good morning good afternoon and good evening everyone and Welcome to our webinar thank you for being here uh so today we're going to be covering how to map services in minutes with automated service suggestions and today's webinar is part of the itom visibility and governance series and we hope that you will join us for future topics so today's session is also a part of the live on servicenow program which is a curated set of events to connect you with servicenow experts and peers that will help you to deploy servicenow products and Achieve value faster you can see the complete schedule by scanning the QR code or by using a link that we're going to post in chat and we hope that you will join us again for another webinar or meet up in the future just a few housekeeping items before we get started so everyone's line is muted so please use the Q a feature to ask your questions throughout the session feel free to introduce yourself when asking a question we'd love to know who you are please participate in our polls it helps us understand where you are on your deployment Journey uh so this session is being recorded and it's going to be shared on the servicenow community as well as YouTube for future playback and then finally after the webinar ends uh you will be prompted to fill out a survey that's a short survey and your feedback is always greatly appreciated to help us improve for future sessions outbound product manager for item visibility and governance here at servicenow and I'll be your host for today's session now as an outbound product manager I wear many hats I'm a product evangelist I do customer value realization and sales enablement internally just name a few but what I love most about my role is that I get to meet with you and hear how you are using our products and I get to share information with you about how our item products can help you achieve your business goals I've been at servicenow for five and a half years and have been working with servicenow platform for 10 years as a customer partner and now an employee and I spent the bulk of my career working in Enterprise I.T roles across a multitude of functions so I know what it's like to be in your shoes and then presenting alongside me today is hail tall Hale can you do a brief introduction please hey hi everybody nice to meet you my name is high tile I'm part of item visibility product team I'm in service now since 20 2014 but in the service mapping area since nebula times the 14 12 almost 12 years three years ago and I'm happy to help you to show you the Journey of a machine learning service mapping and what I have in my role is how we can improve our product to meet our customers needs over to you three oh hi team yeah yeah go ahead I'm sorry go ahead yeah I was just thinking like no sweep product management uh director working for inbound product team Steve urtu thanks Sheree and Shri is going to be behind the scenes today ask you know um answering your questions that you put into the Q a panel so today's webinar is going to focus on how to use automated server suggestions to map services in minutes but before we see how it works let's talk about why you need to map services in the first place so the cmdb is your organization's date um data foundation and it is the data foundation for servicenow it is the central system of record of configuration data for your infrastructure and applications across on-premise Cloud as well as microservices the most successful cmdbs are service aware which enables you to understand the impact of infrastructure and applications to the business now service visibility is the key to service operations excellence and it enables you to make data-driven decisions based on business impact across all the use cases you see here and more now before we get into um our our webinar um the use cases we'd like to know which use cases that you are using today so I'm going to launch a poll here and if you could just take some time to fill out the poll you know we'd like to know where you're using service maps on on a regular basis is it across AI Ops is it across change management or devops change is it across risk in compliance or or bcdr incident or major Incident Management security Cloud transformation application portfolio management certificate management and firewall auditing it asset management and finally customer service management so these are obviously a subset of use cases that service and apps could be used for but we'd like to know which ones you're using I still see some answers coming in we'll give it about five more or to ten more seconds thank you guys for participating this is awesome data that we're getting and I'm going to go ahead and end the poll for the sake of time thanks for those of you who are participated let's see the results so what we see here is a com you know our top ones are Incident Management with major Incident Management uh change management um those are the top two which I would expect for the itsm audience here but we also have aiops is a is pretty you know popularly used as well as it Asset Management so thanks for that stop sharing the results and continue so the servicenow platform of course is underpinned by a single architecture and a single data model now a single architecture means that all platform applications can seamlessly work together and are enhanced by a core set of capabilities such as workflow Integrations Ai and ml just to name a few a single data model of course means that all applications can leverage a single system a record the cmdb that is built following a common data model which we call the common service data model or csdm now as you can see on the screen the app the application service sits right in the center of the csdm and it is the critical element for on representing deployed services in your cmdb and since application services are made up of deployed applications and infrastructure they need to be as accurate as possible to achieve accurate and up-to-date service maps and automating an automated service mapping solution is needed so let's see some example use cases with AI Ops you may receive thousands of