Added mtypes CLI for generating realistic avalanche metric type distributions.

.gitignore

@@ -1 +1,3 @@
-avalanche
+./avalanche
+.build/
+.idea/

.promu.yml

@@ -7,7 +7,9 @@ repository:
 build:
     binaries:
         - name: avalanche
-          path: ./cmd
+          path: ./cmd/avalanche
+        - name: mtypes
+          path: ./cmd/mtypes
     ldflags: |
         -X github.com/prometheus/common/version.Version={{.Version}}
         -X github.com/prometheus/common/version.Revision={{.Revision}}

Dockerfile

@@ -6,6 +6,7 @@ LABEL maintainer="The Prometheus Authors <[email protected]
 ARG ARCH="amd64"
 ARG OS="linux"
 COPY .build/${OS}-${ARCH}/avalanche /bin/avalanche
+COPY .build/${OS}-${ARCH}/mtypes /bin/mtypes
 
 EXPOSE      9101
 USER        nobody

README.md

@@ -9,29 +9,41 @@ This allows load testing services that can scrape (e.g. Prometheus, OpenTelemetr
 
 Metric names and unique series change over time to simulate series churn.
 
-Checkout the [blog post](https://blog.freshtracks.io/load-testing-prometheus-metric-ingestion-5b878711711c).
+Checkout the (old-ish) [blog post](https://blog.freshtracks.io/load-testing-prometheus-metric-ingestion-5b878711711c).
 
-## configuration flags
+## Installing
+
+### Locally
 
 ```bash
-avalanche --help
+go install github.com/prometheus-community/avalanche/cmd/avalanche@latest
+${GOPATH}/bin/avalanche --help
 ```
 
-## run Docker image
+### Docker 
 
 ```bash
-docker run quay.io/prometheuscommunity/avalanche:main --help
+docker run quay.io/prometheuscommunity/avalanche:latest --help
 ```
 
-## Endpoints
+NOTE: We recommend using pinned image to a certain version (see all tags [here](https://quay.io/repository/prometheuscommunity/avalanche?tab=tags&tag=latest))
+
+## Using
+
+See [example](example/kubernetes-deployment.yaml) k8s manifest for deploying avalanche as an always running scrape target.
+
+### Configuration
+
+See `--help` for all flags and their documentation.
+
+Notably, from 0.6.0 version, `avalanche` allows specifying various counts per various metric types.
+
+You can choose you own distribution, but usually it makes more sense to mimic realistic distribution used by your example targets. Feel free to use a [handy `mtypes` Go CLI](./cmd/mtypes) to gather type distributions from a target and generate avalanche flags from it.
+
+On top of scrape target functionality, avalanche is capable of Remote Write client load simulation, following the same, configured metric distribution via `--remote*` flags.
+
+### Endpoints
 
 Two endpoints are available :
 * `/metrics` - metrics endpoint
 * `/health` - healthcheck endpoint
-
-## build and run go binary
-
-```bash
-go install github.com/prometheus-community/avalanche/cmd@latest
-go/bin/cmd --help
-```

cmd/mtypes/README.md

@@ -0,0 +1,53 @@
+# mtypes
+
+Go CLI gathering statistics around the distribution of types, average number of buckets (and more) across your Prometheus metrics/series.
+
+## Usage
+
+The main usage allows to take resource (from stdin, file or HTTP /metrics endpoint) and calculate type statistics e.g.:
+
+```bash
+go install github.com/prometheus-community/avalanche/cmd/mtypes@latest # or locally: alias mtypes="go run ./cmd/mtypes"
+$ mtypes -resource=http://localhost:9090/metrics
+$ mtypes -resource=./cmd/mtypes/exampleprometheustarget.txt
+$ cat ./cmd/mtypes/exampleprometheustarget.txt | mtypes
+```
+
+```bash 
+Metric Type    Metric Families    Series (adjusted)    Series (adjusted) %        Average Buckets/Objectives
+GAUGE          76                 93 (93)              31.958763 (16.909091)      -
+COUNTER        96                 157 (157)            53.951890 (28.545455)      -
+HISTOGRAM      8                  14 (186)             4.810997 (33.818182)       11.285714
+SUMMARY        15                 27 (114)             9.278351 (20.727273)       2.222222
+---            ---                ---                  ---                        ---
+*              195                291 (550)            100.000000 (100.000000)    -
+```
+
+> NOTE: "Adjusted" series, means actual number of individual series stored in Prometheus. Classic histograms and summaries are stored as a set of counters. This is relevant as the cost of indexing new series is higher than storing complex values (this is why we slowly move to native histograms).
+
+Additionally, you can pass `--avalanche-flags-for-adjusted-series=10000` to print Avalanche v0.6.0+ flags to configure, for avalanche to generate metric target with the given amount of adjusted series, while maintaining a similar distribution e.g.
+
+```bash
+cat ./cmd/mtypes/exampleprometheustarget.txt | mtypes --avalanche-flags-for-adjusted-series=1000 
+Metric Type    Metric Families    Series (adjusted)    Series (adjusted) %        Average Buckets/Objectives
+GAUGE          76                 93 (93)              31.958763 (16.909091)      -
+COUNTER        96                 157 (157)            53.951890 (28.545455)      -
+HISTOGRAM      8                  14 (186)             4.810997 (33.818182)       11.285714
+SUMMARY        15                 27 (114)             9.278351 (20.727273)       2.222222
+---            ---                ---                  ---                        ---
+*              195                291 (550)            100.000000 (100.000000)    -
+
+Avalanche flags for the similar distribution to get to the adjusted series goal of: 1000
+--gauge-metric-count=16
+--counter-metric-count=28
+--histogram-metric-count=2
+--histogram-metric-bucket-count=10
+--native-histogram-metric-count=0
+--summary-metric-count=5
+--summary-metric-objective-count=2
+--series-count=10
+--value-interval=300 # Changes values every 5m.
+--series-interval=3600 # 1h series churn.
+--metric-interval=0
+This should give the total adjusted series to: 900
+```