Docker Environment – Logging

Option 1: ELK – Elasticsearch, Logstash, Kibana
Logstash is not recommended due to high CPU, Memory utilization

Option 2: EFK – Elasticsearch, Filebeat, Kibana
Best option. But containers need to write to a specific location to fetch logs.
When we have many containers, it will be tough to modify

Option 3: EFK – Elasticsearch, Fluentd, Kibana
Fluentd is a driver. This fetches logs from docker container console

Option 4: ELK – Elasticsearch, Logstash, Filebeat, Kibana
Logstash is overhead

Option 5: EFk – Elasticsearch, Filebeat, Kibana, JSON Driver
We need to add JSON driver to all containers
More proved stack

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References:
https://logz.io/blog/filebeat-tutorial/
https://logz.io/blog/filebeat-vs-logstash/

https://www.fluentd.org/guides/recipes/docker-logging
Stack Setup
https://codefarm.me/2018/06/29/elasticsearch-fluentd-kibana-docker-compose/

https://docs.fluentd.org/v0.12/articles/docker-logging-efk-compose

View at Medium.com

JSON Driver
https://docs.docker.com/config/containers/logging/json-file/

https://stackoverflow.com/questions/53549955/docker-compose-logging-with-json-file-driver-where-is-all-logging-files-for-the

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Healthcare Domain Specific Language (DSL) – Arden

What Are the Different Standards in Healthcare?

FHIR® – Fast Healthcare Interoperability Resources

—-
https://www.hl7.org/implement/standards/product_brief.cfm?product_id=290

https://en.wikipedia.org/wiki/Arden_syntax

https://www.hl7.org/

Syntax: https://www.hl7.org/implement/standards/product_brief.cfm?product_id=372
Arden Syntax v2.10 (Health Level Seven Arden Syntax for Medical Logic Systems, Version 2.10)
Nov-2014

What is AI System?

AI is having the following categories:
Expert systems
Machine learning
Natural language processing
Computer vision
Automated speech recognition
AI Planning

Reference: https://codebots.com/ai-powered-bots/6-technologies-behind-ai

-o-

Expert Systems: https://www.tutorialspoint.com/artificial_intelligence/artificial_intelligence_expert_systems.htm

AI Planning:
https://researcher.watson.ibm.com/researcher/view_group.php?id=8432

Elasticsearch – Pinpointing problematic shards

https://www.datadoghq.com/blog/elasticsearch-unassigned-shards/#pinpointing-problematic-shards

The master node may not be able to assign shards if there are not enough nodes with sufficient disk space (it will not assign shards to nodes that have over 85 percent disk in use). Once a node has reached this level of disk usage, or what Elasticsearch calls a “low disk watermark”, it will not be assigned more shards.

Keep an eye on disk space

Network Time Protocol (NTP)

In Unix/Linux we need to make sure that servers are configured to sync with time server to have consistent time on all servers. Otherwise, it is tough to map events across systems.

>ntpstat
>ntpq -pn
>timedatectl status

To make sure that ntp is configured to start with every system restart
>chkconfig –list ntpd

Reference:
https://access.redhat.com/documentation/en-us/red_hat_enterprise_linux/6/html/deployment_guide/s1-checking_the_status_of_ntp

https://www.cyberciti.biz/faq/linux-unix-bsd-is-ntp-client-working/