Usman Ahmad: Unlocking Key Metrics and Patterns Using Grafana

This talk focuses on using Grafana to unlock key metrics and patterns from various datasets, particularly Google Sheets. The speaker, Usman Amad, a developer advocate at Grafana Labs, explains how Grafana can visualize data effectively for users without extensive data handling skills. He demonstrates integration with Google Sheets, showing how to configure data sources and utilize plugins for better visualization. The discussion includes practical examples of data transformations, dynamic dashboard variables, and filtering options to enhance data presentation. Usman emphasizes the importance of Grafana's open-source nature and community in facilitating collaborative data analysis and visualization.

[Music] ladies and Gentlemen please welcome our next speaker yusan Amad presenting the topic unlocking key metrics and patterns using Gana yeah uh thank you very much for being here I know I stand between you and the party but uh believe me it will be a cool one it has a lot of visualization so we will not get bored or get sleepy and don't get sleepy it's the

party time so you have to awake um yeah this talk is about um understanding key metrics and patterns uh basically it's about data and and we learn about grafana how we can use it uh small intro about me uh my name is Usman I work in as a developer Advocate at graan Labs um um does this mean that I work a lot with the open- source community

and answering them on community forms or GitHub slack also um documentation and um when I have some opportunities or free time then try to come to the conferences and talk about grafana and its use cases and uh beside work um um I'm a father of three-year-old mostly that time and uh busy at home uh but uh other than than that I like to uh write I have

my own small uh uh uh YouTube channel which I like to create videos sometimes uh not very punctual but whenever I have time I love it and uh yeah um outside of all these tacky work I like to read Comics very big dragon ball Fan and Dragon Ball super the series or someone may know yeah and you can scan this QR code if you want to know

more about me or uh my uh blogs or details or videos uh yeah so um let's get started so yeah today we are here to talk about grafana and uh it will be like this that uh I will explain some uh background and then we will go uh with some uh demos um uh one by one probably I guess there are three to four examples in total

and we will learn how to use grafana in when you have different types of data sets so yeah so this is just a general Market U reference that um a lot of you here are here for the devops conference some of you are for the cyber security conference some of you are from software side so everyone has unique skills and they work in their individual area and

there are also like other areas like healthcare or businesses or some other areas where we also use uh technical data or need expert technical exp expertise I would say and we have we have a lot of data there and we use software tools or Technologies to collect that and uh everyone has different title in their respective Fields um not going to name each and every one of

it but you get the idea and obviously there's one thing in common in all of this so it's all about data data in form of like um maybe in a text file or CSV sheets or maybe just raw data you are collecting data Maybe running a script maybe a very fancy um program or just talk about like open Telemetry there's you've got some raw data but now

you have data data what you will do so that's we are going to talk about today and yeah once you have the data then obviously what you have the knowledge because you process it and then you apply some actions such as where should we focus our work energy or where are the impact points so that our company or industry can uh improve or our product can grow

and um nowadays it's AI world so jet GPT is also used very widely a lot of data is pump into the cloud people store their data in the cloud it could be public or private but cloud is there it's not going anywhere and with AI it's getting more and more so basically we have like a Empire of data so much data that we even don't realize like

how much we are putting up there it's countless and it will remain like that uh forever and uh one example which we going to talk about is some data we use is uh in the form of sheets like Google Sheets um it's available in the cloud because it's from Google and uh we view it no matter how much we want to hate that we don't want to

Lear sheets or because it's not our expertise but there it is because many software like Java or python can give you data in such formats and we use it because for us it it's all about like making our life easier so I am also like I said that I'm also a tech person so I was I have no expertise such as like learning Excel sheets or Google

Sheets whatever and I try to use this research it's like how many of us or in general know about uh how to use Excel so you can take a few seconds to take a look it's not as accurate because the Google even said the result of This research is from 2022 I could not find much recent which is okay but I highlighted the important part and yeah

so we are not experts like my expertise is that I can open a Excel file I can read some data I say yeah this have like permissions of a user yes or no allowed code or no like this this is what I can do not can go any further with that formulas or so and this is a real world example so this is happens a lot of

us in real world that when we try to give this data to some other person those person do not understand like what we are talking about because they also do not know much about it they don't know about how to use Google Sheets or how to use fancy form and if we go one step further that we want to visualize all these data in graphs then that's

