for organizing this for us. So just to get started, just a little bit of housekeeping on our side too as well, before we start talking about the, or get into the presentation itself, is that how we're going to present the topic today of bringing transactionality to the streaming ecosystem is really to talk about a specific use case and then relate that to the evolution that has happened through the streaming ecosystem and the different architectures that exist out there today. So, because it's always best to really understand it from an actual implementation and usage of the system. So that's why Raja from Alpaca has joined us today. He's going to be talking about their order management system and the journey that they've taken from going from their initial implementation of the order management system to a version built on top of a streaming system that is giving them a huge amount of performance benefits and things from that perspective. So Raja is going to take us through their initial implementation of their order management system. I will then talk a bit about the different streaming architectures that we see out there today and that we commonly see across a number of different environments. I'll then also be talking about Red Panda itself, which is a streaming platform that's really focused on low latency transactional type workloads. And then I'll hand it back over to Raja to talk about their order management system that they built on top of Red Panda and then he'll be giving us some real performance results that they've seen with this new architecture and then we'll open it up for questions and answers after that. So without further ado, I'll hand it over to Raja to start talking about Alpaca. Thank you, Roco. And thank you to the Linux Foundation for hosting this session as well. So just to start off, I just want to explain a little bit about what Alpaca is. So Alpaca is an API-first stock and crypto brokerage platform and trading platform. In late 2018, we started off with a trading API which allowed people to trade programmatically via a RESTful interface. To date, we've raised just a little over 70 million in funding. We trade a few billion dollars per month or a couple hundred million dollars per day currently and that's been growing at a very steep rate. It's entirely commission-free and really what we're here to do is provide ability to empower developers no matter where you are in the world with really easy and friction-free access to all financial markets. And in the near future, we'll be expanding past U.S. equities and crypto into other asset classes as well. So at the heart of a brokerage or a trading platform, there's the order management system. Basically anything that touches a trade or touches an order passes through the order management system. It's primarily responsible for validating the order, ensuring that the account state aligns with the order and then finally getting the order to market or routing the order to market. We, as I mentioned in the previous slide, we are currently trading billions of dollars a month for the system and it continues to scale. So one of the most important things, especially for a programmatic trading application and we have a very large algorithmic trading user base as well is the processing time. So the quicker that we can process each order, the better it is for our customers and the data backs that up. The reason why that's important is that a lot of trades or orders are very time-sensitive in nature as the price of the market moves. So if someone is algorithmically placing 1,000 orders at a time, if it's taking a very long duration, by the time they get to the back of the queue of their orders, they might have missed the mark on what they're trying to trade at. So processing time is a huge parameter. So to step back and just level set on the previous order management system, I just want to explain exactly what we were working with. And truthfully, the first version worked pretty well, but we knew that we could do better. So the V1 of our order management system was essentially a singleton. We happened to be a go shop. So the way that we built our order management system, we would spin up a go routine per account and that go routine would handle the orders on a per account basis. Now, this worked fairly well and truthfully scaled pretty well, but it didn't quite have the throughput nor the reliability that we were looking for. So one, it was a single point of failure. It was a single application running on a single pod. So if there was any sort of failure, we'd actually have quite big delay in the time it took to restart the service. Secondly, the state lived within a relational database as well as some other services. So often for each order, for all these validations that we had to do, we were performing several network round trips. And finally, we noticed a lot of contention, especially at high times of volatility, such as the market open, where a significant amount of the trading volume happens within the first 30 minutes. We were just hitting some of the contention what RabbitMQ's throughput was able to do as well. Our P95 for this system was around 150 milliseconds, but sometimes during extremely heavy volatility, such as a week like we're having this week in the market, we would see the response duration as high as 500 milliseconds or more. So thanks so much, Raju, for that initial overview of your first approaches to the order management system you could think of this as being sort of a very simplified diagram of that type of approach, which is something that's been common for quite some time, which is that you have an application that is open either via API or other services to a set of users. And then you're pushing this data into an MQ system or enterprise service bus. Things like TIPCO, MuleSoft, enterprise service bus were pretty common. RabbitMQ is still very common, things like ActiveMQ too as well. And then this was really beneficial because you could easily then link it into a number of different services behind the scenes. So you can push data to a transactional database to have sort of your current state of what the system looks like. You could also push it to a data warehouse to have your sort of change log of all the things that occurred for a customer or kind of a change history for everything. And then you could also link in other different services as well. And this was a nice or kind of that first sort of step of like decoupling services and having a service oriented architecture that we've heard from some time back. The challenge with that architecture though was that it didn't scale just to the same point that Raju was talking about is that once you do sort of hit the maximum throughput that you can do in a single instance of a system like that you have to start thinking about sharding and then you have to do a lot of that management yourself and it becomes very cumbersome to actually work with that type of system. So what most people have moved to and Raju, I think you guys even looked at this at one point in time as well using a database as sort of the front end are kind of like the main sort of source of record for your system too as well, is that right? Exactly, yeah, we did explore the change to capture pattern but ultimately it wasn't performant enough. Yeah, and we see this quite often as well where because of the challenges that we've seen with these types of MQ systems when they hit a certain level of scale is that the first approach or kind of the next approach that people lean towards is using a database as a replacement for the queue. And it can definitely be done. There's ways to work around it. There's different design patterns that can work but ultimately these systems are really only meant to keep sort of the current state of the system itself and actually keeping changes can be pretty burdensome for these types of systems. And also it becomes very challenging trying to implement a queue in a system where you need to be able to have indexes and other things from that standpoint. I've worked with a number of databases myself in the past and the number of times I've seen somebody put an index on a last modified column or created at column. I've seen it too often to count and those are really big bottlenecks in performance for these types of systems unless you're hashing that particular index or you create a hash index on it but then if you're doing a hash index you're very likely going to have to talk to a large number of nodes to be able to do any type of ordering based on that index as well. So it can be done but it definitely has some drawbacks and then still even taking that approach you still wanna have a log of all the changes that have occurred and also to create actionable events from that data. And to do that you have to use another piece of software a change data capture software like Debezium and some databases have this built in to push the data to a streaming platform like Kafka. And I put Kafka here because it's sort of the most prevalent streaming platform that's out there today and there are a few different alternatives out there like Pulsar, Nats and other things but Kafka does make up the larger majority of the market in this regard. So you have changed data capture going into something like Kafka and then you have a number of systems off of that pulling data to either fill in a data lake maybe you have some stream processing happening you might even have other services that are taking actions from that data as that comes in maybe they're executing other services or updating other systems or calling other like partner APIs or other things from that perspective. So this is the kind of current state of what most solutions look like today and you might ask yourself, well, why can't we just take Kafka and sort of replace in what we saw in our previous slide the MQ system, the enterprise service bus why can't we just replace that with Kafka and you kind of call it a day and to really understand why that isn't an approach that is gonna work for most people you really have to understand the assumptions in which Kafka was built upon and to understand those assumptions we have to really look at the history of Kafka and so to look at the history of Kafka we have to look back in when it was first developed it was developed at LinkedIn the first release came out in 2011 and it was initially really focused on shipping logs from web servers to a Hadoop cluster and you probably updated it or you probably put it in a Hadoop cluster and you were doing Hive queries on top of it and those Hive queries would run for 12 hours or for however long that they would take so as you can imagine, latency wasn't super critical for these types of use cases and throughput was much more critical you had a huge amount of logs and you needed to get them to this large centralized system so for that they really focused on building the system with throughput in mind and not so much latency and then also if we look back at 2011 and we'll take a quick look at like whether the state of the art systems looked like back then they also had to work around the hardware that was available to them so one of the ways they did that was by using something called the PageCache the PageCache is something that's provided by the Linux operating system that allows you to cache files into memory outside of the actual process itself and this made a lot of sense for Kafka back then it was definitely a good choice for them to make because running a Java process with more than 16 gigs of memory or 32 gigs of memory was probably not advisable because you could have large garbage collection pauses occur within the system so trying to keep the heap size of your Java application small in Kafka's built on Java was actually critical for back then so being able to actually give off it or give the responsibility for caching data to the Linux kernel and the Linux OS made a lot of sense the challenges with that though is that you don't get a lot of control over how data gets flushed to disk you can specifically tell it to sync to disk but Linux or Kafka by default would just allow the PageCache to flush on its own default schedule which is currently today in most operating systems 10% of system memory becoming dirty before you start flushing to disk so this could be a lot of data that sits in memory that's not actually persisted to disk quite yet and that made a lot of sense when you were running on fairly slow spinning disks that didn't have a huge amount of IOPS or throughput available so this is why they delayed writes to disk by default because then they could actually have larger block sizes so you could write 128 kilobyte block of data to disk and not have to try to do like 16 kilobyte blocks or four kilobyte blocks to disk