 All right, thanks for coming and my name is Carol Chen. I'm going to give a presentation about Managed IQ. This is, I think, the last session for the day for this track. So I thank all of you for being here and also for Force Asia for accepting my talk. So I have the chance to be here to speak to you. If you notice, probably there's another session supposedly after this on Managed IQ integration with Ansible, which was supposed to be delivered by my colleague Daniel Korn, but unfortunately he had a family emergency and was not able to make the trip at all. But I hope I could just give you an intro to Managed IQ and maybe at future events we'll give you more detailed presentations on the different integrations with Managed IQ, which you will learn is a very powerful tool. Doesn't it? So what does Managed IQ do? As you saw in the previous slide, it's an open source management platform and it has the ability to discover, control and optimize your hybrid environment. I'll go into more details about what each of these mean in the future slides, in the later slides. But first, a brief history about myself, an intro about myself. My nickname is Cybert. That's probably the easiest way to find me online because Carol is quite a common name, Carol Chen even. So if you just search for Cybert, most of the stuff should be related to me. So I was actually from Singapore, I mean I lived in Singapore for 14 years, but I left in 1996. So it's a rough idea of, okay, somebody's protesting. So that was almost 20 years ago, or more than 20 years ago, I left Singapore to study in U.S. And after I graduated, I joined Nokia Dallas in Dallas. And when I was working for Nokia, I kind of got acquainted with some open source projects, one of which was Helix. It's a video engine. It's a cross-platform video engine. I was working in the multimedia department. So I kind of got interested in the open source way of working. But it wasn't really until later on when I left Nokia and got more involved in community events and kind of, if you know me, go, which was like the joint effort between Intel and Nokia for open source internet devices that I got really more acquainted with, you know, the open source community, ways of working and collaboration. I really got passionate about all it stood for and the way it encourages participation and innovation. So after leaving Nokia, I joined YOLO. I'm not sure if anybody has heard of that company before. Okay, somebody pointed there. It's a startup, a mobile startup that kind of based some of the stuff from MIGO using the same Mercor and created our own operating system called Sailfish OS, which is, you know, it's a Linux-based mobile operating system. And, you know, it's really like efficient for mobile phones. And so through that, I forgot to mention I was a software engineer in Nokia for like eight and a half years. And when I joined YOLO, I went into more like community outreach and developer engagement type of role. So that's also similarly what I'm doing now in Red Hat, which I joined last year. And so here I am one year after that. Now in fast Asia, speaking to you and back in Singapore, one of my homes, I have like four different homes. I'm very happy to be here. And more of an unrelated note, I also play in an orchestra. So that's kind of like, I always say if I've never gone into this industry, I hope to be like a full-time musician somewhere, but that dream probably will never come true. But, you know, it's a side hobby project, whatever. So now enough about myself, here's kind of a history about managed IQ. So managed IQ actually has been around for quite a while. It was founded in 2006. I should probably get more information from the founders and one of some of the engineers who has been in the project for a longer time to learn about some interesting stories I can share at talks and events like this. But kind of the key dates are when Red Hat acquired managed IQ in 2012. And then of course, you know, Red Hat being an open source company. They, you know, got the code into shape and all the licenses in place and open sourced it in 2014. Anybody besides Red Hatters know which Red Hat product is based on the managed IQ project? Thank you very much. We've all done cloud forms. So, similarly, you know, like Fedora versus Ralph, Oveert versus Ralph. So managed IQ is the upstream open source version of Red Hat Cloud Forms. So you can see some of the kind of milestones. And one of it, which is the first design summit we had was, oh, actually, I don't have the date here. But it was in 2014. And we had the second one last year. I helped organize it when I came on board. I'll have more information about events and stuff at the end. So it has been where I've been trying to, you know, build up more community involvement and hoping to get more people interested in the project. So even though it has been only kind of open source quite recently in a couple of years, two and a half years. But it has, you know, getting already a lot of contributions, of course, mainly from the Red Hat engineers who are working on the project and for the Cloud Forms product. But also we have different partners in the community as well helping us. So recently we have also been splitting the repo, the main managed IQ repo into sub-repos because it was kind of, it was growing quite a lot with different providers, different new features. So it got to a point that it's not very efficient and it's very just a monolithic thing and we want to kind of make it into a more platform thing, plugable and modular. So things are more in the process of being more modular and the UI has been split out, different providers are in the process of being split into their own repos. And we found that actually when this is happening we're getting more commits, more PRs, more activities because the velocity got increased as the modules are smaller and more manageable and they have their own tests to eat and services, so things are also more