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BTOES Insights Official
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June 30, 2020

iBPM Live - SPEAKER SPOTLIGHT : Using AIOps to Improve Your Digital Business Processes

Courtesy of Micro Focus's Wes Cooper, below is a transcript of his speaking session on 'Using AIOps to Improve Your Digital Business Processes' to Build a Thriving Enterprise that took place at BTOES iBPM Live Virtual Conference.

 

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Session Information:

Using AIOps to Improve Your Digital Business Processes

Today many business processes are codified in applications. IT Operations is now a significant partner in making sure these processes are working and if not getting them back up and running. To do this, they need to enlist the help of machine learning, big data analytics, and process automation to operate efficiently in this new era.

In this session, Wes Cooper from Micro Focus will showcase how AIOps from can help improve your digital business processes by assuring the services stay running and optimized with automated monitoring, analytics, and remediation.

Session Transcript:

Look forward to them. Now, our next speaker is going to talk about Using AI ops to improve your digital business processes, where Scooper is the Product manager for the Operations Bridge and Micro Focus. He has six plus years of experience of micro focus in HB Product marketing, global enablement, sales, and business development, all within the IT operations management of market. He's a published author and for time marathon runner, you go as an avid Outdoorsman Outdoorsman. He is based out of him. Out of Dallas, Texas, West. Thanks for being with us today. We're really look forward to your presentation.

Alright, Jose. It's a, It's a pleasure to be here, and hope everybody is staying safe these days. Let me go ahead and I will share my screen again, so you can see our slides as we get started.

All right. So, yeah, like I said, pleasure to be here to present to you all today on how apps can help to improve your digital business processes. Go ahead and move forward one slide, and go to our agenda real quick.

Here we go. Alright, so, here's kind of a look at what we're going to run through, over the next. I think I've got about 30, 35 minutes with you all here, before we get to our Q&A here at the end of this session. So, first, I'm gonna walk you through what is AI ops. This is really, probably been kind of a buzzword in the IT operations industry, recently, so I'm gonna put some meaning behind that term for you all, and really show you where AI ops has come from, and the value benefits that it can give to your business. today.

We'll talk about process discovery, and creation, and implementation of the process. So, how you go out and discover those assets across your hybrid IT estate, finding out what's normal. So, being able to do data collection and analysis effectively. And then, we'll also look at some things that can help you to do process improvement around these digital business services, to help you detect problems faster, and to even put automation behind them, to really put this all to work, at a speed that will support your digital enterprise today.

OK, so, when we talk about the evolution of AI ops, this is something that is involved over several years here. Artificial intelligence for IT operations is what AI ops stands for. This all really dates back to 2005 when the term big data analytics came into the market that was first used by O'Reilly Media back in 2005. And this was really talking about this concept of, hey, we've got all these large datasets today.

How do we, how do we manipulate these and use the data that we have today to make more sense for our business and improve processes? This is really where it all started back in 2005, where machine learning was used to compliment monitoring of IT infrastructure with visual analytics and log analysis. Fast-forward, you know, about nine years.

And gardeners started to introduce this term called IT Operations Analytics, and if you've been an IT operations practitioner for awhile, you've probably come across this term at some given point. Again, this is, at this point, in 20 14, Gartner really introduced this concept of having this central, kind of big data store, having business value dashboard, that's what VVD stands for, there. And that's really the concept of being able to paint a picture for business leaders of their business data, as well as for IT leaders, as far as, you know, technical, infrastructure, and systems, network data that was flowing into those dashboards. Fast-forward to 20 17, Gardner coined this term, AI ops, or artificial intelligence for IT operations to account for this shift to cloud and containerized environments. Or, you've probably heard the term serverless recently.

Screenshot (41)As, well, as the needs for the organizations to really simulate all this data, right. So, today, data doesn't just live in on premise data centers anymore. It lives in the cloud. So, you've heard of Amazon Web Services, probably by, now, a lot of you, I'm sure. use AWS, or Azure, or even Google Cloud Platform. There are several that, are popping up in the market over the last, you know, 10 years, or so. And it's growing at lightning speed. Another thing that's growing, increasingly is Internet of Things, Or IOT, right. We've got, we've got all of these mobile devices, we've got tons of, of data that's flowing out from coming in from outside, just these traditional data centers anymore. So this proliferation of all this data has really require the ability to analyze and reduce the noise around all that data flowing into operations.

