InfluxDB
InfluxDB is an open source time series database platform that lets users collect, process, and analyze data to optimize their infrastructure.
InfluxDB parameters and supported features in Nobl9
- General support:
- Release channel: Stable, Beta
- Connection method: Agent, Direct
- Replay and SLI Analyzer: Not supported
- Event logs: Supported
- Query checker: Not supported
- Query parameters retrieval: Not supported
- Timestamp cache persistence: Supported
- Query parameters:
- Query interval: 1 min
- Query delay: 1 min
- Jitter: 15 sec
- Timeout: 60 sec
- Agent details and minimum required versions for supported features:
- Plugin name: n9influxdb
- Query delay environment variable: INFLUXDB_QUERY_DELAY
- Timestamp cache persistence: 0.65.0
- Additional notes:
- No support for InfluxQL.
- Write queries in Flux instead. Flux queries are only validated against bucket name, params.n9time_start, params.n9time_stop
Creating SLOs with InfluxDBβ
Nobl9 Webβ
Follow the instructions below to create an SLO with InfluxDB in the UI:
- Navigate to Service Level Objectives.
- Click
.
- Select a Service.
It will be the location for your SLO in Nobl9. - Select your InfluxDB data source.
- Metric refers to the way of calculating and interpreting calculate and interpret data from your data source.
- Threshold metric is defined by a single numerical value (the threshold) that separates satisfactory performance from unsatisfactory performance. It's represented by a single time series evaluated against the threshold.
- Ratio metric expresses the performance as a fraction or proportion, typically by dividing the number of successful events by the total number of potential events (successes + failures). It's represented by two-time series for comparison for good events and total events.
For ratio metrics, select the Data count method.SLI values for good and totalWhen choosing the query for the ratio SLI (countMetrics), keep in mind that the values ββresulting from that query for both good and total:- Must be positive.
- While we recommend using integers, fractions are also acceptable.
- If using fractions, we recommend them to be larger than
1e-4=0.0001. - Shouldn't be larger than
1e+20.
-
Specify your Flux Query. The query must include the following:
- A bucket, which is a named location in InfluxDB where your time series data is stored.
- Example:
from(bucket: "your-bucket-name")
- Example:
- A time range defined by Nobl9's
params.n9time_startandparams.n9time_stopplaceholders. Add this by piping arange()function to your query.- Example:
|> range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop))
- Example:
If you are adapting a query from an InfluxDB dashboard, replace the predefined variables
v.timeRangeStartandv.timeRangeStopwith Nobl9'stime(v: params.n9time_start)andtime(v: params.n9time_stop).Time range handlingAlways use Nobl9's placeholders to define the time range. Do not use a fixed or hardcoded time frame (e.g.,
range(start: -1h)), as Nobl9 automatically inserts the correct time window when the query is executed. - A bucket, which is a named location in InfluxDB where your time series data is stored.
Click to open query samples
'from(bucket: "integrations")
|> range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop))
|> aggregateWindow(every: 15s, fn: mean, createEmpty: false)
|> filter(fn: (r) => r["_measurement"] == "internal_write")
|> filter(fn: (r) => r["_field"] == "write_time_ns")'
'from(bucket: "integrations")
|> range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop))
|> aggregateWindow(every: 15s, fn: mean, createEmpty: false)
|> filter(fn: (r) => r["_measurement"] == "internal_write")
|> filter(fn: (r) => r["_field"] == "write_time_ns")'
'from(bucket: "integrations")
|> range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop))
|> aggregateWindow(every: 15s, fn: mean, createEmpty: false)
|> filter(fn: (r) => r["_measurement"] == "internal_write")
|> filter(fn: (r) => r["_field"] == "write_time_ns")'
- Define the Time window for your SLO:
- Rolling time windows constantly move forward as time passes. This type can help track the most recent events.
- Calendar-aligned time windows are usable for SLOs intended to map to business metrics measured on a calendar-aligned basis.
- Configure the Error budget calculation method and Objectives:
- Occurrences method counts good attempts against the count of total attempts.
- Time Slices method measures how many good minutes were achieved (when a system operates within defined boundaries) during a time window.
- You can define up to 12 objectives for an SLO.
Similar threshold values for objectivesTo use similar threshold values for different objectives in your SLO, we recommend differentiating them by setting varying decimal points for each objective.