alerts per day and if hundreds of them are critical severity how do you know which ones to work on first right to store your hands up well if you have your services mapped you will re um you'll receive a critical severity alert for a server that has a database installed on it I should say if you receive a critical severity alert for a server that has a database installed on it that is part of an application service that service will turn red on the service operations workspace like you see there with with order status so why is this important for each service that you map you assign a business criticality level to it and the service operations workspace a range of services by business credit so that you'll be able to map to clearly see which of your most critical services are impacted and prioritize them and when you look at a service map view from service operations workspace to see the specific configuration items that have alerts against them which will help you pinpoint the root cause CI of the alert our Second Use case is change management so that when when you are planning a change how do you know how the business will be impacted by that change when you have your services mapped and you create a change for a specific configuration item or items the refresh impacted Services feature automatically will enable you to see impacted Services right on the chains form so this enables you to reduce the risk of a failed change and easily know who owns a each service to coordinate approvals with and also if you have your services mapped you can enable unauthorized change detection whereby if you do not have a change record opened at the time a configuration change was discovered and on an unauthorized change request will be created of course oftentimes unauthorized changes are the probable root cause of an outage or degradation Now by default unauthorized changes are created as emergency changes now in this example an emergency change request was created for an unauthorized change of a configuration file now servicenow stores versions of configuration files in the same to be which enables you to perform a comparison between two files and see exactly where the change was made and if you determine this change needs to be reverted well you could open up a change request and assign it to the appropriate team for implementation moving on to use case number three so when you respond to vulnerabilities and you have so many that are deemed critical how do you know which systems you should patch first so when you have your services mapped you can prioritize patching of systems based on related business impact you can start with your most critical Business Systems first and you work your way down the criticality scale of course also factoring in the you know severity of the vulnerability itself and finally our last use case example service mapping helps you streamline the build out of your application portfolios using this this following approach here first uh Discovery discovers your infrastructure on your applications including install software and Hardware details Sam Pro and ham normalize software and Hardware product models and provide life cycle details service mapping of course automates the application service discovery which we know is at the core of the csdm there is a suggestion engine that suggests software and Hardware models that belong to an application service and through relationships these hardware and software models become part of the business application and once you have your application portfolios built out you'll be able to manage your technology life cycle at the business level with technology portfolio management or TPM so here you can see the software and Hardware lifecycle events when software reaches end of life it becomes prone to hacks which increases you know risk to your business when Hardware reaches end of life it is less performant which can lead to degradations or outages so TPM enables you to create demands or projects to address the pending end-of-life situation in advance and in doing so you'll be able to reduce risk improve your security posture and save money on unnecessary extended maintenance contracts and you'll be able to avoid potential fines so let's see how automated service suggestions for service mapping works so I just discussed why service mapping is the key to service operations Excellence with some use case examples so now let's see how service mapping in and of itself works as a product so our solution provides three complementary methods to map services together these allow you to address a wide range of service mapping scenarios and requirements that give you the flexibility to choose the optimal approach for your specific goals so tag based mapping builds service Maps using discovered tags or keys and values from your virtualized cloud and containerized resources if you have quality tag data across your resources you can easily map hundreds of tag-based services in minutes and if you don't have quality tag data you can use our tag governance application available from the store to Define and enforce your tagging policies now ml-based service mapping uses machine learning to identify meaningful traffic-based connections to be added to service Maps this makes it ideal for bulk mapping of of services from scratch and extending top-down Maps you'll be able to reduce the amount of time it takes to map services from weeks to minutes and then top-down mapping uses of the pattern-based discovery to identify service connections so this method of course takes the longest because it requires application architecture research up front deep technical knowledge and in pattern building so what because it is so precise uh top down mapping is is very well suited for mapping your mission critical services so today's webinar we're going to focus on the middle one which is the machine learning based mapping with our new automative service suggestions so first as a next poll we'd like to understand which methods of service mapping are you using today so I just launched the poll are using Top Down based tag based ml-based Dynamic CI groups