Today, fast forward into 2019, we're in, what we call, multi domain and operations. So, what we're starting to see in this market of apps is really some differentiation between domain agnostic type vendors in the market, and domain specific. So, this is inclusive of several different data domains that live in IT and business today. That includes things like serve IT, service management, network performance management, and diagnostics. So, how you're bringing in, you know, events and data coming in from your, your networks that span your, you know, companies and organizations, locations, DevOps, data that's flowing in as a very critical part. And, to bring into AI Ops and crunch that effectively, application performance management, as well as IT infrastructure management data.

So this is kind of the, you know, span of where we've gotten to, in the last, you know, 15 years or so, APS is a very new term. But it's actually had some history that's been around for awhile.

OK, so, talk about AI ops.

now that I've told you a little bit about history. In addition of it, where it's come from, let's talk about what you should look for in an AI ops solution. So, point number one. This comes to us from Enterprise Management Associates. They are industry analysts that we work with a lot at Micro Focus, several. Other vendors in this space also work with enterprise management associates. And the model that they've shared here, it's very pragmatic and prescriptive. It's five clear and concise steps to help you get on your way, implement i-ops in your business today. So number one is the assimilation of data from cross domain sources and hide data volumes. I mentioned that today data's living all over the place. Right, it's not just within companies own firewall and their own on premise data.

Hello, ladies and gentlemen. I see your questions. And I'm coming, jumping back in, here. Because I want to make sure that your session is OK, and that you can still see me and hear me. I, I believe that there could be something that happened at the presenters. And so, and, and the reason for that is that, whereas is based in Dallas, Texas, and there are some severe thunderstorms going through his area. So just to do a quick check on that, could you please just type in the questions box that you can hear me and see me, OK. I need some feedback just to make sure that you can hear and see me, OK. And, whereas, if you are on the line, we, there were some problems, if you're a transmission. So, I see you coming back here back. Can you hear me now?

Yeah, I think, I think that they can hear me. And they can see me, OK. But there was a problem with, on your And, well, did you have a power glitch, or something?

Yeah, we've had some. We've had some big thunderstorms that have rolled through Dallas this morning. Also. I really apologize for that, hopefully, Hopefully, we maintain connection here. I have a have a 400 meg connection here, Jose, so I'm hoping that I'm hoping it's just a brief brief glitch. I apologize for that. Completely understand, you know? It's, it's incredible that, you know, in the age of Big Data, incredible analytics. We still need the Electrons to be flowing for all of this stuff to work. So I'm, I'm, going to, excuse myself, I just wanna make sure that the audience knew that everything was OK with the webinar, and what's there. And so, please do carry on. Thank you, As sure, and I think you, probably.

Can you guys all see my screen? Is it still showing?

Yeah, your screen looks good.

OK, so hopefully we're on the app's model slide, Jose, real quick, where did you guys lose me? It was zero point one.

Btog CTAYou're, I think you're right on this slide when we couldn't see you anymore. So, I think you're right on track. OK, cool, I'm gonna go ahead and move forward here, OK. So when we talk about the AI ops model, what what should you look for, OK, so this is a great prescriptive model that comes from industry analysts, enterprise management associates, predominate analysts that we work with here in the IT operations market all the time. And I really like this.

It's a very prescriptive five easy steps to implementing apps today. So number one is the assimilation of data from cross domain sources and high data volumes. You know, I mentioned that we've got data that's flowing in from beyond just on premise and physical data centers anymore, right? A lot of you are adopting cloud services and platforms from Amazon web services, or Microsoft Azure, or Google cloud Platform, or you've got IOT data that's flowing in from all over the place. So, having a centralized data store and a place to centralize that, data is really a core concept that all of the analysts are talking to today. The second is to be able to access all that different type of data that you're collecting today. So, you know, a lot of, you have monitoring tools that you've had in place in IT and the business for several years now. That's not really a surprise to anybody, I don't think.

But, it's the ability to take all those different forms of data, like events, metrics, log data, network flow data, and topology. And to be able to store all that in a centralized data store. Number three, it wouldn't be an AI ops solution if you didn't have some type of self learning Or an algorithm to help you drive prescriptive, predictive, and if then insights. So, the goal here is to have a system.

