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Shared Dashboards Contest—Add Your Queries Here!

shared-dashboards

#67

This dashboard represent the production application status from a performance perspective, and shows information on below critical areas,

  • Query response: Database calls in last 7 days / as required
  • User Experience: web transaction time, apdex score
  • API response: API invocation count
  • JVM usage: Garbage collection CPU time taken, Heap pool, Heap memory usage

If you like this dashboard, :grinning: and hit ‘like’

due to restriction, adding two images :expressionless:

NRSQLs:

SELECT average(databaseCallCount) FROM Transaction FACET httpResponseCode SINCE 7 days AGO TIMESERIES

SELECT count(contextName) FROM ***Statistics SINCE 60 minutes AGO where (statName = ‘ResponseTime’) and (serviceType = ‘API’)

SELECT count(contextName) FROM Statistics SINCE 60 minutes AGO WHERE (contextName IN (‘getAlternateAvailability’, 'getCache’, '’, 'getDetails’, 'getList’, 'getForStore’, 'getDetails’, 'getNodeList’, 'modifyOptions’, 'adj’, ‘’, ) AND (statName = '’) and (serviceType = ‘API’))


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#68

Screenshot

Dashboard Details

Required Products: APM
Level of Effort: Low
This dashboard will work on the standard New Relic data models. One custom attribute (customer) is required for filter entityId. We are using entityId instead of hostname or entityName just for preventing private information.


Chart Details

This dashboard shows overall resource usage of a set of hosts. It contains CPU, Memory, Network and Disk status, and also shows load average information just like the top command on Linux.

Chart Title

Load Average 1 5 15

SELECT entityId, loadAverageOneMinute, loadAverageFiveMinute, loadAverageFifteenMinute FROM SystemSample WHERE customer =‘MyCustm’ SINCE 1 minutes ago LIMIT 6
Load average 1 5 15 minutes, just like top command on linux

Chart Title

CPU Usage

SELECT average(cpuPercent) FROM SystemSample TIMESERIES FACET `entityId` WHERE customer='MyCustm' LIMIT 20 SINCE 60 minutes ago
CPU usage percentage

Chart Title

Memory Used

SELECT average(memoryUsedBytes/memoryTotalBytes*100) FROM SystemSample TIMESERIES FACET `entityId` WHERE customer='MyCustm' LIMIT 20 SINCE 60 minutes ago
Memory Used

Chart Title

Network Traffic

SELECT average(receiveBytesPerSecond+transmitBytesPerSecond) FROM NetworkSample TIMESERIES FACET `entityId` WHERE customer='MyCustm' LIMIT 20 SINCE 60 minutes ago
Network traffic

Chart Title

Disk r/w Bytes per sec

SELECT average(readBytesPerSecond+writeBytesPerSecond) FROM StorageSample TIMESERIES FACET `entityId` WHERE customer='MyCustm' LIMIT 20 SINCE 60 minutes ago
Disk read and write by bytes per second

Chart Title

Disk Used

SELECT average(diskUsedPercent) FROM StorageSample TIMESERIES FACET `entityId` WHERE customer='MyCustm' LIMIT 20 SINCE 60 minutes ago
Disk used



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#69

This Dashboard (SMART NOW ) tells us the first level Information of the Site which can be used for further debugging purpose. Also it shares few traffic details region wise . Main Areas to See are

  1. Active Users
  2. User Time Series
  3. Slow Running Pages
  4. Where Users Coming from…
  5. Popular Browser which users Used.

Dashboard Queries .

  1. Active Users:
  1. UserTime Series

3)Slow Running Pages

4)Page Views

5)Page View By Project

6)Active User By Project

7)Where User Coming from

8)Which Browser

9)Which IE Version

10)Which City

11)Top Page URL

12)Unique Session Graph in last 15 Days

Feed Back Appreciated :slightly_smiling_face:


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#70

Dashboard: Mobile App. Analyzer v3

Motivation

As a subsidiary of a leading mobile operator, we are the frontier, transforming the company into a digital organisation, by using data insights to deliver awesome product experiences.

With New Relic Mobile product which collects all requests from customer mobile devices, we have very useful data to develop a dashboard for monitoring and improving our QoE (Quality of Experience).

Mobile App Analyzer is a Dynamic Dashboard using point and click to retrieve needed information to support their work for every team such as Business Team, Developer, DevOps, Operation, QA and Network and Infra who are not skillfull with NRQL,

For each Mobile App, there’re more than a hundred API Request Domains and each Request Domain may consist of many Request Paths, so we develop this Analyzer to scan the errors much faster.

