Grafana Mimir tools on Grafana Labs

Grafana Mimir listblocks

Fri, 06 Mar 2026 22:21:21 +0000

Grafana Mimir listblocks

The listblocks tool lists blocks and show the block details of a tenant. Listblocks requires at least configuration to access the bucket and tenant.

Listblocks doesn’t use the bucket index; instead, it downloads the meta.json file of every block in the tenant. This means that listblocks has an up-to-date view of the blocks in the bucket.

$ ./listblocks -backend=gcs -gcs.bucket-name=bucket-with-blocks -user=10428
Block ID                     Min Time               Max Time               Duration
01E0HMK47RGAAKZJBMG8B8QXGP   2020-02-07T07:49:46Z   2020-02-08T00:00:00Z   16h10m13.89s
01E0M0VK2KEDZC5AK1PX8K00EX   2020-02-08T00:00:00Z   2020-02-09T00:00:00Z   24h0m0s
01E0PK9B84XJ9KQ0DHZDQECNH6   2020-02-09T00:00:00Z   2020-02-10T00:00:00Z   24h0m0s
01E0S8VAKJ0H41N41GBKQN4G1N   2020-02-10T00:00:00Z   2020-02-11T00:00:00Z   24h0m0s
01E0VTN88859KW1KTDVBS14E7A   2020-02-11T00:00:00Z   2020-02-12T00:00:00Z   24h0m0s
01E0YCZKFG2ME5GZ60AYCQ39V4   2020-02-12T00:00:00Z   2020-02-13T00:00:00Z   24h0m0s
01E111CX17BXFZD97AKSYKX0A5   2020-02-13T00:00:00Z   2020-02-14T00:00:00Z   24h0m0s
01E13JCZK9A5SJMAY6QSSEB0XX   2020-02-14T00:00:00Z   2020-02-15T00:00:00Z   24h0m0s
01E164EJFPT8ZCY6QWEKNJ0VYX   2020-02-15T00:00:00Z   2020-02-16T00:00:00Z   24h0m0s
...

Listblocks has many options you can use to modify the output. The following list contains the most important listblocks options:

  -max-time value
    	If set, only blocks with MaxTime <= this value is printed
  -min-time value
    	If set, only blocks with MinTime >= this value is printed
  -show-block-size
    	Show size of block based on details in meta.json, if available
  -show-compaction-level
    	Show compaction level
  -show-deleted
    	Show deleted blocks
  -show-labels
    	Show block labels
  -show-parents
    	Show parent blocks
  -show-sources
    	Show compaction sources
  -show-ulid-time
    	Show time from ULID

Example

$ ./listblocks -backend=gcs -gcs.bucket-name=bucket-with-blocks -user=10428 -min-time=2022-02-01T00:00:00Z -max-time=2022-02-04T00:00:00Z -show-labels -show-block-size
Block ID                     Min Time               Max Time               Duration   Size     Labels (excl. __org_id__)
01FTWJ3V2TP7N4D7FCSSBJXQ9Z   2022-02-01T00:00:00Z   2022-02-02T00:00:00Z   24h0m0s    69 GiB   {__compactor_shard_id__="1_of_4"}
01FTWJZ3FD4QX4T1FMJJNP7XR1   2022-02-01T00:00:00Z   2022-02-02T00:00:00Z   24h0m0s    69 GiB   {__compactor_shard_id__="2_of_4"}
01FTWMN7AQBPMXWBHVC61ENPT7   2022-02-01T00:00:00Z   2022-02-02T00:00:00Z   24h0m0s    69 GiB   {__compactor_shard_id__="3_of_4"}
01FTWQ5Y87AWVKXH44T2N23BHW   2022-02-01T00:00:00Z   2022-02-02T00:00:00Z   24h0m0s    69 GiB   {__compactor_shard_id__="4_of_4"}
01FTZ4QWE2PNK69ZJGTK2NCWFB   2022-02-02T00:00:00Z   2022-02-03T00:00:00Z   24h0m0s    73 GiB   {__compactor_shard_id__="1_of_4"}
01FTZ55XAZCVHWP9K5AAR5BVHF   2022-02-02T00:00:00Z   2022-02-03T00:00:00Z   24h0m0s    73 GiB   {__compactor_shard_id__="2_of_4"}
01FTZ7AQBCSBB8T6P2Q5QZ416W   2022-02-02T00:00:00Z   2022-02-03T00:00:00Z   24h0m0s    73 GiB   {__compactor_shard_id__="3_of_4"}
01FTYW42TNTZ44QMM9YTFDE6Y4   2022-02-02T00:00:00Z   2022-02-03T00:00:00Z   24h0m0s    73 GiB   {__compactor_shard_id__="4_of_4"}
01FV1S5GQDAFTQ4M9CTN1CD1E4   2022-02-03T00:00:00Z   2022-02-04T00:00:00Z   24h0m0s    77 GiB   {__compactor_shard_id__="1_of_4"}
01FV1JKPH2VFXA4K6XNETC8FBR   2022-02-03T00:00:00Z   2022-02-04T00:00:00Z   24h0m0s    77 GiB   {__compactor_shard_id__="2_of_4"}
01FV1VQQTAJVA287ZY8DC435HD   2022-02-03T00:00:00Z   2022-02-04T00:00:00Z   24h0m0s    77 GiB   {__compactor_shard_id__="3_of_4"}
01FV1FRX39NC1J64D6H6W9VVZ9   2022-02-03T00:00:00Z   2022-02-04T00:00:00Z   24h0m0s    77 GiB   {__compactor_shard_id__="4_of_4"}

