diff --git a/dashboards/data-ingest-entity-breakdown/data-ingest-entity-breakdown.json b/dashboards/data-ingest-entity-breakdown/data-ingest-entity-breakdown.json index bcb6513e12..1b5d945053 100644 --- a/dashboards/data-ingest-entity-breakdown/data-ingest-entity-breakdown.json +++ b/dashboards/data-ingest-entity-breakdown/data-ingest-entity-breakdown.json @@ -1,282 +1,282 @@ { - "name": "Data Ingest Governance Entity Breakdowns", - "description": null, - "pages": [ - { - "name": "APM Applications", - "description": null, - "widgets": [ - { - "visualization": { - "id": "viz.table" - }, - "layout": { - "column": 1, - "row": 1, - "height": 6, - "width": 5 - }, - "title": "Daily Rate Estimate", - "rawConfiguration": { - "dataFormatters": [], - "facet": { - "showOtherSeries": true - }, - "nrqlQueries": [ - { - "accountId": 0, - "query": "FROM Transaction, TransactionError, TransactionTrace, SqlTrace, ErrorTrace, Span select rate(bytecountestimate()/10e8, 1 day) as 'GB Ingest' facet appName limit 100" - } - ] - }, - "linkedEntityGuids": null + "name": "Data Ingest Governance Entity Breakdowns", + "description": null, + "pages": [ + { + "name": "APM Applications", + "description": null, + "widgets": [ + { + "visualization": { + "id": "viz.table" }, - { - "visualization": { - "id": "viz.area" - }, - "layout": { - "column": 6, - "row": 1, - "height": 6, - "width": 7 - }, - "title": "GB Estimate Time Series", - "rawConfiguration": { - "facet": { - "showOtherSeries": true - }, - "legend": { - "enabled": true - }, - "nrqlQueries": [ - { - "accountId": 0, - "query": "FROM Transaction, TransactionError, TransactionTrace, SqlTrace, ErrorTrace, Span select bytecountestimate()/10e08 as 'GB Ingest' facet appName limit 100 TIMESERIES " - } - ] - }, - "linkedEntityGuids": null - } - ] - }, - { - "name": "Browser Applications", - "description": null, - "widgets": [ - { - "visualization": { - "id": "viz.table" - }, - "layout": { - "column": 1, - "row": 1, - "height": 6, - "width": 5 - }, - "title": "Daily Rate Estimate", - "rawConfiguration": { - "dataFormatters": [], - "facet": { - "showOtherSeries": true - }, - "nrqlQueries": [ - { - "accountId": 0, - "query": "FROM PageAction, PageView, PageViewTiming, AjaxRequest, JavaScriptError select rate(bytecountestimate()/10e8, 1 day) as 'GB Ingest' facet appName limit 100" - } - ] - }, - "linkedEntityGuids": null + "layout": { + "column": 1, + "row": 1, + "height": 6, + "width": 5 }, - { - "visualization": { - "id": "viz.area" - }, - "layout": { - "column": 6, - "row": 1, - "height": 6, - "width": 7 - }, - "title": "GB Estimate Time Series", - "rawConfiguration": { - "facet": { - "showOtherSeries": true - }, - "legend": { - "enabled": true - }, - "nrqlQueries": [ - { - "accountId": 0, - "query": "FROM PageAction, PageView, PageViewTiming, AjaxRequest, JavaScriptError select bytecountestimate()/10e08 as 'GB Ingest' facet appName limit 100 TIMESERIES " - } - ] + "title": "Daily Rate Estimate", + "rawConfiguration": { + "dataFormatters": [], + "facet": { + "showOtherSeries": true }, - "linkedEntityGuids": null - } - ] - }, - { - "name": "Mobile Applications", - "description": null, - "widgets": [ - { - "visualization": { - "id": "viz.table" - }, - "layout": { - "column": 1, - "row": 1, - "height": 6, - "width": 5 - }, - "title": "Daily Rate Estimate", - "rawConfiguration": { - "dataFormatters": [], - "facet": { - "showOtherSeries": true - }, - "nrqlQueries": [ - { - "accountId": 0, - "query": "FROM Mobile, MobileRequest, MobileRequestError, MobileSession, MobileHandleException, MobileCrash select rate(bytecountestimate()/10e8, 1 day) as 'GB Ingest' facet appName limit 100" - } - ] - }, - "linkedEntityGuids": null + "nrqlQueries": [ + { + "accountId": 0, + "query": "FROM Transaction, TransactionError, TransactionTrace, SqlTrace, ErrorTrace, Span select rate(bytecountestimate()/10e8, 1 day) as 'GB Ingest' facet appName limit 100" + } + ] }, - { - "visualization": { - "id": "viz.area" - }, - "layout": { - "column": 6, - "row": 1, - "height": 6, - "width": 7 - }, - "title": "GB Estimate Time Series", - "rawConfiguration": { - "facet": { - "showOtherSeries": true - }, - "legend": { - "enabled": true - }, - "nrqlQueries": [ - { - "accountId": 0, - "query": "FROM Mobile, MobileRequest, MobileRequestError, MobileSession, MobileHandleException, MobileCrash select bytecountestimate()/10e08 as 'GB Ingest' facet appName limit 100 TIMESERIES " - } - ] - }, - "linkedEntityGuids": null - } - ] - }, - { - "name": "K8s Clusters", - "description": null, - "widgets": [ - { - "visualization": { - "id": "viz.table" - }, - "layout": { - "column": 1, - "row": 1, - "height": 6, - "width": 5 + "linkedEntityGuids": null + }, + { + "visualization": { + "id": "viz.area" + }, + "layout": { + "column": 6, + "row": 1, + "height": 6, + "width": 7 + }, + "title": "GB Estimate Time Series", + "rawConfiguration": { + "facet": { + "showOtherSeries": true }, - "title": "Daily Rate Estimate", - "rawConfiguration": { - "dataFormatters": [], - "facet": { - "showOtherSeries": true - }, - "nrqlQueries": [ - { - "accountId": 0, - "query": "FROM K8sClusterSample, K8sContainerSample,K8sDaemonsetSample, K8sDeploymentSample, K8sEndpointSample, K8sHpaSample, K8sNamespaceSample, K8sNodeSample, K8sPodSample, K8sReplicasetSample, K8sServiceSample, K8sVolumeSample select rate(bytecountestimate()/10e8, 1 day) as 'GB Ingest' facet clusterName limit 100" - } - ] + "legend": { + "enabled": true }, - "linkedEntityGuids": null + "nrqlQueries": [ + { + "accountId": 0, + "query": "FROM Transaction, TransactionError, TransactionTrace, SqlTrace, ErrorTrace, Span select bytecountestimate()/10e08 as 'GB Ingest' facet appName limit 100 TIMESERIES " + } + ] + }, + "linkedEntityGuids": null + } + ] + }, + { + "name": "Browser Applications", + "description": null, + "widgets": [ + { + "visualization": { + "id": "viz.table" + }, + "layout": { + "column": 1, + "row": 1, + "height": 6, + "width": 5 }, - { - "visualization": { - "id": "viz.area" + "title": "Daily Rate Estimate", + "rawConfiguration": { + "dataFormatters": [], + "facet": { + "showOtherSeries": true }, - "layout": { - "column": 6, - "row": 1, - "height": 6, - "width": 7 + "nrqlQueries": [ + { + "accountId": 0, + "query": "FROM PageAction, PageView, PageViewTiming, AjaxRequest, JavaScriptError select rate(bytecountestimate()/10e8, 1 day) as 'GB Ingest' facet appName limit 100" + } + ] + }, + "linkedEntityGuids": null + }, + { + "visualization": { + "id": "viz.area" + }, + "layout": { + "column": 6, + "row": 1, + "height": 6, + "width": 7 + }, + "title": "GB Estimate Time Series", + "rawConfiguration": { + "facet": { + "showOtherSeries": true }, - "title": "GB Estimate Time Series", - "rawConfiguration": { - "facet": { - "showOtherSeries": true - }, - "legend": { - "enabled": true - }, - "nrqlQueries": [ - { - "accountId": 0, - "query": "FROM K8sClusterSample, K8sContainerSample,K8sDaemonsetSample, K8sDeploymentSample, K8sEndpointSample, K8sHpaSample, K8sNamespaceSample, K8sNodeSample, K8sPodSample, K8sReplicasetSample, K8sServiceSample, K8sVolumeSample select bytecountestimate()/10e08 as 'GB Ingest' facet clusterName limit 100 TIMESERIES " - } - ] + "legend": { + "enabled": true }, - "linkedEntityGuids": null - } - ] - }, - { - "name": "Infrastructure Integrations", - "description": null, - "widgets": [ - { - "visualization": { - "id": "viz.markdown" + "nrqlQueries": [ + { + "accountId": 0, + "query": "FROM PageAction, PageView, PageViewTiming, AjaxRequest, JavaScriptError select bytecountestimate()/10e08 as 'GB Ingest' facet appName limit 100 TIMESERIES " + } + ] + }, + "linkedEntityGuids": null + } + ] + }, + { + "name": "Mobile Applications", + "description": null, + "widgets": [ + { + "visualization": { + "id": "viz.table" + }, + "layout": { + "column": 1, + "row": 1, + "height": 6, + "width": 5 + }, + "title": "Daily Rate Estimate", + "rawConfiguration": { + "dataFormatters": [], + "facet": { + "showOtherSeries": true }, - "layout": { - "column": 1, - "row": 1, - "height": 9, - "width": 12 + "nrqlQueries": [ + { + "accountId": 