Grafana Loki
Grafana Loki (or Loki) is a horizontally scalable, multi-tenant log aggregation system that is extremely easy to operate. Loki does not index the contents of the logs, but rather a set of labels for each log stream. Nobl9 users can leverage Loki to query and build metrics on top of their logs.
Scope of supportβ
- Query parameters retrieval with
sloctl
Currently, the Grafana Loki integration with Nobl9 supports the agent connection only.
Authenticationβ
Loki does not provide an authentication layer.
Authentication is up to the customer.
Users are expected
to run an authenticating reverse proxy in front of their services,
such as NGINX using basic auth
or an OAuth2
proxy.
Nobl9 collects only the URL for the Loki integration definition and calls the GET /loki/api/v1/query_range
URL. For details, refer to HTTP API Grafana Loki | Grafana Loki documentation.
Basic authenticationβ
Since Loki does not provide an authentication layer, the authentication method is up to the users. Normally, Loki's users are expected to run an authenticating reverse proxy in front of their services, such as NGINX
using basic_auth
proxy.
If that's the method you use, the Nobl9 agent version equal to or higher than 0.40.0, allows you to send an additional Authorization request header with the basic_auth
. Refer to the section below for more details.
Adding Grafana Loki as a data sourceβ
To ensure data transmission between Nobl9 and Grafana Loki, it may be necessary to list Nobl9 IP addresses as trusted.
- 18.159.114.21
- 18.158.132.186
- 3.64.154.26
You can add the Grafana Loki data source using the agent connection method.
Nobl9 Webβ
Follow the instructions below to configure your Grafana Loki agent:
- Navigate to Integrations > Sources.
- Click
.
- Click the required Source icon.
- Choose Agent.
-
Select one of the following Release Channels:
- The
stable
channel is fully tested by the Nobl9 team. It represents the final product; however, this channel does not contain all the new features of abeta
release. Use it to avoid crashes and other limitations. - The
beta
channel is under active development. Here, you can check out new features and improvements without the risk of affecting any viable SLOs. Remember that features in this channel can change.
- The
-
Add the URL (mandatory).
Theurl
is an entry point to Grafana Loki. It depends on the configuration of your Loki instance, for more details, refer to the Configuration | Grafana Loki documentation section of Grafana Loki technical documentation.
- 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, Nobl9 uses thedefault
project. - Enter a Display Name.
You can enter a user-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-1
). Nobl9 duplicates the display name here, transforming it into the supported format, 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. - Specify the Query delay to set a customized delay for queries when pulling the data from the data source.
- The default value in Grafana Loki integration for Query delay is
1 minute
.
infoChanging the Query delay may affect your SLI data. For more details, check the Query delay documentation. - The default value in Grafana Loki integration for Query delay is
- Click Add Data Source
sloctlβ
The YAML for setting up an agent connection to Grafana Loki looks like this:
apiVersion: n9/v1alpha
kind: Agent
metadata:
# String, mandatory. The name identifier of the data source. Allowed characters: a-z, 0-9, and dashes
name: grafana-loki-data-source
# String, optional. A user-friendly name of your data source
displayName: Grafana Loki data source
# String, optional. A user-friendly name of your data source
project: my-project
spec:
# String, optional. A user-friendly description of your data source
description: Sample Grafana Loki data source (agent connection)
# String, mandatory. One of: stable || beta
releaseChannel: stable
# Mandatory. Source-specific properties
grafanaLoki:
url: http://grafana-loki.url
queryDelay:
# Numeric, mandatory. Integer 0β1440 minutes (24 hours)
value: 2
# String, one of Second || Minute
unit: Minute
Field | Type | Description |
---|---|---|
queryDelay.unit mandatory | enum | Specifies the unit for the query delay. Possible values: Second | Minute . β’ Check query delay documentation for default unit of query delay for each source. |
queryDelay.value mandatory | numeric | Specifies the value for the query delay. β’ Must be a number less than 1440 minutes (24 hours). β’ Check query delay documentation for default unit of query delay for each source. |
releaseChannel mandatory | enum | Specifies the release channel. Accepted values: beta | stable . |
Source-specific fields | ||
grafanaLoki.url mandatory | string | an entry point to Grafana Loki. The `url` depends on the configuration of your Loki instance. See Configuration | Grafana Loki documentation. |
You can deploy only one agent in one YAML file by using the sloctl apply
command.
Agent deploymentβ
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.