Grafana Mimir tenant injector

Fri, 06 Mar 2026 22:21:21 +0000

Grafana Mimir tenant injector

The tenant injector is a standalone HTTP proxy that injects the X-Scope-OrgID header with a value, which you specify via the -tenant-id flag into incoming HTTP requests, and then forwards the modified requests to the URL you specify via the -remote-address flag.

You can use the tenant injector to query data for a tenant during development or troubleshooting.

Usage of tenant-injector:
  -local-address string
    	Local address to listen on (host:port or :port). (default ":8080")
  -remote-address string
    	URL of target to forward requests to to (eg. http://domain.com:80).
  -tenant-id string
    	Tenant ID to inject to proxied requests.

Grafana Mimir query-tee

Fri, 06 Mar 2026 22:21:21 +0000

Grafana Mimir query-tee

The query-tee is a standalone tool that you can use for testing purposes when comparing the query results and performances of two Grafana Mimir clusters. The two Mimir clusters compared by the query-tee must ingest the same series and samples.

The query-tee exposes Prometheus-compatible read API endpoints and acts as a proxy. When the query-tee receives a request, it performs the same request against the two backend Grafana Mimir clusters and tracks the response time of each backend, and compares the query results.

Download the query-tee

Using Docker:

docker pull "grafana/query-tee:latest"

Using a local binary:

Download the appropriate release asset for your operating system and architecture and make it executable.

For Linux with the AMD64 architecture, execute the following command:

curl -Lo query-tee https://github.com/grafana/mimir/releases/latest/download/query-tee-linux-amd64
chmod +x query-tee

Configure the query-tee

The query-tee requires the endpoints of the backend Grafana Mimir clusters. You can configure the backend endpoints by setting the -backend.endpoints flag to a comma-separated list of HTTP or HTTPS URLs. For each incoming request, the query-tee clones the request and sends it to each configured backend.

Note: You can configure the query-tee proxy listening port via the -server.service-port flag.

How the query-tee works

This section describes how the query-tee tool works.

API endpoints

The following Prometheus API endpoints are supported by query-tee:

GET <prefix>/api/v1/query
GET <prefix>/api/v1/query_range
GET <prefix>/api/v1/query_exemplars
GET <prefix>/api/v1/labels
GET <prefix>/api/v1/label/{name}/values
GET <prefix>/api/v1/series
GET <prefix>/api/v1/metadata
GET <prefix>/api/v1/alerts
GET <prefix>/api/v1/rules

You can configure the <prefix> by setting the -server.path-prefix flag, which defaults to an empty string.

Pass-through requests

The query-tee can optionally act as a transparent proxy for requests to routes not matching any of the supported API endpoints. You can enable the pass-through support setting -proxy.passthrough-non-registered-routes=true and configuring a preferred backend using the -backend.preferred flag. When pass-through is enabled, a request for an unsupported API endpoint is transparently proxied to the configured preferred backend.

Authentication

The query-tee supports HTTP basic authentication. The query-tee can merge the HTTP basic authentication in the received request with the username and configured in a backend URL.

A request sent from the query-tee to a backend includes HTTP basic authentication when one of the following conditions is met:

If the backend endpoint URL is configured with both a username and password, then query-tee uses it.
If the backend endpoint URL is configured only with a username, then query-tee keeps the configured username and injects the password received in the incoming request.
If the backend endpoint URL is configured without a username and password, then query-tee forwards the authentication credentials found in the incoming request.

Backend response selection

The query-tee enables you to configure a preferred backend that selects the response to send back to the client. The preferred backend can be configured via -backend.preferred=<hostname>. The value of the preferred backend configuration option must be the hostname of one of the configured backends.

