 Yeah, thanks again for the nice introduction there and hello everyone. I'm excited to share the some of the walmart's initiatives that we are doing internally, and in this great forum. So but before that, I just want to kind of say introduce some of the cool things outside of the technology walmart is doing. So I'm quite sure that many of your aware of the walmart name, especially in the US because it is within 10 miles distance for 94 90% of the US population. So, some interesting facts about walmart supporting communities. We have seen code 19 kind of bothered us for the last two years and it was painful. During the pandemic walmart work closely with federal governments state governments and insurance companies and labs who expand the testing, like so that we can do more testing for the more people. And we did testing for hundreds of thousands of people in walmart stores, and walmart's pharmacists did the vaccinations and vaccinations were available across 5100 locations in across the US. And walmart and walmart foundation, they contributed to the coordinate in cause and donated $43 million around the globe. And this money was in cash and in can donations to various organizations involved in the communities. And apart from that walmart also donated $1.4 billion to various other causes. And again one more 745 million pounds of food was distributed in globally 2020. And out of that 627 million pounds of food was donated by walmart stores clubs and distribution centers. I was excited about those facts and I wanted to share with the community. Walmart is basically a retail store retail business but we are increasingly growing into e-commerce and then online shopping and walmart is constantly innovating and then trying to find ways to serve customer better. Some of the things are like drone delivery. We are trying out drone delivery in the Arkansas some places, and it is in partnership with drone up. And we're also using driverless trucks between our walmart stores and then the distribution centers. This was also in Arkansas, and we are partnering with Gothic on that. Some places we are trying it's not like everywhere yet. Walmart is also into blockchain space where we are using it for the finding the contaminated food sources fast. When and if that happens contamination of the food. It is extremely important for us to make sure that we find the source of it quickly. This is to kind of control the impact and then also saving the restage. Earlier it used to take seven days for us to find the source of the contamination and that with the blockchain usage as part of the in the in our systems. Now we can do it in a couple of seconds. So it really helps a lot in finding the contaminated food sources quickly. Now, coming to the technology. Walmart uses open source extensively across the stack from top to bottom. And Walmart is from the even from the leadership side, fully committed to the contributing to the open source, and we are kind of started more activity there. And one example is the leaf platform leaf platform was open sourced last year. Actually by our EVP Kobe Avetoh in this Linux Foundation conference. This leaf platform is a complete life cycle management of EVP of programs. And there are lots of goodies with it, which is like it is cloud agnostic and then it can do cool program chaining and out of the box monitoring runtime configurations we internally in Walmart. We are using it for various use cases. Some of them are like security use cases we use it, and observability, we can get a better observability from a BP of them layer seven. And we also use it for the traffic mirroring traffic splitting and then package prioritization, there are very many use cases we're actually using the leaf in Walmart. Now it is shared with the community. So the packages. Our plan is to also increase our open sourcing when it comes to EPP of package repository. And there are many components that we internally have we are planning to open source them with a plan. And our request to the community is to join us and build the help building the great EPP of package repository. One step towards that open sourcing is XLB. XLB is a EPP of based load balancer. We are replacing our level four load balancers in our private cloud with the XLB activity. And this XLB is built on top of that run and EPP of on top of it we have the configuration. Metrics management and health checks, et cetera, we build a lot of functionality around it and made it a lot more futuristic. And coming to the application node side, we use an agent there, and with a DSR functionality. DSR is a direct server return. This means that whenever the application sends the response back to the client, it doesn't need to go through again XLB it can directly go to the client. So that helps in latency improvements. And we also package that application node usually with the chaining couple of more models. In this case rate limiting and connection limiting along with the other stuff in the ELB agent. This helped us kind of protecting the nodes from unwanted or unexpected traffic coming into the nodes. So it will just try to make sure that the resources are not overwhelmed beyond its capacity. So these things, if you look at it it is not really the just load balancer it is more about extended load balancer features. So this one XLB will be open source soon. We are doing some efforts towards that and it will come probably in few weeks. And on the edge computing side, Walmart is constantly looking into the opportunities for edge computing. And one of the things that we did last year was queuing queuing was completely implemented in the CDN edge layer using the computer. And other features there. This really helped us handling the peak traffic and in super peaks. And last holiday season was well run. And that's one of the reasons is because of we put queuing there and protected where it is vulnerable. So the problem that we wanted to solve is we have sales. Sometimes on the special items, maybe they are new or they are in super demand. Whenever we announced those sales. We see tremendous amount of traffic coming to the our site when the sale