mimir Documentation

1. Project Overview & Quickstart (grafana/mimir) Copy Chapter

File: README.md Copy Chapter

Grafana Mimir

Grafana Mimir is an open source software project that provides a scalable long-term storage for Prometheus. Some of the core strengths of Grafana Mimir include:

• Easy to install and maintain: Grafana Mimir’s extensive documentation, tutorials, and deployment tooling make it quick to get started. Using its monolithic mode, you can get Grafana Mimir up and running with just one binary and no additional dependencies. Once deployed, the best-practice dashboards, alerts, and runbooks packaged with Grafana Mimir make it easy to monitor the health of the system.
• Massive scalability: You can run Grafana Mimir's horizontally-scalable architecture across multiple machines, resulting in the ability to process orders of magnitude more time series than a single Prometheus instance. Internal testing shows that Grafana Mimir handles up to 1 billion active time series.
• Global view of metrics: Grafana Mimir enables you to run queries that aggregate series from multiple Prometheus instances, giving you a global view of your systems. Its query engine extensively parallelizes query execution, so that even the highest-cardinality queries complete with blazing speed.
• Cheap, durable metric storage: Grafana Mimir uses object storage for long-term data storage, allowing it to take advantage of this ubiquitous, cost-effective, high-durability technology. It is compatible with multiple object store implementations, including AWS S3, Google Cloud Storage, Azure Blob Storage, OpenStack Swift, as well as any S3-compatible object storage.
• High availability: Grafana Mimir replicates incoming metrics, ensuring that no data is lost in the event of machine failure. Its horizontally scalable architecture also means that it can be restarted, upgraded, or downgraded with zero downtime, which means no interruptions to metrics ingestion or querying.
• Natively multi-tenant: Grafana Mimir’s multi-tenant architecture enables you to isolate data and queries from independent teams or business units, making it possible for these groups to share the same cluster. Advanced limits and quality-of-service controls ensure that capacity is shared fairly among tenants.

Migrating to Grafana Mimir Copy Chapter

If you're migrating to Grafana Mimir, refer to the following documents:

• Migrating from Thanos or Prometheus to Grafana Mimir.
• Migrating from Cortex to Grafana Mimir

Deploying Grafana Mimir Copy Chapter

For information about how to deploy Grafana Mimir, refer to Deploy Grafana Mimir.

Getting started Copy Chapter

If you’re new to Grafana Mimir, read the Get started guide.

Before deploying Grafana Mimir in a production environment, read:

1. An overview of Grafana Mimir’s architecture
2. Configure Grafana Mimir
3. Run Grafana Mimir in production

Documentation Copy Chapter

Refer to the following links to access Grafana Mimir documentation:

• Latest release
• Upcoming release, at the tip of the main branch

Contributing Copy Chapter

To contribute to Grafana Mimir, refer to Contributing to Grafana Mimir.

Join the Grafana Mimir discussion Copy Chapter

If you have any questions or feedback regarding Grafana Mimir, join the Grafana Mimir Discussion. Alternatively, consider joining the monthly Grafana Mimir Community Call.

Your feedback is always welcome, and you can also share it via the #mimir Slack channel.

License Copy Chapter

Grafana Mimir is distributed under AGPL-3.0-only.

File: docs/README.md Copy Chapter

Documentation

Test Mimir and Helm chart documentation together locally Copy Chapter

Testing the documentation accurately requires a copy of Mimir documentation at the target version of the Helm chart.

One way to do this is to use a git worktree to checkout the version branch of Mimir that matches the Helm chart target version.
For example, if the Helm chart target version is v2.9.x, checkout the release-2.9 branch:

$ git worktree add --checkout "$(git rev-parse --show-toplevel)/../mimir-v2.9.x" origin/release-2.9
Preparing worktree (detached HEAD 761114d8b)
HEAD is now at 761114d8b Bump version to 2.9.0 (#5289)

2. Official Technical Reference & Guides (grafana/docs) Copy Chapter

Prometheus Monitoring Mixins

NOTE: This project is beta stage.

A mixin is a set of Grafana dashboards and Prometheus rules and alerts, packaged together in a reuseable and extensible bundle.
Mixins are written in jsonnet, and are typically installed and updated with jsonnet-bundler.

For more information about mixins, see:

• Prometheus Monitoring Mixins Design Doc. A cached pdf is included in this repo.
• For more motivation, see
  "The RED Method: How to instrument your services" talk from CloudNativeCon Austin 2018. The KLUMPs system demo'd became the basis for the kubernetes-mixin.
• "Prometheus Monitoring Mixins: Using Jsonnet to Package Together Dashboards, Alerts and Exporters" talk from CloudNativeCon Copenhagen 2018.
• "Prometheus Monitoring Mixins: Using Jsonnet to Package Together Dashboards, Alerts and Exporters" talk from PromCon 2018 (slightly updated).

How to use mixins. Copy Chapter

Mixins are designed to be vendored into the repo with your infrastructure config.
To do this, use jsonnet-bundler:

You then have three options for deploying your dashboards

1. Generate the config files and deploy them yourself.
2. Use ksonnet to deploy this mixin along with Prometheus and Grafana.
3. Use kube-prometheus to deploy this mixin.