They can go out and look at all your different business processes, and monitor all those, you know, by collecting all that data, and then prescriptive Lee, or proactively be able to say, Hey, based on our, you know, current load, an event that's coming in, you might be seeing some issues come down the pipe here in the next, you know, day or so, based on what's flowing in and be able to create those trends in the environment.

Number four is that it's got to be able to be a strategic overlay that can assimilate multiple monitoring tools and other investments. So on average, what we see in the enterprise market today, and based on EMA's research here, there's over 23 monitoring and management tools. That middle and large enterprises are using every day to manage their IT environments and their business services. That's a ton of different tools, and that's a lot of integrations, You know, to bring in, it's very important that you can have all those tools talking in one place, together. And then, of course, point number five is that it needs to have support for traditional infrastructure, so you can't forget about the on premise systems, but you've gotta be able to take care of what's out there in the private and public clouds today, and, across serverless, and containerized environments as well.

OK, so, moving forward to the next slide here, here's how we deliver i-ops at Micro Focus, and again, this model here that you see in the middle, we refer to as Observe, Engage in Act. This is in line with what industry analysts like Gartner and Forrester, as well, are outlining for their app's model. Right, So, at the top, where you start here, with AI ops, is this concept of observe ability, right? So, I've got to have the ability to automatically go out there and discover all my hybrid IT resources, and start to do monitoring of those, right? I gotta know what I have. And I gotta start monitoring those constantly, so that I'm getting this data flowing in. Also, the ability to go out and create customizable dashboards, and reporting is very key for a lot of organizations that we talk to every day.

They need the ability for IT operations to paint business value dashboards, right? That business leaders can look at and say, OK, I understand how our top, you know, digital business services are running. I see which ones we have critical events or problems coming in. And this helps, you know, IT leaders and business leaders, to be able to talk the same language, and ultimately, it helps them to plan and budget things out more effectively. The next step down there, from observe, we see in purple, is engage. So being able to centralize performance. And events management is very important.

For a lot of your organizations today, they've got dozens of monitoring and management tools. None of them are really talking well, and a lot of organizations, so having this ability to centralize monitoring and event management data is very important. Today, at Micro Focus, we support over 200 plus integrations there, and we've seen customers reduce the amount of events that they're handling by up to 90%. Bringing in application health and user experience management data is very important, as well. So, you can't have application performance management tools out here working in a silo and not talking with AI ops. The point is to bring those together.

3-Jun-30-2020-08-31-08-88-AMThen, act and in pink here are magenta.

Is really about, how do we take the business processes that, that we know, and were collected all this data on. How do we start making it more autonomous. How do we give it the ability to act on itself? And that's the state that we're working with a lot of organizations today to get to. And I'll show you an example of where we've done this here shortly. And then, of course, the central brains or neural network that's bringing all this together is AI ops. Where we, we've built, we have a big data platform, we've built all this on today at micro focus, known as vertical, and we've got 50 plus patents specifically for IT operations. Data management builds on top of vertical today. Businesses like Facebook, and Uber depend on, on vertical every day. Uber, they do a lot of looking at different time trends for rides.

And being able to do analysis and drive their business more effectively on that platform, OK, so, the first step to really being able to get on the train to improving your digital business processes. With AI Ops is automating the process of asset discovery in your IT environments, hybrid IT environments, right?

So Discovery Automation really simplifies monitoring configuration by going out there and constantly looking for new configuration items in the environment. All right, so here on the right, you get a screen that shows a topology view of a business service, right. And this is something that is very important to be able to utilize today, in your IT operations environment is being able to see how things stack up from a business service, right? It's not enough anymore just to look at system health performance. That's not really going to give you a good insight into what your end users are experiencing.

So having this ability to automate, just go to go out and constantly look for environments and populate those into your apps, platform, is very critical.

So, we, we've mentioned also talking about, you know, it's all about the data that you have within within AI Ops today. And what's gonna make it stronger? So, one of the forms of data collection that's very popular out there, especially when we talk about improving business processes, or being able to monitor into business services, effectively, is doing data collection with synthetic monitoring. So, essentially, what this is, synthetic monitoring, it's, it's not necessarily a new concept, but it's a concept that I can tell you, a lot of businesses have huge advantages and benefits of doing.

