Metrics & more
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Monitoring big data systems at scale More Info: http://blog.sematext.com http://www.sematxt.com/
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Metrics & more
- 1. Metrics & more how to monitor big data systems @scale!
- 2. About me Stefan Thies @seti321 ! DevOps Evangelist @sematext!
- 3. Why monitoring is important • Tuning ! • Detecting Bugs! • Stability! • Benchmarks! • Capacity planning!
- 4. Monitoring tools must endure the load
- 5. Would you start building own scales, when you would operate a real zoo? - What’s your mechanical engineering expertise? - How long does it take to get tools and raw material? - Who feeds the animals while being in the workshop? - When do we need it and could it be ‚in time‘?
- 6. Let’s take something from the shelf and build a custom interface ‚load balancers‘!‚Custom Interface‘!
- 8. • Many VM’s & Apps - each one generates ~ 5-130 metrics in short intervals! • Aggregation, Compromises on resolutions etc.! • Transactions - each creates N log entries ! • limit recording, time based indices + aliases! • High throughput - high rate of logs & metrics! • build a monitoring infrastructure (remember this)! !
- 9. METRIC SOURCE! NUMBER OF METRICS TO COLLECT! OS (CPU. Mem, Disk) 21 Hadoop 133 Hbase 68 Elasticsearch 62 Apache Storm 25 Total 309 ~ 3,1 Mio. data points per week x N machines ! ! Example - No. of metrics per application!
- 10. 25 Metric Categories ! Metrics – Apache Kafka!
- 11. • Find out and define metrics to collect ! • Install, configure collectd, statsd, graphite, …! • Build, install / configure available agents! • Define reports or arrange all collected metrics to dashboards e.g. grafana, …! • This are the basics!! • automate deployment for agents! #monitoringsucks
- 12. #monitoringlove • Integrate with the organization ! • alerting workflows + multi-user + security! • Scale out: ! • Distributed event processing (e.g. Kafka)! • Scalable data stores (e.g. Elasticsearch, HBase)! • Add intelligence: ! • Machine learning for metrics & events! • Alerting & Reporting based on it!
- 13. Monitoring Architecture Receiver! Aggregator! Scalable! Storage! Reporting! Machine Learning! Alerting! Forwarding! User Management! Agents for all monitored applications! Visualisation! Admin!
- 15. What can we find in the wild?
- 16. Network Level • Packets: loss, size, counts! • Latency, jitters, delays! • Bandwidth – total, per link, per service, ! • Firewalls / security breaches! • IDS, IPS – yet another malware detected ! • On physical, transport, application layer, ...!
- 17. Server Level • Disk I/O! • CPU load! • Disk Space ! • Memory! • Logs / security / events / syslog!
- 18. Standard Applications • Webservers, Databases, Search Engines, MQ‘s! • Request rates, disk space, partitions, locks, connections, queue sizes, cache sizes! • Logfiles!
- 20. Example: Elasticsearch Link: Top Metrics !
- 21. Own Application Custom Metrics & Logs • Logs & API for measurement! • Time measurements, KPI‘s, Usage tracking, Object counters, Click Streams!
- 22. Application Traces • Post mortem analysis! process.on (‚exit‘, heapdumpAndDie) • Dtrace ! • Call Traces, Error stacks! • Heapdumps & Flamegraphs!
- 23. Log files as source of metrics • Simplest: log rate of an application! • Generate Count for operations! • Apply search and count related events! • E.g. count slow operations! • Extract values from logs ! • Apply regex or field search to extract numbers !
- 24. Logs2Metrics Logs! Index! Scheduled Queries! aggregate all messages matching e.g. „session opened“ every Minute e.g. on auth.log Custom ! Metric! Monitoring ! System!
- 25. A Checklist for the introduction of monitoring solutions
- 26. Define your criterias • Coverage of monitors/agents! • Quality of agents & setup! • Multi-User Support! • Reporting Capability & Secure Sharing! • Alerting capabilities! • Integrations / Notifications / API‘s! • Estimate required resources !
- 27. Map your landscape • Quantity of servers & applications to monitor! • What are the components of your App-Stack?! • Linux on AWS, NGINX, Node.js, REDIS, Elasticsearch! • Which programming languages are used?! • Can you find agents/monitors for all your ‚Apps‘?! • List missing parts -> find other or build a monitor!
- 28. Customizing – custom metrics/plugins • What metrics are relevant for each ‚App‘?! • What is covered by existing agents?! • How to aggregate each of this metrics? ! • min, max, sum, avg! • Pre-Aggregation vs. Query Time Aggregation!
- 29. Dashboards • Graphs! • Which metrics belong together?! • Display options ….! • Query language ! • Dashboards! • What combination of graphs provides best insight?! • Can you share and re-use arranged dashboards for similar setups or situations? ! • Or do you need to configure it again for other servers?! • Is sharing secured? Or just a link to your UI?!
- 30. Alerts • Threshold based alerts! • Status changes ! • Heartbeat alerts! • Anomaly detection! • Challenges: Number of alert rules and queries ! & tuning ‘noise level’!
- 32. • Metrics show „something happens“! • Logs provide evidence „what happened“! • Faster insights by reporting them together! • Correlate logs and metrics! • Metrics could be created from logs! Integrate metrics & logs
- 33. Correlate Logs & Metrics
- 34. A brief overview of Centralizing Logs
- 36. raw logs! parser! Log shipper! storage! Visualization! Kibana!Elasticsearch!Logstash! Where is the work?! Centralizing Logs with ELK ! files, syslog! Format adaption,! & transport! Tuning ! Maintenance! Queries! Security !
- 37. • Input: Unstructured log lines! • Filter & Parser: Grok / RegEx! • Output: Structured JSON! • Forwarder: ! • Elasticsearch, …!
- 38. • Schema: Define the right Mapping • Insert rate:! • Use bulk indexing! • Increase refresh time for higher insert rate! • Volume: ! • Aliases and time based indices! • Memory usage: configure caching limits! Setup Elasticsearch
- 39. • How to secure it? ! • Proxies, Security plugins, Hosted Solutions! • Queries and dashboard creation! • generators/templates for specific setups! • Learn Lucene query language!
- 40. Kibana
- 41. Thank you for ! your attention! http://blog.sematext.com!