When a preferred backend is configured, the query-tee uses the following algorithm to select the backend response to send back to the client:

If the preferred backend response status code is 2xx or 4xx, the query-tee selects the response from the preferred backend.
If at least one backend response status code is 2xx or 4xx, the query-tee selects the first received response whose status code is 2xx or 4xx.
If no backend response status code is 2xx or 4xx, the query-tee selects the first received response regardless of the status code.

When a preferred backend is not configured, the query-tee uses the following algorithm to select the backend response to send back to the client:

If at least one backend response status code is 2xx or 4xx, the query-tee selects the first received response whose status code is 2xx or 4xx.
If no backend response status code is 2xx or 4xx, the query-tee selects the first received response regardless of the status code.

Note: The query-tee considers a 4xx response as a valid response to select because a 4xx status code generally means the error is caused by an invalid request and not due to a server side issue.

Backend results comparison

The query-tee can optionally compare the query results received by two backends. The query results comparison can be enabled setting the flag -proxy.compare-responses=true and requires that:

Two backends have been configured setting -backend.endpoints.
A preferred backend is configured setting -backend.preferred.

When the query results comparison is enabled, the query-tee compares the response received from the two configured backends and logs a message for each query whose results don’t match. Query-tee keeps track of the number of successful and failed comparison through the metric cortex_querytee_responses_compared_total.

Note: Floating point sample values are compared with a tolerance that can be configured via -proxy.value-comparison-tolerance. The configured tolerance prevents false positives due to differences in floating point values rounding introduced by the non-deterministic series ordering within the Prometheus PromQL engine.

Exported metrics

The query-tee exposes the following Prometheus metrics at the /metrics endpoint listening on the port configured via the flag -server.metrics-port:

# HELP cortex_querytee_request_duration_seconds Time (in seconds) spent serving HTTP requests.
# TYPE cortex_querytee_request_duration_seconds histogram
cortex_querytee_request_duration_seconds_bucket{backend="<hostname>",method="<method>",route="<route>",status_code="<status>",le="<bucket>"}
cortex_querytee_request_duration_seconds_sum{backend="<hostname>",method="<method>",route="<route>",status_code="<status>"}
cortex_querytee_request_duration_seconds_count{backend="<hostname>",method="<method>",route="<route>",status_code="<status>"}

# HELP cortex_querytee_responses_total Total number of responses sent back to the client by the selected backend.
# TYPE cortex_querytee_responses_total counter
cortex_querytee_responses_total{backend="<hostname>",method="<method>",route="<route>"}

# HELP cortex_querytee_responses_compared_total Total number of responses compared per route name by result.
# TYPE cortex_querytee_responses_compared_total counter
cortex_querytee_responses_compared_total{route="<route>",result="<success|fail>"}

Grafana Mimirtool

Fri, 06 Mar 2026 22:21:21 +0000

Grafana Mimirtool

Mimirtool is a command-line tool that operators and tenants can use to execute a number of common tasks that involve Grafana Mimir or Grafana Cloud Metrics.

The alertmanager command enables you to create, update, and delete tenant configurations in Grafana Mimir Alertmanager or Grafana Cloud Metrics.

For more information about the alertmanager command, refer to Alertmanager.
The rules command enables you to validate and lint Prometheus rule files and convert them for use in Grafana Mimir. You can also create, update, and delete rulegroups in Grafana Mimir or Grafana Cloud Metrics.

For more information about the rules command, refer to Rules.
The remote-read subcommand enables you to fetch statistics and series from remote-read APIs. You can write series from a remote-read API to a local TSDB file that you load into Prometheus.

For more information about the remote-read command, refer to Remote-read.
The analyze command extracts statistics about metric usage from Grafana or Hosted Grafana instances. You can also extract the same metrics from Grafana dashboard JSON files or Prometheus rule YAML files.

For more information about the analyze command, refer to Analyze.
The bucket-validation command verifies that an object storage bucket is suitable as a backend storage for Grafana Mimir.

For more information about the bucket-validation command, refer to Bucket validation.
The acl command generates the label-based access control header used in Grafana Enterprise Metrics and Grafana Cloud Metrics.

For more information about the acl command, refer to ACL.
The config command helps convert configuration files from Cortex to Grafana Mimir.

For more information about the config command, refer to Config

Mimirtool interacts with:

User-facing APIs provided by Grafana Mimir.
Backend storage components containing Grafana Mimir data.

Installation

To install Grafana Mimirtool, refer to the latest release.