a very very complex and very unhappy story for many of us because we don't know much so just imagine that there's a company meeting in your office and your top uh Google expert guy for the sheets is gone or on vacation and your boss is like hey can you do that what it's written here and oops and you start working on it you say okay I have

to do it because at least the application part is on my side so I know the data but I don't know how to visualize it and you try you are doing like firefighting but you are not getting going anywhere it's like it's a stuck you you don't know what to do so you are hopeless and it will not work the other solution is doing something like this

which is cool but yeah in real world it doesn't work that way so what is the solution how we can use this uh uh data to visualize easily and view all what we need to do like to present it to in a meeting conference or to stakeholders who also do not want to look at like thousand lines of excel uh cells data and say okay now it

is starting to make sense so yeah there is one way and that is like we have Google Sheets yes and we Gana and together we can start visualizing the data and also filter it to our needs that is possible how let's take a look so uh please raise your hand if how many of you know about grafana or have used grafana very nice very nice and how

many of you have sort of expertise or no Sheets yeah it's okay the service says true so I stick to my word yeah so grafana yeah it's a it's available in many flavors so it's basically available in in in form of cloud Docker kubernetes or you can install on Linux Windows Mac and it supports many various visualizations um U coming from core or from the community side

as well and all you need is to configure a data source grafana uh does not need that if like like a traditional software like once you have that software you have to configure the database put some password no it just need a data source so it can connect and talk to it it could be internal or external and then it will start showing you the data in

visual format grafana also have uh we have a plugin uh it is called Google sheet data source plugin and uh it is also available in all grafana variants okay or versions and it also support various visualization formats and it is very easy to integrate and set it up we will have a quick demo about it and we'll see and uh now I put this one extra slide

because um whenever I talk about Gan and I use the word Plug-In or data source there is a confusion among people and they ask me later like is it Plug-In or is it data source so grafana ecosystem have one thing which is called plug-in and plug-in is divided into three types data source which means like you connect your data to a source or connect grafana to a

source which is called data source and in this case it's uh Google Google Sheets plugin the other uh is the panel panel are like add additional way to view your data there are some Community Based or customized panels which you can use and there are some dedicated apps apps like zeix or kubernetes as well so yeah now how it is going to work so this is the

respon requests look like so basically we have graffan and a Google sheet setup and what it need is two things it needs the Google sheet ID and the API token uh when it comes to set up this plugin you have actually three options either you can use the Google sheet API or you can use the JWT token or uh uh GCE uh authentication method as well but

API is the simplest and uh we will for today we will keep talk about keep it at least to the API part and then we send the request and in between the we use the Google s s uh Google SDK module basically what it does it is uh written in go and it translate the data and try to connect it with the Cloud once the data is

there uh it comes in like a row data format and uh and we use a function called Data frame which basically transform this sheet into a data frame and it goes back into Gana in Json format and then we view the uh data so now the next step is to how to configure all of this what we just talked so it's simply twep process first you install

the sheets plugin uh in grafana it's all UI based at least in in the newer versions of graffan you don't need to use any command line or so and uh once you install it the second thing is you need a Google API token which you can also configure very easily there is a simply just go to your Google uh conso uh developer console or Google Cloud console

and uh you can get the API key easily so let's create our dashboard panel and this is how we will going to work today that first we have uh two things at least set up um we will use a sample query and also we will learn how to use a transformation and we will view data in table panel visualization first but in also in other visualization formats

as well a small note about transformation so transformation is a grafana function and uh it allows you to change your data in a different way to represent it also in a different way we will take a look also to it as well so so about demo so I have this sheet here so this is a basic uh temperature data sheet and it may be written in the

output might come from a python script or maybe a bash script or maybe some fancy uh temperature software and there is this data it has some data uh for for month and City's name and so on and now we want to visualize it so how we going to so I will show you at least uh here how it is done um so I first uh let me

just go back so I click on ADD and visualization and go here type the Google Google Sheets this is the data source name and this is my uh Google oops Yeah so this is the sheet ID which I just highlighted okay uh this is the sheet height uh sheet ID and um I will paste this ID here and press enter and it will start loading and um

let's go to the table format in table format it looks something like this so it's not in this format and yes grafana is intelligent because it has uh it has like a Time series data so by default it automatically detects it's a Time series panel visualization but for Simplicity we first go with the table one so um that's one way to view the data it was an

easy example and uh let's go back to the slide so I remain in sync um now we will uh um yeah talk about transformation but I just want to show one thing more now we have this uh panel the table panel and U the time space panel but we can view it in a more different ways as well in more different visual visualization and how to do

