InfluxDB
InfluxDB is an open source time series database platform that enables users to collect, process, and analyze data to optimize their infrastructure.
Scope of Support
Currently, Nobl9 does not support the InfluxQL query language. You can retrieve the metrics using the Flux query language.
Nobl9 does not support full Flux query validation. The validation is performed on the following parameters:
- bucket name
- params.n9time_start
- params.n9time_stop
Authentication
When configuring a Nobl9 Agent or Direct connection to InfluxDB, you need to provide the API Token and Organization ID.
You can create the API Token using the InfluxDB user interface (UI), the command-line interface (CLI), or the InfluxDB API. For detailed instructions, refer to the Create an API Token | InfluxDB Documentation.
You can get your Organization ID from:
- The URL in the InfluxDB UI by looking for the
orgs
value, for example,http://localhost:8086/orgs/03a2bbf46249a000/...
- The Organization Settings in InfluxDB’s UI
- Click the organization name icon in your InfluxDB panel and go to the Organization Settings. You can copy the Organization ID to the clipboard.
For more details, refer to the View Organizations | InfluxDB Documentation.
Adding InfluxDB as a Data Source in the UI
To add InfluxDB as a data source in Nobl9 using the Agent or Direct connection method, follow these steps:
- Navigate to Integrations > Sources.
- Click the
button.
- Click the relevant Source icon.
- Choose a relevant connection method (Agent or Direct), then configure the source as described below.
InfluxDB Direct
Direct Configuration in the UI
A Direct connection to InfluxDB requires users to enter their credentials which Nobl9 stores safely. To set up this type of connection:
Enter an InfluxDB URL (mandatory).
This is the Cluster URL which you can get by clicking the Account settings icon in the InfluxDB panel, and navigating to the Organization Settings. You can also copy and paste it from the address line of your browser after logging in to your InfluxDB account.Enter your InfluxDB API Token (mandatory).
For more details, refer to the Create an API Token | InfluxDB Documentation.Enter your InfluxDB Organization ID (mandatory).
For more details, refer to the Authentication section above.
- Select a Project.
Specifying a Project is helpful when multiple users are spread across multiple teams or projects. When the Project field is left blank then object is assigned to projectdefault
. - Enter a Display Name.
You can enter a friendly name with spaces in this field. - Enter a Name.
The name is mandatory and can only contain lowercase, alphanumeric characters and dashes (for example,my-project-name
). This field is populated automatically when you enter a display name, but you can edit the result. - Enter a Description.
Here you can add details such as who is responsible for the integration (team/owner) and the purpose of creating it. - Click the Add Data Source
InfluxDB Agent
Agent Configuration in the UI
Follow the instructions below to set up an Agent connection. Refer to the section above for the descriptions of the fields.
- Add the InfluxDB URL to connect to your data source.
- Enter a Project.
- Enter a Display Name.
- Enter a Name.
- Create a Description.
- Click the Add Data Source
Agent Using CLI - YAML
The YAML for setting up an Agent connection to InfluxDB looks like this:
apiVersion: n9/v1alpha
kind: Agent
metadata:
name: influxdb
displayName: InfluxDB Agent # optional
project: influxdb
spec:
sourceOf:
- Metrics
- Services
influxdb:
url: https://instance-example.influxdata.com
Important notes:
url
- the Cluster URL which you can get by clicking the Account settings icon in the InfluxDB panel, and navigating to the Organization Settings. You can also copy and paste it from the address line of your browser after logging in to your InfluxDB account.
You can deploy only one Agent in one YAML file by using the sloctl apply
command.
Deploying the InfluxDB Agent
When you add the data source, Nobl9 automatically generates a Kubernetes configuration and a Docker command line for you to use to deploy the Agent. Both of these are available in the web UI, under the Agent Configuration section. Be sure to swap in your credentials (e.g., replace <INFLUXDB_API_TOKEN>
and <INFLUXDB_ORG_ID>
with your organization’s credentials). For more information, refer to the Authentication section above.
- Kubernetes
- Docker
If you use Kubernetes, you can apply the supplied YAML config file to a Kubernetes cluster to deploy the Agent.