it's Kafka is mostly written in Scala on top of the JVM and has used external systems for consensus so it uses a zookeeper which a lot of projects have relied upon zookeeper for external consensus and Kafka is a great example of that where they keep a lot of cluster state information and also use it for consensus and membership coordination of the cluster too as well so let's talk about what did the hardware look like back in 2011 what was sort of state-of-the-art back then and it's always interesting to like go back and look at the Wayback machine and I actually went to like Dell's Wayback or to the Wayback machine and looked at Dell's website just it was a little bit of nostalgia to see what was actually available and this was the typical machine that was recommended for running map reduced type workloads and also Kafka clusters typically and as you can see this is a system that can handle at most 12 cores you most likely probably were running with eight cores at the time and then you were most likely running with a larger number of two and a half inch or three and a half inch SATA drives running at 7200 RPMs and just to give you an idea of what the performance of that looks like down below you can see what the right performance looks like for mixed and sequential workloads so sequentially I could write at about 82 megabytes per second and in a non-sequential write I could do it at about one megabyte per second so doing things or caching data into memory and then doing sequential writes of large blocks of data made a lot of sense for this type of workload that exists or for this type of hardware that existed back then but things have changed dramatically we don't normally go to Dell's website and look at what type of hardware that they have available today we're going to the different cloud providers and looking at the instance types that they can provide us so for AWS they just recently announced some of their Graviton two instances that are very impressive from their overall performance and price standpoint where I can easily get something with 32 cores or 32 vCPUs and the ability to write four gigabytes per second and also have a 50 gigabit connection link the other thing that I didn't really highlight in that previous state of the art for 2011 is that you were typically running with a one gigabit connection for your network so your network was typically a very big limiter back then whereas today you can see here I can get a if you want to go for the larger instances you can absolutely get 100 gigabits per second which is absolutely amazing in comparison to where the networking technology was 10 years ago and the same is true for Google cloud where I can actually have local NVMe storage that can handle millions of IOPS and also allow me to do writes of nearly four and a half gigabytes per second to those disks so we've come a huge way in just a very short period of time so what does it mean to take advantage of this modern hardware that we have available today? What we've seen in building these distributed type systems is that workloads are becoming much more bound by CPU than disk as we just saw like we can have millions of IOPS network has gone drastically better but what hasn't really improved dramatically is the speed of a processor or a speed of a core itself we don't have 12 gigahertz processors and things from that perspective but what we do have is 32 core, 64 core upwards of 200 core machines and really just we become much more bound on that CPU and focused much more on paralyzing processes versus really focused on the fast single process and with these types of this type of architecture there come other issues with it so namely one of them is going across NUMA domains when I have a large number of cores or a large number of sockets I have different memory access paths to the actual memory on the system and going across that path from one core to the other can be quite costly so if your process can be aware of where memory sits and where it gets executed this can be a great advantage to you so you don't do these sort of high latency type requests to access that memory also to make use of these systems kind of the traditional way that you would make use of them and this is a way that a system like Kafka works today is that you have a large number of thread pools so if you wanna take use of it or make use of a very large machine you have to specify that you have 16 threads that are just doing network IO 16 threads that are doing disk IO maybe you have 16 threads that are doing other sort of client operation IO too as well and very quickly you have a large number of different thread pools and different threads that are trying to be scheduled on these cores so this can lead to more context switching which then adds to overall latency on the system as well and then the other thing is that file systems or newer file systems have definitely come into their own back in 2011 most people were running on EXT-3 file systems nowadays EXT-4 is pretty prevalent XFS has become very prevalent as well and XFS provides us a number of advantages specifically the ability to do out-of-border direct memory access rights and also adaptive F allocation which these are both things that I'll talk or the system we're gonna talk about here in a little bit take advantage of because it allows us to be much more performant and allow us to not have to wait for file allocations to occur or to keep things completely sequential across different partitions within the system as well. So let's talk about systems that can take advantage of this modern hardware. First and foremost, there's a framework that exists out there called C-STAR. This is actually used by a few different projects out there today. It's completely written in C++ and it's really focused on making use of these larger machines and really actually sort of treating these larger boxes or the machines that we see today as if they were a distributed system in of themselves. And so what that really means is that looking at a core as if it was a single machine in a cluster of machines and operating with that sort of assumption. So what it actually brings to the table is really the ability to do a lot of async programming via different futures and promises and requires no locks and minimizes IO blocking. Some questions that we get sometimes is, does C-STAR make use of IO urine and things from that perspective? It doesn't today and we don't expect that there is a thought to port it over to IO urine but that's probably only gonna give us about a 5% performance benefit where since we're completely asynchronous already with this type of system, there's not gonna be a huge benefit versus a system that has much more synchronous in nature to begin with. We also have a thread per core architecture which what C-STAR does is that when it first starts up, it looks to see how many cores do I have available? It launches that many threads and then pins those threads to given cores. This really reduces all the majority of the context switching happening in the system and it also allows us to preserve the cache lines in the system too as well because those cores typically have different L1, L2 caches attached to them or that are assigned to them and this allows us to stay on a given core so that we don't have to refill or kind of refresh a different cache line when we do get switched or if a thread does get switched to a different core as well it allows us to also be very by nature, NUMA aware because we can be very specific on the memory that we work with for that given core. So with all that, let's talk about a streaming platform that's actually built to make use of this modern hardware and it's built on C-STAR and that is Red Panda. Red Panda is written completely in C++ makes use of the C-STAR library at the core really focused on a high throughput, low latency and providing strong transactional guarantees. What that really means is, we are persisting to disk after every batch of messages that comes into the system. So we're not delaying writes or anything from that perspective, data gets persisted the moment it comes into the system. It's also provided in a single binary. So it includes the broker in HTTP proxy and a schema registry altogether. These are typically things that are separate components in something like Kafka where you'd have to run Kafka, you'd have to run ZooKeeper, you'd run a HTTP proxy and also schema registry to really get the same level of functionality as you get with a single binary in this regard. It's source available, everything's out on GitHub and you can actually take a look at the issues and features that are being developed on at the moment and it's fully Kafka compatible. So you can make use of all the different sort of projects and things that are available in the ecosystem today. And Raj, I think that was like a main driver for you guys looking at Red Panda was the Kafka API and the single binary, right? Exactly. I've had previous experience with Kafka and Kafka in production is a beast all its own. What we found with Red Panda was, A, just the zero friction aspect of it. We had a very small and diligent engineering team that was able to get started and get something into production relatively quickly. And since it's been in production, it's really been pain free. So that was a huge adoption metric for us. That's always great to hear versus the opposite. So, and this is definitely, this was one of the main reasons why Red Panda wanted to focus on the Kafka API is that, although there's probably simpler APIs that exist out there today, like Nats comes to mind, it is kind of been picked as the standard. It's the VHS versus Betamax debate pretty much. And being able to have that API compatibility allows for all the different client drivers that exist out there today to be used and allows it to be plugged into anything that supports the Kafka API seamlessly as well. We've really focused on the performance safety aspect, which we'll talk about in a second. And then there's no external dependency. So raft is actually used for all consensus internally to the system. It's used for the cluster state and all the data within the cluster as well. So let's talk a little bit about raft because like we're talking about modern hardware, but we should also talk about modern approaches to consensus. Zookeeper and SED, well, SED is raft based in many ways, but zookeeper was sort of before raft was prevalent and raft has sort of taken over as kind of the consensus protocol of choice as sort of a simplified version of Paxos. As raft does have a few sort of requirements around it, you have to have odd number of replicas, each partition inside of Red Panda. So inside of both Kafka and Red Panda, you have a topic and a topic is made up of partitions. And within those partitions, you have guaranteed ordering within those partitions. And that partition can be any sort of key space that you define or it can provide a default key space for you. So in the implementation for Red Panda, each partition is its own raft group, which this gives us a lot of flexibility to move leadership around and to move replicas around on the system. We don't rely upon anything externally because everything is done inside. So this makes it a single fault domain for us. So we don't have to worry about multiple distributed system protocols that exist out there today. You don't have to worry about like your zookeeper connection and your Kafka broker connections or other things from that standpoint. And this also allows you to write out slowness and individual replicas. So if a leader can act to just a majority of the different replicas, you can make forward progress. So if one replica is a bit slow, that isn't going to stop you from being able to reply to a given client in the system. So all of that, what does that lead to? Well, this is some benchmarking that we did earlier this year and we'll actually post in the chat a blog post that highlights sort of our methodology for this. We actually can use the open message benchmark to a link which is actually a Linux foundation project to actually do this benchmarking. So against Kafka and Red Panda. And what this particular example is here is this is doing 500 megabytes per second on a three node cluster inside of AWS using the I3EN success for large instances which provide us guaranteed networking. And we went with the six extra large instances because of the guaranteed networking. If anyone's kind of been familiar with AWS, if it says up to 25 gigabits per second, it means you actually get that for about eight minutes and then you get throttled to eight gigabits per second. So there's a lot of nuances that go into this and we highlight that through the blog post as we sort of discovered that for ourselves as well. And what this