- Kubernetes
- Docker
If you use Kubernetes, you can apply the supplied YAML config file to a Kubernetes cluster to deploy the agent. It will look something like this:
# 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: my-grafana-loki-agent-data-source
namespace: my-namespace
type: Opaque
stringData:
client_id: "unique_client_id"
client_secret: "unique_client_secret"
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-grafana-loki-agent-data-source
namespace: my-namespace
spec:
replicas: 1
selector:
matchLabels:
nobl9-agent-name: "grafana-loki"
nobl9-agent-project: "my-project"
nobl9-agent-organization: "my-organization"
template:
metadata:
labels:
nobl9-agent-name: "grafana-loki"
nobl9-agent-project: "my-project"
nobl9-agent-organization: "my-organization"
spec:
containers:
- name: agent-container
image: nobl9/agent:0.80.0
resources:
requests:
memory: "350Mi"
cpu: "0.1"
env:
- name: N9_CLIENT_ID
valueFrom:
secretKeyRef:
key: client_id
name: my-grafana-loki-agent-data-source
- name: N9_CLIENT_SECRET
valueFrom:
secretKeyRef:
key: client_secret
name: my-grafana-loki-agent-data-source
# 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 donβt 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 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 my-grafana-loki-agent-data-source \
-e N9_CLIENT_ID="unique_client_id" \
-e N9_CLIENT_SECRET="unique_client_secret" \
# 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 donβt want the metrics to be exposed, comment out or delete the N9_METRICS_PORT variable.
-e N9_METRICS_PORT=9090 \
nobl9/agent:0.80.0
Basic authenticationβ
To activate basic_auth for the agent, you need to pass optional environmental variables to an agent:
-
AUTH_METHOD: basic_auth
- is a fixed value, but it must be passed to let know agent thatbasic_auth
will be used. -
USERNAME: REDACTED
- username forbasic_auth
. -
PASSWORD: REDACTED
- password forbasic_auth
.
- Kubernetes
- Docker
If you use Kubernetes, the supplied YAML config file to a Kubernetes cluster to deploy the agent using basic_auth
method. It will look something like this:
# 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: my-grafana-loki-agent-data-source
namespace: my-namespace
type: Opaque
stringData:
client_id: "REDACTED"
client_secret: "REDACTED"
basic_auth_username: "REDACTED"
basic_auth_password: "REDACTED"
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-grafana-loki-agent-data-source
namespace: my-namespace
spec:
replicas: 1
selector:
matchLabels:
nobl9-agent-name: "grafana-loki"
nobl9-agent-project: "my-project"
nobl9-agent-organization: "my-organization"
template:
metadata:
labels:
nobl9-agent-name: "grafana-loki"
nobl9-agent-project: "my-project"
nobl9-agent-organization: "my-organization"
spec:
containers:
- name: agent-container
image: nobl9/agent:0.80.0
resources:
requests:
memory: "350Mi"
cpu: "0.1"
env:
- name: N9_CLIENT_ID
valueFrom:
secretKeyRef:
key: client_id
name: my-grafana-loki-agent-data-source
- name: N9_CLIENT_SECRET
valueFrom:
secretKeyRef:
key: client_secret
name: my-grafana-loki-agent-data-source
- name: AUTH_METHOD
value: "basic_auth"
- name: USERNAME
valueFrom:
secretKeyRef:
key: basic_auth_username
name: my-grafana-loki-agent-data-source-basic-auth
- name: PASSWORD
valueFrom:
secretKeyRef:
key: basic_auth_password
name: my-grafana-loki-agent-data-source-basic-auth
# 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 donβt 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 Docker command to deploy the agent with the basic_auth
method. 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 my-grafana-loki-agent-data-source \
-e N9_CLIENT_SECRET="REDACTED" \
-e N9_CLIENT_ID="REDACTED" \
# 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 donβt want the metrics to be exposed, comment out or delete the N9_METRICS_PORT variable.
-e N9_METRICS_PORT=9090 \
-e AUTH_METHOD="basic_auth" \
-e USERNAME="REDACTED" \
-e PASSWORD="REDACTED" \
nobl9/agent:0.80.0
Creating SLOs with Grafana Lokiβ
Nobl9 Webβ
Follow the instructions below to create your SLOs with Grafana Loki in the UI:
-
Navigate to Service Level Objectives.
-
Click
.
-
In step 1 of the SLO wizard, select the Service the SLO will be associated with.
-
In step 2, select Grafana Loki as the data source for your SLO.
-
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).
-
Choose the Data Count Method for your ratio metric:
- Non-incremental: counts incoming metric values one-by-one. So the resulting SLO graph is pike-shaped.
- Incremental: counts the incoming metric values incrementally, adding every next value to previous values.
