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Merge pull request #223 from vertica/update
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Update documentation
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roypaulin authored Jan 10, 2024
2 parents 96697c3 + 2cf6785 commit d0562f5
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4 changes: 4 additions & 0 deletions .github/workflows/makefile.yml
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Expand Up @@ -41,3 +41,7 @@ jobs:
run: make grafana-uninstall
- name: uninstall verticapylab
run: make verticapylab-uninstall
- name: Create and run a prometheus container
run: make prom-start
- name: uninstall grafana
run: make prom-uninstall
34 changes: 33 additions & 1 deletion README.md
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Expand Up @@ -145,11 +145,43 @@ Each example is annotated and walks you through step-by-step through various Spa
## Grafana
Grafana is an open-source observability platform for visualizing metrics, logs, and traces collected from your applications. When Verticalab is installed, a grafana container is created and connected to the single node database. Two extensions are available on the jupyterlab launcher to make use of it:
Grafana is an open-source observability platform for visualizing metrics, logs, and traces collected from your applications. When VerticaPyLab is installed, a grafana container is created and connected to the single node database. Two extensions are available on the jupyterlab launcher to make use of it:
- Grafana: Opens a new tab containing a Grafana Explorer for running sql queries.
- Performance: Opens a new tab containing a performance dashboard to visualize CPU usage, Memory usage, SQL statements, etc..
You can also install Grafana standalone without also installing Vertica and VerticaPyLab:
- Start Grafana container:
`make grafana-start` and open `http://localhost:3000`
- Stop Grafana:
`make grafana-stop`
- Remove the grafana container and its associated images:
`make grafana-uninstall`
## Prometheus
Prometheus a monitoring and alerting system that is very popular with cloud native deployments. It collects time series events for different machines, called targets.
In version 23.3.0, Vertica introduced in-database metrics. Vertica is already very rich in metrics with the various system and DC tables that it offers, but now you can get them cheaply with Prometheus in-database metrics.
We provide a few commands that can help you set up Prometheus to fetch metrics from your remote cluster nodes or from the CE vertica container installed with VerticaPyLab:
- Configure Prometheus. if you do not have your own db, Prometheus is configured to use the single node CE database:
Edit prometheus.yml and add your own section to tell Prometheus how to access your nodes.
- Start Prometheus container:
`make prom-start` and open `http://localhost:9090`
- Stop Prometheus container:
`make prom-stop`
- Delete the prometheus container and its associated images:
`make prom-uninstall`
Once installed, Prometheus can be used as a DataSource by [Grafana](#grafana)
## Contributing
For a short guide on contribution standards, see [CONTRIBUTING.md](CONTRIBUTING.md)
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14 changes: 13 additions & 1 deletion docker-prometheus/prometheus.yml
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Expand Up @@ -15,4 +15,16 @@ scrape_configs:
metrics_path: '/v1/metrics'
scrape_interval: 5s
static_configs:
- targets: ['verticadb:8443']
- targets: ['verticadb:8443']
# Add more jobs to fetch your remote nodes
# - job_name: 'myvertica'
# scheme: https
# basic_auth:
# username: 'yourusername'
# password: 'yourpasswd'
# tls_config:
# insecure_skip_verify: true
# metrics_path: '/v1/metrics'
# scrape_interval: 5s
# static_configs:
# - targets: ['node1:8443', 'node1:8443', 'nodeN:8443']
2 changes: 1 addition & 1 deletion etc/VerticaPyLab.conf.default
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Expand Up @@ -21,7 +21,7 @@ VERTICA_CONTAINER_NAME=verticadb
VERTICA_HOST_NAME=$VERTICA_CONTAINER_NAME
VERTICA_DB_NAME=$VERTICA_CONTAINER_NAME
DB_NAME=demo
VERTICA_DOCKER_IMAGE=vertica/vertica-k8s:latest # see https://hub.docker.com/r/vertica/vertica-k8s
VERTICA_DOCKER_IMAGE=vertica/vertica-k8s:23.4.0-0-minimal # see https://hub.docker.com/r/vertica/vertica-k8s
VSQL_USER=dbadmin
#VERTICA_RUNARGS+=( ) # add more args to the docker run command

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