workload shows is this is an end to end latency in the system. And we were telling Kafka to actually persist to disk after every batch of messages. So you can see that the average latency there is about 14 milliseconds and for Red Panda it's a little over two milliseconds. But what the more interesting part is around the actual tell latencies. And this is the part that becomes really important for transactional systems and systems like the order management system is that when we start going out to the 99.9 or 99.999 latencies, we can see that Red Panda stays very consistent at about 120, 150 milliseconds. Whereas Kafka goes out to about three seconds at these max latencies. So because of this, a lot of people over provision instances for Kafka to reduce the effects of these tell latencies. And that really creates large clusters with underutilization in general. So bringing it full circle, technology itself is pretty cyclical in nature. And this is an exempt from that particular trend that we see. Whereas now we can actually go back and put something like Red Panda that can provide this low latency transactionality within the streaming ecosystem for these types of use cases like the order management system that Alpaca has built. So now we can have our application talk directly to Red Panda and now we can feed into our different databases that exist out there, the different data warehouses or data lakes and also the different microservices that exist out there today. So with that, I'll hand it back over to Rasha. Thanks again, Rocco. So just building on what Rocco stated in the previous slides, we really evaluated a lot of different ways to approach this problem. We sort of set a very high bar for ourselves. So when we started this project on reevaluating our architecture of the order management system, our goal was to bring that P95 from 150 milliseconds down to five milliseconds. The other big goal was the throughput. So we wanted to be able to handle around $10 billion in trading activity. And those were just synthetic goals that we set based on the growth for business but I'll walk you through sort of how we approach the problem, how Red Panda played a part in that and then some of the numbers. By the way, if you're interested more about the design and the implementation of our OMS, we've also created a blog post that walks through the major aspects of it as well as some of the throughput. So the OMS itself is entirely in memory and that horizontally scalable. So you can have multiple shards of the OMS system that are running. The OMS is responsible for a subset of or total accounts and it handles all the state in memory itself including things like the positions or the details around the equity or buying power that are required. In order for this to be durable, we need to persist this data somewhere and we need it to persist very quickly and also be able to consume it very quickly. So that's where Red Panda comes in for the right of head log. When an OMS starts up, it basically rebuilds its state, the memory state from the Red Panda topic and then its ability to start working so in the event of a failure, another pod will come back up, read from the Red Panda right ahead log and it'll be active again. Another really happy side effect of decoupling the wall and building the center system was that we have a lot of other services that would love to be aware and to be able to observe the state of trade events or order events and having that wall live within a streaming engine like Red Panda makes it so that other consumers can simply subscribe to that wall as well. So here's a high level architecture of our order management system. We have basically a customer or an order comes in via one of our API services. So at El Paco, we have a few different APIs. We have a live trading API, a paper trading API, a broker API and then finally a market data API. So if it's an order related event or request, it connects to our order management system over GRPC and at the top of our order management system, we have scalable balancers so they're horizontally scalable as well. Think of these as sort of an oracle. So they abstract away the order management system and its implementation details away from the consumers so that they're sort of act of the oracle and they'll route the right request to the right OMS. The OMS themselves, like I said before, keeps everything in memory but it's persisting its transaction log to a streaming engine and we're using Red Panda here. We also have the happy benefit where we can consume that wall that lives within the streaming engine and persist it back into the relational database in the same way that it was propagating before, meaning that the applications don't necessarily need to be aware that there was a system change in place. On the other side of what happens with the order, so once an order gets processed, we communicate to the market. So most of our infrastructure is in GCP yet we have infrastructure in Socockus, New Jersey at Aquedets Data Center. We have an interconnect from GCP to our trade execution rack at Socockus and then from Socockus we have cross connects, fiber cross connects directly to a variety of execution gateways depending on the asset type. So that's generally how our OMS works. And these are the results we saw. So these are actual results from our production environment. So the version of the OMS that was replaced, like I said before, had P95 or around 150 milliseconds but was really not deterministic by any nature. During high volatility, we saw very erratic and concerning performance behavior. Now with OMS V2, which is in memory and a wall powered by Red Panda, we see extremely deterministic performance even at extremely high load and P95 of around 1.5 milliseconds. So way under what are super aggressive benchmarks of five milliseconds. And again, this is a synthetic benchmark but when we were evaluating our system before going into production, we just wanted to see how fast we could push it. Now there's no way with our previous system that we would even be able to come close. And truthfully, we didn't decide to push it even further than this because the results were just outstanding. So the test scenario was 100,000 accounts concurrently sending 10 orders each. They all happened to be a market order. So they didn't have a price determined by a limit. There were randomized symbols and these are actually just a reworked Grafana dashboard. So this was sampling every 30 seconds. And the Red Panda cluster was just three nodes. A few things about the Red Panda cluster. So a relatively recent Linux kernel, almost no tuning on the kernel and then almost no tuning in the Red Panda configuration. It was really just provision, set it up and away we went. And here's the results we've received. So again, it would be P95 well under two and a half milliseconds and we were able to process just under 1.7 million orders a minute. The latency was, we didn't really experience great tail latency. It was great to see deterministic latency. And as I mentioned before, very easy to scale out. So as we required more throughput, we're hitting actual kernel constraints. We can just scale out in a horizontal fashion. And just to touch upon the no kernels tuning, that was actually, that's something that Red Panda just does automatically. So this was one of the great things that Rajen team were able to take advantage of is that when you install Red Panda, the first thing it does is set a number of different kernel parameters to just make that very automatic for you. So when we launched this, we sort of started rolling this out gradually, but the feedback, and I'm not going to go through it, just came in unsolicited. The, one of the patterns that we saw that we didn't anticipate was some of our algorithmic community, we saw their volume of trade volume, pretty much double or triple overnight. So it's been a game changer, not just for us in terms of our ability to scale alpaca, but also it's been a phenomenal performance improvement that's had great financial and material impact to our user base. Thank you so much, Rajen. You know, a few things just before we start answering some of the questions that have been asked is, you know, you can go and check out the source code for Red Panda. The link here is, you know, from on GitHub. We have a blog post that talks about a number of different things. We have a one that's in there that's great that talks about the different chaos testing that we do on top of the system. We actually are currently working with the Jepsen team to do a full sort of Jepsen test or sort of correctness test on top of Red Panda right now that we'll be releasing pretty soon. We have a community Slack channel if you would like to engage with us or ask us further questions. And also, I know Rajah alpaca has a few things for you guys to also share as well. Yeah, I would encourage anyone that's interested in our trading API or a brokerage API. So if you want to incorporate financial market access, internet-existing product, we have an API for that as well. Then most importantly, especially for this audience, we're always hiring. So what we spoke about is of interest or if you want to be working with Red Panda, please either email careers at alpaca.markets or our job board, as well as our Slack community and our user base are posted in the slide as well. And finally, if you need to reach out, please reach out via Twitter. alpaca is available at alpaca HQ and I'm personally available at Rajah. Perfect, yeah. So opening it up to a few of the questions that we've received, the first one was, can one consider Red Panda as a real replacement for Kafka in terms of guarantees? Like exactly once semantics required for Kafka stream commits to source offsets and target topic, are there features where you don't have parity with the current Kafka versions? So for the first part of the question, you absolutely can see it as a full Kafka replacement. We do support the full transactions API. So alpaca is actually making use of item producers, which allows for much higher throughput on the system as well. And we do support the full transaction side of things. So it works with Kafka streams out of the box. There are some things around the full parity for Kafka that we don't have. And those things are things that we're working on to be addressed, like follower reads for replicas and a few other things that are much more specific to that. But the large majority of the Kafka API is implemented. So I think that and also the Flex Protocol, the newer version of the Flex Protocol for Kafka, we don't fully support. And that's more just from a standpoint that we haven't seen a huge amount of usage for that quite yet. The second question is, does Red Panda also implement the Kafka admin API? And yes, yes, it does implement the Kafka admin API. So you can set ACLs, you can do all the topic administration. You can use tools like Cal or K-minion or a number of other of those types of systems right on directly on top of Red Panda. And they work on Red Panda just exactly as you would expect them to with Kafka as well. One question for Alpaca is, how long did it take you to develop the order management system V2? What did the timeline for that look like? Yeah, so we started looking at this in the second quarter of this year. And we started skunking it out with one of our most talented engineers, Alpaca. And basically, we gave them the freedom to explore the space. We introduced them to Red Panda. We were able to get this into production in four or five months. And a lot of that was just experimentation. So as we're now adopting Red Panda in other aspects of our application, we're finding that it's almost, a lot of implementation can be done in a week or two. Given the complexity of the order management system and the in-memory aspect, that took a little bit more time than we anticipated, but it's worked out really, really well for us and our user base. Well, I don't see any other further questions. So if there's any last minute questions that people wanna get in, we'll just give it a couple seconds. Otherwise, I think that's all we had from our side. So if you do have any further questions, we have both of the different Slack channels listed here. Please do join us. We're always happy to help. And there's a multitude of different ways to make use of Red Panda and also Alpaca as well. And with that, thank you so much, Raja, for taking the time today. And thank you for the Linux Foundation for hosting us. Yes, absolutely. Thank you both for being here and for speaking on these topics. And thank you to all our participants who joined us today. As a reminder, this recording will be on our YouTube page later today and we hope to see you back at future webinars. Have a wonderful day, everyone.