Dashboard Details

Required Products: Mobile
Level of Effort: High

  • Dashboard Filter: Enabled
  • Enabled Event Types: mobileRequest,mobileRequestError
  • Enabled Attributes:requestUrl,requestDomain,responseBody

Usecase #1:

We 're about to launch a new version of Mobile App, Business team and QA team can have a quick impression seeing the user demographic from the dashbaord.

For Business team, This is also beneficial for business provisioning on the business communication plan.

For QA folks , They can as well use the data from New Relic dashboard to decide on the mobile device which need tested.

Chart Title = By Mobile App., By OS Name, By App. Version, By Device Manufacturer, By OS Version, By ASN Owner, By Carrier, By Connection Type

Pie Chart

  • SELECT uniquecount(uuid) as '#Devices'FROM MobileRequest,MobileRequestError where appName like '%.Prod%' FACET appName
  • For Other Chart just FACET osName, appVersion, deviceManufacturer,osVersion, asnOwner, carrier and connectionType
    * To count number of devices using our Mobile App, percentage of other Attribute, link to current dashboard to filter attribute

Chart Title = By Device Model

Table

  • SELECT uniquecount(uuid) as '#Devices'FROM MobileRequest,MobileRequestError FACET deviceModel
  • How many devices for each Device Model?

Usecase #2:

Operation Team and Developer would like to set Monitoring Alert for high severity service. They can select ‘Mobile1-App.Prod’ and see what is the mostly ‘Request Url’ that are called.



Chart Title = Request Url

Table

  • SELECT uniquecount(uuid) as '#Devices',count(*) as '#Requests',percentage(count(*),WHERE errorType ='HTTPError') as '%Http Err by Req.',percentage(uniquecount(uuid),WHERE errorType ='HTTPError') as '%Http Err by Devices',percentage(count(*), WHERE errorType ='NetworkFailure') as '%Network Err by Req.',percentage(uniquecount(uuid), WHERE errorType ='NetworkFailure') as '%Network Err by Devices' FROM MobileRequest,MobileRequestError facet requestUrl
  • To count number of devices, request, %http error by request, %http error by device, %network error by request and %network error by device for each Request Url
  • To sort to parameter using table.
  • To link to current dashboard to filter attribute

Usecase #3:

Operation Team and Developer 'd like to track performance of ‘Moble#4-App.Prod’ new version that we just update


and we found that there’re high %http error and %network error on ‘domain4.com’ which were managed by our partners.

In the response body section, we saw 500 Internal Server Error and 502 Bad Gateway, which were then reported to our partners.

After they received this information, they added more server capacity immediately and the problem was solved. Error 500 and 502 no longer show in the graph report.



Chart Title = By Http Error Code

Bar Chart

  • SELECT uniquecount(uuid) as '#Devices'FROM MobileRequestError where errorType='HTTPError' FACETstatusCode``
  • To count number of devices receive each Http Error Code To link to current dashboard to filter attribute_

Chart Title = By Http Error Code

Line Chart

  • SELECT uniquecount(uuid) as '#Devices' FROM MobileRequestError where errorType='HTTPError' FACET statusCode
  • To see each Http Error Code Pattern within a time frame

Chart Title = Request Errors

Table

  • SELECT uniqueCount(uuid) as '#Devices'FROM MobileRequestError FACET requestErrorFingerprint,responseBody,statusCode,networkError
  • To see Request Errors Summary

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#71

@newrelic.admin @prd_newrelic Hope I am eligible. Let me know if I need to amend anything and I dont have any private info in screenshot.


#72

API Overview dashboard

This dashboard represents our API Usage overview in real time, performance and potential issues, it contains four main areas, important for check of health:

  • Overall API Throughput, Average API response time, apdex
  • Error Rate, Error Rate per host, Number of 4xx and 5xx errors, Error Response by Code, etc.
  • Informations about requests (f.e.: UserAgent, IP Address, Origins, etc.)
  • AWS EC2 current count and informations

Once SRE/DevOps Engineer needs to check high level status of API, they open this API Overview dashboard, from there it leads them to possible Infrastructure overview, Database overview, Synthetics overview dashboards, RedAlert dashboard (DataApps collection of linked dashboards), etc.