Configuration options

For Mimirtools to interact with Grafana Mimir, Grafana Enterprise Metrics, Prometheus, or Grafana, set the following environment variables or CLI flags.

Environment variable	Flag	Description
`MIMIR_ADDRESS`	`--address`	Sets the address of the API of the Grafana Mimir cluster.
`MIMIR_API_USER`	`--user`	Sets the basic auth username. If this variable is empty and `MIMIR_API_KEY` is set, the system uses `MIMIR_TENANT_ID` instead. If you’re using Grafana Cloud, this variable is your instance ID.
`MIMIR_API_KEY`	`--key`	Sets the basic auth password. If you’re using Grafana Cloud, this variable is your API key.
`MIMIR_TENANT_ID`	`--id`	Sets the tenant ID of the Grafana Mimir instance that Mimirtools interacts with.

Commands

The following sections outline the commands that you can run against Grafana Mimir and Grafana Cloud Metrics.

Alertmanager

The following commands interact with Grafana Mimir Alertmanager configuration and alert template files.

Get configuration

The following command shows the current Alertmanager configuration.

mimirtool alertmanager get

Load configuration

The following command loads an Alertmanager configuration to the Alertmanager instance.

mimirtool alertmanager load <config_file>
mimirtool alertmanager load <config_file> <template_files>...

Example

mimirtool alertmanager load ./example_alertmanager_config.yaml

./example_alertmanager_config.yaml:

route:
  receiver: "example_receiver"
  group_by: ["example_groupby"]
receivers:
  - name: "example_receiver"

Delete configuration

The following command deletes the Alertmanager configuration in the Grafana Mimir Alertmanager.

mimirtool alertmanager delete

Alert verification

The following command verifies if alerts in an Alertmanager cluster are deduplicated. This command is useful for verifying the correct configuration when transferring from Prometheus to Grafana Mimir alert evaluation.

mimirtool alerts verify

Rules

The rules command features sub-commands for working with Prometheus rule files and with the APIs in the Grafana Mimir ruler.

The commands in this section enable you to perform the following actions:

Load and show Prometheus rule files
Interact with individual rule groups in the Mimir ruler
Manipulate local rule files

List

The following command retrieves the names of all rule groups in the Grafana Mimir instance and prints them to the terminal.

mimirtool rules list

Print

The following command retrieves all rule groups in the Grafana Mimir instance and prints them to the terminal.

mimirtool rules print

Get

The following command retrieves a single rule group and prints it to the terminal.

mimirtool rules get <namespace> <rule_group_name>

Delete

The following command deletes a rule group.

mimirtool rules delete <namespace> <rule_group_name>

Load

The following command loads each rule group from the files into Grafana Mimir. This command overwrites all existing rule groups with the same name.

mimirtool rules load <file_path>...

Example

mimirtool rules load ./example_rules_one.yaml

./example_rules_one.yaml:

namespace: my_namespace
groups:
  - name: example
    interval: 5m
    rules:
      - record: job:http_inprogress_requests:sum
        expr: sum by (job) (http_inprogress_requests)

Lint

The lint command provides YAML and PromQL expression formatting within the rule file.

This command edits the rule file in place. To perform a trial run that does not make changes, you can use the dry run flag (-n).

Note: This command does not verify if a query is correct and does not interact with your Grafana Mimir cluster.

mimirtool rules lint <file_path>...

The format of the file is the same format as shown in rules load.

Prepare

This prepare command prepares a rules file that you upload to Grafana Mimir. It lints all PromQL expressions and adds a label to your PromQL query aggregations in the file. The format of the file is the same format as shown in rules load.

Note: This command does not interact with your Grafana Mimir cluster.

mimirtool rules prepare <file_path>...

Configuration

Flag	Description
`-i`, `--in-place`	Edits the file in place. If not set, the system generates a new file with the extension `.result` that contains the results.
`-l`, `--label="cluster"`	Specifies the label for aggregations. By default, the label is set to `cluster`.

Example

mimirtool rules prepare ./example_rules_one.yaml

./example_rules_one.yaml:

namespace: my_namespace
groups:
  - name: example
    interval: 5m
    rules:
      - record: job:http_inprogress_requests:sum
        expr: sum by (job) (http_inprogress_requests)

./example_rules_one.yaml.result:

namespace: my_namespace
groups:
  - name: example
    interval: 5m
    rules:
      - record: job:http_inprogress_requests:sum
        # note the added cluster label
        expr: sum by(job, cluster) (http_inprogress_requests)

After the command runs, an output message indicates if the operation was successful:

INFO[0000] SUCCESS: 1 rules found, 0 modified expressions

Check

The check command checks rules against the recommended best practices for rules. This command does not interact with your Grafana Mimir cluster.

mimirtool rules check <file_path>...