APM service graph connectors such as dynatrace or op Dynamics uh manual Maps or you're not mapping services at all which I put yikes there because you should be mapping your services so let's take another 10 seconds or so great data coming in guys thank you all right I'll share the results and it looks like the bulk of you are doing manual mapping right which is which is which is okay if you have static Based Services but really you want to start to map your services in a more automated fashion and top down which is our traditional method seems to be the second most used some of you are using tag base some of you are using ml based and some of you are not mapping your services at all which is very concerning to me but I digress move on to our next slide and two more slides before we get to demo folks um this will give you an understanding of how we have evolved the mlbase service mapping solution since we introduced it so we first introduced ml-based mapping with Quebec and which uses machine learning of course to suggest those meaningful traffic based connections uh each connection suggestion has that confidence score to help you decide which connections you'll want to add so in Rome it was more of a manual method to add the connections to the map fast forward to I'm sorry that was Quebec uh fast forward to Rome we introduced a rules engine to automatically add connections to service Maps globally or to specific Services based on criteria that you define so for example you can create a global rule for adding all high confidence connections to all service Maps globally or you can create a local rule to add all processes listening on a specific port to a specific application service around the time that Rome was released we also introduced the service mapping Plus store application where it first had an application service Readiness dashboard for monitoring the health of your mlbased service mapping and also a Readiness dashboard a prerequisite track essentially and the San Diego family release we introduced load balancer connection suggestions which detected whether or not a connection suggestion is a virtual IP address or a VIP so confidence scores for VIP connecting suggestions are based on connections to resources behind the VIPs and then in Tokyo we decoupled service mapping from the family release what that means is that going forward all service mapping Innovations are now part of the service mapping Plus store application to ensure that we can release updates more frequently and then it's not it's no longer tied to a specific family release as well and then of course with November 22 we introduced uh the automated service suggestions feature with service mapping Plus so until today the question of where do I begin when mapping Services was the biggest challenge right so it was difficult to understand what entry point I should use essentially so we are very pleased to announce uh the release of automated service suggestions which eliminates this question by suggesting service candidates that include a pre-identified set of resources to be included in the map and with just a few clicks you'll be able to gain business context for your infrastructure and apps and the service Maps will be kept up to date for ongoing use across all the use cases we talked about earlier so with that said I'm going to turn things over to hell to show you how to set up and use ml-based mapping as well as automated server suggestions of course but of course as a reminder please place your questions in the Q a box and we'll answer them behind the scenes or we'll answer some of them live later on so hail over to you thank you Steve and I hope everybody see my screen now yes so uh as we mentioned a traditional mapping use pattern to create a connection so you can see if I Define patterns for Webster or okay and Define connection section it create a connection between the CIS so if you open the law if you open the log you can see there are a connection section a notification section and that as a a Steve mentioned need a familiarity with the technology with a configuration file and need to also be experienced in a python development when we and release the ml based mapping and so we came with a traffic-based solution that consumed a TCP information and running process information uh collected on the horizontal Discovery there were a machine learning a job that bind process to process using the connect to and listen to Port information and once you do that and you define a rule you can see that the map build automatically you added entry point if we check the connection suggestion you see that all the connection added automatically to the uh to the service using the the role that you defined before creating the map but again it's required uh for military with the entry points and and and go to the service owner and ask ask them questions and when we come with the uh with the new feature service mapping plus that released in several plus November Stories the service candidate so again it's part of service mapping uh home page new home page and we have the readiness uh dashboard that show you if the application fingerprint job that released in Paris uh consumed the data in the running process data in your system if the uh UI suggestion uh job uh consume the the TCP information in your system and this the system property and if some of the properties are not instead already you can click on it and you navigate uh to the relevant property you can set it save and go back to the to the machine to the machine learning dashboard and as as I mentioned uh Steve mentioned in sorry in November timeline we added a new feature that is also part of the service mapping Plus in your home page it's called application service candidate and you can see a here candidates that generated using your information the running processes and TCP information you can check uh the service click on preview map see how the service look like and if you please you can choose to create a service soe so if I placed from the preview map I can click on create service give it a name and click on create service and that's it