# DISCLAIMER: This deployment description contains only the fields necessary for the purpose of this demo.
# It is not a ready-to-apply k8s deployment description, and the client_id and client_secret are only exemplary values.
apiVersion: v1
kind: Secret
metadata:
name: nobl9-agent-nobl9-dev-influxdbproject-influxdb-agent
namespace: default
type: Opaque
stringData:
influxdb_api_token: <INFLUXDB_API_TOKEN>
influxdb_org_id: <INFLUXDB_ORG_ID>
client_id: "unique_client_id"
client_secret: "unique_client_secret"
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: nobl9-agent-nobl9-dev-influxdbproject-influxdb-agent
namespace: default
spec:
replicas: 1
selector:
matchLabels:
nobl9-agent-name: influxdb-agent
nobl9-agent-project: influxdbproject
nobl9-agent-organization: nobl9-dev
template:
metadata:
labels:
nobl9-agent-name: influxdb-agent
nobl9-agent-project: influxdbproject
nobl9-agent-organization: nobl9-dev
spec:
containers:
- name: agent-container
image: nobl9/agent:latest
resources:
requests:
memory: "350Mi"
cpu: "0.1"
env:
- name: N9_CLIENT_ID
valueFrom:
secretKeyRef:
key: client_id
name: nobl9-agent-nobl9-dev-influxdbproject-influxdb-agent
- name: INFLUXDB_API_TOKEN
valueFrom:
secretKeyRef:
key: influxdb_api_token
name: nobl9-agent-nobl9-dev-influxdbproject-influxdb-agent
- name: INFLUXDB_ORG_ID
valueFrom:
secretKeyRef:
key: influxdb_org_id
name: nobl9-agent-nobl9-dev-influxdbproject-influxdb-agent
# The N9_METRICS_PORT is a variable specifying the port to which the /metrics and /health endpoints are exposed.
# The 9090 is the default value and can be changed.
# If you don’t want the metrics to be exposed, comment out or delete the N9_METRICS_PORT variable.
- name: N9_METRICS_PORT
value: "9090"
If you use Docker, you can run the supplied Docker command to deploy the Agent. It will look something like this:
# DISCLAIMER: This Docker command contains only the fields necessary for the purpose of this demo.
# It is not a ready-to-apply command, and you will need to replace the placeholder values with your own values.
docker run -d --restart on-failure \
--name nobl9-agent-nobl9-dev-region-asia-influxdb-agent \
-e N9_ORGANIZATION="nobl9-dev" \
-e N9_CLIENT_ID="unique_client_id" \
# The N9_METRICS_PORT is a variable specifying the port to which the /metrics and /health endpoints are exposed.
# The 9090 is the default value and can be changed.
# If you don’t want the metrics to be exposed, comment out or delete the N9_METRICS_PORT variable.
-e N9_METRICS_PORT=9090 \
-e INFLUXDB_API_TOKEN="<INFLUXDB_API_TOKEN>"\
-e INFLUXDB_ORG_ID="<INFLUXDB_ORG_ID>"\
nobl9/agent:latest;
Creating SLOs with InfluxDB
Creating SLO in the UI
Follow the instructions below to create an SLO with InfluxDB in the UI:
Navigate to Service Level Objectives.
- Click the
button.
In step 1 of the SLO wizard, select the Service the SLO will be associated with.
In step 2, select InfluxDB as the Data Source for your SLO, then specify the Metric. You can choose either a Threshold Metric, where a single time series is evaluated against a threshold or a Ratio Metric, which allows you to enter two time series to compare (for example, a count of good requests and total requests).
noteFor the Ratio Metric, you can choose the Data Count Method:
- For the Non-incremental method, we expect it to be the components of the sum.
- For the Incremental method, we expect the value of a metric to be the current sum of some numerator.
For more information, refer to the SLO Calculations Guide.