It allows them to quickly go out. And for each business application that you're running, it allows you to simulate virtual users on those applications and to see how that application is performing. So, real quick, your presentation is not updating the slides, you know, as you as you're going through them. Just, so just go ahead and click on the presentation to make sure it's going through OK, for you. We're not seeing the updates on your slides. Yeah, that's interesting, because it's rolling through for me.

Do you want maybe if I start to share the camera, Jose, maybe it will give some additional bandwidth for you. You can do that, or you can stop sharing your presentation and start again, just reset that.

OK, and I think currently Jose, I'm just showing as a it's just show panelists, which is interesting, you have me as a presenter right now, So OK, so I'm sending back to you so that you can take control again.

You shouldn't see a popup come up, Yeah, let me go OK! Let me know if you can see that now.

Yes, we can.

OK, perfect The way thank you for everybody online who's providing the feedback? Because I see something That's slightly different from sometimes what they see. So thank you for the feedback sure We're right on track with you now.

OK, sure, so We were talking about this synthetic monitoring concept, and I think you've been able to hear me, right, Jose? But here's the visual behind this, right? So this gives you an example of what synthetic monitoring or data collection will allow to help within your environment and making your business services or applications effective, effectively perform better for your users, right? So, this concept of synthetic monitoring, again, it allows you to simpler, Simulate a virtual load on an application, and you can do that from multiple points, right? We realized that a lot of your organizations are working in a global capacity, right? So, what if we have the ability, 20, 4 7, 365, to be able to monitor our business services from any location across the globe, and get down into the transaction layer to be able to see every step of the process, an application, that a user?

And that's very important, important to be able to overall improve your users' variance.

OK, so let's move forward.

So here's an example, just again, the process of how synthetic monitoring works and the benefit it can provide is it allows you to run a simple script. So here you see one of the United Airlines. United Airlines here and their business application, The recording a script against that application of a user process, they can replay that from multiple times and locations across the globe, to make sure and see how that application is performing across, you know, any one of their critical areas, and then, the ability to do visual analysis. So having dashboards and reports, or SLAs at your fingertips. And then, you know, finally, being able to isolate those issues and see where the transactions are breaking down or not performing well. That's critical to operations teams, to be able to look at those issues that are coming in.

But it's even more critical to for the development teams and app dev to be able to see, hey, where do we need to go back? Where do we need to re code? Where do we need to retest these applications and kick them back to production?

So here's some examples of some business value dashboard examples for application health and user experience management, of what we do, even at Micro Focus. And, again, these are fully customizable, so I just have some examples here. And these are really meant for both IT operations, as well as the lines of business to be able to look at quickly and be able to make decisions based upon the data that's flowing in.

So, we mentioned centralized event and performance management. That was a really important piece to AI ops, and improving these digital processes is the idea that you need to be able to centralize all of your data into one console and make sense of that. So, here, we have an example of what our operations bridge manager looks like, which is the main console of Operations Bridge and our AI ops solution. And here, you can see in the bottom left is our event browser, we've got a lot of these different types of network events and application data events flowing in on the top right. It's a full topological view of the business service. So, from all the way from the top level application view here, at the very top of the screen.

And, we can drill down literally all the way into the VM or container kernel layer, and just that's very important to be able to see how that whole business service is flowing, OK, so when we talk about analytics, we talk about AI ops, what's the benefit, OK? The benefit is that it's going to be able to look at all of your data in a centralized place, and it's going to be able to help you learn patterns in that data. And that's going to help you to proactively spot issues before they occur. And it's going to help you to look at even anomalies that are flowing in and really be able to become more predictive and prescriptive in your environment. So, here we have just kind of a dashboard example of what flows in here.

Screenshot (4)A quick example of this is over here on the left, we have all the logs that are flowing in from the environments which are you know, log file is a very basic level keystroke that we can go out and monitor and bring into the environment. And you can also, through all this data, fast-forward. And you can rewind as these critical events are flowing in and you can drill down into these. On the bottom left, you can kind of see where we've got that predictive baseline. So, you know, the real-time data is flowing in and you have some graph of that. But also, your solution needs to be able to go out. Your AI ops solution needs to be able to go out and do some predictive analysis of what's coming in the environment.

So, one of the big things of making apps effective is, Hey, what if I don't have a data scientist? Well, what if I don't have a person that has a PHD to go and do data science in my environment today? That's one of the key things that we're talking about here with configuration free, apps, and our solution. This is something that, it requires zero touch. You literally go.

