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InfluxDays 2022
Build, Ship, Repeat
Barbara Nelson, VP of Engineering
We keep building what developers need,
wherever you are:
• OSS
• On-premise
• Cloud
Barbara Nelson
VP, Engineering
For Cloud, we have a CI/CD pipeline:
• Develop/Test/Stage/Release within hours
• Feature flags for sophisticated control over
when features ‘go live’
InfluxDB is getting better
Collecting Data
Native Collectors Telegraf Client Libraries
Scrapers Ecosystem InfluxDB API
Native Collectors are a no-code
way to ingest real-time, streaming,
messaging event data to InfluxDB.
Telegraf is a plugin-driven server
agent for collecting and sending
metrics and events from
databases, systems, and IoT
sensors.
Language and platform-specific
packages that provides a
programmatic way to interface
with InfluxDB.
Scrape Prometheus-formatted
metrics from an HTTP-accessible
endpoint and store them in
InfluxDB.
Configure third-party
technologies to send line
protocol directly to InfluxDB.
Build your own with the
InfluxDB API, which provides a
programmatic interface for
interactions with InfluxDB
Storing the data
By the numbers (in our multi-tenanted Cloud environment)
A few example customer workloads:
• One customer is writing 345GB every hour.
• Another customer is executing 80k queries per hour.
268TB
Compressed
tsdb data
10.9B/s
Ingest bytes
11M
Points/s
~2000
Queries/s
Querying the data - from the UI
Save and Reuse queries
Language enhancements
Flux: polymorphic labels
Flux: dynamic types
Flux: inner, outer, left and right joins
Flux: isType
Flux modules
Performance – It gets better and better
Twelve months of query performance for our performance test suite.
from(bucket: v.bucket)
|> range(start: v.timeRangeStart)
|> filter(fn: (r) => r["_measurement"] == "cpu")
|> group(columns: ["_field"])
|> aggregateWindow(every: v.windowPeriod, fn: mean)
A few extra goodies
• Explicit schema
• Flux: http and json
import "array"
import "experimental/json"
import "experimental/http/requests"
headers = ["x-api-key": TOKEN_REDACTED,]
url = "https://yfapi.net/v6/finance/quote"
response = requests.get(url:url, params: ["symbols":["AAPL"]], headers: headers)
array.from(rows: [{headers: display(v: response.headers)}])
jsonData = json.parse(data: response.body)
array.from(rows: jsonData.quoteResponse.result)
|> map(fn: (r) => ({ _time: now(),
_field: "marketPrice",
_measurement: "stockQuote",
_value: r.regularMarketPrice,
symbol: r.symbol,
}))
|> yield(name: "ts")
Tying it all together - the edge and the cloud
InfluxDB Platform
Telegraf
Client
Libraries
Native
Ecosystem
Data
Sources
Edge
Telegraf
Client
Libraries
Native
Ecosystem
Data
Sources
Edge
Telegraf
Client
Libraries
Native
Ecosystem
Data
Sources
Edge
T H A N K Y O U

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Barbara Nelson [InfluxData] | Build, Ship, Repeat: Milestones for InfluxDB | InfluxDays 2022

  • 1. InfluxDays 2022 Build, Ship, Repeat Barbara Nelson, VP of Engineering
  • 2. We keep building what developers need, wherever you are: • OSS • On-premise • Cloud Barbara Nelson VP, Engineering For Cloud, we have a CI/CD pipeline: • Develop/Test/Stage/Release within hours • Feature flags for sophisticated control over when features ‘go live’ InfluxDB is getting better
  • 3. Collecting Data Native Collectors Telegraf Client Libraries Scrapers Ecosystem InfluxDB API Native Collectors are a no-code way to ingest real-time, streaming, messaging event data to InfluxDB. Telegraf is a plugin-driven server agent for collecting and sending metrics and events from databases, systems, and IoT sensors. Language and platform-specific packages that provides a programmatic way to interface with InfluxDB. Scrape Prometheus-formatted metrics from an HTTP-accessible endpoint and store them in InfluxDB. Configure third-party technologies to send line protocol directly to InfluxDB. Build your own with the InfluxDB API, which provides a programmatic interface for interactions with InfluxDB
  • 4. Storing the data By the numbers (in our multi-tenanted Cloud environment) A few example customer workloads: • One customer is writing 345GB every hour. • Another customer is executing 80k queries per hour. 268TB Compressed tsdb data 10.9B/s Ingest bytes 11M Points/s ~2000 Queries/s
  • 5. Querying the data - from the UI
  • 6. Save and Reuse queries
  • 7. Language enhancements Flux: polymorphic labels Flux: dynamic types Flux: inner, outer, left and right joins Flux: isType Flux modules
  • 8. Performance – It gets better and better Twelve months of query performance for our performance test suite. from(bucket: v.bucket) |> range(start: v.timeRangeStart) |> filter(fn: (r) => r["_measurement"] == "cpu") |> group(columns: ["_field"]) |> aggregateWindow(every: v.windowPeriod, fn: mean)
  • 9. A few extra goodies • Explicit schema • Flux: http and json import "array" import "experimental/json" import "experimental/http/requests" headers = ["x-api-key": TOKEN_REDACTED,] url = "https://yfapi.net/v6/finance/quote" response = requests.get(url:url, params: ["symbols":["AAPL"]], headers: headers) array.from(rows: [{headers: display(v: response.headers)}]) jsonData = json.parse(data: response.body) array.from(rows: jsonData.quoteResponse.result) |> map(fn: (r) => ({ _time: now(), _field: "marketPrice", _measurement: "stockQuote", _value: r.regularMarketPrice, symbol: r.symbol, })) |> yield(name: "ts")
  • 10. Tying it all together - the edge and the cloud InfluxDB Platform Telegraf Client Libraries Native Ecosystem Data Sources Edge Telegraf Client Libraries Native Ecosystem Data Sources Edge Telegraf Client Libraries Native Ecosystem Data Sources Edge
  • 11. T H A N K Y O U