Important: This documentation is about an older version. It's relevant only to the release noted, many of the features and functions have been updated or replaced. Please view the current version.

Documentation Grafana Mimir Operator and user guide Grafana Mimir tools Mimirtool

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.

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.

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mimirtool alertmanager get

Load configuration

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

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

Example

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mimirtool alertmanager load ./example_alertmanager_config.yaml

./example_alertmanager_config.yaml:

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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.

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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.

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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.

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mimirtool rules list

Print

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

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mimirtool rules print

Get

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

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mimirtool rules get <namespace> <rule_group_name>

Delete

The following command deletes a rule group.

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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.

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mimirtool rules load <file_path>...

Example

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mimirtool rules load ./example_rules_one.yaml

./example_rules_one.yaml:

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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.

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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.

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mimirtool rules prepare <file_path>...

Configuration

Example

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mimirtool rules prepare ./example_rules_one.yaml

./example_rules_one.yaml:

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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:

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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:

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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.

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mimirtool rules check <file_path>...

Example

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mimirtool rules check rules.yaml

rules.yaml

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

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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.

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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.

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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

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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:

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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

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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:

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{__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.

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# 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:

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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.

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promtool tsdb analyze ./local-tsdb

The following command dumps all values of the TSDB.

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promtool tsdb dump ./local-tsdb

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

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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.

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

Example

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

Example output:

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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.

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mimirtool analyze grafana --address=<url>

Configuration

Example output file

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{
  "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.

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

Configuration

Example output file

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{
  "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.

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mimirtool analyze dashboard <file>...

Configuration

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.

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mimirtool analyze rule-file <file>

Configuration

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.

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

Configuration

Example output

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{
  "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.

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mimirtool bucket-validation

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

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.

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

cortex.yaml input file:

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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:

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

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

mimir.yaml converted output file:

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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:

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-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:

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 #!/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:

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

The script outputs results that are similar to the following:

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-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:

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#!/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.