Example

mimirtool rules check rules.yaml

rules.yaml

namespace: my_namespace
groups:
  - name: example
    interval: 5m
    rules:
      - record: job_http_inprogress_requests_sum
        expr: sum by (job) (http_inprogress_requests)

ERRO[0000] bad recording rule name error="recording rule name does not match level:metric:operation format, must contain at least one colon" file=rules.yaml rule=job_http_inprogress_requests_sum ruleGroup=example

The format of the file is the same format as shown in rules load.

Diff

The following command compares rules against the rules in your Grafana Mimir cluster.

mimirtool rules diff <file_path>...

The format of the file is the same format as shown in rules load.

Sync

The sync command compares rules against the rules in your Grafana Mimir cluster. The command applies any differences to your Grafana Mimir cluster.

mimirtool rules sync <file_path>...

The format of the file is the same format as shown in rules load.

Remote-read

Grafana Mimir exposes a remote read API which allows the system to access the stored series. The remote-read subcommand mimirtool enables you to interact with its API, and to determine which series are stored.

Stats

The remote-read stats command summarizes statistics of the stored series that match the selector.

Example

mimirtool remote-read stats --selector '{job="node"}' --address http://demo.robustperception.io:9090 --remote-read-path /api/v1/read

Running the command results in the following output:

INFO[0000] Create remote read client using endpoint 'http://demo.robustperception.io:9090/api/v1/read'
INFO[0000] Querying time from=2020-12-30T14:00:00Z to=2020-12-30T15:00:00Z with selector={job="node"}
INFO[0000] MIN TIME                           MAX TIME                           DURATION     NUM SAMPLES  NUM SERIES   NUM STALE NAN VALUES  NUM NAN VALUES
INFO[0000] 2020-12-30 14:00:00.629 +0000 UTC  2020-12-30 14:59:59.629 +0000 UTC  59m59s       159480       425          0                     0

Dump

The remote-read dump command prints all series and samples that match the selector.

Example

mimirtool remote-read dump --selector 'up{job="node"}' --address http://demo.robustperception.io:9090 --remote-read-path /api/v1/read

Running the command results in the following output:

{__name__="up", instance="demo.robustperception.io:9100", job="node"} 1 1609336914711
{__name__="up", instance="demo.robustperception.io:9100", job="node"} NaN 1609336924709 # StaleNaN
...

Export

The remote-read export command exports all series and samples that match the selector into a local TSDB. You can use local tooling such as prometheus and promtool to further analyze the TSDB.

# Use Remote Read API to download all metrics with label job=name into local tsdb
mimirtool remote-read export --selector '{job="node"}' --address http://demo.robustperception.io:9090 --remote-read-path /api/v1/read --tsdb-path ./local-tsdb

Running the command results in the following output:

INFO[0000] Create remote read client using endpoint 'http://demo.robustperception.io:9090/api/v1/read'
INFO[0000] Created TSDB in path './local-tsdb'
INFO[0000] Using existing TSDB in path './local-tsdb'
INFO[0000] Querying time from=2020-12-30T13:53:59Z to=2020-12-30T14:53:59Z with selector={job="node"}
INFO[0001] Store TSDB blocks in './local-tsdb'
INFO[0001] BLOCK ULID                  MIN TIME                       MAX TIME                       DURATION     NUM SAMPLES  NUM CHUNKS   NUM SERIES   SIZE
INFO[0001] 01ETT28D6B8948J87NZXY8VYD9  2020-12-30 13:53:59 +0000 UTC  2020-12-30 13:59:59 +0000 UTC  6m0.001s     15950        429          425          105KiB867B
INFO[0001] 01ETT28D91Z9SVRYF3DY0KNV41  2020-12-30 14:00:00 +0000 UTC  2020-12-30 14:53:58 +0000 UTC  53m58.001s   143530       1325         425          509KiB679B

Local TSDB examples

The following command uses promtool to analyze file contents.

promtool tsdb analyze ./local-tsdb

The following command dumps all values of the TSDB.

promtool tsdb dump ./local-tsdb

The following command runs a local Prometheus with the local TSDB.

prometheus --storage.tsdb.path ./local-tsdb --config.file=<(echo "")

ACL

The acl command generates the label-based access control header used in Grafana Enterprise Metrics and Grafana Cloud Metrics.

Generate header

The following command enables you to generate a header that you can use to enforce access control rules in Grafana Enterprise Metrics or Grafana Cloud.

