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rfrattorfratto
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prepare for 0.6.0 (#183)
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‎CHANGELOG.md

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@@ -4,6 +4,12 @@ NOTE: FreeBSD builds will not be included for this release. There is a bug in an
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upstream library preventing cross-compilation of the Grafana Cloud Agent for
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this platform. FreeBSD builds will return in a future release.
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# v0.6.0 (2020-09-04)
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NOTE: FreeBSD builds will not be included for this release. There is a bug in an
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upstream library preventing cross-compilation of the Grafana Cloud Agent for
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this platform. FreeBSD builds will return in a future release.
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- [FEATURE] The Grafana Cloud Agent can now collect logs and send to Loki. This
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is done by embedding Promtail, the official Loki log collection client.
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(@rfratto)

‎docs/configuration-reference.md

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@@ -1541,7 +1541,7 @@ docker run \
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-v "/proc:/host/proc:ro,rslave" \
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-v /tmp/agent:/etc/agent \
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-v /path/to/config.yaml:/etc/agent-config/agent.yaml \
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grafana/agent:v0.5.0 \
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grafana/agent:v0.6.0 \
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--config.file=/etc/agent-config/agent.yaml
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```
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@@ -1581,7 +1581,7 @@ metadata:
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name: agent
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spec:
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containers:
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- image: grafana/agent:v0.5.0
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- image: grafana/agent:v0.6.0
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name: agent
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args:
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- --config.file=/etc/agent-config/agent.yaml
@@ -1848,7 +1848,7 @@ docker run \
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-v "/proc:/proc:ro" \
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-v /tmp/agent:/etc/agent \
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-v /path/to/config.yaml:/etc/agent-config/agent.yaml \
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grafana/agent:v0.5.0 \
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grafana/agent:v0.6.0 \
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--config.file=/etc/agent-config/agent.yaml
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```
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@@ -1865,7 +1865,7 @@ metadata:
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name: agent
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spec:
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containers:
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- image: grafana/agent:v0.5.0
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- image: grafana/agent:v0.6.0
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name: agent
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args:
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- --config.file=/etc/agent-config/agent.yaml

‎docs/getting-started.md

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@@ -46,7 +46,7 @@ Currently, there are five ways to install the agent:
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### Docker Container
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```
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docker pull grafana/agent:v0.5.0
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docker pull grafana/agent:v0.6.0
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```
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### Kubernetes Install Script
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docker run \
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-v /tmp/agent:/etc/agent \
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-v /path/to/config.yaml:/etc/agent-config/agent.yaml \
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grafana/agent:v0.5.0
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grafana/agent:v0.6.0
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```
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### Locally

‎docs/maintaining.md

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@@ -53,10 +53,12 @@ export GPG_TTY=$(tty)
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for generating the list (modifying the date to the date of the previous release): `curl https://api.github.com/search/issues?q=repo:grafana/agent+is:pr+"merged:>=2019-08-02" | jq -r ' .items[] | "* [" + (.number|tostring) + "](" + .html_url + ") **" + .user.login + "**: " + .title'`
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4. Go through the entire repository and find references to the previous release
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version, updating them to reference the new version.
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5. *Without creating a tag*, create a commit based on your changes and open a PR
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5. Run `make example-kubernetes` and `make example-dashboards` to update
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manifests in case they are stale.
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6. *Without creating a tag*, create a commit based on your changes and open a PR
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for updating the release notes.
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6. Merge the changelog PR.
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7. Create a new tag for the release.
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7. Merge the changelog PR.
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8. Create a new tag for the release.
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1. After following step 2, the CI will be triggered to create release
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artifacts and publish them to a draft release. The tag will be made
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publicly available immediately.
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git tag -s $RELEASE -m "release $RELEASE"
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git push origin $RELEASE
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```
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8. Watch GitHub Actions and wait for all the jobs to finish running.
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9. Watch GitHub Actions and wait for all the jobs to finish running.
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## Publishing the Release Draft
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‎example/docker-compose/grafana/dashboards/agent-operational.json