so you don't need to know to look for the entry points you don't need to to go over and and run afterwards owner and once you you download it you have a message that the service created successfully if you click on delete link it you have a new tab navigate to the service and you can see the service Creation in option in running and you can go and let's skip okay so you can see the service that created using the candidate if I'm compare it to the same service I created using device suggestion so you can see that it's the same service just this one created by automatically defining the entry point so how it's happened how it's how this happening so we have the uh process to process binding a job that released in San Diego on top of it will release the machine learning generate candidate jobs that that taking all the the all the process to process information in just a minute yeah it's taking all the process information and start split them to Services okay so each service have a bunch of process to process and once it's the job done with splitting all the pairs of processor process itself a running algorithm that minimize the data point eliminate the entry point to have the minimum entry point that can build the service so once uh this job also done if I click on the candidate you'll see the candidate information the the FP suggestion the application fingerprint job that run and give a suggestion for this process and if I click and on preview map you can show me how the service will look and I can choose to create this service okay so once you have this information and you have the candidate in place uh you can and filter out the candidates or the default filter shows minimum four CIS means if the CIS have less than four if the service have less than four CIS participated filter out again we also show a candidates in less than 100 CI so we won't create a huge map but again you can apply with this filters remove them or set them to different threshold if you want I show I should I will show it in a minute and another default filter is that all the entry points suggested for the candidate not participate in other services you know that when you create a map if a cemetery Point added to new service you have exception that block the creation of the map because the entry point is unique per service so you see this filter that show that all the participate entry points in the candidate are not in use with other services okay and if you want to change the default you can click on Advanced View and then you can change the parameters [Music] sorry or add all and condition let's say that you you have the the candidate number and you want to create candidate I don't know that contains zero zero five so so again and once you update the the the list will be updated with the candidate or the filter that you apply in my case it has less than five CI so it's a filter output anyway in anywhere in any point of time you can restore the default and get the out of the box defaults and see the candidates the generated uh and again you can once you create a service you can continue with that and you have the application hint so if if uh you know the the processes participate in the service you can filter the candidates uh by that if the it's Java based kubernetes uh or uh or other processes that you deserve you want to to map uh if nmap is available and there is response for Emma nmap uh the candidate's suggestion name extract the header and put it here okay uh and this is for November release in our future release we plan to add another uh criteria or attribute to the to the to the table one of them is a comma separator device list so if you know the device participate in the maps you can filter the candidates per device or and the other attribute is the if these candidate has any lb service participate on it so you'll see the lb service name so it can give you uh also hint if this is the the candidates you want to map it so the value that service can be financed up Etc and so this is I will create a candidate again the prerequisite for it is that you have the service mapping plus uh version uh 1.6.0 Deployable instance and this is this is stop is uh free of charge for all uh all uh instances that has service mapping plugin activated for that and that's it for the candidates yeah maybe we can uh have you questions answered because I see a lot of questions coming in uh no from the audience uh so if I want to summarize uh know the questions right so what is the key difference between the automated service mapping versus the top down mapping right how this is uniquely differentiated right if you look into the narrative right of typical top-down mapping you have to give an entry point and for entry point you'll be talking to an application team or run a survey and ask them hey give me the entry point give me the architectural diagrams but majority of times uh we will have all the raw Discovery data when you run the horizontal Discovery it collects running process traffic data it's a very raw data set and using the running process data we create application fingerprints and this was introduced in Paris release and then the traffic data again you know is super raw so we synthesize all the raw information using the machine learning algorithms the automated service suggestions is giving you the list of service maps that you can create with a single click experience where you don't have to give an entry point right that is the key messaging so if you have existing uh no Discovery data strongly encourage you to deploy the service mapping Plus store application it will deploy certain clustering scripts and algorithms will Kickstart will identify the candidates and there are two tabs that hail showed you one is the Readiness checklist will give you a complete perspective whether of all the settings are ready all the algorithms are collecting and no synthesizing data using our ml algorithms and then if you go to the service candidates it'll show you all the candidates right and here again the key differentiating factor is you are not giving an entry point the machine learning is auto suggesting the