0, + "query": "FROM Mobile, MobileRequest, MobileRequestError, MobileSession, MobileHandleException, MobileCrash select rate(bytecountestimate()/10e8, 1 day) as 'GB Ingest' facet appName limit 100" + } + ] + }, + "linkedEntityGuids": null + }, + { + "visualization": { + "id": "viz.area" + }, + "layout": { + "column": 6, + "row": 1, + "height": 6, + "width": 7 + }, + "title": "GB Estimate Time Series", + "rawConfiguration": { + "facet": { + "showOtherSeries": true }, - "title": "", - "rawConfiguration": { - "text": "## Install the Cloud Integration Dashboard\n\nCloud Integrations can often be the source of data ingest growth. Without good visualizations it can be very difficult to pinpoint where the growth is coming from. This is partly because these integrations are so easy to configure and they are not part of an organizations normal CI/CD pipeline and may also not be part of a formal configuration management system.\nFortunately this powerful set of dashboards can be installed [directly from New Relic I/O](https://onenr.io/0EPwJJO9Ow7).\nIndividual dashboards installed by this pakage include:\n\n- AWS Integrations\n- Azure Integrations\n- GCP Integrations\n- On-Host Integrations\n- Kubernetes\n\n\n![AWS Integration Breakdown](https://raw.githubusercontent.com/newrelic/newrelic-quickstarts/v0.99.1/quickstarts/audit/infrastructure-integrations-data-analysis/dashboards/aws-integrations-data-ingest-analysis.png)" + "legend": { + "enabled": true }, - "linkedEntityGuids": null - } - ] - }, - { - "name": "About this dashboard", - "description": null, - "widgets": [ - { - "visualization": { - "id": "viz.markdown" + "nrqlQueries": [ + { + "accountId": 0, + "query": "FROM Mobile, MobileRequest, MobileRequestError, MobileSession, MobileHandleException, MobileCrash select bytecountestimate()/10e08 as 'GB Ingest' facet appName limit 100 TIMESERIES " + } + ] + }, + "linkedEntityGuids": null + } + ] + }, + { + "name": "K8s Clusters", + "description": null, + "widgets": [ + { + "visualization": { + "id": "viz.table" + }, + "layout": { + "column": 1, + "row": 1, + "height": 6, + "width": 5 + }, + "title": "Daily Rate Estimate", + "rawConfiguration": { + "dataFormatters": [], + "facet": { + "showOtherSeries": true }, - "layout": { - "column": 1, - "row": 1, - "height": 5, - "width": 6 + "nrqlQueries": [ + { + "accountId": 0, + "query": "FROM K8sClusterSample, K8sContainerSample,K8sDaemonsetSample, K8sDeploymentSample, K8sEndpointSample, K8sHpaSample, K8sNamespaceSample, K8sNodeSample, K8sPodSample, K8sReplicasetSample, K8sServiceSample, K8sVolumeSample select rate(bytecountestimate()/10e8, 1 day) as 'GB Ingest' facet clusterName limit 100" + } + ] + }, + "linkedEntityGuids": null + }, + { + "visualization": { + "id": "viz.area" + }, + "layout": { + "column": 6, + "row": 1, + "height": 6, + "width": 7 + }, + "title": "GB Estimate Time Series", + "rawConfiguration": { + "facet": { + "showOtherSeries": true }, - "title": "", - "rawConfiguration": { - "text": "# How these charts work\nThese charts use the `bytecountestimate()` operator which can estimate the data ingest overhead for nearly any event or metric in NRDB. \n\nHere is an example of a query that estimates data ingest overhead for Browser data faceted by appName:\n\n```\nFROM PageAction, PageView, PageViewTiming, AjaxRequest, JavaScriptError\nSELECT rate(bytecountestimate()/10e8, 30 day) AS 'GB Ingest'\nFACET appName SINCE 1 DAY AGO\n```\n\n### Benefits\n- The data is far more granular than what is in the main [Data Governance Baseline](https://docs.newrelic.com/docs/new-relic-solutions/observability-maturity/operational-efficiency/dg-baselining#install-dashboard) dashboard which rely only on NrConsumption metrics\n- We are able to facet by nearly any attribute\n\n### Drawbacks\n- The queries are slower as the data can be quite high volume and the bytecountestimate() operator has some overhead.\n- They can only be queried up to the data retention period for that telemetry. For some telemetry types this may not be more than a week.