It results in a constantly increasing SLO graph.
- Enter a Query, or Good Query and Total Query for the metric you selected.
Refer to the Query Examples section below for more details.
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
.
- In step 3, define a Time Window for the SLO.
-
Rolling time windows are better for tracking the recent user experience of a service.
-
Calendar-aligned windows are best suited for SLOs that are intended to map to business metrics measured on a calendar-aligned basis, such as every calendar month or every quarter.
- In step 4, specify the Error Budget Calculation Method and your Objective(s).
- Occurrences method counts good attempts against the count of total attempts.
- Time Slicesmethod 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. For more information, check the Composite SLOs Guide.
See the use case example and the SLO calculations guide for more information on the error budget calculation methods.
- In step 5, add the Display name, Name, and other settings for your SLO:
- Create a composite SLO
- Set notification on data, if this option is available for your data source.
When activated, Nobl9 notifies you if your SLO hasn't received data or received incomplete data for more than 15 minutes. - Add alert policies, labels, and links, if required.
You can add up to 20 links per SLO.
- Click Create SLO.
sloctlβ
- rawMetric
- countMetric
Hereβs an example of Grafana Loki using a rawMetric
(threshold metric):
apiVersion: n9/v1alpha
kind: SLO
metadata:
name: my-threshold-slo
project: my-project
spec:
description: ""
service: my-service
indicator:
metricSource:
name: my-grafana-loki-agent-data-source
timeWindows:
- unit: Day
count: 1
isRolling: true
budgetingMethod: Occurrences
objectives:
- displayName: My objective 1
name: my-objective-1
op: lte
rawMetric:
query:
grafanaLoki:
logql: sum(sum_over_time({topic="my-topic", consumergroup="my-consumergroup", cluster="my-cluster"} |= "kafka_consumergroup_lag" | logfmt | kafka_consumergroup_lag!="" | line_format "{{.kafka_consumergroup_lag}}" | unwrap kafka_consumergroup_lag [1m]))
value: 5
target: 0.50
- displayName: My objective 2
name: my-objective-2
op: lte
rawMetric:
query:
grafanaLoki:
logql: sum(sum_over_time({topic="my-topic", consumergroup="my-consumergroup", cluster="my-cluster"} |= "kafka_consumergroup_lag" | logfmt | kafka_consumergroup_lag!="" | line_format "{{.kafka_consumergroup_lag}}" | unwrap kafka_consumergroup_lag [1m]))
value: 10
target: 0.75
Hereβs an example of Grafana Loki as a countMetric
(ratio metric):
apiVersion: n9/v1alpha
kind: SLO
metadata:
displayName: My ratio SLO
name: my-ratio-slo
project: my-project
spec:
alertPolicies: []
budgetingMethod: Occurrences
description: ""
indicator:
metricSource:
kind: Agent
name: my-grafana-loki-agent-data-source
project: my-project
objectives:
- countMetrics:
good:
grafanaLoki:
logql: count(count_over_time(({component="my-component", container="my-container"} | json | line_format "{{.log}}" | json | http_useragent != "ELB-HealthChecker/2.0" | http_status_code >= 200 and http_status_code < 300)[1m]))
incremental: false
total:
grafanaLoki:
logql: count(count_over_time(({component="my-component", container="my-container"} | json | line_format "{{.log}}" | json | http_useragent != "ELB-HealthChecker/2.0" | http_status_code > 0)[1m]))
displayName: My objective
target: 0.99
value: 1
name: my-objective
service: my-service
timeWindows:
- count: 1
isRolling: true
unit: Hour
Metrics for Grafana Loki have one mandatory field:
logql
is a query written in the PromQL (Prometheus Query Language). For more details, refer to Introduction to PromQL | Grafana documentation. You can see working examples of Grafana Loki queries in the Query examples section below.
Query examplesβ
- Ratio metric for Grafana Loki:
Good Query:
count(count_over_time(({app="nobl9", component="ingest", container="ingest container"} | json | line_format "{{.log}}" | json | http_useragent != "ELB-HealthChecker/2.0" | http_status_code >= 200 and http_status_code < 300)[1m]))
Total Query:
count(count_over_time(({app="nobl9", component="ingest", container="ingest-container"} | json | line_format "{{.log}}" | json | http_useragent != "ELB-HealthChecker/2.0" | http_status_code > 0)[1m]))
Querying the Grafana Loki serverβ
Nobl9 calls Loki API every minute to retrieve the log data from the previous minute. Nobl9 aggregates the total number of points to 4 per minute.
Users should refrain from adding duration and Nobl9 will append [1m]
to the query.