For example, if you want to use threshold value1for two objectives, set it to1.0000001for the first objective and to1.0000002for the second one. - Add the Display name, Name, and other settings for your SLO:
- Name identifies your SLO in Nobl9. After you save the SLO, its name becomes read-only.
Use only lowercase letters, numbers, and dashes. - Select No data anomaly alert to receive notifications when your SLO stops reporting data for a specified period:
- Choose up to five supported Alert methods.
- Specify the delay period before Nobl9 sends an alert about the missing data.
From 5 minutes to 31 days. Default: 15 minutes
- Add alert policies, labels, and links, if required.
Limits per SLO: 20 alert policies or links, 30 labels.
- Name identifies your SLO in Nobl9. After you save the SLO, its name becomes read-only.
- Click CREATE SLO
YAMLβ
- Threshold (rawMetric)
- Ratio (countMetric)
apiVersion: n9/v1alpha
kind: SLO
metadata:
name: api-server-slo
displayName: API Server SLO
project: default
labels:
area:
- latency
- slow-check
env:
- prod
- dev
region:
- us
- eu
team:
- green
- sales
annotations:
area: latency
env: prod
region: us
team: sales
spec:
description: Example InfluxDB SLO
indicator:
metricSource:
name: influx-d-b
project: default
kind: Agent
budgetingMethod: Occurrences
objectives:
- displayName: Good response (200)
value: 200
name: ok
target: 0.95
rawMetric:
query:
influxdb:
query: >-
from(bucket: "integrations")
|> range(start: time(v: params.n9time_start), stop: time(v:
params.n9time_stop))
|> aggregateWindow(every: 15s, fn: mean, createEmpty: false)
|> filter(fn: (r) => r["_measurement"] == "internal_write")
|> filter(fn: (r) => r["_field"] == "write_time_ns")
op: lte
primary: true
service: api-server
timeWindows:
- unit: Month
count: 1
isRolling: false
calendar:
startTime: '2022-12-01 00:00:00'
timeZone: UTC
alertPolicies:
- fast-burn-5x-for-last-10m
attachments:
- url: https://docs.nobl9.com
displayName: Nobl9 Documentation
anomalyConfig:
noData:
alertMethods:
- name: slack-notification
project: default
alertAfter: 1h
apiVersion: n9/v1alpha
kind: SLO
metadata:
name: api-server-slo
displayName: API Server SLO
project: default
labels:
area:
- latency
- slow-check
env:
- prod
- dev
region:
- us
- eu
team:
- green
- sales
annotations:
area: latency
env: prod
region: us
team: sales
spec:
description: Example InfluxDB SLO
indicator:
metricSource:
name: influx-d-b
project: default
kind: Agent
budgetingMethod: Occurrences
objectives:
- displayName: Good response (200)
value: 1
name: ok
target: 0.95
countMetrics:
incremental: true
good:
influxdb:
query: >-
from(bucket: "integrations")
|> range(start: time(v: params.n9time_start), stop: time(v:
params.n9time_stop))
|> aggregateWindow(every: 15s, fn: mean, createEmpty: false)
|> filter(fn: (r) => r["_measurement"] == "internal_write")
|> filter(fn: (r) => r["_field"] == "write_time_ns")
total:
influxdb:
query: >-
from(bucket: "integrations")
|> range(start: time(v: params.n9time_start), stop: time(v:
params.n9time_stop))
|> aggregateWindow(every: 15s, fn: mean, createEmpty: false)
|> filter(fn: (r) => r["_measurement"] == "internal_write")
|> filter(fn: (r) => r["_field"] == "write_time_ns")
primary: true
service: api-server
timeWindows:
- unit: Month
count: 1
isRolling: false
calendar:
startTime: '2022-12-01 00:00:00'
timeZone: UTC
alertPolicies:
- fast-burn-5x-for-last-10m
attachments:
- url: https://docs.nobl9.com
displayName: Nobl9 Documentation
anomalyConfig:
noData:
alertMethods:
- name: slack-notification
project: default
alertAfter: 1h
Click to open field reference
| Field | Type | Description |
|---|---|---|
apiVersion mandatory | string | API version. Use n9/v1alpha |
kind mandatory | string | The resource type. Use SLO |
| Metadata | ||
metadata.name mandatory | string | Name identifier for the SLO. Use only lowercase alphanumeric characters |
metadata.displayName | string | User-friendly SLO name |
metadata.project mandatory | string | The name identifier of the project where you need to host your SLO |
metadata.labels | object (map: string[]) | Grouping labels for filtering or viewing |
metadata.annotations | object (map: string) | Flat string annotations |
| Spec | ||
spec.description | string | SLO description |
