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K8S LOG DISTRIBUTION
2
HELLO!
I am Gregory Fodé Sanderson
Jive DevOps team
You can email me at gregory.sanderson@logmein.com
3
PROBLEM DEFINITION
1
8 DATACENTERS
Distributed across US, Brazil & Europe
5
4000 PODS
Distributed across US, Brazil & Europe
6
10600 CONTAINERS
Distributed across US, Brazil & Europe
7
2TB LOGS PER DAY
Distributed across US, Brazil & Europe
8
A LOT OF LOGS !
How do we store them ?!?!?!?!?!
9
10
SOLUTION & DESIGN
2
SOLUTION & DESIGN
SOLUTION: LOG PRODUCERS
 Docker reconfigured to add log metadata
 DOCKER_OPTS=
--log-driver=json-file
--log-opt env=K8S_CLUSTER
--log-opt labels=
io.kubernetes.pod.name,
io.kubernetes.container.name,
io.kubernetes.container.restartCount,
io.kubernetes.pod.namespace
--log-opt max-size=20m
--log-opt max-file=2
SOLUTION: LOG PRODUCERS
 Filebeat
 Daemonset
 /var/lib/docker/containers/*/*.log
 Push logs to kafka
 Journalbeat
 Daemonset
 Reads logs from journald (system logs)
 Push logs to kafka
15
SOLUTION: LOG TRANSPORT
 Kafka
 Distributed data streaming pipelines
 Producer & Consumer model
 Fault tolerance for cluster & consumers
 Logstash
▻ Consumes logs and sends to ES cluster
▻ All instances part of the same consumer group
▻ Adds metadata to logs
SOLUTION: LOG TRANSPORT
grok {
match => { '[attrs][io.kubernetes.pod.name]' =>
'(?<service>.*).[0-9]+-(?<pod_id>[A-Za-z0-9]{5})' }
}
mutate {
add_field => {
'container' => '%{[attrs][io.kubernetes.container.name]}'
'provider' => ‘K8S'
}
replace => { "hostname" => "%{[beat][name]}.%{site}"}
}
SOLUTION: LOG STORAGE
 Elasticsearch
 Search engine + distributed document index
 Fault tolerant: shard replication
 Vast community of open source tooling
 Retention of 5 days
 Kibana
▻ Web UI for filtering Elasticsearch
▻ Used for searching and consulting logs
▻ Tag-based filtering
FUTURE PLANS: MOVE ES TO AWS
 Current cluster
▻ 3 bare metal servers
▻ 56 CPUs
▻ 256 RAM
▻ 2 Disks (2TB + 4TB)
 AWS cluster
▻ AWS ES managed
▻ 10 i3.2xlarge instances
▻ 64GB RAM
▻ NVMe 1.9 TB disks
▻ 2 AZ
20
21
THANKS!
Any questions?
You can find me at
gregory.sanderson@logmein.com
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Distributed Logging with Kubernetes

  • 2. 2 HELLO! I am Gregory Fodé Sanderson Jive DevOps team You can email me at gregory.sanderson@logmein.com
  • 3. 3
  • 5. 8 DATACENTERS Distributed across US, Brazil & Europe 5
  • 6. 4000 PODS Distributed across US, Brazil & Europe 6
  • 7. 10600 CONTAINERS Distributed across US, Brazil & Europe 7
  • 8. 2TB LOGS PER DAY Distributed across US, Brazil & Europe 8
  • 9. A LOT OF LOGS ! How do we store them ?!?!?!?!?! 9
  • 10. 10
  • 13. SOLUTION: LOG PRODUCERS  Docker reconfigured to add log metadata  DOCKER_OPTS= --log-driver=json-file --log-opt env=K8S_CLUSTER --log-opt labels= io.kubernetes.pod.name, io.kubernetes.container.name, io.kubernetes.container.restartCount, io.kubernetes.pod.namespace --log-opt max-size=20m --log-opt max-file=2
  • 14. SOLUTION: LOG PRODUCERS  Filebeat  Daemonset  /var/lib/docker/containers/*/*.log  Push logs to kafka  Journalbeat  Daemonset  Reads logs from journald (system logs)  Push logs to kafka
  • 15. 15
  • 16. SOLUTION: LOG TRANSPORT  Kafka  Distributed data streaming pipelines  Producer & Consumer model  Fault tolerance for cluster & consumers  Logstash ▻ Consumes logs and sends to ES cluster ▻ All instances part of the same consumer group ▻ Adds metadata to logs
  • 17. SOLUTION: LOG TRANSPORT grok { match => { '[attrs][io.kubernetes.pod.name]' => '(?<service>.*).[0-9]+-(?<pod_id>[A-Za-z0-9]{5})' } } mutate { add_field => { 'container' => '%{[attrs][io.kubernetes.container.name]}' 'provider' => ‘K8S' } replace => { "hostname" => "%{[beat][name]}.%{site}"} }
  • 18. SOLUTION: LOG STORAGE  Elasticsearch  Search engine + distributed document index  Fault tolerant: shard replication  Vast community of open source tooling  Retention of 5 days  Kibana ▻ Web UI for filtering Elasticsearch ▻ Used for searching and consulting logs ▻ Tag-based filtering
  • 19. FUTURE PLANS: MOVE ES TO AWS  Current cluster ▻ 3 bare metal servers ▻ 56 CPUs ▻ 256 RAM ▻ 2 Disks (2TB + 4TB)  AWS cluster ▻ AWS ES managed ▻ 10 i3.2xlarge instances ▻ 64GB RAM ▻ NVMe 1.9 TB disks ▻ 2 AZ
  • 20. 20
  • 21. 21 THANKS! Any questions? You can find me at gregory.sanderson@logmein.com

Editor's Notes

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