what is up so it's currently 118 and it is Saturday and we are downtown Vancouver we just got here we're just parking because my dad works down here so we're just gonna park at his work so then we get a parking spot because parking down here first of all so are defined especially on a Saturday second of all is expensive so we're lucky to have that and we're just gonna shop around I told them I told Julia am I going the right way downtown stresses me out so much because the city is so busy and it's like the pedestrians the cars the one ways everything it just stresses me out like Brittany thank you for driving I'm a very good driver I just I thought that it was nobody stopped me did anybody stop me well I'm not driving well are you you're in the front seat watching Brittany I've done that before too probably a thousand times I'm pretty I went the wrong way on a one Julia has passed like five red lights like in a row in a row like not even just one every like no in a row we've all had experiences driving downtown so it's like if someone did that I would never get mad I'd be like oh you know what I'm here for you like it's fine like I'll move out of your way you can turn around like I would never ever judge any way at least that's but anyway so we haven't eaten yet and it's one o'clock and none of us have eaten yet except Brittany I had egg what are they oh Joel didn't eat yet I thought you have something at Tim's had it well Brittany had a bit to eat Joel Joel Julia had nothing so we want to find a place to eat but we want to go to like a cute place and we're downtown so there should be a lot to find something and we don't know any of them because we don't really come down here often and it literally took us so long to get I'm like pointing with my because there is so much traffic and I'm pretty sure there's an accident or something must happen because it took us forever to get here that's what we're doing the Starbucks is so nice I've never been to before but it's literally so nice it's just like decorated so nice and it's like the nicest less busy Starbucks I've never been to because usually we go to Starbucks downtown like it's like it's so popular but this one I was like no line it was empty you're so nice in here over at sale is a really adult house right now like everyone is everywhere and it's so hard to be in here because as you guys know like it's just like I'm trying to stay away because everything is like over $50 so it's really painful but it's my wallet is happy love and hate this place at the same time. Everything is so freaking cute when you don't face time so we're currently in Indigo chapters I don't know if this chapters in Indigo is the same thing but that's over and Julia has been getting me into like a whole bunch of fiction books I'm gonna be getting my recommendation from her because she's been really into reading like she got into it first but I was into like nonfiction books like I'll just read like self help books kind of thing and then she started saying how good these fiction books were so then I just started reading like one of the series she suggested and I just talked about it in another vlog but I've read like 15 books I think I'm almost finished my 16th I told her that we should start a book club I feel like I read too fast because she can read out work like it's because one of her jobs like she works at like a hair salon so she's like has a lot of down time because she's just like a receptionist so she can like read when she's like not doing anything so she's like zoom and also she reads on her phone like I can't read on my phone yeah well I'd rather have a book but it's like when I work it's easier to read off my phone yeah like since I'm on the computer all day and stuff I just can't read on read from a book I mean read from the phone like I need a physical book copy get a bookmark get a bookmark I don't know Colleen Hoover's family really good look at how cute this parking full I guess I'm like a good matching yes I'm gonna mama bear one oh my god yeah okay so we just finished shopping we're walking back it's like six six o'clock so we were here for like we've been here for like five hours and honestly shopping is very exhausting like all the stores are on different streets then we parked somewhere else so it's like a lot of walking and it's just like your I guess you're standing for that amount of time so it could get exhausting and just like so many people really exhausting and after I shop I just feel like doing nothing because I get like lazy hey guys what's up so it's like another day from when I got back from Vancouver but we are going thrifting today and I know I literally went thrifting in just a couple vlogs ago or like two vlogs ago but there's this place that I got told about it's half an hour away and they're doing a 50% off so I'm like I have to go and apparently it's like a really good thrift store so I'm like I have to go check that out because how can you pass up an opportunity like that and thrifting is like an experience it's not just like you're going shopping I don't even consider thrifting going shopping technically it is going shopping but it's more of an adventure to me like I get to explore and find cool pieces like that's what I love about it like this jacket is thrifted and like you wouldn't just find this jacket like it's like a race car it's Joel's but you wouldn't just find it like off the shelf on a regular store you know what I mean so it's kind of like cool better for the environment and yeah I just love thrifting so much so that's why we're doing it again because I didn't have like enough footage for the Vancouver vlog just to make like a whole vlog about it because I didn't like there wasn't enough content this is still like a Vancouver vlog but mixed with this thrifting portion we just got gas it's half an hour away we're just leaving now and I'm honestly really excited because I love I love when people that come up to me and they're like oh this thrift store is so good you got to go to it because it's honestly hard to find like good ones yourself like this value village and that's the only really one around here that I know of and like one other one but it's cool when people like refer you to good thrift stores and it's perfect because they're having 50% off today so I can't wait and I still have to give you guys like the haul of the stuff that they got from Vancouver so I'll do that all in one go tonight when I get like if I buy anything from the thrift store I'll just give you guys like a massive haul so yeah that's what we're doing today ocean my phone but it's kind of a gloomy day today but I kind of like it to be honest because I'm just tired today and chill so I don't mind honestly let's go so we just got here and we are just like going pee because we gotta go Joel really has to piss I really have to piss and Joel also wants to get a coffee from Tim Hortons and Horns is literally like right across from here so we're like let's go pee get a coffee and then we'll go in I can't believe it's 50% off like I'm so excited I've never been here before but Joel said he's heard of it that is in like the States or something it's called play to the closet I think there's only like one around here so can't wait I already found so many things it's cheap it's like I can't wait to give you guys this haul what'd you find so many things you guys this place is like having to be like thrifting have been I cannot wait to give you guys a haul so I'm home from thrifting obviously it's like later at night and I was just like doing other things during the day um but I got a lot of shit and I'm gonna show you guys I'm just in my downstairs bathroom right now to give you guys a different change of scenery because I feel like doing like in the same video in the same place or sorry doing videos in the same place is like boring so I just want to switch the scenery up we've got a lot like we got a lot I'm debating if I want to do a try on home probably should for you guys it probably should also I thought that everything was like 50% off but it turns out only like the tags like the clearance tags were 50% off and I even called before I went and I'm like hey I heard that everything is 50% off today is that true and they're like yeah it's true and then once I got to the till it's like everything's 50% off right she's like no only the clearance tags and I'm like are you kidding me like I had I like doubled this stuff like I had to cut my stuff down because I thought it was gonna be half the price so I just like cut down that's fine anyways so here's the first thing that I got this is just like a disney shirt as you can see and I think that it's so just cute the neckline is really nice on it because like sometimes when I thrift I find that the necklines get like really droopy and like I just whenever there's a good neckline I appreciate it this one is really nice and just like an oversized comfy t-shirt just to wear on the house or literally just for pumpiness whenever I want even as a pajama shirt it would be cute that's the back back says something I don't even know what it says right next all right so the next thing that I got is just this plain white turtleneck because I feel like I might have a white turtleneck but it's not really like it's getting old and raggedy so you can never have enough white turtlenecks for the fall slash like wintertime I feel like I just always reach for a white turtleneck it's just a basic it goes under anything style it with anything next I got these really big baggy pink sweatpants and you might be like okay those are huge yes I know they're huge you can't really see them but like I thrive wearing huge sweatpants at home like that's like my comfy zone like I put on a good pair of comfy sweatpants big oversized and I'm just like feeling like I'm in bed but I'm not so that's literally what I love wearing during like a winter cold season when I'm just sitting at home and I just want to feel cozy so I just really love the color of these and they're just like baggy cute pink so I'm like how can I pass these out and I got this jacket and it's adorable like it's like a leatherish leather jacket like this would be so cute it's like hoodie underneath or like layering with something you know because fall you layer I've been looking for like one like this for a long time and I was like holy shit like that this I'm sure we're like the best store I've ever been to this is super dope this is the next thing that I got it just is a green turtleneckish moch neck type of shirt just you know for the fall I really just like the color of this green and again this can go with a lot of things layer on top of it nice jacket on top okay so this is the next thing that I got and I don't know if you can tell but it's a dress like a turtleneck dress um so if you can see in this mirror which is kind of hard because I'm really short basically this turtleneck dress and I feel like I can style this like a whole bunch of ways it's just cute oversized and super comfortable like I'm just imagining wearing this with like a whole bunch of like layered jewelry here um a cute purse with some booties this would be a look and so I got this purse as well and this is just like the most fall purse I've ever seen and it's in such good condition and it's just like such a look like it's so sleek and it's just kind of different and I was just picturing me like bringing my laptop in this because it was like perfect size for that so I don't know this just like I feel like I can make some cute like looks with this bag and I also bought this pink bag it's like a wrap around and it is so cute like this bag is literally like it's from Zara and it looks like a puffer like it's a little puffer bag and it's pink like it is literally the cutest thing ever I've been wanting like some new purses and I've been really into like usually like shoulder purses but I just really liked how this one was like a strap on and it kind of gives like a different look to so I feel like I could make some cute looks with this and I just look how it's like a puffer material and I put it inside so like I don't know it's just really different and cute so the next thing that I got is just like black plain tank top and this was like just really cheap and it's really like in good condition that's brand new great quality you can never go wrong it's just like a basic simple tank top and then I also have this laser okay can you hear me out so here it is and I'm thinking of wearing this like imagine a cute like mini skirt with like a turtleneck or something to go white turtleneck and then this over top with some booties like how cute would that be I just think that this is so cute like the checkered blue pattern so cute like I'm obsessed with this okay so here's the next thing that I got sorry remember all like I just have a sports bra on and I tuck these straps it so looks weird it's just this dress um I feel like I can use it just like I don't know if I ever have like a like a fallish event to go to it's just really digging the one shoulder and it's just a neutral color so it can go with anything and yeah I don't really have a one shoulder dress like this so that's what caught my eye about it is I was just like like I don't own anything like this so there's always a situation where I need a dress and then I can't find anything so so yeah from the thrift store that's all that I got and I still need to show you guys what I got from Vancouver even though I got so much stuff this was like under $100 like it was a really good pricing that's why I love thrifting so I'm just gonna like throw everything in the wash right now and I'm gonna go upstairs and show you guys what I got from Vancouver all right changes to me once again we're in Madison's room my little sister so