AMS Prometheus
Amazon Managed Service for Prometheus (or AMS Prometheus) is a monitoring and alerting service that ensures easy-to-use monitoring of containerized applications and infrastructure. It's scalable, and you don't have to worry about hosting it yourself.
Scope of supportβ
Currently, Nobl9 integration with AMS Prometheus does not support IAM roles for bare EC2 instances: (IAM Roles | AWS documentation).
Authenticationβ
For more details, refer to Authentication for AMS Prometheus.
To set up the connection, AMS Prometheus requires users to enter the URL
. To get the URL:
Sign in to your AWS account.
Click the AMS Prometheus in the Management & Governance panel:
Image 1: Configuring authentication for AMS Prometheus (1) Click All workspaces.
Image 2: Configuring authentication for AMS Prometheus (2) Choose a relevant workspace:
Image 3: Configuring authentication for AMS Prometheus (3) In the Summary screen, copy the
Endpoint - query URL
Image 4: Configuring authentication for AMS Prometheus (4)
The url
that you need is the Endpoint - query URL
without the /api/v1/query
string at the end of the URL
.
Adding Amazon Managed Service for Prometheus as a data sourceβ
To add Amazon Managed Service for Prometheus as a data source in Nobl9 using the agent connection method, follow these steps:
- Navigate to Integrations > Sources.
- Click
.
- Click the relevant Source icon.
- Choose a relevant connection method (Agent or Direct), then configure the source as described below.
AMS Prometheus agentβ
Agent configuration in the UIβ
Follow the instructions below to create your AMS Prometheus agent connection:
- 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 may be subject to change.
- The
Add the URL to connect to your data source (mandatory).
Refer to Authentication for AMS Prometheus for detailed instructions on how to get the URL.Enter a Region (mandatory).
The list of supported Regions for AMS Prometheus is here.
- 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. - Specify the Query delay to set a customized delay for queries when pulling the data from the data source.
- The default value in Amazon Prometheus integration for Query delay is
0 seconds
.
infoChanging the Query delay may affect your SLI data. For more details, check the Query delay documentation. - The default value in Amazon Prometheus integration for Query delay is
- Enter a Maximum Period for Historical Data Retrieval.
- This value defines how far back in the past your data will be retrieved.
- The value for the maximum period of data retrieval depends on the data source. Check the Replay documentation for details.
- A greater period can extend the loading time when creating an SLO.
- The value must be a positive integer.
- Enter a Default Period for Historical Data Retrieval.
- It is used by SLOs connected to this data source.
- The value must be a positive integer or
0
. - By default, this value is set to 0. When you set it to
>0
, you will create SLOs with Replay.
- Click Add Data Source
Agent using CLI - YAMLβ
The YAML for setting up an agent connection to AMS Prometheus looks like this:
apiVersion: n9/v1alpha
kind: Agent
metadata:
name: amazon-prometheus-agent
displayName: AMS Prometheus Agent # optional
project: default
spec:
description: Agent settings for Amazon Managed Service for Prometheus datasource # optional
sourceOf:
- Metrics
releaseChannel: beta # string, one of: beta || stable
queryDelay:
unit: Minute # string, one of: Second || Minute
value: 720 # numeric, must be a number less than 1440 minutes (24 hours)
amazonPrometheus:
url: https://aps-workspaces.eu-central-1.amazonaws.com/workspaces/some_workspace_id
region: eu-central-1
historicalDataRetrieval:
maxDuration:
value: 30 # integer greater than or equal to 0
unit: Day # accepted values: Minute, Hour, Day
defaultDuration: # value must be less than or equal to value of maxDuration
value: 0 # integer greater than or equal to 0
unit: Day # accepted values: Minute, Hour, Day
Important notes:
region
Β is required.roleArn
is optional. Amazon Resource NamesΒ (ARNs) are unique identifiers for AWS resources such asroles
.url
- is theEndpoint - query URL
in AMS Prometheus. Refer to Authentication for AMS Prometheus for detailed instructions on how to get it.spec[n].historicalDataRetrieval
- refer to Replay Documentation | Nobl 9 documentation for more details.
You can deploy only one agent in one YAML file by using the sloctl apply
command.
The Nobl9 agent makes one request to API per minute per unique query. Make sure that your AMS Prometheus server can handle additional traffic. For more details, go to AMP Quotas.