potential connections that are super important for the map creation right that's Point number one secondly there was also questions on saying that if you already have a service map build can you uh know instead of creating a new application right can we add it to an existing app service that was another set of questions I see in the Q a and even for this like no it's a it's a roadmap item that we are tracking for the next release that you know in the main timeline we will definitely unlock this capability uh but the other important uh Factor about the ml based mapping is uh you know if you look into that AFP suggestions AFP stands for application fingerprinting and and this is again a prerequisites that like you need to have successful horizontal discovery running on all the infrastructure and if you go to those two tables in your cmdb a table called Running process and a table called cmdb underscore TCP so these two table data sets are the only requirement for the successful service mapping automated service mapping suggestions and you don't have to give complex config file access like top-down mapping which was one of the biggest challenge where you'll be able to discover the Tomcat but you cannot discover the config files and without config files the top-down will just stop because it's going to you know parse the config file to find the next hub connections but in case of automated service Editions we are purely dependent on these two tables if you have data sets these two tables the algorithms will do the prerequisite checks the mapping will create candidates and you'll be able to successfully you know quickly build maps without even entry points so let me pass here and let's look into no other questions that we can answer so I think we kind of answered most of the questions uh just like please again you know share some of those Q A's as well um but to again as add a few summary on the overall mapping techniques that we have introduced uh so so Steve if you have that slide right that shows different mapping techniques uh we can quickly go over this uh one by one and see which mapping no can be applied you know for what use cases I'll bring it up right now SRI yeah so by default like we have this three important mapping techniques that we support with our Solutions tag so traditionally if you look into your workload strategy you can run your workload on-prem with the vcenters with hypervisors or you can run your workloads in Cloud VMS or you can run your workloads in containers or with modern Cloud native functions so when you look into these different workload dimensions right you you will see that which mapping technique can be used for what workload I would say top down is best fit if you have a Data Center and you know where you have load balances where you wanted to build a surgical mapping experience and you have some good credential access within the server infrastructures because the way top-down works is like you need to have an entry point as an input parameter and it goes to the load balances it finds all the connections uh using the top-down approach which requires patterns that has to be executed on the target devices on the cloud and container workloads we have seen tag based mapping uh very effective we have several thousand customers using this approach to quickly build simplistic maps and even customers who were able to add tags to the Mainframe data sets even things that we don't discover and then they use Tag based maps to build an application context the third dimension is the machine learning based approach and this again is an evolution of capability that started you know with the Paris timeline where the application fingerprinting looks into the clustering of those processes then it evolved into and service mapping ml connection suggestions where within your top-down map you can just go to connection suggestions and add extended connections to your map easily without writing any complex pattern steps and then in the next release we introduced a policy based approach so that if machine learning is saying hey I'm confident that this connection is important then all those can be automatically added with a simple policy rules engine but now you're seeing the final evolution of how the product was uh not initially designed to work right where as a customer as a partner you don't have to give an entry point if you look into the raw traffic data you are able to see the traffic between server a server B server C you know what process is opening up ports what process is listening to the ports you also have the load balancer discovery that has visibility to the bips and the physical IP address now machine learning is able to connect all the dots and it's saying hey here's the list of all servicemap candidates that you can create with a single click experience you select and candidate you can preview a map you can see all the logical application service connections and then you'll be able to quickly build a map and an entry point is automatically added to the service map right that's a huge value statement for our customers the other big question Steve I see is if you can open up the csdm data model there was questions around like how this uh you know enables uh the app Services candidate so let's quickly go into the cstm conceptual model yeah so here uh if you look into the data model angle on csdm um csdm has different entities like uh business application is an entity heavily used to buy design teams and you have business services which is an entity that heavily you know being used for the consumer facing uh customer facing apps and then there is an entity called application service which is related to the configuration item so when we talk about Discovery it is the responsibility of Discovery to collect the service load balances network devices populate the raw information into the config management table cmdb tables an application service is a construct that is not going to build the relationships between the apps that we have discovered from the discovery a good example is you may have a checkout service in a banking application and the