the first thing that I got downtown so I got this green crop shirt from H&M and it was literally $5 it's perfect it's so comfortable and it's just ways to have like shirts like this this is the exact same one but I got this in a gray and then from H&M I also got these like really just like comfortable they're long wide leg um kind of like sweatpants type of vibe so this is like the recycled line um so it's better for the environment and these are just really cute and comfortable like to wear every single day I just love comfy clothing and then the last thing that I got from downtown is this pink crew neck and I'm obsessed with this color I'm obsessed with crew necks and headies so if I could I would literally own a million of them because I can't get enough like I just like my dream closet honestly it's just I have like a whole bunch of matching sweatsuits that's all I want I'm like no joking but like low-key like I actually do really want that okay so I feel like this video was like a lot of shopping but I hope you guys enjoyed it anyways because the half of this video feels just like a haul and stuff but I hope you guys enjoyed that because I honestly love fashion and like I'm really sad that the summer is like technically over now like I'm really sad about it because like summer's my favorite season but with that being said I also really do love fall fashion so I'm really excited to get into it style some cute looks yeah so I really do love fashion and summer isn't like the best fashion season I wouldn't say because there's no layering going on like it's just kind of basic like that in like fall and winter season is to look forward to but it's just yeah you just go always have to find the bright side but anyways I just wanted to end this off with the moments with Mikaela and I basically just wanted to say that like right now in our world as you guys know this huge thing going on um I don't even want to say the word because it's all people talk about nowadays and I want my channel to be more of an outlet where you guys can come to you for like a break and for motivation or whatever you guys come and watch my videos for whether just be solely for entertainment I want you guys to feel at peace here and kind of away from the rest of the world what I'm getting at is there's a lot going on right now and there's a lot of divide happening it's honestly really really sad to see and witness firsthand the like the divide that is going on between us as humans and it's almost like we're turning ourselves against each other and that is the last thing that we should be doing despite our differences we should all be coming together and making peace everybody is different everybody is unique no one thinks the same we all have differences we all think a different way for a different reason because of our life experiences what we've been taught and that's why it's so important to respect other people's opinions and to not judge them based on their opinions their values or their beliefs about something and to really at the end of the day accept everybody for who they are and all come together instead of going against each other nowadays I refuse to watch the news because all the news shows is bad things it shows missing people amount of cases per day that scares you fires going on everything bad is on the news like everything scary is on the news that's why I refuse to watch the news because I don't want to wake up with that every day I don't want to ever watch that because that puts fear into you and I don't want to absorb that any of that fear yes I'm not delirious to the problems going on in our world obviously there's lots of prep things going on and just lots of problems and etc but it's so important to realize that there is more good things than bad things happening in the world and the reason why the bad things are on the news is because that's news that's out of the ordinary it's different meaning that like there's only bad things on the news because bad things don't happen that often if that makes sense so that's why they broadcast it on the news and all these good things that are happening every day you may not even notice because it's quite normal like just something as small as somebody holding the door open for you walking into a store little things like that it's like that we don't maybe even notice those are good things happening in the world the thing is is that the news doesn't tell you these good things you don't hear these good things you have to notice these good things happening and kind of realize them for yourselves and that's why every day try and point the good things out instead of pointing bad things out and focus on the good things and don't fill yourself up with fear because that fear is just going to keep growing and growing and growing until it spirals out of control so yeah I just want to let you guys know that even if you feel sad in the times that we're in if you feel stressed out about it anxious about it just know that um there are still so many good beautiful things happening in the world that are not broadcasted on the news for you to see that you have to search for other places or just notice in your day-to-day life and I'm sure you can I think there's websites that you can search up like good news that happened today and I'm sure there's like apps or websites that you can like look at the good news so I'd encourage you guys to do that instead of if you guys watch like if you guys are always paying attention to the bad things that are happening because I can really take a toll on you I feel like and fill you with fear but yeah just I just wanted to reassure you guys that everything is going to be okay and the world is not a bad place there are horrible things that happen in the world but there are also beautiful things that happen in beautiful people but yeah that's why just so important that we all come together and love each other despite our differences I think that is just so important in living a peaceful life on this planet because we're all stuck on a planet together like if you think about it that way it's like we're floating in the universe in the middle of space and we're all stuck together basically on this planet yeah next time if somebody has a different opinion than you I challenge you just to respect it and um hopefully they respect yours as well because I feel like that's just very important spread peace spread positivity and spread love get in the end that's what's gonna bring everything back together yeah that's pretty much what I wanted to talk about today and I'm getting really tired I still have to catch up on my sleep so I'm gonna go to bed oh oh my god I'm so tired anyways thank you guys so much for just listening to that rant I was gonna say if you guys are still here but obviously if you're watching this right now you're still here so thank you like I really appreciate you guys listening to me I'm gonna go to bed and I hope you guys have an amazing day evening night whatever it is and spread love spread positivity there's good things happening out there don't forget that see you my next video oh oh my god you guys were sitting on this clean next box I'm gonna pick up the camera I literally pulled the clean next house


Hello, I'm Tim Waters, volunteer for Longmont Public Media and host of The Future We Deserve. I'm inviting you to join me on May 12th, 6 p.m. right here, Longmont Public Media, for a conversation with a collection of outstanding local leaders in the development community. The topic of our conversation, rediscovering our soul in the development of our land and our economy. 6 p.m. right here, Longmont Public Media.


Mae'r fideisi mae'r fideisi yn bwysig gydaeddiant. Mae'r fideisi yn bwysig gydaeddiant mae'n bwysig gydaeddiant o'r ddafod ddau o'r hyn sydd, oes gds rhywbeth o'r peth ar y rhan. A oedd yn rhan o'r fideisi ar ddech chi, gyda'i'r link yn y sgrivodiau sydd eich rhan o gael. Felly yna'r fideisi'r fideisi hwnnw, yn ddechrau a i ddim yn ei rhan o'r hoffi. Rwy'n gwybod yn y TV o'r Clif Farching, mae y cwmdd. I am joined by Max Carlisle. He's going to be satty yet. Giving me his knowledge on Everton. No, we're just going to have a little chat about something that I think it was on Sunday Andy Hunter broke it. Talking about Everton's plans for the summer and plans for players currently in the squad on a couple of the lone players. So, let's start with Henry Ong Ycury, who, Andy Hunter said, was there Everton were going to be hopefully getting a work permit for, and he was going to be part of Marko Silver's plans going forward. And I suppose he's 22 years of age. Everton brought him in for seven million quid a couple of summers ago. Obviously, they have no chance of getting a work permit for him, so he went off to Andalect, come back and went off to Galatasaray this season. So, I mean, it's difficult to talk about him in a great length because we haven't seen that much of him, really. We've seen the old Champions League game where he's played, remember he played against Celtic last year. He's played against, I think it was PSG this year, but is he someone, is he someone who excites you, Max? The thoughts of it, or are you a bit undershaded given that she wants you over? No, most definitely. I'd be excited for him to come back into the squad because you think about it, essentially, that if you get that work permit cleared, he'd be like a new sign as a whole. We'd get to see him pull on a blue shade and see what he can do for Everton. It's absolutely fantastic to see the him and Ong Nicola Vosys that we're talking about later. They have been getting game time, which is what I feel, you know, the players under 20, 20, what was it? Max Elbrann said we're looking to identify players on the age of 24, 25, 25, so they set me for that profile. And from our perspective, from a fan perspective, you see how tired someone can get seeing Theo walk off the town. You know, it's freshing things up and how many goals have he got now? 11 goals for Galatasaray. Although we've seen how well that translates to the Premier League, we don't quite know. We've seen Chegg Towson come over and struggle. But he looks like he has the physical capability and the attributes to hit the ground running in the prem. Fingers crossed he does. I think the one thing he'll have over at Jank, bless him, is the pace. Ong Nicola is quite quick, so he's a bit slighter than Towson. But if you've got that pace, you know, pace can get you round so many difficulties. And if you struggle with a lack of pace as, you know, Shenke has given the physical demands of the Premier League, it's difficult.  I think that when you've got players who reverse the tyre like that, it makes it easier, I think, for you to adapt game by game, I think. If you had for argument's sake, if it was like the Charleston on Y Cwru and Bernard, you know, they're quite fluid, and all Calvert-Lewam was in there, and Ong Y Cwru playing wide, right? To let them the Charleston, you've got three quicklads. So I think the thought of him being able to hit the ground running, like you said, is one that fills me with a bit of hope. Cos I think when you're looking to move the team on, I think Marco Silva now has a team that he trusts, I think. We're seeing players who he can kind of trust now, who are getting some results for him. Which means that there's question marks over a lot of other people in the squad now. You mentioned Theo Walcott there, right at the start. He's someone who isn't, he's just not contributing at the moment, is he? I mean, that's fair to say, isn't it? For a player who's got a lot of Premier League experience and scored a lot of goals in his career. I suppose so. I mean, I was a huge fan of Theo Walcott at Jordan's time of Arsenal, especially when he based on the 16-year-old kid coming in at the Welfare Cup. But obviously his Arsenal career, for me personally, didn't quite live up to those hypes and those expectations. He's come in to Everton as a short-term fixer. Have we brought in an overload on number 10s in central players? He's just provided pace that we didn't have. Now, you will lose the two with the players like Bernard and Richard and which Marcel Brans has brought in. In terms of technical ability, I just don't think Theo Walcott's quite at that level. That's where you can look at a player like on your career. Although we haven't seen him in the Premier League, you see him perform in Europe, for God's grace or anything, and that could translate. Having that tool in your box, as you said, to play across the front line in a variety of different positions, like we've seen with Charleston do at times. If you've got to look back at that Western performance, just how vital the wing play was and the emphasis on pushing the ball down the wing, if on your career it's physically prepared for the transition, who knows, who's not to say a regular starter, because I doubt it would be that smooth of a transition, but he could play a serious part in the season. Definitely. Pre-season will be key for him if we get the way it is. Obviously there will be a lot of games this pre-season. For all we know, everything could end up in Seventon in Europe. We don't know yet. We've given ourselves a chance, and that brings different options, but he's played seven games in Europe this year. He's had five Champions League games for Galatasaray, played in both the Europa League games for Galatasaray. So he's someone with European experience, he had Champions League experience with Anderlech last season, so he's playing for Nigeria now and doing well there, so he's got all of that experience. If you say he can translate that, then he could be an exciting addition. That's him, and we haven't seen any of him, on to a player who we saw a little bit of last season, Nicolab Lasich.


