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[131] packetbeat과 elasticsearch

This document summarizes a presentation about Packetbeat and monitoring distributed systems. It discusses how Packetbeat passively captures network packets, decodes protocols, and matches requests and responses to create JSON objects. It then sends this data to Elasticsearch for analysis. Aggregations like histograms, percentiles, and moving averages are used to analyze latency, identify slow methods, and detect anomalies in metrics over time. Other Beats like Topbeat, Filebeat, and Metricsbeat are also briefly introduced.

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Get real-time insights from your application with Packetbeat & Elasticsearch
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 2 This presentation contains • Lots of JSON objects • Pictures of cows, elks and musical instruments • A bit of Go code • Anomaly detection via moving averages
www.elastic.co 3 Tudor Golubenco twitter.com/tudor_g github.com/tsg I am
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 4 I work for
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 5 the company behind Elasticsearch Logstash Kibana
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 6 also known as the ELK stack Photo  credit:  https://www.flickr.com/photos/lsmith2010/8215026548
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 7 Distributed from day 1 Logstash 1.5 release party
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 8 Open source culture Image  credit:  https://www.flickr.com/photos/tappnel/5798812875 • We live in GitHub • We talk Pull Requests • Conferences • Community • Blog posts
www.elastic.co Copyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 9 That’s not all Found Beats Watcher ShieldMarvel ES  for  Hadoop
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 10 Started an open source project Packetbeat
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 11 We wanted to do better monitoring and troubleshooting for distributed systems
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 12 Idea look at the communication between services
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 13 Capture network packets • Passively listen to network packets • Works on a copy of the traffic • It doesn’t add latency • It cannot break your application Image  credit:  https://www.flickr.com/photos/bigdrumthump/3223280727
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 14 Packet capturing 1.  Using  port  mirroring 2.  As  an  “agent”
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 15 Sniffing from a technical PoV • libpcap (tcpdump), supports all Unix like systems • Winpcap, supports Windows • For Go, gopacket provides bindings and more • High speed API for packet capturing on Linux: af_packet Image  credit:  https://www.flickr.com/photos/57881779@N04/7930362242/
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 16 Decoding
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 17 Matching requests and responses • Pipelining complicates matching the requests with the responses.
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 18 Create a JSON object for each request-response pair
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 19 SQL example
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 20 Memcache example
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 21 DNS example
www.elastic.co Copyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 22 • Control information: IP addresses, TCP/ UDP ports • Request type: HTTP method, SQL query, RPC function • Request data: form parameters, payload • Response data: status code, error message, payload • Timing data: timestamp of the request, latency Packet data
www.elastic.co Copyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 23 Packetbeat: Overview
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 24 There’s more to apps than packets Packetbeat   Listens  to  the  “beat”  of   the  network  packets. Topbeat   Listens  to  the  “beat”  of   the  operating  system   metrics. Image  credits:   https://www.flickr.com/photos/7147684@N03/921738874/   https://www.flickr.com/photos/bigdrumthump/3223280727   https://www.flickr.com/photos/jadeashleyphotography/6584949945/   https://www.flickr.com/photos/mitosettembremusica/2839965900/   Filebeat   Listens  to  the  “beat”  of   logs. Metricsbeat   Listens  to  the  internal   “beat”  of  systems  via   APIs.
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 25 Topbeat • Like the Unix top command but sending the data periodically to Elasticsearch • Works also on Windows
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 26 Topbeat system wide and per process stats CPU  “steal”  time Total  /  used  /  free   memory CPU  stats Per  process  stats CPU  time     consumed Process  pid,  name,   parent  pid,  etc. Memory  used
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 27 Topbeat output objects File  system  stats Mount  point Device  name Total,  used,  free   disk  space
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 28 Filebeat • Do one thing well: • Send log files to Logstash & Elasticsearch • Light on consumed resources • Easy to deploy on multiple platforms • A “Beat” based on the Logstash-Forwarder source code
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 29 Beats have libbeat in common • Go library • Provides common things for all Beats: • logging, service handling, configuration file handling, CLI flags • Outputs and filters Dev  guide  for  creating  a  new  Beat:  https://www.elastic.co/guide/en/beats/libbeat/current/index.html
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 30 Deployment: directly to ES • Option 1: Insert directly into Elasticsearch via the bulk API • Security can be provided via Shield and HTTPs
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 31 Deployment: Send to Logstash • Option 2: Insert via Logstash • Uses the Lumberjack protocol which offers security • Gives the opportunity of enriching or modifying the data
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 32 Getting insights from the data • Elasticsearch aggregations • Split the data into buckets • Apply a function over the data • Freely combine them by nesting • Work with multiple shards
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 33 Date histogram •Splits data in buckets of time
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 34 Date histogram response
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 35 Percentiles aggregation 95th percentile value means that 95% of the values are smaller than it
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 36 Percentile aggregation response
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 37 Percentile aggregation •Approximate values •T-digests algorithm by Ted Dunning •Accurate for small sets of values •More accurate for extreme percentiles
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 38 Date histogram nested with percentiles
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 39 Date histogram with nested percentiles
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 40 Result
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 41 Kibana config
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 42 Latency histogram
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 43 Histogram by response time • Splits data in buckets by response time • [0-10ms), [10ms-20ms), …
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 44 Histogram by response time
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 45 Add a date histogram
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 46 Response times repartition
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 47 Kibana config
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 48 Slowest RPC methods •Combines terms and percentiles aggregations
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 49 Terms aggregation • Buckets are dynamically built: one per unique value • By default: top 10 by document count • Approximate because each shard can have a different
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 50 Order by 99th percentile
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 51 Kibana config
www.elastic.co 52 • New in Elasticsearch 2.0 (currently in beta) • Work on the results of other aggregations Pipeline aggregations
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 53 Derivative aggregation • Metric constantly growing • Take first order derivate to see the speed of growth
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 54 Simple moving average • [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] • with a window size of 5: • (1 + 2 + 3 + 4 + 5) / 5 = 3 • (2 + 3 + 4 + 5 + 6) / 5 = 4 • (3 + 4 + 5 + 6 + 7) / 5 = 5 • etc.
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 55 Exponentially weighted moving average • Older values become exponentially less important
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 56 Moving average - dynamic thresholds • yellow - measured values • purple - moving average (ewma) • green - threshold, mean + (3 * standard deviation)
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 57 Request Extended  stats  agg  for   mean  and  std   deviation Moving  averages   aggs  for  mean  and   std Bucket  script  agg Details:  https://www.elastic.co/blog/staying-­‐in-­‐control-­‐with-­‐moving-­‐averages-­‐part-­‐1
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 58 Cyclic trends - anomalies • EWMA lags behind too much • The values constantly hit the threshold
www.elastic.coCopyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 59 Cyclic trends - anomalies • Holt-Winters (triple exponential) model works better for seasonal data • Requires two periods to bootstrap the algorithm
www.elastic.co Copyright Elastic 2015 Copying, publishing and/or distributing without written permission is strictly prohibited 60 Thanks • https://discuss.elastic.co/c/beats • Twitter: @tudor_g • We have stickers!