SCALING YOUR TIME
SERIES DATA WITH NEWTS
Jesse White
CTO, The OpenNMS Group Inc.
Presenter bio
▪ OpenNMS since 2012
▪ Cassandra since 2014
▪ ScyllaDB since 2017
OPENNMS
OPENNMS
▪ World's First
▪ Enterprise Grade
▪ Network management
▪ Application platform
▪ Open Source
Scylla Summit 2018: Scaling your time series data with Newts
TIME SERIES
RRDTOOL
TIME SERIES STRATEGIES
▪ rrdtool via JNI (1.0 - 2002)
▪ JRobin (1.1.4 – 2004)
▪ jrrd2 (17.0.0 - 2015)
▪ Newts (17.0.0 - 2015)
▪ Kafka (24.0.0 - 2018)
WRITES > READS
NEWTS
Scylla Summit 2018: Scaling your time series data with Newts
THE MODEL
Resources are used to group
related metrics.
Metrics are used to identify
specific values.
Samples represent the value of
a resource metric at some
instance in time.
MODEL EXAMPLE
Resource ID:
1:opennms-jvm:org_opennms_newts_name_repository_insert_time
Metrics:
NewtsInsert50, NewtsInsert75, NewtsInsert95, NewtsInsert98, …
SAMPLES
LATE AGGREGATION
The target range is split into
intervals, where we take
weighted averages of the
corresponding samples.
The heartbeat defines up to
how long a sample is
considered to be valid.
TERMS
SEARCH
env:uat AND (dc:dc1 OR dc:dc2)
NEWTS + OPENNMS
GRAPHING
SCALE UP AND OUT
▪ 1004234.38 samples/s
▪ Cassandra:
• 5 * i3.4xlarge
▪ Load:
• 3 * m5.4xlarge
ScyllaDB
▪ Cassandra (3.11)
• 1004234.38 samples/s
▪ ScyllaDB (2.3.1)
• 1823485.12 samples/s
• 1.8x improvement on
write heavy workload
OPERATIONAL ISSUES
▪ Estimating disk space usage
▪ Cluster management
▪ Data mangling
• Deleting a point
• Renaming a series
NEWTS.IO
Thank You
Any Questions ?
Please stay in touch
jesse@opennms.ca
@jesse_white_

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Scylla Summit 2018: Scaling your time series data with Newts