\n\n## View the [data governance guide](https://docs.newrelic.com/docs/new-relic-solutions/observability-maturity/operational-efficiency/dg-intro) for more information\n" + "legend": { + "enabled": true }, - "linkedEntityGuids": null - } - ] - } - ] - } \ No newline at end of file + "nrqlQueries": [ + { + "accountId": 0, + "query": "FROM K8sClusterSample, K8sContainerSample,K8sDaemonsetSample, K8sDeploymentSample, K8sEndpointSample, K8sHpaSample, K8sNamespaceSample, K8sNodeSample, K8sPodSample, K8sReplicasetSample, K8sServiceSample, K8sVolumeSample select bytecountestimate()/10e08 as 'GB Ingest' facet clusterName limit 100 TIMESERIES " + } + ] + }, + "linkedEntityGuids": null + } + ] + }, + { + "name": "Infrastructure Integrations", + "description": null, + "widgets": [ + { + "visualization": { + "id": "viz.markdown" + }, + "layout": { + "column": 1, + "row": 1, + "height": 9, + "width": 12 + }, + "title": "", + "rawConfiguration": { + "text": "## Install the Cloud Integration Dashboard\n\nCloud Integrations can often be the source of data ingest growth. Without good visualizations it can be very difficult to pinpoint where the growth is coming from. This is partly because these integrations are so easy to configure and they are not part of an organizations normal CI/CD pipeline and may also not be part of a formal configuration management system.\nFortunately this powerful set of dashboards can be installed [directly from New Relic I/O](https://onenr.io/0gR7VXxnnwo).\nIndividual dashboards installed by this pakage include:\n\n- AWS Integrations\n- Azure Integrations\n- GCP Integrations\n- On-Host Integrations\n- Kubernetes\n\n\n![AWS Integration Breakdown](https://raw.githubusercontent.com/newrelic/newrelic-quickstarts/v0.99.1/quickstarts/audit/infrastructure-integrations-data-analysis/dashboards/aws-integrations-data-ingest-analysis.png)" + }, + "linkedEntityGuids": null + } + ] + }, + { + "name": "About this dashboard", + "description": null, + "widgets": [ + { + "visualization": { + "id": "viz.markdown" + }, + "layout": { + "column": 1, + "row": 1, + "height": 5, + "width": 6 + }, + "title": "", + "rawConfiguration": { + "text": "# How these charts work\nThese charts use the `bytecountestimate()` operator which can estimate the data ingest overhead for nearly any event or metric in NRDB. \n\nHere is an example of a query that estimates data ingest overhead for Browser data faceted by appName:\n\n```\nFROM PageAction, PageView, PageViewTiming, AjaxRequest, JavaScriptError\nSELECT rate(bytecountestimate()/10e8, 30 day) AS 'GB Ingest'\nFACET appName SINCE 1 DAY AGO\n```\n\n### Benefits\n- The data is far more granular than what is in the main [Data Governance Baseline](https://docs.newrelic.com/docs/new-relic-solutions/observability-maturity/operational-efficiency/dg-baselining#install-dashboard) dashboard which rely only on NrConsumption metrics\n- We are able to facet by nearly any attribute\n\n### Drawbacks\n- The queries are slower as the data can be quite high volume and the bytecountestimate() operator has some overhead.\n- They can only be queried up to the data retention period for that telemetry. For some telemetry types this may not be more than a week.\n\n## View the [data governance guide](https://docs.newrelic.com/docs/new-relic-solutions/observability-maturity/operational-efficiency/dg-intro) for more information\n" + }, + "linkedEntityGuids": null + } + ] + } + ] +} diff --git a/data-sources/catchpoint-quickstart/config.yml b/data-sources/catchpoint-quickstart/config.yml index 6a1e1a8caa..449fdfb351 100644 --- a/data-sources/catchpoint-quickstart/config.yml +++ b/data-sources/catchpoint-quickstart/config.yml @@ -1,6 +1,6 @@ id: catchpoint-quickstart displayName: Catchpoint -description: This quickstart uses Catchpoint Test Data Webhook to send data to the New Relic Platform, this is accomplished by using New Relic’s Metrics API. You can visualize Catchpoint's digital experience data with New Relic’s Application Performance Monitoring (APM) data together. +description: This