it so this is um maybe I can make it bigger so this is a Time series panel and then you can use different visualization panel options like bar chart heat uh State timeline uh gauge panel and so on and this this started to make sense because now that raw data which you have which is only you can read or only few person can read but now you

can show it to others and they can easily read it okay yeah and some more so going back to the slides uh transformation so yeah transformation is a way to uh transform our data and uh alter it and Gana has this transformation function built in and it is really powerful and um I use it a lot because sometimes the data which I got from the output is

okay but it exactly not to my needs because there might be something which is extra or uh um I need to remove it or I need to change its uh look and this is where a transformation comes handy so yeah this is what I just talk about and the talk uh next uh or the next demo is about filtering the data so as an example data I

have this uh Google uh sheet data uh this is actually taken from our community forms so basically uh it has a ID and a topic name with some other details like reply account how many views and so on and now I have this data so I can again use the same way like I use the sheet ID and uh view this uh in in grafana um I

have it already set up here yeah so this is how it looks like right and um and now we want to use this transformation so now I'm again in my edit mode and what I will do um I will click on on transform data okay and and select add another visual visualization the visualization name will will be organized field with names and then once it is I

when I select it this automatically appears and it exactly gives me the uh same details as in the above um the title uh ID title and so on with trans with this transformation I can rename the content so ID means like category ID for example and and uh title I want to give it as description and so on and there is one field um um um the

category ID at the bottom the blue one I have hide it because I don't want to show it to other because it may come from this actually this data come from the SQL post SQL and it come but it's not usable for anyone and I don't want to show it to other so I can hide it and um you see this uh this looks right now up

like this yeah we just talk about it and once I say yeah everything is fine the final data looks something like this so basically you can see that the uh heading has changed and there is no uh um uh the the category ID which was telling from which area this data come from so I hide one field because it was useless but uh it is not useful

for others so they don't get distracted and they have the data which they need to only panel configuration so now we will go up with advance in this area we have done this part okay um um the next part is the panel configuration so in Gana every panel has its own configuration settings mostly they are same but in some areas it differs so panel configuration for example

give you um on on this uh left side you see two uh box which says override and inside there's a cell config and data links and then there's value mapping override is a special uh way also uh to to modify data it is very very similar to transformation uh the only difference that when we apply a transformation the change is permanent however when we apply a override

it's basically a masking so if we remove the override uh the Json will remain symol but uh in transformation the Json data also get changed and notice two things or one thing here that the table panel visual visualization box is in green and cell config is also in green this is because as we just discussed that panel configuration each panel configuration has uh its own uh uh

special settings so cell config is only available in table panel visualization it is not available in Time series or any other so yeah we just talk about it um override so you can modify specific uh fields or series and uh you can customize this to your needs so now we going to take a look how to use cell type how to use override for cell type so

we have this data here okay this is the same data which we just view how um in in the previous slides and we want to apply a uh over a property called cell cell type basically what it means that the cell which we have on the on my left which says solved unsolved we will make it more prettier or clarify because then it become more readable how

to do it there's a small um and please ignore this bottom area because I could not create a new video in time but um let me just just rewind it back quickly okay so yeah we are in the edit mode and we go on the on the area where it says uh override and we select field with name and the field which we want to select is

the status field right we select the status field we click the next add overwrite property and we use cell type once we have selected this we we since we want color background so we'll use color background option and select it and now we have a colored background available for our specific field not for the whole data but only for a specific field so this is again very

powerful feature the second uh override property is known as data link data links as the name says link your data to a particular URL or or particular um page for example and this is exactly what we are doing that we had a Top Field name with topic ID which is also can be called as customer ID or or topic ID or or get customer ID let's say

both are same um and since this data is coming from our community forms so we want to link it and how we link it we use the data link same we go in the override and select topic with name topic ID and select the next option as data link you will see this black combo Box open and here in the URL we first type the static part

so it's Community gra.com SLT and then we Define this variable with a dollar sign indicating that we want for uh uh uh data links for this uh field with is topic ID and what it will do is that we have now uh uh this field linkable to our community page so if if I go and click one of these uh links I will go to the that

particular uh page this example maybe not for Community but very useful for GitHub if someone is working on GitHub every GitHub ID is unique so you can use data link there as well the third is value mapping value mapping means that you have a data right and you want to map it in a way that if this means true then it looks like this otherwise it remains