And when you, when you deploy our solution, it's constantly doing analysis of all the data that you just are pointing at it. And so, it doesn't require a data scientist or an operator to go out and look at these trends and analysis or build them over time. It's automatically doing that.

And so, having that ability to, You know, for machine learning, to take its place, and allow your operators to go out and focus on other priorities for innovation, is really key, and that's what's going to help you get ahead here in the future.

The last thing, one of the last things that we'll talk about here is a closed loop incident, process management or clip. And this is really to help the whole incident flow remediation process, right? So, once you're able to identify a problem, right, in a business service. Maybe one of our business applications, in Germany, per se, maybe you have an online banking application in Germany, and users can't even get into the login process, or it's taken, you know, a minute and a half for them to get into the login process.

Here in the top left, you, you would see an event would be triggered there. And then the idea is that a lot of times, IT operators, they have separate people that are doing IT service management. So, we've all probably used a service desk at some point of our career. Right. You gotta go to the Help IT icon on your PC, log A ticket. It takes a lot of time. For a user, and they're expensive. For the business. Right. An average first level ticket today is over $20, so, if you think about a business that has several thousands of those flowing in every month, that's a ton of costs for the business. What, if you could allow your IT operators to not have to go to other tools, right? They could simply kickoff automated ticketing throughout their monitoring console and also be able to close out those tickets as the problems are resolved within one integrated solution. And that's what we're providing the operations teams today.

And it's very key. Again, when we're talking about apps, when we're talking about becoming more autonomous and, you know, improving the way you're doing business processes, this is a very key benefit area. A lot of our customers have seen.

Another key on this topic Foreclose the incident process is automated remediation, right?

So how do we get to State in our environment today? So, we provide an orchestration engine. one of the most robust in the industry today has over 8000 automated workflows, and it allows basically those IT operators that, as they see these redundant task and processes coming up, right? If there's recurring issues on these business applications, that they can go out and employ quickly, some automated workflows, to help resolve these issues. And I'll show you an example here in a minute, But we've got a customer that's that's employing this on a high level in their organization, and they've actually automated over 95% of operator interactions in their environment.

Also, it's, it's important to mention this concept of chat ops. So, what does chat ops? Chat ops is a ability to increase collaboration within your business and IT operations departments, and allows you to use tools like Slack matter most, and Microsoft teams, to be able to go out there and pull some really key and important operational data. So, not everybody always has access to the key monitoring console. The IT users, but they need some of the reports, are some of the data or knowledge management that's coming out of those systems. And chat ops is something we provide, and it's definitely a way to help you improve that end to end process automation and collaboration piece.

OK, so let's talk about a real-world example. There's a large oil and gas tech services company that we work with. that's using our AI ops platform and automation to, to automate this entire detect to correct process, right?

So, to be able to monitor the environment, find the issues, or find that needle in the haystack, then be able to go out, and execute those actions, without having operators manually have to do that. Right? We call this autonomous operations. Or, another term, of course, is AI. AI ops today is what's being used, and, so, here's some of the results that they've seen in just 2019 alone, They were able to automate over 95% of executed actions that were carried out by a virtual workforce. So, they implemented nine bots, chatbots into their IT operations environment, And those bots did over. I think, there was 1.4, 7 million actions executed in 20 19 alone, and those bots. They did over 95% of that load in diagnosing and fixing those issues without any human intervention.

Screenshot (41)That saved them over 107,000 man hours, and I think that came out to about 62 FTEs as what they were shown in their dashboard at the time, and $4 million of cost savings in 20 19 alone. As you can imagine, with oil and gas today, $4 million in cost savings is gonna get the attention of any CIO or CEO, and it's a major beneficiary for the business.

All right, so, with that being said, Jose, I'm going to go ahead and stop sharing my screen, and we can open up to do some Q&A.

Fantastic, Wass, fantastic, thanks for, thanks for us, recovery in the, In the, With all, the storms are going through Dallas, and I'm still getting the, your presentation done, and the really great insights on the i-ops and the all that's going on when the technology world, which is which is really exciting. So, I'm gonna ask this. I'm going to open up for questions here. And there and give some time for the audience to catch up and ask some questions. And I already see some coming through, so I'm gonna, I'm gonna ask. The first one that is coming through here is from Ruler, and the ruled out there is asking what is the upfront work that's needed to clean the processes and process data before you can apply the solutions?