spec.indicator.metricSource.name mandatory | string | Data source name |
spec.indicator.metricSource.project mandatory | string | Project containing the data source |
spec.indicator.metricSource.kind mandatory | string | Data source connection method. Can be Agent or Direct |
spec.budgetingMethod mandatory | enum | Error budget calculation method. Can be Occurrences or Time slices |
spec.objectives mandatory | array | Your SLO objective definition, up to 12 objectives per SLO. |
spec.objectives[].displayName | string | User-friendly objective name |
spec.objectives[].value mandatory | number | Data point values that is considered "good" (e.g., 200.0).In SLOs with two or more objectives, keep each objective's value unique. In ratio ( count) metrics, value is retained for legacy purposes. |
spec.objectives[].name mandatory | string | Name identifier for this objective |
spec.objectives[].op mandatory | string (enum) | Operator for objective. One of:lte (less than or equal to)lt (less than)gte (greater than or equal to)gt (greater than) |
spec.objectives[].target mandatory | float | The percentage of the good minutes or occurrences that must meet the desired performance (e.g., is the target is 0.95, the good performance is expected to be observed in at least 95% of the time window) |
spec.objectives[].rawMetric/.countMetric mandatory | object | The metric type indicator. Set:rawMetric for a threshold metriccountMetric for a ratio metric.A ratio metric requires the additional fields: countMetric.incremental (boolean) the data count methodcountMetric.good/.bad and countMetric.total a numerator and denominator queries |
spec.objectives[].countMetric.incremental mandatory | boolean | The data count method for a ratio (countMetric) metric type |
spec.objectives[].primary | boolean | The indicator of a primary SLO objective |
spec.service mandatory | string | The name identifier of a service to host this SLO. The service must exist in the project specified in metadata.project |
spec.timeWindows mandatory | array | Defines SLO time window for error budget calculation. Set: isRolling: true for the rolling time window typeisRolling: false for the calendar-aligned type |
spec.timeWindows.unit mandatory | integer | The time window units. One of:Day | Hour | Minute for the rolling time windowYear | Quarter | Month | Week | Day for the calendar-aligned time window |
spec.timeWindows.count mandatory | integer | The number of units in a time window |
spec.timeWindows.startTime | string | Mandatory for calendar-aligned time windows. Date and time in the format YYYY-MM-DDTHH:mm:ss |
spec.timeWindows.timeZone | string | Mandatory for calendar-aligned time-windows. A valid IANA Time Zone Database name |
spec.timeWindows.isRolling mandatory | boolean | true for the rolling time window typefalse for the calendar-aligned type |
spec.alertPolicies | array | The name identifiers of alert policies to be linked to this SLO (must be from the same project as the SLO). Up to 20 alert policies per SLO. |
spec.attachments | array | Links to any additional attributes of this SLO |
spec.anomalyConfig | object | Settings for a manual no data anomaly detection rule |
spec.noData.alertMethods | array | List of alert methods for no-data anomaly. Up to five alert methods per SLO. Every alert method must have the name and project fields |
spec.noData.alertAfter | string | Waiting time before sending a no-data notification. Must be 5m to 31d.Default: 15m |
| Source-specific fields | ||
influxdb.querymandatory | string | An InfluxDB query. β’ Must contain range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop)) placeholders and a bucket nameβ’ aggregateWindow() aggregates data into fixed time windows. Use it to group data if there are more than 4 points per minuteβ’ yield() specifies the query's output data. Required when using multiple sources in a query to identify each result by name |
Querying the InfluxDB serverβ
Nobl9 queries the InfluxDB server leveraging the /api/v2/query REST API on a per-minute basis with a maximum resolution of 4 data points.
InfluxDB API rate limitsβ
The API rate limits apply to the point density for the agent. If the point density fetched from database per one minute is greater than 4, an error occurs. Then, you must rewrite the query with point aggregation.