same as an example there are more example of varing like you can use rex or in null cases as well but keeping it simple uh we will use like how it looks like so if let's say we want to use value mapping for our same status solv and unsolved and we want to view those unsolved in a more prettier or more useful way so so that for

our eye we can see like where we need our attention so we uh this panel this option comes in the on the panel side we click on add value mapping then this combo Box open we Define the condition uh for the value that the condition will be like if any text which says unsolved display it as unsolved we can maybe say not yet solved or in progress

and we can also set the color once we set DEC color as red for example and update it this is how the output will look like on our uh uh panel so it's now starting to make sense and very useful so the demo now yeah so this is the default data we we we we just saw and this is the filter data the next one uh the

difference here is that uh again uh it is us it is not using any transformation so there there was this category ID but in this one there is no category ID because it is simply using transformation and then we have a modified data format which is exactly what we just saw that topic ID or category ID same sorry for the name convention um but uh it's a

yeah it's it's just logical name whatever we can give it and it has links so if I for example uh click on this link I will go to that particular Community web page yeah okay it was a bit slow but loading but yeah this is uh for the for the data links I just don't don't want to wait too much because maybe we run out of time

and don't want to spoil okay okay I guess internet problems for now yeah internet is extremely slow back now we come to the last part of the demo which is a little bit complex but really interesting use case we will talk about Dynamic dashboard variables so in the world of grafana this is something every user wants it is also known as templating that uh you define uh

you you you create dashboard in a way that it is all Dynamic and you don't need to um make too much effort and once you create Dynamic dashboard then yeah it becomes very interactive and yeah I I make this in bold it says a avoids duplication what does it mean it means that imagine that you have let's say you have running many scripts bash script which is

giving you uh data in form of like text or CSV file or and you are putting it on on the cloud in in Google Sheets but now you have so many different files one way is that you create each and everyone every dashboard for those or maybe you find a creative way that you pull down a menu and say I want to select this file then just

uh and the dash same dashboard shows you the file uh data for or visualization for that file instead of like creating thousand dashboards with single dashboard you can do that as well and how to do it we will take a look and and uh dashboard variables comes in many options like you can query them you can use Global variables chain but for today we're going to to

take a look at the custom variables and uh for demo um I have a very this this also take interest of me because it was a tricky one so I sheet um okay okay I have to spoil a little bit of fun but it's okay so I have this Google sheet now this is this is a pure real world example that there's a sheet with a lot

of tabs like one is for job tracking the other is something null fine then inspect uh inspector inspection and there's a pager Duty now for me for example this pager Duty data is important because my boss or the team wants a reporting of it it is coming from a maybe a uh tool from a ticketing tool that does not support a visualization but it gives me the

data about the server performance and so on and it looks something like this yeah it's it's messy but I need a way to find out to make it visualize so what what one thing I see is that since in in in the world of Google Sheets everything is in celles so once you know the cell number you can get that data and in this case I know

that this is my cell A1 to um um A1 to um oops it's my shift is not working yeah this is my data so it says A1 to E15 and same for from i1 to something um M15 just as yeah um maybe I can try again yeah i1 to M15 so I know the celles but how I can visualize it so um I can use Dynamic dashboard

variable uh uh or templating and to do that um I have a sample dashboard created I go in uh in settings and I click on variables I this is the variable name so you can in your case um you can click a new variable give this variable uh type as custom and Define a Define a name to it like sheet bar sheet variable and so on and

here we can Define the custom type so we know that that uh this the incident total one is um is from A1 to E15 something like that so uh A2 to E15 we named this an incident total and same for the next two ones which are in different cells but all in one sheet and this is where I can preview the result right so this is um

the data is showing up that yes uh this is the value I will get now um once I have defined this variable I have available here in my dashboard right and I say like okay now I can uh created some panels in different uh in uh uh different uh formats in time Ser table pie chart and so on and I want to view for example the incident

total so it will update and now it's giving me data about the incident total and I can view also uh yeah graphs as well if I want to say a mean seconds to acknowledge then I can view it and I can also customize uh it because this is not the default way to because it's all in in raw table format um uh from coming from the sheets

but I have used some uh Transformations uh and also some uh override to make it um in a way like it comes in a um yeah in in bar chart sorry I was just struggling to find out okay yeah here so in not in bar in in gauge panel so say the cell type here is gauge panel and yeah and I also apply some variance like okay