Generate config files Copy Chapter

You can manually generate the alerts, dashboards and rules files, but first you
must install some tools:

$ go install github.com/jsonnet-bundler/jsonnet-bundler/cmd/jb@latest

# macOS
$ brew install jsonnet-bundler

# Archlinux AUR
$ yay -S jsonnet

Then, grab the mixin and its dependencies:

$ git clone https://github.com/<mixin org>/<mixin repo>
$ cd <mixin repo>
$ jb install

Finally, build the mixin:

$ make prometheus_alerts.yaml
$ make prometheus_rules.yaml
$ make dashboards_out

The prometheus_alerts.yaml and prometheus_rules.yaml file then need to passed
to your Prometheus server, and the files in dashboards_out need to be imported
into you Grafana server. The exact details will depending on how you deploy your
monitoring stack to Kubernetes.

Using with prometheus-ksonnet Copy Chapter

Alternatively you can also use the mixin with
prometheus-ksonnet,
a ksonnet module to deploy a fully-fledged
Prometheus-based monitoring system for Kubernetes:

Make sure you have the ksonnet v0.8.0:

$ brew install https://raw.githubusercontent.com/ksonnet/homebrew-tap/82ef24cb7b454d1857db40e38671426c18cd8820/ks.rb
$ brew pin ks
$ ks version
ksonnet version: v0.8.0
jsonnet version: v0.9.5
client-go version: v1.6.8-beta.0+$Format:%h$

In your config repo, if you don't have a ksonnet application, make a new one (will copy credentials from current context):

$ ks init <application name>
$ cd <application name>
$ ks env add default

Grab the kubernetes-jsonnet module using and its dependencies, which include
the kubernetes-mixin:

$ go get github.com/jsonnet-bundler/jsonnet-bundler/cmd/jb
$ jb init
$ jb install github.com/kausalco/public/prometheus-ksonnet

Assuming you want to run in the default namespace ('environment' in ksonnet parlance), add the follow to the file environments/default/main.jsonnet:

local prometheus = import "prometheus-ksonnet/prometheus-ksonnet.libsonnet";

prometheus {
  _config+:: {
    namespace: "default",
  },
}

Apply your config:

$ ks apply default

Using kube-prometheus Copy Chapter

See the kube-prometheus docs for instructions on how to use mixins with kube-prometheus.

Customising the mixin Copy Chapter

Mixins typically allows you to override the selectors used for various jobs,
to match those used in your Prometheus set.

This example uses the kubernetes-mixin.
In a new directory, add a file mixin.libsonnet:

local kubernetes = import "kubernetes-mixin/mixin.libsonnet";

kubernetes {
  _config+:: {
    kubeStateMetricsSelector: 'job="kube-state-metrics"',
    cadvisorSelector: 'job="kubernetes-cadvisor"',
    nodeExporterSelector: 'job="kubernetes-node-exporter"',
    kubeletSelector: 'job="kubernetes-kubelet"',
  },
}

Then, install the kubernetes-mixin:

$ jb init
$ jb install github.com/kubernetes-monitoring/kubernetes-mixin

Generate the alerts, rules and dashboards:

$ jsonnet -J vendor -S -e 'std.manifestYamlDoc((import "mixin.libsonnet").prometheusAlerts)' > alerts.yml
$ jsonnet -J vendor -S -e 'std.manifestYamlDoc((import "mixin.libsonnet").prometheusRules)' >files/rules.yml
$ jsonnet -J vendor -m files/dashboards -e '(import "mixin.libsonnet").grafanaDashboards'

Guidelines for alert names, labels, and annotations Copy Chapter

Prometheus alerts deliberately allow users to define their own schema for
names, labels, and annotations. The following is a style guide recommended for
alerts in monitoring mixins. Following this guide helps creating useful
notification templates for all mixins and customizing mixin alerts in a unified
fashion.

The alert name is a terse description of the alerting condition, using
camel case, without whitespace, starting with a capital letter. The first
component of the name should be shared between all alerts of a mixin (or
between a group of related alerts within a larger mixin). Examples:
NodeFilesystemAlmostOutOfFiles (from the node-exporter
mixin,
PrometheusNotificationQueueRunningFull (from the Prometheus
mixin).

To mark the severity of an alert, use a label called severity with one of
the following label values:

• critical for alerts that require immediate action. For a production system,
  those alerts will usually hit a pager.
• warning for alerts that require action eventually but not urgently enough
  to wake someone up or require them to immediately interrupt what they are
  working on. A typical routing target for those alerts is some kind of ticket
  queueing or bug tracking system.
• info for alerts that do not require any action by itself but mark something
  as “out of the ordinary”. Those alerts aren't usually routed anywhere, but
  can be inspected during troubleshooting.

An alert can have the following annotations:

• summary (mandatory): Essentially a more comprehensive and readable version
  of the alert name. Use a human-readable sentence, starting with a capital
  letter and ending with a period. Use a static string or, if dynamic expansion
  is needed, aim for expanding into the same string for alerts that are
  typically grouped together into one notification. In that way, it can be used
  as a common “headline” for all alerts in the notification template. Examples:
  Filesystem has less than 3% inodes left. (for the
  NodeFilesystemAlmostOutOfFiles alert mentioned above), Prometheus alert notification queue predicted to run full in less than 30m. (for the
  PrometheusNotificationQueueRunningFull alert mentioned above).
• description (mandatory): A detailed description of a single alert, with
  most of the important information templated in. The description usually
  expands into a different string for every individual alert within a
  notification. A notification template can iterate through all the
  descriptions and format them into a list. Examples (again corresponding to
  the examples above): Filesystem on {{ $labels.device }} at {{ $labels.instance }} has only {{ printf "%.2f" $value }}% available inodes left., Alert notification queue of Prometheus %(prometheusName)s is running full..

Note that we plan to add recommended optional annotations for a runbook link
(presumably called runbook_url) and a dashboard link
(dashboard_url). However, we still need to work out how to configure patterns
for those URLs across mixins in a useful way.