quickstart uses Catchpoint Test Data Webhook to send data to the New Relic Platform, this is accomplished by using New Relic’s Metrics API. install: primary: link: diff --git a/data-sources/confluent-cloud/config.yml b/data-sources/confluent-cloud/config.yml deleted file mode 100644 index e67c3b91fa..0000000000 --- a/data-sources/confluent-cloud/config.yml +++ /dev/null @@ -1,22 +0,0 @@ -id: confluent-cloud -displayName: Confluent Cloud -description: Observability for Confluent Cloud's fully managed service for Apache Kafka delivered using an OpenTelemetry Collector. -icon: logo.png -install: - primary: - link: - url: https://github.com/newrelic/newrelic-opentelemetry-examples/tree/main/other-examples/collector/confluentcloud -keywords: - - Confluent - - Confluent Cloud - - Metrics - - OTel - - OpenTelemetry - - open telemetry - - OTelCol - - OpenTelemetry Collector - - open telemetry collector - - Collector - - Kafka -categoryTerms: - - infrastructure diff --git a/data-sources/confluent-cloud/logo.png b/data-sources/confluent-cloud/logo.png deleted file mode 100644 index 92ce822d5d..0000000000 Binary files a/data-sources/confluent-cloud/logo.png and /dev/null differ diff --git a/data-sources/datazoom/config.yml b/data-sources/datazoom/config.yml index 26960f7064..073da21330 100644 --- a/data-sources/datazoom/config.yml +++ b/data-sources/datazoom/config.yml @@ -1,7 +1,7 @@ id: datazoom displayName: Datazoom description: | - The Datazoom quickstart provides a fast and easy launching point into video metrics built on top of New Relic One dashboards, allowing you to gain insights about your viewers, content, ads and your platform's performance. Customize the dashboard to use only the metrics that fit your goals and easily edit metric calculations and tailor them to your needs. + The Datazoom quickstart provides a fast and easy launching point into video metrics built on top of New Relic One dashboards, allowing you to gain insights about your viewers, content, ads and your platform's performance. icon: logo.png install: primary: diff --git a/data-sources/fastly/config.yml b/data-sources/fastly/config.yml index d32ede9cbe..e58e4d38a6 100644 --- a/data-sources/fastly/config.yml +++ b/data-sources/fastly/config.yml @@ -1,9 +1,7 @@ id: fastly displayName: Fastly CDN description: | - Fastly helps people stay better connected with the things they love. Fastly's edge cloud platform enables customers to create great digital experiences quickly, securely, and reliably by processing, serving, and securing our customers' applications as close to their end-users as possible — at the edge of the internet. Fastly's platform is designed to take advantage of the modern internet, to be programmable, and to support agile software development with unmatched visibility and minimal latency, empowering developers to innovate with both performance and security. Fastly's customers include many of the world's most prominent companies, including Pinterest, The New York Times, and GitHub. - - For more information or support, please go to https://support.fastly.com/ + Fastly's edge cloud platform enables customers to create great digital experiences quickly, securely, and reliably by processing, serving, and securing our customers' applications as close to their end-users as possible. icon: logo.png install: primary: diff --git a/data-sources/gcp-pubsub/config.yml b/data-sources/gcp-pubsub/config.yml index 4f5e6660a3..6f7f84cb4a 100644 --- a/data-sources/gcp-pubsub/config.yml +++ b/data-sources/gcp-pubsub/config.yml @@ -2,7 +2,6 @@ id: gcp-pubsub displayName: Google Cloud Pub/Sub Java Agent Extension description: | Java agent extension to monitor Google Cloud Pub/Sub with New Relic. Once installed, the instrumentation will monitor both the publish and the subscribe of messages sent via the PubSub framework. - In addition, the instrumentation will take care of distributed tracing so that the publish will provide the distributed tracing headers on the message and the subscribe will read the headers and process