Note: Grafana Mimir does not support ACLs.

mimirtool acl generate-header --id=<tenant_id> --rule=<promql_selector>

Example

mimirtool acl generate-header --id=1234 --rule='{namespace="A"}'

Example output:

The header to set:
X-Prom-Label-Policy: 1234:%7Bnamespace=%22A%22%7D

Analyze

You can analyze your Grafana or Hosted Grafana instance to determine which metrics are used and exported. You can also extract metrics from dashboard JSON files and rules YAML files.

Grafana

The following command runs against your Grafana instance, downloads its dashboards, and extracts the Prometheus metrics used in its queries. The output is a JSON file. You can use this file with analyse prometheus --grafana-metrics-file.

mimirtool analyze grafana --address=<url>

Configuration

Environment variable	Flag	Description
`GRAFANA_ADDRESS`	`--address`	Sets the address of the Grafana instance.
`GRAFANA_API_KEY`	`--key`	Sets the API Key for the Grafana instance. To create a key, refer to Authentication API.
-	`--output`	Sets the output file path, which by default is `metrics-in-grafana.json`.

Example output file

{
  "metricsUsed": [
    "apiserver_request:availability30d",
    "workqueue_depth",
    "workqueue_queue_duration_seconds_bucket"
  ],
  "dashboards": [
    {
      "slug": "",
      "uid": "09ec8aa1e996d6ffcd6817bbaff4db1b",
      "title": "Kubernetes / API server",
      "metrics": [
        "apiserver_request:availability30d",
        "apiserver_request_total",
        "cluster_quantile:apiserver_request_duration_seconds:histogram_quantile",
        "workqueue_depth",
        "workqueue_queue_duration_seconds_bucket"
      ],
      "parse_errors": ["unsupported panel type: \"news\""]
    }
  ]
}

Ruler

The following command runs against your Grafana Mimir, Grafana Enterprise Metrics, or Grafana Cloud Prometheus instance. The command fetches the rule groups and extracts the Prometheus metrics used in the rule queries. The output is a JSON file. You can use this file with analyse prometheus --ruler-metrics-file.

mimirtool analyze ruler --address=<url> --id=<tenant_id>

Configuration

Environment variable	Flag	Description
`MIMIR_ADDRESS`	`--address`	Sets the address of the Prometheus instance.
`MIMIR_TENANT_ID`	`--user`	Sets the basic auth username. If you’re using Grafana Cloud, this variable is your instance ID.
`MIMIR_API_KEY`	`--key`	Sets the basic auth password. If you’re using Grafana Cloud, this variable is your API key.
-	`--output`	Sets the output file path, which by default is `metrics-in-ruler.json`.

Example output file

{
  "metricsUsed": [
    "apiserver_request_duration_seconds_bucket",
    "container_cpu_usage_seconds_total",
    "scheduler_scheduling_algorithm_duration_seconds_bucket"
  ],
  "ruleGroups": [
    {
      "namspace": "prometheus_rules",
      "name": "kube-apiserver.rules",
      "metrics": [
        "apiserver_request_duration_seconds_bucket",
        "apiserver_request_duration_seconds_count",
        "apiserver_request_total"
      ],
      "parse_errors": null
    }
  ]
}

Dashboard

The following command accepts Grafana dashboard JSON files as input and extracts Prometheus metrics used in the queries. The output is a JSON file. You can use the output file with analyze prometheus --grafana-metrics-file.

mimirtool analyze dashboard <file>...

Configuration

Environment variable	Flag	Description
-	`--output`	Sets the output file path, which by default is `prometheus-metrics.json`.

Rule-file

The following command accepts Prometheus rule YAML files as input and extracts Prometheus metrics used in the queries. The output is a JSON file. You can use the output file with analyse prometheus --ruler-metrics-file.

mimirtool analyze rule-file <file>

Configuration

Environment variable	Flag	Description
-	`--output`	Sets the output file path, which by default is `prometheus-metrics.json`.

Prometheus

The following command runs against your Grafana Mimir, Grafana Metrics Enterprise, Prometheus, or Cloud Prometheus instance. The command uses the output from a previous run of analyse grafana, analyse dashboard, analyse ruler or analyse rule-file to show the number of series in the Prometheus instance that are used in dashboards or rules, or both. This command also shows which metrics exist in Grafana Cloud that are not in dashboards or rules. The output is a JSON file.