Error Rate per Host

Faceted Line Chart

select filter(count(*), where error.message is not null)100 / filter(count(), where duration is not null) as ‘Error Rate’ from Transaction, TransactionError FACET host WHERE appName = ‘API’ AND host NOT LIKE ‘pre-release%’ SINCE 3 hours ago LIMIT 50 TIMESERIES

Running [only scaling] API EC2 Instances

Count Chart

SELECT uniqueCount(entityId) from ComputeSample WHERE provider = ‘Ec2Instance’ AND providerAccountId = ‘999’ AND ec2State = ‘running’ AND ec2Tag_Name LIKE ‘production-chef12 - api-scaling%’ facet provider.awsRegion

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#74

Hi Dan,

Yes, I exported from APM Screen
There is option on APM screen to add to an Insights Dashboard, which appears below the graphs.
image

We added this to get required information on one screen.

Website Performance Dashboad

Many Thanks
Umesh


#75

Good Stuff!

Gracias!


December 2018 Coffee Chat: Insights & Dashboards & NRQL - OH MY!
#76

Mobile Analysis Dasboard

This dashboard provids complete Analysis of Mobile users.

Few Metrics provided are

  • Mobile Sessions compared to Last week
  • Unique Mobile Users
  • Average Duration
  • Mobile Sessions by Country
  • Mobile Sessions by City
  • Mobile Sessions by Carrier
  • Mobile Sessions by Device
  • Average Session Length by Country
  • Average Session Length by Device
  • Histogram Breakdown of Session Length

NRQL
SELECT count(*) FROM Mobile SINCE 1 week ago COMPARE WITH 1 week ago

SELECT uniqueCount(uuid) FROM Mobile SINCE 1 week ago
SELECT average(sessionDuration) FROM Mobile SINCE 1 week ago
SELECT Count(*) FROM Mobile WHERE countryCode IS NOT NULL FACET countryCode SINCE 1 week ago

SELECT Count(*) FROM Mobile WHERE city IS NOT NULL FACET city SINCE 1 week ago

SELECT average(sessionDuration) FROM Mobile FACET deviceGroup SINCE 1 week ago

SELECT count(*) FROM Mobile FACET device SINCE 1 week ago

SELECT average(sessionDuration) FROM Mobile FACET countryCode SINCE 1 week ago

SELECT percentile(sessionDuration,95) as ‘95th Percentile’,percentile(sessionDuration,90) as ‘90th Percentile’,
percentile(sessionDuration,75) as ‘75th Percentile’, percentile(sessionDuration,50) as ‘50th Percentile’ FROM Mobile SINCE 1 week ago

SELECT percentile(sessionDuration,95) as ‘95th Percentile’,percentile(sessionDuration,90) as ‘90th Percentile’,
percentile(sessionDuration,75) as ‘75th Percentile’, percentile(sessionDuration,50) as ‘50th Percentile’ FROM Mobile SINCE 1 week ago


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#77

Screenshot

_

Dashboard Details

Required Products: APM, Browser, Infrastructure
Level of Effort: Low
This dashboard will work on the standard New Relic data models and does not require any custom attributes or events.

Pageview Comparison

API Perf

`SELECT average(duration) from Transaction SINCE 1 day ago where appName = ‘IIS-API’ and name like ‘%v3_5%’ COMPARE WITH 1 week ago’
*Average duration of transactions for the last day. Covers off those questions of ‘Is the system running slow today’ *

Error Counts

Chart Type

SELECT count(*) FROM TransactionError FACET error.class WHERE appId = 52052748 SINCE 1 day ago
Captures and sums up the errors for the last day. Shows at a high level any unexpected behaviours


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#78

Dashboards - Mobile ETop-up performance;

This dashboards represents the performance of an Etop-up in a mobile top-up Production environment of particular country .
There are two servers for which the performance needs to be monitored.

  1. Http-Dispatcher Dashboard -Monitors the response time of the overall top-up Application and records the http dispatcher time consuming records and displays.

2.Production-All External- This dashboard the time consumption of all external services involved in the top-up journey.

3.Top-Up-Production-Apdex- This dashboard defines the Apdex value defined for the Top-up APM service.

  1. This dashboard has the Key transaction defined for particular transaction in which if there is any decrease or zero callcount ,chances are there it could be due to low activity or no top-up being performed ,may be an outage.
    "SELECT sum(externalCallCount) FROM Transaction SINCE 30 MINUTES AGO COMPARE WITH 1 WEEK AGO WHERE name = ‘KeyTransaction/service’ TIMESERIES

SnapShot:


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#79

Hi,
I have a java application, which is set up new relic and we use this tool for checking performance, Average response time, System Load, CPU Usage.