these data the data type of in this case is operations per second so I use operations per second as as the standard here yeah standard units um and select operation per second so this is just a a good example because this is how in the real world we deal we deal with Excel sheets because it's all combined and looks messy and it's very hard to produce such

kind of visualization and U sometimes we simply do not have expertise or cannot go for other options like to use some other expensive sof expensive softwares yeah so yeah okay I think we are about to end anyway um the last topic is annotation annotations means that um um I can Mark points also on my uh on my visualizations when a particular event has happened um and it's

like vertical lines as an example it is already available here that um in one of the um panel it is marked uh yeah so okay it's not there no problem but uh simply clicking okay it doesn't work sorry but yeah you you can do it it it it was working before yeah okay now it's coming so it's it's my mouse click so add annotations and I can

add uh description for um High consumption or high volume and even can add text like it's coming from the operations so I can add this and save it and it's a little bit outside of the graph scope but you get the idea that you can do it uh it's doable and um yeah so troubleshooting uh now we saw that okay we can visualize all of this we

can can even filter out we can do some custom and complex stuff but when it comes to troubleshooting it's a tricky part because some of some or many time because I have my background also in the support area so I know that uh those data maybe even in the Google Sheets or somewhere in the cloud are confidential and it is not allowed to share even if you

have a support contract because you say like I can't share it with you luckily in grafana we have this feature uh shooting feature so um um let's say that I have this data uh this is actually um or give me give you a more better example yeah so I have this data and I want I say that I want to there's some problem after an update and

I need help so for troubleshooting you simply uh go in the first in the edit and click on this breadcrumb and simply select get help and there's a feature called uh randomize uh your data so you can say uh anything with name or labels or values uh it tries to uh randomize it and now you can see the description looks funny and uh but at the same

time it gives you all the debug information and you can C copy this uh this dashboard Json and send it to the support so this is really a useful feature because um again in support field of support um it's very complicated because of SLA to share the these kind of data to the other side uh because uh yeah if data got leaked or um there there are

some serious consequences in the payment Vice so uh but there is this feature in Gana which can be really helpful so final takeaways um uh what we have learned so far that uh using uh Google sheet plugin with Gana it gives you a centralized visibility not just for you for your whole team for your company anyone who does not even understand anything about Google Sheets can use

grafana you don't need to do a extra course from your budget and say like hey boss I I have expertise or learn Google sheet so you don't yeah it makes your life easier uh yeah collaboration and transparency you can share it with others easily they can also share it with others um um without knowing any uh technical de knowledge so yeah very similar to first point but

um yeah um cross crossplatform support this is important because as I said earlier that there are many tools in the market which also support uh visualization formats you can filter data create fancy graphs but they have either um um not available in every uh platform or some cost issues so uh but in this case it's available everywhere because grafana can be installed on any any operating system

and uh and it's this plugin is also available uh everywhere in graffan either using cloud or locally or even on on your uh uh Raspberry Pi so yeah uh some future improvements which we are going to make uh the first thing is that we are trying to make support uh support for alerting currently alerting supported and uh the second is uh we are giving uh d uh

improving the drive integration so basically it means that uh there's uh this is coming from actually uh what we have learned that some Google expert user who knows about Google Sheets uh Google provide this uh Drive driven uh Innovation support which means like you can read your data somewhere from the drive it's it works but it's flacky so we are working on that as well and yeah

if you want to get involved we will be really happy because we need need your your we need we need to know your issues what bugs you run it so we can fix our software and yeah so um yeah sorry I I ski and there are other resources as such as uh you joining the uh Gana community on the slack Channel and also on the community form

and yeah we discussed the problem we understand how we can find the solution and with that solution we can success and and yeah you can also be one of this to your team that now you also know how to create fancy visualizations and even can filter data without needing any Google expertise from a Google expert So yeah thank you for participating um I'm really glad that you

guys joined and uh all the details what we just talk even the slides are available if you scan this QR code there's also link to the documentation even uh put the link for the API reference and how to even use Gana if someone is new to Gana So yeah thank you thank you for your talk uh we still have couple of minutes for questions if there are

any also as always but I don't I think you know the drill by now slido QR code if you don't want to ask or if you want to ask just raise a hand and uh I'll come to you with the mic okay then I'll start what is the fanciest um plot type available in Gana so the fanciest plot type is actually obviously time series is something everyone