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@@ -45,10 +45,10 @@
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"steppedLine": false,
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"targets": [
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{
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"expr": "rate(go_gc_duration_seconds_count{cluster=~\"$cluster\", namespace=~\"$namespace\", job=~\"$job\"}[5m])",
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"expr": "rate(go_gc_duration_seconds_count{cluster=~\"$cluster\", namespace=~\"$namespace\", container=~\"$container\", pod=~\"$pod\"}[5m])",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{job}}",
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"legendFormat": "{{pod}}",
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"legendLink": null,
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"step": 10
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}
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"steppedLine": false,
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"targets": [
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{
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"expr": "go_memstats_heap_inuse_bytes{cluster=~\"$cluster\", namespace=~\"$namespace\", job=~\"$job\"}",
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"expr": "go_memstats_heap_inuse_bytes{cluster=~\"$cluster\", namespace=~\"$namespace\", container=~\"$container\", pod=~\"$pod\"}",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{job}}",
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"legendFormat": "{{pod}}",
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"legendLink": null,
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"step": 10
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}
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"steppedLine": false,
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"targets": [
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{
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"expr": "go_goroutines{cluster=~\"$cluster\", namespace=~\"$namespace\", job=~\"$job\"}",
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"expr": "go_goroutines{cluster=~\"$cluster\", namespace=~\"$namespace\", container=~\"$container\", pod=~\"$pod\"}",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{job}}",
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"legendFormat": "{{pod}}",
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"legendLink": null,
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"step": 10
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}
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"steppedLine": false,
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"targets": [
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{
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"expr": "rate(container_cpu_usage_seconds_total{cluster=~\"$cluster\", pod_name=~\".*grafana-agent.*\"}[5m])",
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"expr": "rate(container_cpu_usage_seconds_total{cluster=~\"$cluster\", container=~\"$container\", pod=~\"$pod\"}[5m])",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{job}}",
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"legendFormat": "{{pod}}",
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"legendLink": null,
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"step": 10
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}
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"steppedLine": false,
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"targets": [
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{
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"expr": "container_memory_working_set_bytes{cluster=~\"$cluster\", pod_name=~\".*grafana-agent.*\"}",
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"expr": "container_memory_working_set_bytes{cluster=~\"$cluster\", container=~\"$container\", pod=~\"$pod\"}",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{job}}",
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"legendFormat": "{{pod}}",
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"legendLink": null,
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"step": 10
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}
@@ -513,18 +513,18 @@
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"steppedLine": false,
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"targets": [
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{
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"expr": "rate(container_network_receive_bytes_total{cluster=~\"$cluster\", namespace=~\"$namespace\", pod_name=~\".*grafana-agent.*\"}[5m])",
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"expr": "sum by (pod) (rate(container_network_receive_bytes_total{cluster=~\"$cluster\", namespace=~\"$namespace\", pod=~\"$pod\"}[5m]))",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{job}}",
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"legendFormat": "{{pod}}",
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"legendLink": null,
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"step": 10
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}
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],
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"thresholds": [ ],
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"timeFrom": null,
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"timeShift": null,
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"title": "RX",
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"title": "RX by Pod",
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"tooltip": {
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"shared": true,
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"sort": 0,
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"steppedLine": false,
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"targets": [
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{
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"expr": "rate(container_network_transmit_bytes_total{cluster=~\"$cluster\", namespace=~\"$namespace\", pod_name=~\".*grafana-agent.*\"}[5m])",
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"expr": "sum by (pod) (rate(container_network_transmit_bytes_total{cluster=~\"$cluster\", namespace=~\"$namespace\", pod=~\"$pod\"}[5m]))",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{job}}",
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"legendFormat": "{{pod}}",
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"legendLink": null,
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"step": 10
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}
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],
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"thresholds": [ ],
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"timeFrom": null,
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"timeShift": null,
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"title": "TX",
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"title": "TX by Pod",
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"tooltip": {
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"shared": true,
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"sort": 0,
@@ -677,18 +677,18 @@
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"steppedLine": false,
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"targets": [
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{
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"expr": "(sum by (job, instance) (avg_over_time(go_memstats_heap_inuse_bytes{cluster=~\"$cluster\", job=~\"$job\", instance=~\"$instance\"}[1m])))\n/\n(sum by (job, instance) (agent_wal_storage_active_series{cluster=~\"$cluster\", job=~\"$job\", instance=~\"$instance\"}))\n",
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"expr": "(sum by (pod) (avg_over_time(go_memstats_heap_inuse_bytes{cluster=~\"$cluster\", namespace=~\"$namespace\", container=~\"$container\", pod=~\"$pod\"}[1m])))\n/\n(sum by (pod) (agent_wal_storage_active_series{cluster=~\"$cluster\", namespace=~\"$namespace\", container=~\"$container\", pod=~\"$pod\"}))\n",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{instance}}",