Note: The command makes a request for every active series in the Prometheus instance. For Prometheus instances with a large number of active series, this command might take time to complete.

mimirtool analyze prometheus --address=<url> --id=<tenant_id>

Configuration

Environment variable	Flag	Description
`MIMIR_ADDRESS`	`--address`	Sets the address of the Prometheus instance.
`MIMIR_TENANT_ID`	`--user`	Sets the basic auth username. If you’re using Grafana Cloud this variable is your instance ID.
`MIMIR_API_KEY`	`--key`	Sets the basic auth password. If you’re using Grafana Cloud, this variable is your API key.
-	`--grafana-metrics-file`	`mimirtool analyse grafana` or `mimirtool analyse dashboard` output file, which by default is `metrics-in-grafana.json`.
-	`--ruler-metrics-file`	`mimirtool analyse ruler` or `mimirtool analyse rule-file` output file, which by default is `metrics-in-ruler.json`.
-	`--output`	Sets the output file path, which by default is `prometheus-metrics.json`.

Example output

{
  "total_active_series": 38184,
  "in_use_active_series": 14047,
  "additional_active_series": 24137,
  "in_use_metric_counts": [
    {
      "metric": "apiserver_request_duration_seconds_bucket",
      "count": 11400,
      "job_counts": [
        {
          "job": "apiserver",
          "count": 11400
        }
      ]
    },
    {
      "metric": "apiserver_request_total",
      "count": 684,
      "job_counts": [
        {
          "job": "apiserver",
          "count": 684
        }
      ]
    }
  ],
  "additional_metric_counts": [
    {
      "metric": "etcd_request_duration_seconds_bucket",
      "count": 2688,
      "job_counts": [
        {
          "job": "apiserver",
          "count": 2688
        }
      ]
    }
  ]
}

Bucket validation

The following command validates that the object store bucket works correctly.

mimirtool bucket-validation

Flag	Description
`--object-count`	Sets the number of objects to create and delete. By default, the value is 2000.
`--report-every`	Sets the number operations afterwhich an operations progress report is printed. By default, the value is 100.
`--test-runs`	Sets the number of times to run the test. By default, the value is 1.
`--prefix`	Sets the path prefix to use for test objects in the object store.
`--retries-on-error`	Sets the number of times to retry if the object store returns an error.
`--bucket-config`	Sets the CLI arguments to configure a storage bucket.
`--bucket-config-help`	Displays help text that explains how to use the -bucket-config parameter.

Config

Convert

The config convert command converts configuration parameters that work with Cortex v1.10.0 and above to parameters that work with Grafana Mimir v2.0.0. It supports converting both CLI flags and YAML configuration files.

Configuration

Flag	Description
`--yaml-file`	The YAML configuration file to convert.
`--flags-file`	A file containing a newline-delimited list of CLI flags to convert.
`--yaml-out`	File to use for the converted YAML configuration. If not set, output to `stdout`.
`--flags-out`	File to use for list of converted CLI flags. If not set, output to `stdout`.
`--update-defaults`	If you set this flag and you set a configuration parameter to a default value that has changed in Mimir 2.0, the parameter updates to the new default value.
`--include-defaults`	If you set this flag, all default values are included in the output YAML, regardless of whether you explicitly set the values in the input files.
`-v`, `--verbose`	If you set this flag, the CLI flags and YAML paths from the old configuration that do not exist in the new configuration are printed to `stderr`. This flag also prints default values that have changed between the old and the new configuration.
`--gem`	If you set this flag, the tool will convert from Grafana Metrics Enterprise (GEM) v1.7.x to v2.0.0.

Example

The following example shows a command that converts Cortex query-frontend YAML configuration file and CLI flag to a Mimir-compatible YAML and CLI flag.

mimirtool config convert --yaml-file=cortex.yaml --flags-file=cortex.flags --yaml-out=mimir.yaml --flags-out=mimir.flags

cortex.yaml input file:

query_range:
  results_cache:
    cache:
      memcached:
        expiration: 10s # Expiration was removed in Grafana Mimir, so this parameter will be missing from the output YAML
        batch_size: 2048
        parallelism: 10
      memcached_client:
        max_idle_conns: 32

cortex.flags input file:

-frontend.background.write-back-concurrency=45

After you run the command, the converted output should be:

mimir.yaml converted output file:

frontend:
  results_cache:
    memcached:
      max_get_multi_batch_size: 2048
      max_get_multi_concurrency: 10
      max_idle_connections: 32

server:
  http_listen_port: 80

Note: As a precaution,server.http_listen_port is included. The default value in Grafana Mimir changed from 80 to 8080. Unless you explicitly set the port in the input configuration, the tool outputs the old default value.

mimir.flags converted output file:

-query-frontend.results-cache.memcached.max-async-concurrency=45

Verbose output

When you set the --verbose flag, the output explains which configuration parameters were removed and which default values were changed. The verbose output is printed to stderr.