efficient. So talking about the partners, some of these here are some of the partners that we have worked with to add capabilities into managed IQ. I won't go into the details, it's just some of the companies. So this is a high-level architecture diagram. In the nutshell, managed IQ is what we call a manager of managers or if you will, a meta-manager. It does not replace actually some of these element managers you might be familiar with like VMware vCenter, Kubernetes where you manage container clusters and so on. But what it does is it creates API connections to the different element managers and then it gets the information through this API and then creates this unified view or dashboard that you can see what's happening to the different providers and different elements. Another view which kind of gives a better picture of all the different types of providers we support which is not just clouds, so for the longest time we say this is a cloud management platform but it's really not just clouds, it's also like from middleware to containers to software-defined networking and storage. So each individually have the API connections to manage IQ and through the managed IQ interface you can drill down to the different levels and get more information, get reports, check the resources utilization and so on and so forth. So we can start with one of the features of managed IQ which is self-service. So what it does is through a service catalog you have different configurations and users can just select what they want and submit the request and while service request management is nothing new but the key things are automated. Previously maybe like with a manual fulfillment of the request it may take days for somebody or even up to weeks depending on the system but with the managed IQ we have this workflow orchestration process which helps to automate all this stuff and it will just take tens of minutes to come back with the resources needed to fulfill the request. So that definitely speeds up things, makes things more efficient but that's not sufficient. What happens when the resources are done with, what do you do with them? So we also have full, that's why we say complete life cycle management where you define the rules, what happens, certain time frame or certain conditions where you have to retire the resources that you deployed. So that's clear ownership rules, how to go about managing this for the retirement phase. So this is an example of a service catalog where you can select whether you want Amazon deployment or REL or Vmware and then you can select even multiple, you don't have to get one implemented deployed wait for the next one and so on because there's this shopping cart functionality where you can just select multiple or select all and say I send one request for all of them. And then the automated provisioning happens. So Managed IQ will provision everything configured according to what's specified in the service catalog and regarding provisioning, the automation part, there are two ways to do it. Previously the main way is to use the native Managed IQ which is writing scripts in Ruby and this may not be for everyone and it's kind of a very involved process and quite complicated. There's even a thick book written just on this automation topic but with the recent integration with Ansible which I think a lot of people are familiar with you can actually use playbooks to automate some of these stuff. But there's a choice, you can do it either way, whether natively or with Ansible. One of the other key features in Managed IQ is what we call continuous discovery. So what this does is that once you have connected a certain provider to Managed IQ it will continuously check the resources, discover the inventory and the relationship between the instances and gather all this information. And also when there are updates it listens for them and then it will reflect those updates in the system as well. So tracking all this data and configurations over time which will help with also later on we'll talk about root cause analysis because you have all this history of data. And to go more in depth we have what we call smart state analysis which has a nickname called Fleecing. If you know Fleecing like Fleecing a sheep you pull back the wool you expose some stuff but in a non-destructive way. So instead of just getting the metadata like the names of the VMs and the hypervisors they run on you're also getting the types of apps they have and the types of user accounts and things like that more in depth information. So with lifecycle management you basically get the visibility and control of the instances over their whole lifecycle from their history and you can clone the instances or migrate them from different providers and retire them or even suspend them the power functions shut down, suspend and so on. So you have access to all of that. So talking about the root cause analysis because Manage IQ gathers and tracks this performance data and configuration information over time so with this history information if something changes you can pinpoint when it happened and what changes caused it to happen. And with detailed these topology graphs you can see the relationships between the VMs which ones they are being deployed from and so through that you can also again go down into the layers and see what were the underlying issues and solve the problems through that. So not just problems and finding out information that way but you also want to optimize the system and again because of monitoring and tracking things that have been utilized, the resource utilization Manage IQ can use this information to kind of get trends and then predict future usage so you can suggest like maybe you can for this you can deploy things, instances of this size so you can better utilize all your resources so in this way you can optimize the system. So policies again with all this information drawn from smart state analysis you can define policies