Good morning, Endeavor. Good morning, Tong. Ohio was IMAF. Good morning, Carr. Ohio was IMAF. I'm ready to grapple the SFU. Great. We thought you'd say a little traditional music to get you all tuned up for it. Never Houston, we've gone around the room here. The SOC, MCC, and the satellite are all ready for the TI burn. Up to you folks. Okay, we'll take that. I think we'll go for it. Go ahead for SFU. Koichi, we are proceeding towards Jettison of the Saps. The SOC is picked up in step 5 on page 2-5, Saving 2. And we'd like you to confirm in step 6 that we have the right attitude for Jettison. Okay, we confirm as if you're using the proper attitude for Jettison. Copy that. Endeavor, Houston, stand by for Canister Jettison command. Standing by. You see a good Jettison visually and on the spec there, Houston. Copy that. And, Endeavor, can you get us a laser ray on the departing SAP? Hey, Houston, Endeavor. We see SFU maneuvering both from the spec and visually. We copy, Winston. And Brent, can you elaborate on your camera alpha problem? Yeah, Tom, I'll forget. On camera is the color bars we thought maybe Inko was using it or something. Negative. We'll get you some words. Endeavor, you should see motion momentarily. Endeavor, we see it on TV. Roger. Copy that. Endeavor, Houston, your crew has been very patient. It's time to release all that coiled pent up energy and your go for final approach. Let's go get it. Thanks, Tom. Run away. Inko, we've got it, Houston. We knew the man would come through. Flight controllers confirm the successful capture of the space flyer unit bringing to an end. It's 10 months of scientific research. Applause on the mission control center following the successful capture of the space flyer unit. The SFU was grappled at 4.57 a.m. central time bringing to an end its 10 months in orbit. To do that and all the practice that we put into it all paid off. We're all real happy up here and we're sure you are down there as well. We knew we had the plan all along there, Brian. Fast startup if you like it now, if there aren't any constraints. Say again, Endeavor. Yeah, Tom, just look at the flight plan. We can give you that topping. Fast startup, I guess, if it doesn't break any constraints. Any other pilots? We'll check. Okay, Endeavor, if you'll confirm you're down all the way around visually, then we can start with Akille. Okay, Tom, as far as we can tell, it's down, so we're going to proceed. I'll take care of it, we hope. Hello? This is Matsui, President of NASA speaking. Commander Duffy? Yes, Mr. Matsui. We're reading you loud and clear on Endeavor and hello. Commander Duffy, your voice is loud and clear. Yes, it's a working mission control team in Houston and also at the Saga Mahara Operations Center. We were very successful with rendezvousing with and grappling the SFU satellite. Things went not exactly according to our plan, however it was according to the way we expected things could possibly go. And because of all the great teamwork between NASA and NASA and all the prior planning that was done with many, many people, it also was the real-time execution of those plans. Everything came together today and we now have the SFU about 50 feet behind us in the payload bay. Congratulations on the success of launch and SFU retrieval over. Thank you, Mr. Matsui. Things are going very well. We're very excited and very happy. Today's been a very big day for us and for you all in NASA as well. Please hand the mic to Dr. Wakata, please. Please hand the mic to Dr. Wakata, please. Now the Space Shuttle Endeavour is flying at a altitude of 480 km, and is flying between Japan and America. I suggest 14-7 rig system 1 to close, system 2 to open.


Going on everyone Sam here with Leighton's board charts We are ripping 10 bucks Tuesdays 10 bucks definitive Bowman baseball mixer number 199 191 that random team style there's a look again at your random results As always you can find these on the website under the results tab as well as the link in chat Get five to go on one-in-one breaking next everybody that means 10 spots are off the board 10 spots off the board 23 chrome choice we'll start with 23 at Bowman chrome at choice.  I don't know dude. I don't know Adrian Pinto first base auto for the Blue Jays That's one there Toronto will Warren Ville Warren for the Yankees first base auto and 2499 Gordon Graceffo refractor first auto for the Cardinals STL All right 21 chrome choice now God it's nice eggy Rosario on the first to 75 now an MLB air for the Padres yellow Charging bucks combo. Nice. Thank you guys JC correct first base auto for the Astros and then first refractor Ethan herne 81 of 499 for the Coveys That's on that Chicago. Thank you. Mr. Hobbs Jay Hobbs on that one. Appreciate you brother. All right We'll do 22 Bowman chrome sapphire now 22 Bowman chrome sapphire 22 Bowman chrome sapphire the compadon on this one too. Oh Kyle See a Papadia Get the magic to win more right now Daniel Vasquez and Gavin sheets like three dollars in the magic one damn West cat Brian De La Cruz Yasser Mercedes and Cattel Marta Wilford Varis dandy day and trot a upper pool house Nissan more bell the Leonardo Balkas are and Cal Raleigh First in this which is in dad Ryan Wreckley Joe Adele L.E. De La Cruz and Starling Marta Mandas Luba nice Roderick Arias to 99 Congrats. Yanks. That's dope. Let's go man That'll play that'll play just fine. Mr. Arias on the teal to 99 that would work just fine One of the best prospects in this entire we got an orange of Trey Sweeney to 75 just got traded That's on that one there at Yanks runs a contraria ziti. No, it can't be Like that one Samuel Muneo. It's my guy. Let's go. I give Kyle a break here for a minute with the sapphire and we'll go to 2020 Bowman go Is there gonna be a Poisson in here? I I would like to assume there's gonna be Bismac let's go Yeah, well I was gonna say where is he? Busy busy Busy Bismac Where's my 64 million dollars And all paper will be donated out of this everybody just so you know Where'd that go? During to ran Ryan Rollison gold shimmer to 50 for the rocks Question with the magic's worst contract ever you'd say so yeah, so it's for your 64 million you played two of them Philip Clark refractor out of 499 For the blue jays stay over at Grant Hill Grand Hill is pretty bad. Yeah No, but beyond those terrible. I'll give you that awful Drew Mendoza to 299 right now at least was hurt. Yeah, I mean Grant Hill. I mean Is that because he played because he played one good series and yeah play also paid him valentunas on the Raptors Hey, we're balling though. They were where is he no man? I mean, I'm going through the paper pretty quickly, so I may have already gone by one You're rooting for Poissons, I mean I guess you got to do it for the culture eat them You got to do it for the culture pure law up to 250. I can't beat him so As well join rara Nice Anthony Volpe first base auto for the inks. Let's go. There he is. Hell. Yeah, dude That's sweet. Take that of course the full sake Volpe very nice. I saw that chase I saw the video of that He'll out at all 92 yards of the drive game Bradbury then Guy sold. Thank you Tom with a choice spot. That's down to five to go Parley going yeah, very solid Volpe for sure y'all hits a huge three to cut it to 32 Gigantic three Cut it to 35 points. Who's that taking this fast? I know Brian thank you mr. J blazing commanders in both blacks Keith with a spot in choice. Let's go John Riggins auto. I'm all in that's dope. I'm in J blazing. I'm in I'm in Tim Riggins. It is a yellow Tariq school ball first to 75 Tariq school ball. Congrats Tigers We've got a 23 Bowman sapphire now 23 Bowman sapphire see a huge auto out of this Favorite football player John John Rick. He was he was the man dude Love me some John Riggins be la Cruz. That is a green Gavin cross to 60 Ray Balls romances and Matt Mervis. That's a good pack there actually Scoop Scoobos six feet really damn They don't really stinks that bad now. There's a Lafire, that's rough man No offense to Tariq school ball. He's not bad, but Thanks chains out man. Ah Kumar rocker nice one there for the Rangers. That's dope And I guess that does make sense Valid Roman Anthony purple Martin Gonzalez 25 a 25 That's on that Mariners Thank you, Robert picking up the Vends in NT love it. Love it. Love it. Love it Good stuff Robert got five to go breaking next Is One in one basketball one and plan the basketball. That is also an orange of Moises by a steros 250 for the Cubs and Leonardo Arias. I'll do 23 bowman draft jumbo now I don't think so Roman with a spot in one in one Joel with the Jets in number 34 Thank you guys down to four to go on one in one four to go on one in one Let's go man over two-thirds of the way there as the best appreciate it We can get that break on time. You guys are killing it.  I mean you guys are insane anyway I don't gonna be wrong, but That is pretty cool It's very with the twins in a bowman draft mixer. Thank you buddy. All right, let's do like I said We'll do 23 bowman jumbo now 23 bowman draft jumbo Can they're feeling a Jacob Wilson out of this? I'm on Jacob Show yourself Yeah, a little bit. It's kind of random I mean, I feel like Dallas is a very like recently has been a very like move to area though Max Clark first of howke and well-been friends see Scott now. You know to 250 Hurley and trivia is all refractors Yeah, all right, that's weird For my Shots and Wiggins and I'm sorry. I Never seen that happen. Of course. They're one of these mixers right after a sapphire box.  