checkout service may be having a checkout service Dev Checkers service production checkout service stage and behind each application service you will have the infrastructure that is responsible for providing that service so the service mapping is responsible for connecting the infrastructure to application to application services and then build that model uh you know in a constructive way so that we can use it for different outcomes like you know the its um AI Ops and all other outcomes that you know Steve highlighted but the other entities that like Business Services business applications this data model has to be constructed because these are all non-discoverable data model and if you look into the store we have an application called service Builder and there are some YouTube narratives that we have created strongly encourage you to try service Builder because it helps you to augment the app services with the constructs other constructs that we you can dynamically build and that was again uh you know a set of questions that I see in the chat as well so Steve I'll hand over the floor to you thanks Shri um I believe we can go back to our demo Now by Hill we're done with the demos too oh you finished the demo okay yeah alrighty so let me then re-share my screen and continue one second all right so what we like to do is I'll share another poll with you and what we'd like to understand is now that you have seen this in action right how soon do you plan to try this out um do you try it out today you were so excited what you saw you can try it out today uh maybe next month or the next six months within a year or maybe you just don't know yet um and there'll be a question as you leave the survey um if you want a help with this so you could actually put your contact information in there and somebody will reach out to you to help you with it but I'll leave the poll up for just a little while longer foreign then we'll go ahead and end the poll okay so it looks like most of you are going to be trying this out within the next six months uh you know a lot of you will try it out within one month and then some of you are actually going to try it out today which is awesome uh and again um so if you have any questions on on how it works there will be some resources that I'll share with you to get in touch with us um but stock sharing so we do have some time SRI for more questions before we we wrap up yeah so let me then go over the remaining questions uh so question from Peterson Candace automated feature fill in the gaps if you already have some relationships such as application to server Peterson dancer is absolutely yes when Discovery discovers we discover the server but also the running applications like an Apache SQL databases like Oracle SQL servers and so on but what service mapping solves is the connectivity between this application so if I have an entry point like an IP address and port and or a URL uh that is again an entry point no needed for from the application uh consumption perspective how what kind of infrastructure elements are connected between each other that's exactly what service mapping solves and ml based mapping can further accelerate your service map creation because you don't have to ask for an entry point it's already looking into the data sentence coming out with recommendations saying hey you can build this Maps automatically what service mapping cannot solve is automated building of the csvm constructs or like we cannot name a service right like hey somebody has to tell this is checkout service right the naming convention uh the nomenclature that you follow with your uh you know APM and SPM related uh you know products you'll have to you know have some human intelligence added to this automated service mapping features uh the next one is from Kiran how horizontal Discovery is related to ml horizontal discovery plays the foundational uh data layer where it goes and collects the running process and traffic data if these two data sets are collected by horizontal discovery then the algorithms work on top of it and then it will give you all the recommendations for service mapping suggestions and once you build a service map it again goes and validates whether the running process and traffic data exists on the target host so it's not just going to build a map based on the data sets that it sees from the cmdb tables the beauty of service mapping is like it wants validation it wants verification that the application CI let's say SQL Server exists and it's listening to a port right this validation will be done by service mapping and do my process how to come from cmdb Discovery or can it be integrated from titanium this is again a phenomenal question so the question from David uh we introduced service graph connectors that can Source data from third-party data sources data sources like tanium SCCM uh and even like no customers use crowdstrike and all other security agents and as of today we have ability to collect this extended data set from titanium like specially running process and traffic data and you if you apply machine learning on top of it we can still build Maps and there is already a feature in the backlog to support a map building based on the cmdb data and you're going to see that in action no pretty soon uh next year where this feature will unlock the service graph connectors to contribute their data sets and service mapping you know automated service mapping can also build maps on top of it today you can use Tag based and the other approaches with third-party sources the ml based approaches coming soon uh archana the recording will be available in YouTube so you can definitely take advantage of it uh let me check what other questions we have I think majority of questions are we'll try to answer it in the chat itself uh we do have a very nice blog written by Steve and there is already an YouTube narrative on this product so if you are planning to try it uh no deploy the selection give you uh no hours for the machine learning to uh to synthesize the process and in order to start recommending some suggestions and and also it requires a decent data