Centralized Logging Patterns
A presentation at Jfokus in in Stockholm, Sweden by Philipp Krenn
Centralized Logging Patterns Philipp Krenn @xeraa @xeraa
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Developer @xeraa
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Disclaimer I build highly monitored Hello World apps @xeraa
Example: Java SLF4J, Logback, MDC with logstash-logback-encoder Alternative https://github.com/vy/log4j2-logstash-layout @xeraa
And Everywhere Else .NET: NLog JavaScript: Winston Python: structlog PHP: Monolog @xeraa
Anti-Pattern: print System.out.println(“Oops”); @xeraa
Anti-Pattern: Coupling @xeraa
Parse @xeraa
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Collect Log Lines filebeat.inputs: - type: log paths: - /mnt/logs/*.log @xeraa
Grok https://github.com/logstash-plugins/logstash-patterns-core/blob/ master/patterns/grok-patterns @xeraa
Dev Tools Grok Debugger @xeraa
[2018-09-28 10:30:38.516] ERROR net.xeraa.logging.LogMe [main] user_experience= , session=46, loop=15 Wake me up at night java.lang.RuntimeException: Bad runtime… at net.xeraa.logging.LogMe.main(LogMe.java:30) ^[%{TIMESTAMP_ISO8601:timestamp}]%{SPACE}%{LOGLEVEL:level} %{SPACE}%{USERNAME:logger}%{SPACE}[%{WORD:thread}] %{SPACE}-%{SPACE}%{GREEDYDATA:mdc}%{SPACE}-%{SPACE} %{GREEDYDATA:themessage}(?:\n+(?<stacktrace>(?:.|\r|\n)+))? @xeraa
Logstash Key Value Filter for MDC kv { source => “labels” field_split => “,” trim_key => ” ” } @xeraa
Machine Learning Data Visualizer @xeraa
Pro: No change Con: Regular expression, multiline, format changes @xeraa
Send @xeraa
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logback.xml <appender name=”logstash” class=”net.logstash.logback.appender.LogstashAccessTcpSocketAppender”> <destination>logstash:4560</destination> <encoder class=”net.logstash.logback.encoder.LogstashEncoder”/> </appender> @xeraa
Pro: No files Con: Outages & coupling @xeraa
Structure @xeraa
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Collect JSON filebeat.input: - type: log paths: - /mnt/logs/*.json json: message_key: message keys_under_root: true @xeraa
Stack(trace) Hash @xeraa
Pro: Right format Con: JSON serialization overhead @xeraa
Containerize @xeraa
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Where to put Filebeat? Sidecar @xeraa
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https://github.com/elastic/beats/tree/ master/deploy/docker @xeraa
Docker Logs filebeat.autodiscover: providers: - type: docker hints.enabled: true processors: - add_docker_metadata: ~ @xeraa
Metadata No Docker metadata with the other methods { “docker”: { “container”: { “image”: “java-logging_java_app”, “labels”: { “com”: { “docker”: { “compose”: { “container-number”: “1”, “project”: “java-logging”, “service”: “java_app”, “version”: “1.23.2”, “oneoff”: “False”, “config-hash”: “2b38df3c73c6 } } }, “app”: “fizzbuzz” }, “id”: “9d6d5a7640a457a1e08c422cb0a08 “name”: “java_app” } } 1a68a37443c2006f3f3e4fc16c3c 2a1d7793f2a38841e274b607” f96ff3631fb5356f749b2ac7d8f3719687f” , } @xeraa
Missing the Last Line Waiting for the newline @xeraa
Hints labels: - “app=fizzbuzz” - “co.elastic.logs/multiline.pattern=^\[” - “co.elastic.logs/multiline.negate=true” - “co.elastic.logs/multiline.match=after” @xeraa
Registry File filebeat.registry_file: /usr/share/filebeat/data/registry @xeraa
Ingest Pipeline output.elasticsearch: hosts: [“http://elasticsearch:9200”] index: “docker” pipelines: - pipeline: “parse_java” when.contains: docker.container.name: “java_app” @xeraa