starts. So the problem is when so many people coming for this item, we see 50 x 200 x normal traffic during the, the time peak time. The peak goes very sharp. The ramp up time for the peak is very quick in seconds. And then it won't last the peak doesn't last for long and it will quickly come down to reasonable levels within a few minutes. But the problem is the peak is 50 to 100 x high depends on what the item is. So this kind of problems cannot be solved by using the traditional prescaling, because we are talking about several x and it's not practical to when we are thinking about 50 and 100 x. We don't it's not economical and then practically there. So that's not a solution. And then there is another thing like maybe what about auto scaling. The problem is, in this case, what we saw was the ramp up time is few seconds. It just quickly goes up. And the overall peak time doesn't last long. It will be for a few minutes only. So this is a problem we cannot solve by auto scaling or prescaling so we came up with the solution, the queuing solution which is basically built with Walmart specific components and then just tightly coupled with a lot of systems we had, but we built it at the edge and the Syrian edge so that that peak traffic doesn't come to the Walmart network. So we, we successfully handled and stop the customer at the edge, and then allowed some control traffic to the, our notes based on our capacity and then whatever was the plan. So this one really worked out well for during the last holiday period. And this is this gives a general perspective on how the chewing from customer perspective. I can go into more detail so I just giving this whatever is makes gives a better understanding. And then the customer likes to buy a hot item that is on sale. They click on the item, and then they go through two phases in the queuing experience. One is the waiting phase, another is the purchasing phase. In the waiting phase customer will know like what is the possibility of getting that item so that will be some kind of message. This timer tells how long they have to be in the waiting phase before they go to the purchasing phase. So this when customer time times out on the timer or their turn comes, they go to purchasing phase and the purchasing phase we give another timer so that the customer has enough time to check out. The important thing is when customer is in the purchasing phase, we make sure that that item is allocated to the customer and then block for them so behind the scene whatever is needs to be done on the application side, we do that. And this purchasing phase has timer when that expires it releases the item, if the customer does check out before that then it will be successful. So this purchasing phase is just like we can say, keeping a physical item into the physical cart in a physical store just like that is with you until you check out. This itself changed a lot during our sales because this has given a lot of power to the customer to kind of not to rush and then try to compete with other users on the web. This is more about they can do more peacefully on this shopping. So this is all implemented on the CDNH and we eventually might even take it to further down the lane but that's at this point that's how we implemented it. How this helped Walmart, it helped both customers and then the business. It's a great customer experience because we got a lot of feedback saying that earlier the sale used to end very quickly and within few seconds and mostly it is bots or some other things by them and then real customer work kind of very painful. They always get to check out and then get a error there. So customer experience improved predictable buying in the purchasing phase. They are guaranteed the item and customer has a full flexibility where they can join more queues where there are queued items. Or they can drop out the queue and then give up on their own wanted, or they can just drop something else. So customer wise this gives a lot of value there. On the business side, it is a control info scaling because when we are talking about 50x100x which is not practical. We could handle it very well and with a limited scaling that is what we plan for and then make sure that funnel is allowing that much. So the real time inventory check every customer is kind of associated with the inventory item when they check out. So there is nothing like we ran out of inventory at the end of checkout. So that was really helpful. And we sold to the real customer we tried to we put best efforts to filter the bots and then this is a constant cat and mouse game. So it was successful says we ended up with and we ended up with happy customers. So yeah, that's all I wanted to share. And these two are interesting projects. So we finished recently and wanted to share. Thank you. Very nice. Great, great stuff, Ravi. I mean it is amazing that if you can stop sharing. Yeah, there you go. It is amazing that from, you know, what, what retail has gone through and what happens behind the scenes we're so excited that Walmart has become, you know, a tech first company. And, and more importantly, you know, using open source as pillars, there is one question that has come up from the attendees and again, you know, please ask Q&A on the on your Q&A box will answer live as much as possible. Given that you have multiple stores in distributed location and your edges getting enabled. Are you thinking of becoming an edge of this provider now you don't have to answer it because it's a strategic question. I think that is fairly interesting. Yeah, you said is right. I think I can't answer that. And yeah, I don't know. This is a tough question. No, anyway, good. No, but we really appreciate the, the leadership. And, you know, we've seen ebpf and leaf specifically grow significantly in the community in the open community. And especially, you know, it, if I understand correctly, it, it was able to withstand the onslaught of the heavy Thanksgiving after Thanksgiving sale, you know, and the Christmas sale so congratulations, you know, open source works. Thank you. Thank you for the great keynote. Appreciate it. Bye.