It is important for a time-series database to provide efficient storage, aggregation, and query of time-series data. Elevating a time-series database to a core operational technology of the enterprise, however, involves so much more. In this talk, I will explore important considerations that take a time-series database from being just another data-store, to a critical infrastructure for operational intelligence. I will explore challenges related to time, change management, incorporating asset models from the business domain, and integration with other operational technologies, like streaming-data platforms.

1. FromaTime-Series Database
toaKey OperationalTechnology
forthe Enterprise

7. Time
Assets
Integrations

10. Time
Assets
Integrations

18. Whatdatawereavailable
for operational decisions?

20. Whatabout
revising data?

23. Timeat Scale

27. Time Frames

31. Time
» A lot more than just sampled time
» Latency, modifications, deletions
» Time frames for context
» Investments in ingestion pipeline

32. Time
Assets
Integrations

33. cpu,
app=billing,
version=2.0,
data_center=OAK,
cost_center=FIN,
usage_idle=99.01
1515955376000000000

35. Whatisanasset?

40. Howareassets performing
inthe aggregate?

46. Howare assets
changing overtime?

51. Whatis upstream, downstream?

55. Assets
» We need more than GROUP BY
» Hierarchical, directional, proximal relationships
» Assets and relationships change over time
» Cannot associate all metadata on ingest
» Security and role-based access

56. Time
Assets
Integrations

57. SCADADCS
AMS EMS DMS OMS MES
GIS CRM ERPSCM
PKI LDAP OIDC
Databases Services

58. Howdoweintegrate
assetdata
and
time-series?

62. Integrationwith
Streaming-Data
Platforms?

64. Howdoweintegrate
Systems reliably?

71. Source

72. Sink

73. Element

74. Flow

75. Graph

76. Influx Flow

77. Influx Flow

78. Influx Flow

79. AkkaStreams
Consumer.committableSource(settings, topic)
.map(parse)
.filter(x => x.isLegacy)
.via(influxdb)
.runWith(commitOffset)

82. Integrations
» Many systems-of-record for asset information
» An asset service is inevitable
» Affinity to streaming-data platforms
» Embrace Reactive Systems / Reactive Streams

83. Time
Assets
Integrations

84. TakeAways
» Time is multifaceted
» Ingestion pipeline requires a lot of investment
» Asset data and relationships for context
» Asset data from many sources, changes over time
» Integrate with many other systems
» Reactive Systems/Streams for reliability

85. @breckcs
www.colinbreck.com

86. Questions?