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"legendFormat": "{{pod}}",
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"legendLink": null,
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"step": 10
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}
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],
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"thresholds": [ ],
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"timeFrom": null,
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"timeShift": null,
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"title": "Bytes/Series/Instance",
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"title": "Bytes/Series/Pod",
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"tooltip": {
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"shared": true,
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"sort": 0,
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"steppedLine": false,
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"targets": [
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{
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"expr": "(sum by (job) (avg_over_time(go_memstats_heap_inuse_bytes{cluster=~\"$cluster\", job=~\"$job\", instance=~\"$instance\"}[1m])))\n/\n(sum by (job) (agent_wal_storage_active_series{cluster=~\"$cluster\", job=~\"$job\", instance=~\"$instance\"}))\n",
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"expr": "(sum by (container) (avg_over_time(go_memstats_heap_inuse_bytes{cluster=~\"$cluster\", namespace=~\"$namespace\", container=~\"$container\", pod=~\"$pod\"}[1m])))\n/\n(sum by (container) (agent_wal_storage_active_series{cluster=~\"$cluster\", namespace=~\"$namespace\", container=~\"$container\", pod=~\"$pod\"}))\n",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{job}}",
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"legendFormat": "{{container}}",
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"legendLink": null,
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"step": 10
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}
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"steppedLine": false,
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"targets": [
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{
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"expr": "sum by (instance) (agent_wal_storage_active_series{cluster=~\"$cluster\", job=~\"$job\", instance=~\"$instance\"})",
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"expr": "sum by (pod) (agent_wal_storage_active_series{cluster=~\"$cluster\", namespace=~\"$namespace\", container=~\"$container\", pod=~\"$pod\"})",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{instance}}",
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"legendFormat": "{{pod}}",
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"legendLink": null,
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"step": 10
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}
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],
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"thresholds": [ ],
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"timeFrom": null,
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"timeShift": null,
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"title": "Series/Instance",
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"title": "Series/Pod",
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"tooltip": {
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"shared": true,
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"sort": 0,
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"steppedLine": false,
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"targets": [
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{
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"expr": "sum by (instance_name) (agent_wal_storage_active_series{cluster=~\"$cluster\", job=~\"$job\", instance=~\"$instance\"})",
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"expr": "sum by (instance_group_name) (agent_wal_storage_active_series{cluster=~\"$cluster\", namespace=~\"$namespace\", container=~\"$container\", pod=~\"$pod\"})",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{instance_name}}",
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"legendFormat": "{{instance_group_name}}",
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"legendLink": null,
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"step": 10
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}
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"steppedLine": false,
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"targets": [
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{
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"expr": "sum by (job) (agent_wal_storage_active_series{cluster=~\"$cluster\", job=~\"$job\", instance=~\"$instance\"})",
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"expr": "sum by (container) (agent_wal_storage_active_series{cluster=~\"$cluster\", namespace=~\"$namespace\", container=~\"$container\", pod=~\"$pod\"})",
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"format": "time_series",
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"intervalFactor": 2,
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"legendFormat": "{{job}}",
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"legendFormat": "{{container}}",
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"legendLink": null,
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"step": 10
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}
@@ -1111,11 +1111,11 @@
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"datasource": "$datasource",
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"hide": 0,
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"includeAll": true,
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"label": "job",
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"label": "container",
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"multi": true,
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"name": "job",
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"name": "container",
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"options": [ ],
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"query": "label_values(agent_build_info, job)",
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"query": "label_values(agent_build_info, container)",
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"refresh": 1,
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"regex": "",
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"sort": 2,
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"useTags": false
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},
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{
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"allValue": null,
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"allValue": "grafana-agent-.*",
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"current": {
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"selected": true,
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"text": "All",
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"datasource": "$datasource",
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"hide": 0,
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"includeAll": true,
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"label": "instance",
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"label": "pod",
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"multi": true,
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"name": "instance",
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"name": "pod",
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"options": [ ],
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"query": "label_values(agent_build_info, instance)",
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"query": "label_values(agent_build_info{container=~\"$container\"}, pod)",
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"refresh": 1,
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"regex": "",
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"sort": 2,

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