Its very useful for us as our app is critical for business and cant go down.

Thanks.
Rahul Gurnule


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#80

Hello,

We are using New Relic as our Dashboard for our Management Server and to collect API metrics like response time, average response time, CPU usage.

Query : SELECT average(cpuPercent) from SystemSample SINCE 10 minutes ago FACET hostname LIMIT 24 WHERE fullHostname LIKE ‘%rc-web%’ or fullHostname LIKE ‘%db%’ TIMESERIES

Also, we can check Network Traffic IN and Out to monitor traffic from our Clients.

SELECT average(receiveBytesPerSecond) FROM NetworkSample TIMESERIES FACET entityAndInterface WHERE hostname LIKE ‘%q4web-prod-content%’ LIMIT 100 SINCE 60 minutes ago


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#81

Because, if you set your alerts right and notifications correct and thoroughly the errors and violations are the most important part to keep an eye one, everything else is just what follows :slightly_smiling_face:

SELECT count(responseStatus) from SyntheticRequest Since 1 day ago WHERE responseStatus  != 200

SELECT Sum(criticalViolationCount) FROM InfrastructureEvent SINCE 1 day ago

SELECT count(error.message) from TransactionError Since 1 day ago

SELECT count(*) from JavaScriptError Since 1 day ago

SELECT Sum(warningViolationCount) FROM InfrastructureEvent SINCE 1 day ago

These provide valuable information about relative to us error information and count. Even tho we receive alerts and notifications, it is nice too also display and see any issues occurring live on a screen.

*Required Products:*  APM, Synthetics, Infrastructure.

*Level of Effort:*   **Low**

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#82

Entering into the era of micro services where different application push data metrics to new relic and carving out of it the meaningful data to complete cycle funnel, we created various insights that helps us to monitor the happenings on our business in realtime and action .

Dashboards, metrics, funnels of onboarding user through various channels along with performance metrics, data, response time.

Screenshot:

Dashboard details:

Required products: APM , Insights

Level of effort: Medium

Joint Funnel query:

SELECT funnel(gi_trace_id or GI-Trace-Id , where application =‘pigeon’ and callback_msg_content like ‘Sign me into Goibibo%’ As ‘Pigeon’ , where channel=‘GI_WHATSAPP’ and nr_intent=‘auth.loginviawhatsapp’ As GIA, where appName=‘golambda’ and stage=‘lambda_fun_initiated’ As ‘Lambda fun’, where appName=‘golambda’ and stage=‘magic_link_received_at_lambda_fun’ As ‘MagicLink succ’, where channel=‘GI_WHATSAPP’ and nr_event=‘Task completed’ As ‘GIA returns’, where application=‘pigeon’ and event=‘msg_sent’ As ‘LoggedIn’) FROM pigeon, RobinProcessMessage, whatsAppLogin WITH TIMEZONE ‘Asia/Kolkata’ SINCE today

Histogram bucket:

SELECT histogram(otp_entered_time_diff, 420,20) from Transaction where otp_entered_time_diff IS NOT NULL with TIMEZONE ‘Asia/Kolkata’ FACET flavour SINCE today

Cool,
Tushar


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#83

We like to track our number of page views with the number of unique sessions.

PageViews: SELECT count(*) from PageView WHERE appId=________ since today

Unique Sessions: SELECT uniqueCount(session) FROM PageView WHERE appId=________ since today

Device Types: SELECT count(*) FROM PageView WHERE appId=________ since today FACET deviceType


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#84


#85

Geographic Details:

While not necessarily a dashboard in and of itself, I figured out a while back how to scope and filter the results of of insights queries by country, state and/or city. This will allow you to view the pertinent information for any dashboard in regards to what geo locations are seeing specific responses and details.

Dashboard Details

Required Products: APM
Level of Effort: Low
This dashboard will work on the standard New Relic data models and does not require any custom attributes or events.

Settings
Use the gear button to edit your dashboard and configure the following settings (below is an example):

  • Dashboard Filter: Enabled
  • Enabled Event Types: PageView
  • Enabled Attributes: `city’, ‘countryCode’ and "regionCode’

Chart Details

The whole purpose is to use these more as widgets associated with an Insights dashboard to be able to answer questions around questions associated with “Where…” What Country, State/Region or City are seeing the fastest response times? What location does a certain app have the most traffic for the day?