Oh boy class of 22 Hi for Lord and Kate that and yeah Kyle nobody got you Kyle got you Okay, this is back. Who's that? They want you to think yeah, right? And I'll be like ha ha gotcha Because they're fans. That's awesome. I love it. I love it J Blades, and we got rose gold coming up here Rose gold tie TJ Nichols that is five of ten for the race nice nice one there congrats raise on the first Right as intros there's some goodie eras to 499 Lucas Gordon Sabaos and Justin Crawford. I'm in Zach Thornton first base. I'll a nice one there for the Mets Rimer analog Floyd and Samuel the sio noble minor to 199 Bradfield Maya And True blue hunger butch to 150 this one there for the Padres Pete's and Luisa made 23 choice now Jamie with a choice spot. Thank you, buddy. Ah, you missed it Anthony. We didn't hit one actually Yeah 23 Bowman draft choice. I guess there's might be some in 2020 Bowman Bowman draft like a Goober guy myself Rock rod into 150 it's one there for the Mariners that is a first base auto Johnny for a mellow another nice one there for the Mariners For it mellow and then a hunter haze to 99 green lava Green Yaba All right, 2020 Super Jumbo. We got everybody get a four to go on one and one breaking after this guys four to go on one And one rock with this Aussie McCambley to co-aroby Kirstad first See Abrams to 250 nice refractor Heston Kirstad Going to the Orioles congrats on that Orioles I was gonna say yeah, I tried to play it off that I didn't see it But it's off course get that into a mad congrats on that Purple Jeff Criswell to 250 Bailey grossions Bryson Stott's Riley green No, they don't I really don't I'm assuming they're gonna trade like one or two of them away and get some stupidly good pictures like it's gonna be so annoying Robert plus on there we go first of all favorite. Let's go. Come on. There's a plus on base, too Let's go candler that's Bailey. Let's go dude Yeah, let the hate pour in everybody PCA And by all the hate I mean let the hate from Vaughn pour in Strider And Levi Prater first base order Hey, I literally turned my phone down to volume one for that out first Hey, you were rooting for Busan earlier. Yeah, I was mistaken Go back and change that. What was I thinking? Well, well many laps of judgment there Lomgrin Volpe Three to go three. Oh my god. It's insane, dude.  Thank you, buddy. Chris W with a choice spot We are like almost sold out on choice as well and T down to 12 to go now That's the most spots we have left today is 12 in freaking credible Incredible man. Cavalli and Austin Hendrick Libertor Quinn caught in Nick Lofton and Levi Prater true green to 99 second Levi Prater auto the Cads Three to go in one-on-one basketball to a true blue coming up there That is a Jackson Miller to 499 Strider Bishop Walker first Westburg first Austin Wells first Foskew Rushman base again Base to start us off. We've got Hendrick Vukovic Lutz and Jackson Miller Schmidt Take hence Like in the gold gold first to it is Milan Tolentino 250 Sir and Nick York to 150 that would have been a massive at release day Congrats on that one blue wave for the Red Sox still decent prospect Blue wave to 150 that would have been that would have been a bomb Mr. Charlie P picking up these Steelers in both 33 and 34 pinning black. Thank you buddy. Don't love the team you picked But thank you for the sport Do appreciate it very much true Romo first to 150 that's my same high school's Mitch Hannigar Huh, I've been Carter Zach Britton Sick, let's go Let's go Nick York was that was yeah, it's not that much to say about evidently not now Aaron Shortridge Three to go one-on-one basketball break in next ladies and gents. That is awesome. Appreciate you guys in Wogo McMahon PCA Garrett Mitchell first pork first Zach Deloach to The Mariners base autumn nice one there. Congrats on that madness Mr. Robert B with a mosaic choice spot. Thank you, buddy. That's pretty much gone. I think at this point I don't know if there's any more spots in that available 19 Bowman draft now 19 draft jumbo It's a fun one man. We'll finish with deep in Finish with some deep in everybody See a banger out of this Hold up orange chrome carol out of this not non-auto, but still yeah kind of nasty That that works all day the day first To 250 is Lake Walston and Brennan Malone Isaiah Campbell to 499 day in Dunning Ryan Nelson first base auto for the Dbex That's on that at his owner Bryson stop first Three to go on one-on-one is kind of insane man kind of it make it freaking to Scott F With a spot and the bucks and NT. Let's go Scott my baby Appreciate you our Florida brethren Trajan Fletcher Spencer steer first. I know he's a twin Nice green paper Josh young first to 99 Grats on that one. That's awesome Good stuff Rangers Reese Hines Two left in one-on-one basketball everybody on freaking believable Veerling Ryan Garcia to 99 green true green auto for the Rangers Still one in choice one to go in choice. Thank you one to go in mosaic choice basketball or football everybody To imagine that will be gone relatively soon on sooner side and then 11 to go on NT or 12 to go on 11 rep 80 First green Kendall Williams to 99 a lot of greens in this tea swag this on Brown Yeah, I know right Make that make sense Ryan Jensen and Gabe Kissinger Adley Victor Victor Mesa and Neil said I will take the last spot. Thank you, buddy Oh, Neil Neil be closing us out on Mosaic choice. Thank you all Davis when's the when hell? Wenzel, I guess I don't know. I say Campbell had a malfunction there for a second. We've got mr. Procopio with the flawless spots Thank you there, mr. Chiwe picking up some Red Sox definitive's Kurt with a flawless collegiate spot.  That is a Andrew Schultz true blue to 150 on the base Lays Alexander Keanu Kavako Lewis Glen Allen Hill Davis Wenzel, of course, it's gotta be the guy I can't pronounce nice one there for the Rangers to 499 Why wouldn't it be? Again, two to go one-on-one everybody two to go on one-on-one basketball This is your back Good Anderson. What's up? This is your back Shay Langlears Riley green Let's go first your fracter. All right on it to defend everybody. Good luck 23 definitive baseball See something crazy See something crazy two frames To golden frames Yeah, three ranger autos in that. It's kind of wild actually that is a David Ortiz 25 and 30 That's on that one there Red Sox 30 We've got nice one here for the Yankees Anthony Rizzo is gonna be two of 15 very nice Louise picking up the Panthers and Jags. Thank you, buddy Chul hem with a spot in one and one we're down to one insane. Thank you Joel That is gonna be five of ten on the purple Kyle Schwerber three colored patch on Nice one there for the good ol Phillies Rookie out of for the Marlins is gonna be a Max Meyer 36 of 50 Max Meyer Max Maya the hawk Andre Dawson 13 of 40 Grats on that one there Cubs Two colored game use Jersey on Eight of 25 will the thrill will Clark go into the Giants You've got a George Springer 22 out of 30 That is going to the blue jays on the game used patch auto 22 of 30 and Last frame is gonna be Mike Piazza one of ten going to the Mets nice one there new at York Mets Very cool great cool Brad E. Selina south dude on belief Thank you guys all for selling out one one. I appreciate that Not the best box of definitive I do apologize on that that was not a good box So I Again happened the other day with a really bad case event. Yeah, I apologize. I feel I don't I don't like that I don't I really don't I wish I could go back and we can go back in time and pick a different one believe me I would All right start with our color. We have to 60 Gavin Cross To 99 Kendo Williams Josh young Roger Garia to 99 voices by a stereo straight. We need a 50 Milan Torrentino 250 is dual for the DBACs Ryan Rawison Martin Gonzalez to 25 TJ Nichols to 10 That is going to be Anthony Rizzo David Ortiz autos of Ryan Nelson Zach Deloach Levi Prater Johnny Farmello Zach Thornton Luke Kieschel Kumar rocker JC Correa Adrian Pinto will Warren Davis Wenzel Philip Clark Ethan Herne Gordon Graceffo to 150 Brock Rodden Nick York Homer Bush It's a 99 Ryan Garcia Levi Prater Hunter Haas to 75 Tariq Scoobal Eggy Rosario to 50 Max Meyer to 10 Kyle Schwerber To 40 40 is Andre Dawson to 10 Mike Piazza to 30 George Springer to 25 will Clark We had Heston Kirstad to 499 and Anthony Volpe on the base auto That will do it for the break everybody. Thanks again for the film coming up next is one in one which is sold out


how to clean the patient's dentures and what to tell them, how to clean them when they're at home. So the biggest thing is, yes, they need to take out their removable dentures at night. Whether it's a partial, a full denture, two full dentures, it doesn't matter, needs to be taken out at night. You will have patients that say to you, no, I'm not taking them out at night, I'm not sleeping with no teeth.  