Ingest Pipeline { “description” : “Parse Java log lines”, “processors”: [ { “grok”: { “field”: “message”, “patterns”: [ “^\[%{TIMESTAMP_ISO8601:timestamp}\]%{SPACE}%{LOGLEVEL:log.level} %{SPACE}%{USERNAME:log.package}%{SPACE}\[%{WORD:log.method}\]%{SPACE}%{SPACE}%{GREEDYDATA:labels}%{SPACE}-%{SPACE}%{GREEDYDATA:message_rest} (?:\n+(?<stacktrace>(?:.|\r|\n)+))?” ], “ignore_failure”: true } } ] } Note: \, message vs message_rest, @timestamp vs timestamp, ignore_failure @xeraa
ASCII Art ..-__ ''-._ _.-.. ”-._ .-.-```. ```\/ _.,_ ''-._ ( ' , .-` | `, ) |`-._`-...-` __...-.-.|’_.-'| |-.._ / _.-' |-._ -._-./ .-’ .-’ |-._-.-.__.-' _.-'_.-'| |-.-._ _.-'_.-' |-._ -._-..-‘.-’ .-’ |-._-.-.__.-' _.-'_.-'| |-.-._ _.-'_.-' |-._ -._-..-‘_.-’ _.-’ -._-..-’ _.-’ -._ _.-'-..-’
Redis 4.0.9 (00000000/0) 64 bit Running in stand alone mode Port: 6379 PID: 55757
http://redis.io
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Configuration Templates filebeat.autodiscover: providers: - type: docker templates: - condition: equals: docker.container.image: redis config: - type: docker containers.ids: - “${data.docker.container.id}” exclude_lines: [“^\s+[-`(‘.|_]”] @xeraa
Who Logs the Logger Avoid loops Process without -e filebeat.yml: logging.to_files: true @xeraa
Pro: Hot Con: Complexity @xeraa
Orchestrate @xeraa
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Where to put Filebeat? DaemonSet @xeraa
https://github.com/elastic/beats/tree/ master/deploy/kubernetes @xeraa
Metadata Either in cluster or not processors: - add_kubernetes_metadata: in_cluster: true - add_kubernetes_metadata: in_cluster: false host: <hostname> kube_config: ${HOME}/.kube/config @xeraa
Metadata { “host”: “172.17.0.21”, “port”: 9090, “kubernetes”: { “container”: { “id”: “382184ecdb385cfd5d1f1a65f78911054c8511ae009635300ac28b4fc357ce51”, “image”: “my-java:1.0.0”, “name”: “my-java” }, “labels”: { “app”: “java”, }, “namespace”: “default”, “node”: { “name”: “minikube” }, “pod”: { “name”: “java-2657348378-k1pnh” } }, } @xeraa
Configuration Templates filebeat.autodiscover: providers: - type: kubernetes templates: - condition: equals: kubernetes.namespace: redis config: - type: docker containers.ids: - “${data.kubernetes.container.id}” exclude_lines: [“^\s+[-`(‘.|_]”] @xeraa
Customize Indices output.elasticsearch: index: “%{[kubernetes.namespace]:filebeat}-%{[beat.version]}-%{+yyyy.MM.dd}” @xeraa
Pro: Hot Con: Complexity++ @xeraa
Moar @xeraa
Index Patterns Time based (default: daily) Versioned @xeraa
Sizing Daily volume x retention x replication @xeraa
Index Lifecycle Management ! ” @xeraa
Frozen Indices https://www.elastic.co/guide/en/elasticsearch/reference/6.6/ frozen-indices.html @xeraa
Conclusion @xeraa
Examples https://github.com/xeraa/java-logging @xeraa
Parse Send Structure Containerize Orchestrate @xeraa
Questions? Philipp Krenn @xeraa @xeraa
Most organizations feel the need to centralize their logs once you have more than a couple of systems, SSH and tail will not serve you well any more. This talk presents multiple approaches and patterns with their advantages and disadvantages:
- Parse: Take the log files of your applications and extract the relevant pieces of information.
- Send: Add a log appender to send out your events directly without persisting them to a log file.
- Structure: Write your events in a structured file, which you can then centralize.
- Containerize: Keep track of short lived containers and configure their logging correctly.
- Orchestrate: Stay on top of your logs even when services are short lived and dynamically allocated on Kubernetes.
Video
Resources
The following resources were mentioned during the presentation or are useful additional information.
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GitHub Demo Code
How to log from a Java application to the Elastic Stack.
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