Paste the Flux query in the Query, or Good Query and Total Query fields for the metric you selected. An InfluxDB query must contain:
A
bucket
value that points to a bucket in your organization that you want to query. Abucket
is a named location where time series data is stored in InfluxDB. For more details, refer to the Manage Buckets in InfluxDB | InfluxDB Documentation.params.n9time_start
andparams.n9time_stop
placeholders that define the time range of the query.When generating a Flux query in the InfluxDB UI, replace InfluxDB
v.timeRangeStart
andv.timeRangeStop
variables with Nobl9params.n9time_start
andparams.n9time_stop
placeholders. For more information, refer to the Predefined dashboard variables | InfluxDB Documentation.When creating a Flux query in the Nobl9 UI, append the query with
range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop))
function. For query examples, refer to the section below.
noteDo not add a time frame to the query, as Nobl9 appends the query times as needed.
For more information on the Flux query language, refer to the Get Started with Flux | InfluxDB Documentation.
In step 3 of the SLO Wizard, define a Time Window for the SLO.
In step 4, specify the Error Budget Calculation Method and your Objective(s).
In step 5, add a Name, Description, and other details about your SLO. You can also select Alert Policies and Labels on this screen.
When you’re done, click Create SLO.
Query examples
The following are Flux query examples:
Threshold Metric
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")'
Ratio Metric:
Good 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 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")'
SLOs using InfluxDB - YAML samples
- rawMetric
- countMetric
Here’s an example of InfluxDB using rawMetric
(Threshold Metric):
apiVersion: n9/v1alpha
kind: SLO
metadata:
displayName: influxdb-calendar-occurrences-threshold
name: influxdb-calendar-occurrences-threshold
project: influxdb
spec:
budgetingMethod: Occurrences
description: ""
indicator:
metricSource:
name: influxdb
rawMetric:
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")'
service: influxdb-service
objectives:
- target: 0.8
op: lte
displayName: average
value: 300000000
- target: 0.5
op: lte
displayName: so-so
value: 250000000
timeWindows:
- calendar:
startTime: "2020-11-14 12:10:00"
timeZone: Etc/UTC
count: 1
isRolling: false
unit: Day
Here’s an example of InfluxDB using countMetric
(Ratio Metric):
apiVersion: n9/v1alpha
kind: SLO
metadata:
displayName: influx-ratio-co-calendar
name: influx-ratio-co-calendar
project: default
spec:
alertPolicies: []
budgetingMethod: Occurrences
description: ""
indicator:
metricSource:
kind: Agent
name: influx-test
project: default
objectives:
- countMetrics:
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")'
incremental: false
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")'
displayName: ""
target: 0.95
value: 1
service: influxdb-service
timeWindows:
- calendar:
startTime: "2022-05-01 00:00:00"
timeZone: UTC
count: 1
isRolling: false
period:
begin: "2022-05-01T00:00:00Z"
end: "2022-06-01T00:00:00Z"
unit: Month
Notes:
query
:query
- must containrange(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop))
placeholders and abucket
name.aggregateWindow ()
- applies an aggregate or selector function to fixed windows of time. If you need to aggregate points when there are more than 4 points per minute, group the data using this function.yield ()
- a function that indicates what input data will be provided as a result of the query.yield()
is required when using multiple sources in a query. Each query result is then identified by the name provided to theyield()
.For more information, refer to the Flux universe package | InfluxDB Documentation.
Querying the InfluxDB Server
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 Limits
The API Rate Limits applies to the point density for the Agent. If the point density fetched from database per 1 minute is greater than 4, an error occurs. Then, you must rewrite the query with point aggregation.
Useful Links
InfluxDB API Reference | InfluxDB Documentation
Create an API Token | InfluxDB Documentation
View Organizations | InfluxDB Documentation
Influx Query Language | InfluxDB Documentation
Get Started with Flux | InfluxDB Documentation
Flux universe package | InfluxDB Documentation
Manage Buckets | InfluxDB Documentation
Predefined dashboard variables | InfluxDB Documentation
Agent Metrics | Nobl9 Documentation
Creating SLOs via Terraform | Nobl9 Terraform Documentation
Creating Agents via Terraform | Nobl9 Terraform Documentation