AMS Prometheus

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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 support

Currently, Nobl9 integration with AMS Prometheus does not support IAM roles for bare EC2 instances: (IAM Roles | AWS documentation).

Authentication

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)

warning

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 source

To ensure data transmission between Nobl9 and your data source, it may be necessary to list Nobl9 IP addresses as trusted.

IP addresses to add to your allowlist:

18.159.114.21
18.158.132.186
3.64.154.26

⚠ Applies to app.nobl9.com only. In all other cases, contact Nobl9 support.

You can add the Amazon Prometheus data source using the agent connection method. Start with these steps:

Navigate to Integrations > Sources.
Click .
The Data Source wizard opens.
Select Amazon Managed Service for Prometheus.

AMS Prometheus agent

Agent configuration in the UI

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 a beta 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.
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, Nobl9 uses the default 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 Amazon Prometheus integration for Query delay is 0 seconds.
info
Changing the Query delay may affect your SLI data. For more details, check the Query delay documentation.
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.
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 - YAML

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
  project: default
spec:
  description: Agent settings for Amazon Managed Service for Prometheus datasource
  sourceOf:
    - Metrics
  releaseChannel: beta
  queryDelay:
      unit: Minute
      value: 720
  amazonPrometheus:
    url: https://aps-workspaces.eu-central-1.amazonaws.com/workspaces/some_workspace_id
    region: eu-central-1
  historicalDataRetrieval:
      maxDuration:
        value: 30 # Max value for Amazon Prometheus
        unit: Day
      defaultDuration:
        value: 0
        unit: Day

Field	Type	Description
`queryDelay.unit` mandatory	enum	Specifies the unit for the query delay. Possible values: `Second` \| `Minute`. • Check query delay documentation for default unit of query delay for each source.
`queryDelay.value` mandatory	numeric	Specifies the value for the query delay. • Must be a number less than 1440 minutes (24 hours). • 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
`amazonPrometheus.url` mandatory	string	is the `Endpoint - query URL` in AMS Prometheus. Check Authentication for AMS Prometheus for detailed instructions on how to get it
`amazonPrometheus.region` mandatory	string	Check the list of supported regions for AMS Prometheus.
Replay-related fields
`historicalDataRetrieval` optional	n/a	Optional structure related to configuration related to Replay. ❗ Use only with supported sources. • If omitted, Nobl9 uses the default values of `value: 0` and `unit: Day` for `maxDuration` and `defaultDuration`.
`maxDuration.value` optional	numeric	Specifies the maximum duration for historical data retrieval. Must be integer `≥ 0`. See Replay documentation for values of max duration per data source.
`maxDuration.unit` optional	enum	Specifies the unit for the maximum duration of historical data retrieval. Accepted values: `Minute` \| `Hour` \| `Day`.
`defaultDuration.value` optional	numeric	Specifies the default duration for historical data retrieval. Must be integer `≥ 0` and `≤` `maxDuration`.
`defaultDuration.unit` optional	enum	Specifies the unit for the default duration of historical data retrieval. Accepted values: `Minute` \| `Hour` \| `Day`.

warning

You can deploy only one agent in one YAML file by using the sloctl apply command.

caution

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 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.

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:0.73.2
          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 don’t 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 don’t want the metrics to be exposed, comment out or delete the N9_METRICS_PORT variable.
  -e N9_METRICS_PORT=9090 \
  nobl9/agent:0.73.2

Creating SLOs with AMS Prometheus

Creating SLOs in the UI

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).
1. 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 (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=""}
  SLI values for good and total
  When choosing the query for the ratio SLI (countMetrics), keep in mind that the values resulting from that query for both good and total:
  - Must be positive.
  - While we recommend using integers, fractions are also acceptable.
  - Shouldn't be larger than 1e+20.
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 you’re done, click Create SLO.

SLO using AMS Prometheus - YAML samples

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 – 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 server

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.