By adding these you can filter the results to get a better idea of how your performing in specific locations around the world!!!

Step 1: Pick a country

Linked bar chart

SELECT count (*) from PageView FACET countryCode since this month limit 1000 with TIMEZONE 'America/Los_Angeles'
List of countries of origin for end user interaction

Sept 2: Pick a state/region

Linked bar chart

SELECT count (*) from PageView FACET regionCode since this month limit 1000 with TIMEZONE 'America/Los_Angeles'
List of states or regions of origin for end user interaction

Step 3: Pick a city

Linked bar chart

SELECT count (*) from PageView FACET city since this month limit 1000 with TIMEZONE 'America/Los_Angeles'
List of cities of origin for end user interaction


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#86

Dashboard: - Mobile Applications

This dashboard provides a business / ops view of the mobile status from a performance / utilisation perspective.
It can be used to quickly see how new app releases are going, identifying when, how and what customers are using the application.

Devices - Number of unique devices connected, number of applications upgrades, New installs on devices
Sessions - number of sessions, session times, number of crashes
Application Utilisation:- sessions & transactions over time compared to same time last week. Great for identifying changes to performance or utilisation.
Usage - How many sessions per hour, what devices are connected…

Dashboard Details

Required Products: Mobile.
Level of Effort: Low

This dashboard will work on the standard New Relic Mobile data models and does not require any custom attributes or events.

Queries:

Daily Unique Active Devices:
SELECT uniqueCount(uuid) AS ‘Users’ from MobileSession since today WITH TIMEZONE ‘Australia/Sydney’

Daily Sessions:
SELECT uniqueCount(sessionId) AS ‘Sessions’ from Mobile since today WITH TIMEZONE ‘Australia/Sydney’

Customers at Risk (Crash):
SELECT uniqueCount(uuid) as Users from Mobile where category = ‘Crash’ since today WITH TIMEZONE ‘Australia/Sydney’

Users & Sessions (Over Time):
SELECT uniqueCount(uuid) AS ‘Users’, uniqueCount(sessionId) AS ‘Sessions’ from Mobile since today COMPARE WITH 7 days ago TIMESERIES 5 minutes WITH TIMEZONE ‘Australia/Sydney’

New / Upgraded Devices Today:
SELECT filter(uniqueCount(deviceUuid), WHERE upgradeFrom is NOT NULL) as ‘Upgraded Devices’, filter(uniqueCount(deviceUuid), WHERE install IS TRUE) as ‘New Devices’, filter(uniqueCount(deviceUuid), WHERE install IS TRUE OR upgradeFrom is NOT NULL) as ‘Total New / Upgraded Devices’ FROM MobileSession where appVersion like ‘4.%’ AND osName = ‘iOS’ SINCE today WITH TIMEZONE ‘Australia/Sydney’

Users Today (by Hour):
SELECT uniqueCount(uuid) AS ‘Unique ID’ FROM MobileSession FACET hourOf(timestamp) SINCE today WITH TIMEZONE ‘Australia/Sydney’

Users Per OS & Release Version
SELECT uniqueCount(uuid) as ‘Unique Users’ FROM Mobile FACET osName, appVersion SINCE today WITH TIMEZONE ‘Australia/Sydney’

Daily User Session Time:
SELECT average(sessionDuration)/60 from Mobile facet cases ( where deviceManufacturer like ‘%Apple%’ as ‘Apple’, where deviceManufacturer like ‘%Android%’ as ‘Android’ ) since today TIMESERIES WITH TIMEZONE ‘Australia/Sydney’

Total Mobile Transactions:
SELECT count(*) FROM Mobile SINCE today TIMESERIES 5 minute COMPARE WITH 7 days ago WITH TIMEZONE ‘Australia/Sydney’

Enjoy


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#87

SELECT count(error.message) FROM Transaction,TransactionError FACET appName SINCE 1 DAY AGO

SELECT count(httpResponseCode) FROM Transaction,TransactionError FACET appName SINCE 1 day ago

SELECT count(*) FROM Transaction since 1 day ago FACET appName

SELECT count(databaseCallCount) FROM Transaction FACET appName SINCE 1 DAY AGO

SELECT count(*) FROM Transaction since 7 day ago FACET weekdayOf(timestamp)

SELECT count(aggregateFacet) from TransactionError WHERE aggregateFacet like ‘%HttpClientError%’ COMPARE WITH 30 minutes ago TIMESERIES


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