The output includes the following entries:

field is no longer supported: <yaml_path>

This parameter was used in the input Cortex YAML file and removed from the output configuration.
flag is no longer supported: <flag_name>

This parameter was used in the input Cortex CLI flags file, but the parameter was removed in Grafana Mimir. The tool removed this CLI flag from the output configuration.
using a new default for <yaml_path>: <new_value> (used to be <old_value>)

The default value for a configuration parameter changed in Grafana Mimir. This parameter was not explicitly set in the input configuration files. When you run Grafana Mimir with the output configuration from mimirtool config convert Grafana Mimir uses the new default.
default value for <yaml_path> changed: <new_value> (used to be <old_value>); not updating

The default value for a configuration parameter that was set in the input configuration file has changed in Grafana Mimir. The tool has not converted the old default value to the new default value. To automatically update the default value to the new default value, pass the --update-defaults flag.

Extracting flags from Jsonnet

When using the Grafana Mimir Jsonnet library, all configuration uses flags set as object member key-value pairs. To perform conversion with mimirtool, you first need to extract the flags from the JSON manifested from the Jsonnet evaluation.

Use the following bash script to extract the arguments from a specific component:

 #!/usr/bin/env bash

 set -euf -o pipefail

 function usage {
   cat <<EOF
 Extract the CLI flags from individual components.

 Usage:
   $0 <resources JSON> <component>

 Examples:
   $0 resources.json ingester
   $0 <(tk eval environments/default) distributor
   $0 <(jsonnet environments/default/main.jsonnet) query-frontend
 EOF
 }

 if ! command -v jq &>/dev/null; then
   echo "jq command not found in PATH"
   echo "To download jq, refer to https://stedolan.github.io/jq/download/."
 fi

 if [[ $# -ne 2 ]]; then
   usage
   exit 1
 fi

 jq -rf /dev/stdin -- "$1" <<EOF
 ..
 | if type == "object" and .metadata.name == "$2" then .spec.template.spec.containers[]?.args[] else null end
 | select(. != null)
 EOF

The first parameter of the script is a JSON file containing Kubernetes resources. The second parameter of the script is the name of a container.

To retrieve the arguments from the distributor for a Tanka environment:

<PATH TO SCRIPT> <(tk eval environments/default) distributor

The script outputs results that are similar to the following:

-consul.hostname=consul.cortex-to-mimir.svc.cluster.local:8500
-distributor.extend-writes=true
-distributor.ha-tracker.enable=false
-distributor.ha-tracker.enable-for-all-users=true
-distributor.ha-tracker.etcd.endpoints=etcd-client.cortex-to-mimir.svc.cluster.local.:2379
-distributor.ha-tracker.prefix=prom_ha/
-distributor.ha-tracker.store=etcd
-distributor.health-check-ingesters=true
-distributor.ingestion-burst-size=200000
-distributor.ingestion-rate-limit=10000
-distributor.ingestion-rate-limit-strategy=global
-distributor.remote-timeout=20s
-distributor.replication-factor=3
-distributor.ring.consul.hostname=consul.cortex-to-mimir.svc.cluster.local:8500
-distributor.ring.prefix=
-distributor.shard-by-all-labels=true
-mem-ballast-size-bytes=1073741824
-ring.heartbeat-timeout=10m
-ring.prefix=
-runtime-config.file=/etc/cortex/overrides.yaml
-server.grpc.keepalive.max-connection-age=2m
-server.grpc.keepalive.max-connection-age-grace=5m
-server.grpc.keepalive.max-connection-idle=1m
-server.grpc.keepalive.min-time-between-pings=10s
-server.grpc.keepalive.ping-without-stream-allowed=true
-target=distributor
-validation.reject-old-samples=true
-validation.reject-old-samples.max-age=12h

Use the output of the script as input to run the mimirtool configuration conversion.

After conversion, you can use the following script to transform the converted flags back into JSON:

#!/usr/bin/env bash

set -euf -o pipefail

function usage {
 cat <<EOF
Transform Go flags into JSON key value pairs

Usage:
 $0 <flags file>

Examples:
 $0 flags.flags
EOF
}

if [[ $# -ne 1 ]]; then
 usage
 exit 1
fi

key_values=$(sed -E -e 's/^-*(.*)=(.*)$/  "\1": "\2",/' "$1")
printf "{\n%s\n}" "${key_values::-1}"

The only parameter of the script is a file containing the flags, with each flag on its own line.

License

Licensed AGPLv3, see LICENSE.