in two ways either across all the environments that you have for example you can say all the users across all my environments will have this type of access or you can say like okay firewall access so for production environments I want this set of rules but for development environments they are more permissive or something so you can enforce different policies for that and with resource utilization you want to find out for example this user how much he or she is using and this platform what type of usage is being consumed so you can rates apply to compute, memory storage network and you can use this information and get charged back and show back data which is show back is just reporting the data and then also monitor the usage if somebody is using too much figure out if you want to have some rules against that or charge them more so all these cool features of managed IQ but what platforms of what providers are supported well traditional virtualization platforms like VMware like Microsoft Hyper-V like Oveert which is the open source version of ReHat enterprise virtualization you can provision VMs and all those things we mentioned going to smart state analysis of the VMs and so on of course clouds have cloud management platform Google Cloud, Microsoft Azure, Azure how do you pronounce it and Amazon and nowadays containers are being used everywhere we also have full container management through OpenShift which is another product supported by ReHat and we have advanced containers scanning and you can check for vulnerabilities and making sure everything is secured so I think that's the overview of the features more about the project itself managed IQ releases are roughly in the six months, six to eight months well actually for the past four releases about six months cycle and we named them alphabetically Anand, Botvinnik, Kappa Blanka, Darga and Elva who knows what's the relationship between these names great, alright so because one of the founders of managed IQ is an avid chess player and so he named other releases after chess masters Ops, went too far and actually our next release will be named after the American grandmaster Ruben Fine so we're going to have a fine release coming up and I think in a week or so we're going to vote on the name of the G release so if you're interested check out we'll have links later on on the website when is the voting taking place and cast your vote you can get to name our next release so as I was saying previously about the first summit being 2014 so last year we had the second summit and you can see we have a crazy bunch of people fun bunch of people and we even have a chess somehow going on by Oleg who is our chess master so what chess somehow means that he goes one player to the next one person playing nine people at the same time and he beat them all so yeah it was really fun I guess that's one way we party and also there's this hallway track which as you know in conferences that's always sometimes even more interesting than some of the presentations although I think this one coincided with the coffee break so more events we have actually quite a lot of recently more and more interest about the project so we have been getting requests and also people have been just kind of organizing meetups to learn more about the project or you know work on it so here are some of them and if you notice they are mainly in Europe for now and we have some in the US as well and like the manager I could summon it was in the US last year and the two years, three years ago but we are also hoping that we get more interest in Asia region Asia Pacific region and we can have more events in these places as well actually we were in Picon, Pune last month was it last month because some of the QE stuff is written in Python so that's kind of related so maybe there will be more okay so we are trying to come up with avatar or mascot for the project and remember what I said about the nickname for smart state analysis anyone? yes thank you so if you might see a bit of relation with that but it's funny because we had that design for our last year's Red Hat Summit and somebody called it a bunny goat because it has long horse or years that make it look like a bunny and it has a sharp face which looks more like a goat than a sheep I don't know but it kind of also go with the whole hybrid theme I guess but we have been having some interesting designs by some of the community guys so just saying that sometimes contribution to an open source project is not just about coding but just different ways of participating because for example for myself when I first learned about project I was very overwhelmed because it's a huge platform and it's written in Ruby on Rails which I have no idea about because even though I've been an engineer for a while I've never touched Ruby but still up to today I don't really know how to contribute code-wise but there's many ways to be involved in the project so I hope I've given you an overview of what the project is about and how you might if you're interested to collaborate or connect with us so just basically remember ManageIQ because even though I list all these URLs over here it doesn't really matter the main thing ManageIQ.org you can anyway connect to most of these channels we have of course GitHub account and the Gitter is our chat pool of choice I don't see it anymore nowadays but Gitter is anyway tied to GitHub account I think GitHub as well we didn't get that much of them recently yeah exactly so you can use that talk it's our kind of forum and all these social channels and if you want to reach me again Cybert, just Google it so I think that's about it I'm in my own time well right on time so any questions, feedback if not I have some cool stuff here I have bags, I have stickers I need to find them in my bag and some microfiber cloths which are useful for cleaning glasses and phone screens and stuff like that so come on and grab something and thank you for your time