them appropriately. install: primary: link: diff --git a/data-sources/mongodb-prometheus-integration-docs/config.yml b/data-sources/mongodb-prometheus-integration-docs/config.yml index 3e1cb8e478..4e8ccc8216 100644 --- a/data-sources/mongodb-prometheus-integration-docs/config.yml +++ b/data-sources/mongodb-prometheus-integration-docs/config.yml @@ -1,7 +1,7 @@ id: mongodb-prometheus-integration-docs displayName: MongoDB monitoring integration description: | - Our MongoDB integration collects and sends inventory and metrics from your MongoDB cluster to our platform, where you can aggregate and visualize key performance metrics. We collect data on mongos, mongod, and config servers, as well as on databases and collections to help pinpoint performance bottlenecks. + Our MongoDB integration collects and sends inventory and metrics from your MongoDB cluster to our platform, where you can aggregate and visualize key performance metrics. install: primary: nerdlet: diff --git a/data-sources/netlify-builds/config.yml b/data-sources/netlify-builds/config.yml index 39e5a4479d..647e8f7fe8 100644 --- a/data-sources/netlify-builds/config.yml +++ b/data-sources/netlify-builds/config.yml @@ -1,7 +1,7 @@ id: netlify-builds displayName: Netlify Builds description: | - Netlify is an all-in-one platform for automating modern web projects. Replace your hosting infrastructure, continuous integration, and deployment pipeline with a single workflow. Integrate dynamic functionality like serverless functions, user authentication, and form handling as your projects grow. + Netlify is an all-in-one platform for automating modern web projects. Replace your hosting infrastructure, continuous integration, and deployment pipeline with a single workflow. icon: logo.png install: primary: diff --git a/data-sources/netlify-logs/config.yml b/data-sources/netlify-logs/config.yml index 26111f5f74..e9d3565308 100644 --- a/data-sources/netlify-logs/config.yml +++ b/data-sources/netlify-logs/config.yml @@ -1,7 +1,7 @@ id: netlify-logs displayName: Netlify Logs description: | - Netlify is an all-in-one platform for automating modern web projects. Replace your hosting infrastructure, continuous integration, and deployment pipeline with a single workflow. Use this quickstart to quickly parse traffic and function logs from Netlify into meaningful metrics in New Relic. + Netlify is an all-in-one platform for automating modern web projects. Replace your hosting infrastructure, continuous integration, and deployment pipeline with a single workflow. icon: logo.png install: primary: diff --git a/data-sources/network-routers-and-switches/config.yml b/data-sources/network-routers-and-switches/config.yml index ba6da5edf4..76a25491d6 100644 --- a/data-sources/network-routers-and-switches/config.yml +++ b/data-sources/network-routers-and-switches/config.yml @@ -2,7 +2,6 @@ id: network-routers-and-switches displayName: Network Routers and Switches description: | The Network Routers and Switches datasource provides a dashboard that gives you a holistic view of the interface traffic across all of the routers and switches in your network. - Use this datasource together with New Relic's Network Performance Monitoring (NPM) feature to visualize anomalies and/or bottlenecks in your network. icon: logo.svg install: primary: diff --git a/data-sources/newrelic-cli/config.yml b/data-sources/newrelic-cli/config.yml index f06b23c181..550ccba85f 100644 --- a/data-sources/newrelic-cli/config.yml +++ b/data-sources/newrelic-cli/config.yml @@ -1,7 +1,7 @@ id: newrelic-cli displayName: New Relic CLI description: | - Access the New Relic platform from the comfort of your terminal. You can use the New Relic CLI to manage entity tags, define workloads, record deployment markers, and much more. In short, you can use the CLI to automate common tasks in your DevOps workflow. + Access the New Relic platform from the comfort of your terminal. You can use the New Relic CLI to manage entity tags, define workloads, record deployment markers, and much more. install: primary: link: diff --git a/data-sources/nuxtjs/config.yml b/data-sources/nuxtjs/config.yml index 18e10fb8e1..afe8039143 100644 --- a/data-sources/nuxtjs/config.yml +++ b/data-sources/nuxtjs/config.yml @@ -8,6 +8,6 @@ install: nerdletId: marketplace.install-data-source nerdletState: dataSourceId: nuxtjs - frameworkConfigId: nuxtjs + frameworkConfigId: new-relic-browser requiresAccount: false icon: logo.png diff --git a/data-sources/ocsf/config.yml b/data-sources/ocsf/config.yml index 70625f43f9..32a08c0d09 100644 --- a/data-sources/ocsf/config.yml +++ b/data-sources/ocsf/config.yml @@ -4,6 +4,10 @@ description: | Monitor and instrument your OCSF with New Relic to gain deep insights into your performance. install: primary: - link: - url: https://docs.newrelic.com/docs/infrastructure/host-integrations/host-integrations-list/ocsf-integration/ + nerdlet: + nerdletId: marketplace.install-data-source + nerdletState: + dataSourceId: ocsf + frameworkConfigId: ocsf + requiresAccount: false icon: logo.png \ No newline at end of file diff --git a/data-sources/pihole/config.yml b/data-sources/pihole/config.yml index 4824dfbe6d..1c0e74ea49 100644 --- a/data-sources/pihole/config.yml +++ b/data-sources/pihole/config.yml @@ -1,9 +1,7 @@ id: pihole displayName: PiHole description: | - A PiHole is a free DNS server utility that runs on a Raspberry Pi (or other inexpensive device) and captures DNS requests before they're sent out of the network, filtering discrete elements that are spam, harmful, or wasteful. The result is a faster and safer network. - - This quickstart monitors the PiHole by leveraging it's built-in API to display information about the type and quantify of network requests being handled. + A PiHole is a free DNS server utility that runs on a Raspberry Pi (or other inexpensive device) and captures DNS requests before they're sent out of the network, filtering discrete elements that are spam, harmful, or wasteful. icon: logo.svg install: diff --git a/data-sources/sendgrid-integration/config.yml b/data-sources/sendgrid-integration/config.yml index 94011fad0a..393ca73d1f 100644 --- a/data-sources/sendgrid-integration/config.yml +++ b/data-sources/sendgrid-integration/config.yml @@ -1,7 +1,7 @@ id: sendgrid-integration displayName: SendGrid Events Webhook description: | - SendGrid provides a cloud-based service that assists businesses with email delivery. In order to integrate SendGrid Events with New Relic, you will need to send SendGrid events by using the SendGrid Event Webhook. If you are already sending events to AWS S3 using the SendGrid Event Webhook, these events can be transferred to New Relic by using NewRelic-log-ingestion-s3. + SendGrid provides a cloud-based service that assists businesses with email delivery. In order to integrate SendGrid Events with New Relic, you will need to send SendGrid events by using the SendGrid Event Webhook. install: primary: link: diff --git a/data-sources/vertx-eventbus/config.yml b/data-sources/vertx-eventbus/config.yml index 891128e42d..12f63de951 100644 --- a/data-sources/vertx-eventbus/config.yml +++ b/data-sources/vertx-eventbus/config.yml @@ -2,8 +2,7 @@ id: newrelic-java-vertx displayName: New Relic Java Instrumentation for Vert.x Event Bus description: | Provides instrumentation code for monitoring the Vert.x Event Bus. Tracks flow across the event bus. - Vertx-Verticles provides instrumentation for classes extends AbstractVerticle. It does this by - instrumenting each class that is deployed. + Specifically designed for Vert.x Verticles that extend AbstractVerticle. install: primary: link: @@ -17,4 +16,4 @@ keywords: - vertx - vert.x - eventbus - - NR1_addData \ No newline at end of file + - NR1_addData diff --git a/utils/schema/core-datasource-ids.json b/utils/schema/core-datasource-ids.json index cd4815b834..477f2a1969 100644 --- a/utils/schema/core-datasource-ids.json +++ b/utils/schema/core-datasource-ids.json @@ -29,6 +29,7 @@ "change-tracking", "chef-install", "comet", + "confluent-cloud", "consul", "cordova", "couchbase",