Organizing Metrics: Hierarchical or Tagged?

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Organizing Metrics: Hierarchical or Tagged? Paul Dix CEO of InﬂuxDB paul@inﬂuxdb.com @pauldix

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Organizing Metrics?

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Necessary when you have thousands, tens, hundreds, or millions

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Discovery What metrics do I have?

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Merging and Aggregating Combine these and give me a result

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Hierarchy

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Artifact of Whisper’s implementation

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Series are round robin ﬁles on disk organized in directories (hierarchy)

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Meta data encoded in series name

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Tagged?

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OpenTSDB Metrics mysql.bytes_received \ ! 1287333217 327810227706 \ ! schema=foo host=db1

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mysql.bytes_received \ ! 1287333217 327810227706 \ ! schema=foo host=db1 Name

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mysql.bytes_received \ ! 1287333217 327810227706 \ ! schema=foo host=db1 Tags

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Single Level Hierarchy + Tags

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Hierarchy: names

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Meta data encoded in series name and tags

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Data [ { "name": "cpu", "columns": ["time", "value", "host"], "points": [ [1395168540, 56.7, "foo.influxdb.com"], [1395168540, 43.9, "bar.influxdb.com"] ] } ]

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Flat

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list series

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list series /.*dc\.USWest/

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select percentile(90, value) from merge(/cpu_wait.*dc\.USWest.*/) group by time(10m) where time > now() - 4h

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Doesn’t scale well to millions of series!

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select percentile(90, value) from cpu_wait group by time(10m) where time > now() - 4h and dataCenter = ‘USWest’

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Doesn’t scale well to thousands of hosts!

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We have to pick a method

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Hierarchy vs. Tags?

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Religious Debate?

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Emacs vs. Vim

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i.e. debates that can’t be solved

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Scientiﬁc Debate?

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acceleration due to gravity

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Things that have a clear testable answer

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Hierarchy vs. Tags a bit of both?

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Tags are vastly superior to hierarchies

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What questions can you ask?

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What sensors do I have? CPU Idle, network in bytes, memory used, redis key count, etc.

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OpenTSDB names

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cpu_wait network_in_bytes network_out_bytes …

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Graphite traverse hierarchy

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app.foo.dc.uswest.host.servera.cpu_wait app.foo.dc.uswest.host.servera.network_in_bytes app.foo.dc.uswest.host.servera.network_out_bytes …

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app.foo.dc.uswest.host.servera.cpu_wait app.foo.dc.uswest.host.servera.network_in_bytes app.foo.dc.uswest.host.servera.network_out_bytes … Sensor at the end

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What values do I have on dimension X? hosts, data centers, services, applications

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OpenTSDB traverse one level and tags

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redis_connections response_times.90 …

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app.foo.dc.uswest.host.servera.cpu_wait app.foo.dc.uswest.host.servera.network_in_bytes app.foo.dc.uswest.host.servera.network_out_bytes …

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Show me all time series for X dashboard for MySQL, dashboard for host

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Computations percentiles across sets of hosts, data centers, services

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Pure tagging

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{! "Name": "CPU Wait",! "Host": "serverA.influxdb.com",! "Data Center": "US West"! }!

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{! "Name": "CPU Wait",! "Host": "serverA.influxdb.com",! "Data Center": "US West"! }! Readable Names!

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{! "Name": “Redis Connections",! "Host": "serverA.influxdb.com",! "Data Center": "US West"! }! Queryable! Which hosts have redis connections?

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{! "Name": "Erorrs",! "Host": "serverA.influxdb.com",! "Data Center": "US West",! "Application": "My super rad app"! }! Queryable! What names (sensors) do I have for My super rad app?

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Queryable! What names (sensors) do I have at 1h precision? {! "Name": "Erorrs",! "Host": "serverA.influxdb.com",! "Data Center": "US West",! "Application": "My super rad app",! "Precision": "1h"! }!

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Computation select percentile(90)! from ("Name": "CPU Wait", "Data Center": "US West")! group by time(10m)! where time > now() - 6h!

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Hierarchy on the ﬂy What tags co-occur with a given tag?

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Faceted Serch

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Given “Host” and “Data Center” what other tags are there?

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"Data Center" = "US West" ! "Name": 2153 "Host": 256 "Service": 20 "Precision": 10 "Application": 4

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Need to be able to add dimensions/tags

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Need to support a large number of tags Both for a single data point and over all

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Pure tagging gives you much more power than hierarchies

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Can be combinatorial OpenTSDB hot spots, etc

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Need to be able to deﬁne indexing behavior for tags

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Can it work?

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This is part of what InfluxDB is working on Feedback welcome! http://influxdb.com/community.html @InfluxDB