wants to use because uh with time series data it is uh easy to see where the uh direction of your data is actually going it gives you Insight the second something very highly used is like bar charts because with bar charts you know like where for for stat statistics uh as well and and if you are someone like something like a scientist uh then heat Maps uh

heat Maps is also used because it gives you the data the one example which we saw for the temperature there was like um actually giving a sort of like a heat map panel that where the temperature are most high in all the three region and where is the what their lowest point so uh these are the few examples can you add something custom or is it uh

just limited no you can definitely add custom in fact uh you can create your own panel maybe you have some software running in your company which do some sort of uh data and provide some visualization uh you can uh uh create your uh you can create it and integrate it with Gana because grafana is completely open source and we have a lot of Community Based data sources

panels and some apps as well and we will be happy uh to get more because um this is how we grow we try to keep it all open source and open for everyone and last question from my side uh you showed mainly simple examples like no super complex transformation of the data from the spreadsheet uh is it advised to do the transformation like smoing or something else

on the spreadsheet and then import data or can you do it in grafana so you can you can do advaned transformation in grafana or in the spreadsheet like the concept of spreadsheet is that you have some data you you put in the cloud because nobody keeps it locally however there's a small uh thing to understand that if if you have this option to uh to filter the

data uh on your uh if you if you instead of grafana filter data where you are where you are getting it from it's better because once you apply transformation Inside grafana Yes it helps it makes your data different but it also takes some processing power and processing time so if you have a lot of queries like in my SQL case or even in the Excel sheet case

if you have a lot of sheets it will take time and it will slow down the performance as well doable but there's a cost okay now we have couple of questions uh from sidal let's try to do it in a blitz manner because we don't have that much time so is it possible to import CSV from python script directly to grafana without integration to Google Sheets yes

it is possible so we have if you have a CSV data and let's say you don't want it in Cloud we have a CSP plugin which is very really simple the concept is same like you you you install the data source the CSV data source plug-in and then just uh say this is my CSV file path and it will fetch the data and apply the filters and

so on all right uh tricky one what is the actual benefit of grafana integrating with Google Docs or Excel they already have built-in functionality to visualize data yes it they have visual functionality and I'm not saying that it it should be replaced Excel is yeah very powerful I'm um nothing to say against it but that was the point that not everyone knows how to create a fancy

stuff in Excel I mean I I can say for myself I don't know and many of us even don't know like how to use those functions with Gana um you you saw that we do we not we did not do any kind of coding or or any fancy stuff we just use the buil-in option click and try it out and there we have we have all the

visualization uh fancy stuff without learning any uh additional software skills because grafana is used in operations or in observa field so but not as Excel because that's uh for for data science or someone in the business site so visualizations for damis gotcha yeah and next one would be how easy is it to synchronize parameters from different shits in a plot example visualize spatial and time information such

as position of a person XY coordinates in a 2d map uh well that's a very very good and difficult question definitely uh we have a panel XY panel um which works with the coordinates um um um I believe it should be possible because at the end if your data is defined in a way that it has X and Y coordinates accordingly then the panel can autod detect

like we saw that if we have time series data then by default it was picking um time series not table panel as table panel should be so in this case if you have something like that but the data is defined in a right way then you can use XY panel plus there are some custom made python or matlb panel which also work in these area of visualization

like XY or z uh uh graphs and uh you can use that as well from the community and integrate it thanks and the last question given grafana dashboard is using open shift p fluctuations as a data source how would you adjust peritus scrape interval so it would not uh be total negro I sorry I'm sorry I do not even understand the question correctly got you a little

bit too technical uh let me try to rephrase the so any who has wrote the uh question I guess I won't be able to decipher it quickly okay so okay maybe just yeah just just come up to Usman and ask him directly and if you could explain exactly what you mean but I guess it's about the size of the data source yeah I mean I'm not Prometheus

expert I have some knowledge I know where it is coming from from the data like when you have a lot of metrics but we can talk whoever feel free to come me and yeah okay then last question instead of that one would you say that data sources are first class citizens example reusable over dashboards and so I don't understand what what it means by first class citizens

but in Gana Gana is nothing without a data source so you need a data source uh once you have the data source then you can uh make it working and even Define alerts like for example someone who asked the Prometheus question yeah you can once you have the data source and it supports alerting then you can define alerting define some rules like when it should be triggered

and so on so data source is needed without it it's just plain software it will not do much so the answer is probably yes okay uh since we are out of time now thank you for your presentation thank you for all you of being here