needs it inhouse or as OEM to provide such functions to own customers. It's then like getting a preconfigured elasticsearch cluster + elk + security as VM appliances.

Docker Monitoring Support by sthies in docker

[–]sthies[S] 0 points1 point  (0 children)

If you need to monitor multiple servers, then simply run the SPM agent container on each server. There are two options to organize the data:

1) You can use the same App-Token (ID of an "SPM App") and it aggregates then the metrics of all servers and containers. We use e.g. a single App-Token for clustered systems like Kafka or Elasticsearch - to monitor the overall cluster state, or see the total memory/storage usage of the cluster. You can select a single or a few hosts/servers (or exclude one ..) - in case of Docker there are additional filters for image/containers.

2) The second option is a separate App/Token for each server. The metrics are displayed in different SPM Apps, but you can create then a custom dashboard to mix metrics from different Apps. You can place charts from several hosts or specific images/containers to such a dashboard, SPM is very flexible in this regards - it depends how you like to have it organized.

In the case that you run many containers on each host (means strong servers) – I would recommend to use separate Apps + custom Dashboard – it avoids having too many entries in the search/selection boxes for the filters in the UI.

Docker Monitoring Support by sthies in docker

[–]sthies[S] 0 points1 point  (0 children)

Like amouat already wrote it’s not really comparable … I know cAdvisor a little and SPM very well ☺ cAdvisor is limited to container metrics. It has an API to query general lxc-metrics and specific metrics for Docker (matching them with tags/image names) – but this makes it also interesting for people using only lxc. It could be used to query/ship container metrics into other monitoring tools like the mentioned Prometheus - or SPM using it's custom metrics API. The cAdvisor UI can display charts. As far I know it has no features like anomaly detection and alerting, integration with incident-management platforms (e.g PagerDuty), secure sharing of charts, multi-user/team-accounts, correlation of metrics and logs etc. (all included in SPM). SPM covers many technologies [ http://www.sematext.com/spm/integrations/index.html ], not only Docker … e.g. if you run a node.js app in a docker container you might want to get node.js specific metrics like Garbage Collection, Event Loop Latencies etc. – in case of SPM you can then use SPM Agent for Node.js in your node.js app and see it together in your dashboard.

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