Deploying AMS Prometheus agentβ
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: nobl9-agent-nobl9-dev-awsprometheus-month-prom
namespace: default
type: Opaque
stringData:
client_id: "unique_client_id"
client_secret: "unique_client_secret"
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: nobl9-agent-nobl9-dev-awsprometheus-month-prom
namespace: default
spec:
replicas: 1
selector:
matchLabels:
nobl9-agent-name: "prom"
nobl9-agent-project: "awsprometheus-month"
nobl9-agent-organization: "nobl9-dev"
template:
metadata:
labels:
nobl9-agent-name: "amazon-prom"
nobl9-agent-project: "amazon-prometheus-month"
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-awsprometheus-month-prom
- name: N9_CLIENT_SECRET
valueFrom:
secretKeyRef:
key: client_secret
name: nobl9-agent-nobl9-dev-awsprometheus-month-prom
# 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"
# N9_ALLOWED_URLS is an optional security parameter that limits the URLs that an Agent can query
# for metrics. URLs defined in the Nobl9 app are prefix-compared against the N9_ALLOWED_URLS list of
# comma separated URLs.
# - name: N9_ALLOWED_URLS
# value: "http://172.16.0.2/api/v1/query,http://172.16.0.3"
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 nobl9-agent-nobl9-dev-awsprometheus-month-prom \
-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:latest
Creating SLOs with AMS Prometheusβ
Creating SLOs in the UIβ
Follow the instructions below to create your SLOs with AWS Prometheus in the UI:
Navigate to Service Level Objectives.
- Click
.
In the SLO wizard, select a 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).
- 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.
- Choose the Data Count Method for your ratio metric:
Enter a Query (for the Threshold metric) or Good Query, and Total Query (for the Ratio metric). The following are query examples:
Threshold metric for AMS Prometheus: Query:
sum(changes(kube_pod_status_ready{condition="true"}[5m]))
Ratio metric for AMS Prometheus: Good Query:
sum(server_requests{code=~"2xx|3xx",host=""})
Total Query:server_requests{code="total",host=""}
In step 3, 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 youβre done, click Create SLO.
SLO using AMS Prometheus - YAML samplesβ
- rawMetric
- countMetric
Here's an example of Amazon Managed Service for Prometheus using rawMetric
(threshold metric):
apiVersion: n9/v1alpha
kind: SLO
metadata:
displayName: My AMS Prometheus SLO
name: my-awsprometheus-slo
project: my-awsprometheus-project
spec:
budgetingMethod: Occurrences
description: ""
indicator:
metricSource:
name: my-amsprometheus-source
service: my-service
objectives:
- target: 0.8
op: lte
rawMetric:
query:
amazonPrometheus:
promql: myapp_server_requestMsec{host="*",job="nginx"}
displayName: average
value: 200
- target: 0.5
op: lte
rawMetric:
query:
amazonPrometheus:
promql: myapp_server_requestMsec{host="*",job="nginx"}
displayName: so-so
value: 150
timeWindows:
- calendar:
startTime: "2020-11-14 11:00:00"
timeZone: Etc/UTC
count: 1
isRolling: false
unit: Day
Here's an example of Amazon Managed Service for Prometheus using countMetric
(ratio metric):
apiVersion: n9/v1alpha
kind: SLO
metadata:
displayName: amazon-prometheus-calendar-timeslices-ratio
name: amazon-prometheus-calendar-timeslices-ratio
project: my-amazon-prometheus
spec:
budgetingMethod: Timeslices
description: ""
indicator:
metricSource:
name: amazon-prometheus
service: amazon-prometheus-service
objectives:
- target: 0.75
countMetrics:
good:
amazonPrometheus:
promql: sum(production_http_response_time_seconds_hist_bucket{method=~"GET|POST",status=~"2..|3..",le="1"})
incremental: true
total:
amazonPrometheus:
promql: sum(production_http_response_time_seconds_hist_bucket{method=~"GET|POST",le="+Inf"})
displayName: available1
timeSliceTarget: 0.75
value: 1
timeWindows:
- calendar:
startTime: "2020-11-14 11:00:00"
timeZone: Etc/UTC
count: 1
isRolling: false
unit: Day
Important notes:
Specification for metric from Prometheus has one mandatory field:
promql
β a Prometheus query in the PromQL (Prometheus Query Language) that allows the user to select and aggregate time-series data in real-time.
Querying the AMS Prometheus serverβ
Nobl9 agent makes one request to API per minute per unique query. Make sure that your Prometheus server can handle additional traffic. For more details on Amazon service quota, go to Service Quotas | Amazon Managed Service for Prometheus documentation.
Useful linksβ
Service Quotas | Amazon Managed Service for Prometheus documentation
Credential Types | Amazon Managed Service for Prometheus documentation
Specifying Credentials | Amazon Managed Service for Prometheus documentation
AWS Service Endpoints | Amazon Managed Service for Prometheus documentation