Kristina Robinson | Engineering Manager
UI, InfluxData
Understand and
Visualize your Data with
InfluxDB Cloud

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| Understand and Visualize your Data with InfluxDB Cloud: Agenda
- Ingest (covered by previous talk)
- Explore
- Analyze
- Act

Data Explorer / Notebooks
Dashboards
Visualizations
Explore

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● Data Explorer and Notebooks both allow:
○ Simple query construction of bucket data
○ View capability of query results as visualizations
○ Saving queries as dashboard cells or tasks
● Notebooks has added streamlined table views, in line
commenting while creating queries and graphs, and the ability
to save your interim work that lead to dashboard cells or tasks,
for reuse or sharing among co-workers.
Data Explorer / Notebooks

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Notebooks View

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Notebooks View (cont)

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New Visualizations -- Mosaic
blue: win
purple: loss
red: bye
orange: tie

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Mosaic Pt 2 - GitHub Repo Build Status
blue:
success
purple:
failure

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Geo Maps
● Currently requires hard-coding either “lat/lon” pairs or calculated
geo-temporal location returned by Flux in the “s2_cell_id” tag. (see
article on Geo-Temporal Flux: an overview)
International Space Station Trajectory Mapping

Flux
Downsampling Tasks
Annotations
Analyze

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“Downsampling is the process of aggregating high-resolution time series within windows of time
and then storing the lower resolution aggregation to a new bucket.” Anais Dotis-Georgiou
Why Downsample?
● allows you to reduce the overall disk usage as you collect data over time.
● improve query performance for InfluxDB OSS or Cloud
● eliminate the noise of high-precision time series which in turn allows you to analyze and derive value from
your historical time series faster
How To Downsample?
● Use a downsampling task
○ Source bucket is high precision data, typically lower retention policy
○ Destination bucket is aggregated data, typically higher retention policy
● Create the task with the API or the UI
Flux and the Art of Downsampling

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View Task Runs
● Select a Task, then to look at its logs, click the gear icon on the right of your
task. Select View Task Run.
● If you click View Logs, you can see the errors that caused a task failure.

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Annotations
● Click on `Annotations` to view
● Click on `Enable 1-Click
Annotations` to enable writing
● Double click on the plot to
annotate, and add description

Checks (Deadman, Threshold)/Statuses
Notification/Notification Rules
Alerts/Notification EndPoints ( Slack, PagerDuty,
Email)
Coming Soon - Triggers
Act

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Checks
● Threshold
● Deadman
● Custom
Notifications
Notification Rules
Statuses Notification
Endpoints
InfluxDB
● Slack
● Email
● PagerDuty
While statuses are the output of a check, notifications are the output of a notification rule.
1. Run Check
2. Write Status
3. Run Notification Rules
4. Write Notification to
InfluxDB
5. Send MetaData to Endpoint

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Tasks vs. Checks vs. Notification Rules
● All are tasks under the covers
● Custom Tasks are written to user’s bucket
● Checks and Notification Rules are written to the “_monitoring” bucket
● Custom Checks must have a defined schema, and use the
“monitor.check()” function and only use “CRIT”, “WARN”, “INFO”, and
“OK” values assigned to your time series data.
● Custom Notification Rules must have a defined schema, write a
notification to the “_monitoring” bucket, using a polling interval (can
use “schedule every internal function”), and optionally can a
notification endpoint.
● For detailed information please refer to this article:
https:/
/www.influxdata.com/blog/influxdbs-checks-and-notifications
-system/

Questions