set right and if you are trying it in subprod right and especially if you have a production clone make sure the mid server will especially connect it to the subprod environment does have access to the prod because when you add a service map it is going to do the real top-down mapping of saying hey go and doing performing validations whether the CIS exist right and it works only with the production CIS that means like now the server has to be you know the life cycle state has to be in certain stage uh if the life cycle status not uh in production right so it's going to be stopped so make sure that you know in your cloned environment all the prerequisites are met no before you start the exercise so Steve I'll hand over the floor to you for final thoughts and comments yeah thank you Shri um and for those of you on the chat I just reposted the link to uh the document with the links in it um it's got the links for everything in this webinar um so for those of you who joined after I posted it last time you would now have access to that uh so some resources that SRI was mentioning you can see here on the screen uh we have a getting started blog we have a how-to demo uh we have a video on ML based mapping in general we have a guide in our now support for ML based connection suggestion troubleshooting if you should come across any issues there and also one thing we didn't mention is the preview Mac the preview map functionality that hail showed that works out of the box on Tokyo if you have Rome or San Diego you just need to apply an update set for the preview map functionality to work there's a link there to download the update set from our now support site so please make full use of these resources we appreciate that Now The Innovation that you see in servicenow products is really largely based on on your needs our customers so we always encourage you to submit ideas on our idea portal also recently this was moved over to the now support from the servicenow community so go to support.servicenow.com ideas and you can submit a new idea or you could upvote an existing idea so once an idea receives upvotes from at least 10 unique customers it's automatically raised to shree into hail right so that our product team can consider it for our roadmap so we have a call to action for everyone here today and we have a challenge for you as well and I'll get to the challenge towards the end here but you know just to recap the steps to start using this automated service suggestions right install service mapping plus 1.60 use the application service Readiness dashboard to check to see if your instance is ready for ML mapping and if it's not just follow the steps to turn on the net you know necessary plugins and things like that right then you can start to use the application service candidates dashboard to begin mapping your service candidates and again these are new Services only right it's not for existing services that you've already mapped so we just had uh up at our world forum uh three and hail were there so you know they can attest to this we had uh you know a customer who was able to map 50 services in one day by using automated service suggestions and they presented their story at the world Forum in Toronto um we're trying to get a link to that available to everybody and I'll share it out once it's available but you know this is extremely powerful and these were not regular maps these are very complex service Maps so begin mapping your service candidates showcase those maps that you've built over to your stakeholders right all the use cases I showed you at the beginning of the webinar get those stakeholders for those use cases excited about it and then what we'd love you to do is this is a challenge right is share how many services that you've mapped on LinkedIn with the hashtag service mapping is back and we'll keep an eye on that to see you know you know how many services you know you are mapping and we encourage everyone to do an active search for that hashtag to see how you're doing it and you can then interact with one another to see how you're using our Technologies and of course we are here to help you all right so ask your servicenow smes for help uh reach out to your account team um ask a question on our community there's lots of very great smes there uh you you know your account team can engage Us free myself Hale or any right resources to help you uh if you have any questions about how this works or if you just like to work with us you know on this technology so we are taking a break from from uh from hosting webinars in December so but we will be back in January to continue this visibility and governance webinar series so please join Severn and me on January 17th where we're going to cover how to deploy and manage agent client collector at scale now the registration link is not yet there but but it will be there soon so now would also be a great time to go back and watch our other webinars in the series uh so see see the links in the chat document that I put in there with all of our on-demand content I know you know a lot of you have asked about you know availability of this solution so service mapping the product itself all the methods that we we talked about are all part of service mapping service mapping is included with itom visibility which is a suite of products that enable you to gain visibility across your entire estate right we didn't talk about any of these other products you know today except for Discovery and we touched on service graph connectors but you know for complete visibility you have the ability to use our solutions to really help you so to learn more about how we can help you you know you could certainly watch those on-demand videos um you know as I mentioned where we cover a lot of these different topics but you could also reach out to your servicenow account team and somebody will get a whole you know in touch with you to get to kind of walk you through our Solutions so with that said I wanted to thank everyone for attending we had a great audience today thanks for your interaction um and have a great rest of your day everyone bye-bye now