Yeah! So, that's a great question.

So when we're talking about you're making AI ops effective, right. It is truly about the data that you're working with today.

So, a lot of organizations have been monitoring their business applications, and business processes for quite some time, right, so they've, they've got this data out there, right, but I think your question there is, like, how do I take this data and start making sense of all of it, right. It's all flowing in from disparate systems or domains.

And, and that's what this concept of i-ops is really helping to do, is that you're able to start centralizing that data in a, in a centralized data lake or data store, as what we're talking about here, that can ingest and analyze all that data in real time as it's flowing in. So I would tell you the first step, if we if we can. If you'll remember on that, maybe that first slide that I showed on the five processes are five steps The Enterprise management associates highlighted.

The first one is to be able to get all of your monitoring data, or your business process data into one place. So that would, I would tell you, that would be the first thing to do. And you want to make sure that you've got a data store or a data lake that has the performance capabilities, and scalability, that as this data continues to grow in your business, it will be able to handle. Right. We're not seeing any slowdown of data that's flowing in. And it's only going to become more robust. So having that centralized data lake, and starting to explore that for your organization, I would tell you, is probably the first step that you want to do, and looking at making that more effective.

So, that's very good. And another question, just as a follow up, was how do you how do you decide where where to start. You know, if you have kind of some sort of ideal scenario aware. Because implicit on, that question was that there was a lot of time that we have data for things, and the red, the underlying processes for that is a mess. So, the quality of that data, the quantity, maybe they're, the quality may not be so good. So, I'm curious from a, like, from an AI ops perspective coming into an organization where where would you find the best applications of AI ops, if maybe I'm starting the journey? Maybe prepare myself. Where would you point AI ops in the beginning if you can talk a little bit about that process?

Yeah, so, I think AI ops really the key, the key users of AI, ops, the, the beneficiaries are all over the business, right?

But, the key really users or the orchestrators of AI ops or is going to be your IT organization and specifically, IT operations management, right? So, it's those cruise in your organization that are managing the critical business infrastructure, right? That your business applications are running on.

And, and what we talked about, their Jose's, That first concept, right, is, I guess the first place you would start, right? Is, you need to be able to know what's in your environments, right, to know what business services or applications are in the environment. Collectively, IT has to know, they have to have visibility and all of that stuff, right?

If they don't, then when there's application outages or service outages, they're not going to be able to go out and fix those because they don't know what's happening, right. So that process, Discovery slide, I think it was one of the first in my presentation today. That's really where it starts, right? With IT is they've gotta be able to go out and discover what all's in the environment, what what all applications we have. And then be able to monitor those environments. And then analysis is, what kinda helps to drive and make those environments smart? Does that make sense from a high level?

Yeah, absolutely, absolutely. Lots of extra questions coming in, So I'm going to try to Furniture Kit bump on the Bay C and cover as many as possible. I'm going to take the next one from Mark McDonald here. So, he's talking about what is the impact of external influences that? Impact the processing environment. And the, for example, the covert impact on health provider patient interaction, going from physical to virtual, Does this require a significant change to AI Ops? How does how, how do you flex AI ops when their shifts like that? Yeah, so, that's a really good question. And AI Ops has played kind of a key role for a lot of companies and how they can handle this whole surge and remote work.

3-Jun-30-2020-08-31-08-88-AMSo, really good question, And we've actually been addressing this quite a bit recently in our industry, is, Hey, we've got a ton of our workers right now. Like, 97% of people, I think have been working from home recently. I know we all are.

And so, what business leaders and IT operations leaders are saying is, OK, how do I make sure that all of these remote workers have access to the business applications, that they need to run every day, Or their business processes? Whether that Salesforce or Microsoft Teams, or they need to be on a VPN. Right. Being able to monitor the status of VPN in itself is huge right now for companies because, you know, most people were working in the office now. they're working remote, they're having to login through those VPNs and they're being overloaded. So if anything, AI ops is really going to help organizations to pivot as we move forward.

You know, what we're seeing through all of this right now is, Yeah, sure. During ..., 19, over the last 4 or 5 months, a lot of us have been working remotely, but I think what a lot of organizations have seen is, Hey, we can You know, we can save cost through this. We can evolve our business if people, sometimes they are working more remotely. And what IT operations is now looking at is, OK, so, now that this is kind of becoming a permanent thing, let's start looking at apps more effectively, because that's what provides analytics on top of what you're doing for monitoring. And it can help you to automate process remediation, right? So, as problems occur in those applications, let's say that teams goes down one day. Or you get back like, a bandwidth issue. Like, I've got right now with all these, you know, storms, the rolling through, that you have, the ability to go out and to help automate the recovery of those processes. And another thing is, to Jose.

A lot of a lot of IT operations teams today are working remote to. Right. They're not sitting in the data centers right now. So they need the ability to have that central console that we were just talking about, and be able to look at all that data collectively and automate processes. That's really important.

Good, very good.

one more, at least one more question, here, that we have time for, Cameron .... She is asking some good specific questions here. This is a good, because there's a very practical questions so he's asking can you give some more specific examples on the types of incidents? The chatbots are able to do the triage and solve the problem? And then before you answered that, he follows up saying that, if you have ServiceNow ... work with a sass solution like ServiceNow, and I'm not sure if you have, or if you're familiar, you know, in court. But a, two part question. The first one, is that the examples of chatbots able to triage and solve problems? And then maybe a bit of a connection of AI ops with ServiceNow.

Sure. So, with chat ops, I'll start with that one, so, chat ops, right?

Bots can be used to go out and do some basic commands and reporting, right? So, if I need to, If I'm an IT operator, right? And I want to see maybe what's happened on a specific business application in the last hour, what event data, what log data, what metric data is flowing in from those events, and maybe maybe you I want to get performance threshold data. Maybe I want to see, OK, what's the current load that's running on those applications? Maybe I need to be able to see.

Maybe I need to be able to run some reports and get that information to me readily pretty quickly. Right. That's what chat bots will allow you to do, is to pull information quickly. It also allows for the non traditional IT folks that use, you know, popular collaboration tools, that they can access those bots, right, through like Teams or Slack or matter most. And, they can, you know, grab some of that important. Maybe it's their business application they're concerned about, right? So, if I'm a line of business, you know, person and I own application, maybe I use a chat bot to go out and pull some of that data, and I can report that up to my chain of command.

The second one, I think, was about, so what do you do about, like ServiceNow integration with, with apps? So, that's a good quote, are a great question.

And we, we work with this all the time, so, micro Focus, we integrate with ServiceNow, we integrate with BMC Remedy and shareware, and those are all third party service management solutions that are popular in the industry today to do what we called that closed loop incident process management, right. So, we have a lot of customers that use our AI Ops, or our monitoring console with Ops Bridge, and they will integrate that with Ops Bridge, with ServiceNow, to do automated ticketing, right. So, as a problem comes in and their Main Operator console, they can automatically notify the Service Management team that, Hey, we've opened a ticket for this, and we can even automate the process to win.

That problem is fixed, that it'll close the ticket and ServiceNow, we do it with our own solution, we have a service management automation solution, as well, but hopefully that that answers the question as well.

Screenshot (4)It does. So, as it does, was fantastic. I mean, we are up on time here, but thank you so much for sharing this wealth of information with navigating all the technological challenges that we had. The Senate still provide such great insight and onto onto this leading edge technologies that are being incorporated into Intelligent Business Process Management today. Well, thanks for having me, Jose, again, all apologies for the interruption, but thanks for sticking with me, and definitely, I was glad to be a part of it today. Thanks so much.

Thank you, Ross.

See you later. Thanks guys.

Ladies and gentlemen, we are going to wrap up the session now, and our next session will be with Mark .... He's a senior director of Operations Solutions for ..., and he's going to talk about very great applications, real practical applications of intelligent BPM in manufacturing and many other areas equivalent areas. So you do not want to miss Michael's session. We're going to start that up at 5, 2, 5, 2. At the top of the hour. We open the session up at around 5 to 10 minutes before the top of the hour, and fill out the survey as you close out of this session, and we'll see you back soon. Thank you.

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About the Author

more (14)Wes Cooper,
Product Marketing Manager, Operations Bridge,
Micro Focus.

Wes is Product Marketing Manager for the Operations Bridge at Micro Focus. He has 6 years of experience with Micro Focus and HPE in product marketing, global enablement, sales and business development all within the IT Operations Management market.

He is a published author, 4-time marathon runner, and cycling enthusiast. Wes is based out of in Dallas, TX.

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