Under the dentures needs to be able to properly heal itself and get that air. I mean, it's not air, but it just simply needs to be able to not have an appliance on it all day, all night. It needs to properly be able to breathe, okay? So that's what I tell patients. If they're not taking it out at night, they could develop cold sores, they could develop inflammation. There's so many things that could be happening underneath. They need to be taken out. As a side note, if I have patients that just simply say that's not happening, then I tell them, then you need to be taking them out sometime during the day. Do you watch a movie for two hours at night? You need to take them out to allow your mouth to have that space to heal properly and have it be no issue. So the patient needs to be taking them out at night and they should be storing them in a closed container with a denture solution or a tablet solution with water, that kind of thing. That helps to get rid of that bacteria and helps to clean the denture. So in a closed container with solution and water. Now they should be cleaning their denture before with a soft denture toothbrush and toothpaste or some sort of like dentures paste, but it cannot be abrasive. So something non abrasive is the main thing. I have patients that want to use soap. I let them know toothpaste kind of makes more sense, but I guess some toothpaste is considered abrasive. So if they want to use soap, just make sure it's non abrasive, but how do you really do that? I don't know, but make sure that they're rinsing the denture afterwards because you don't put soap in your mouth for a reason. It's not meant to be in the mouth, right? So that's what I tell patients as well. And when they're brushing the denture, they must fill the sink partially with water. So that way, if they're cleaning it and the denture slips out of their hands, it's not going to crack or break because it goes into the sink with water or a towel lining the sink, something like that. So if they mistakenly drop the denture, it does happen. It's not going to break because dentures are very expensive to fix. So that's something I want you guys to let your patients know. So yes, it is okay to submerge them overnight with a cleaning solution. In some textbooks, they tell you not to do that, but in the most updated one, shoot, I forget the year, but that is still what we want to do. The main thing is it needs to be done at night. It needs to be cleaned every day. There are denture solutions. There are extra soft like denture cleaning appliances. It must be done. If the denture isn't being cleaned, if it's not being removed at night, think about the gums underneath. Think about the patient's mouth underneath the dentures. They're going to develop sores like probably plaque. Stuff is going to collect in there. That's a lot of bacteria, not good. They should also be taking a very soft brush when they take out the denture and then cleaning inside their mouth as well because their mouth still needs that cleaning factor to it. So let me know you guys if any questions. This is very important and I'll see you guys in the next one.


Tom here from Warren Systems, and this video is a little bit different. I need to do this video about the Cisco Business Dashboard because I'm reviewing some other Cisco products that support the Cisco Business Dashboard. But the big but here, I like doing videos that are tutorials that teach you things like how to set this up or how to get this going. And yes, I'm aware I do a lot of unified videos, but I've also done a video on the Aruba Instant On gear. I've also talked about the ingenious gear, and some of those have their cloud controllers that they tie to. But the question comes up all the time, what about a self-hosted controller? And Unify pretty much dominates the market in this next one down. What about TP-Link Omata? I've done a review of those. I think the Omata is well, they just copied Unify and made it cheaper. But I don't feel like they've up security. Matter of fact, I don't really trust their whole security, but I'm not going to get too deep into that as a topic. I just don't know how good of a product it is for any large scale deployments. Also, I don't know anyone who's done Omata at large scale. Now, I spent some time on this a few months ago, because I did a video with David Bumble, and he connected me with some Cisco people who sent me the Cisco switch and Cisco access points that support the dashboard. And this dashboard is self-hosted from Cisco. You get free 25 licenses to put 25 devices inside the self-hosted dashboard that can manage them in a similar way to the way Unify dashboard works. So I wanted to really give this product a look because this is something that I think would be interesting to my audience and interesting from a, hey, can we look at a Unify alternative? And Cisco's a pretty big name in networking. They have the resources to build a solid, well-built product. But I don't really feel that's what they did here. And that's where this video goes into a little bit of a rant. I spent some time on it. And then I set it down because I couldn't get it working. I thought it was just me not understanding Cisco. Then I really took the time to reach out to a lot of friends who also tried and couldn't get it working. And they were Cisco people, not Unify people. Matter of fact, they were trying to go from Meraki to looking at this and found the Meraki platform better, was their opinion. One person had messaged me that they hired a Cisco consultant and spent like a month working on this. And Cisco never, they got it further than I did, but didn't get it working to where they thought it was a good product either. So then I did a post on Reddit and no one really had any good comments on the Reddit post. I'll leave that link down below. I just did that the other day. I just wanted to try to do what I feel is some level of due diligence before I say this thing isn't that great. The first thing is the documentation is not wonderful. It says use version Ubuntu 16. And that's obviously an unsupported end of life version. So I tried it with 22 and that didn't work. So I went back to version 20. It does work with 20 Ubuntu. So that hopefully will save you a little bit of trouble if you're trying to get this dashboard deployed. I will also let you know that the minimum requirements of four gigs of RAM is not really a minimum requirements. I would really recommend six or eight gigs to get this running because four gigs of RAM causes it to chug and take forever to start. Speaking of taking forever to start, one of the other quirks is it takes seven minutes from the time the system boots, then the system goes idle for seven minutes and then it starts. I don't know why, but that creates confusion where you think the dashboard doesn't start because it gets stuck in a loop saying Cisco dashboard initializing. It sits there for seven minutes before whatever it's doing for those seven minutes at almost no processes running a very low load on the CPU before it starts. And I've tried this on some rather fast AMD new server equipment, even in the cloud, and still didn't work. The forum posts that got me the furthest were the ones that basically said, Hey, it's putting the dashboard settings doesn't work. And Cisco engineer said, try this, try this. Then someone had posted, Hey, you got to turn on SNMP, which is disabled by default on the switches, which then at least makes it reach out to the dashboard. I don't know why SNMP being on is what causes it to reach out to the dashboard. But Hey, I did learn that going through there, but didn't find that in the Cisco documentation. So I went through a lot of these processes. I found nothing in the Cisco dashboard event log that ever led me to a clue as to why things weren't working. I could have absolutely reached out to Cisco because they sent me this stuff. And they probably would have loved to talk to me and, you know, walk me through as someone who's got an audience that talks about networking gear and held my hand and done a whole setup demo for me. But I don't think that gives you the people watching this the best experience because I wanted to experience more as you would experience it. Once it liked to set this up, spin it up in a cloud instance, it does have let's encrypt that which they have that embedded within there. So try it that way too. And didn't get me any further. Well, that means far as I am here is making this video. So I want you to leave your thoughts and comments down below on this. I'm going to leave this video as a reference when I do the reviews of the switches and access points when people ask about the dashboard or when I reference that. Yes, it says it supports the Cisco business dashboard for, you know, managing these things. But here's my video on that particular topic. So I'm going to stop ranting right here just so I don't make this video really long. If you have a better experience than I've been able to find with the Cisco dashboard, leave your comments down below on that. If you have a link to some easy tutorial on getting this set up that I was just unable to find by going through and reading the Cisco documentation, DM me on the socials, hit me up in my forums, those are great places to engage me on that. So I'm curious if any of my audiences had a better experience with this. Any of my friends who are also using Cisco products, so they are more pro Cisco than me didn't share that experience with me. Even as I said, they didn't have a great experience setting up and testing it, but nonetheless, I will take this video down.  But I've configured so many different networking devices over the years, and it's a lot more than the ones I've reviewed on my channel, because sometimes we get contracted to do jobs. So I've worked with even like extreme networks and Arrow Hive and all those other words, I know Arrow Hive became extreme, but those seem more intuitive to use than this. So this stuff really kind of drove me nuts. Like I didn't have to spend time on engineers with any of these, even the Aruba stuff that I reviewed, or even the little modest stuff. I just followed the documentation and it worked, even in Genius. Their documentation, I commented, wasn't that great, but I got it all working. I can muddle my way through some networking. I've been doing this for a long time. So why the Cisco one? I feel defeated. I couldn't tell if it was just me. I don't want to seem biased, but those are my thoughts. Let me know yours. Thanks.


Dear students, in this topic we shall discuss the transport of carbon dioxide in blood. You know that cells release carbon dioxide generated by the cellular metabolism into the intracellular spaces. Cells say carbon dioxide intracellular spaces may dissolve in the tissue fluid which surrounds the cells. This dissolved carbon dioxide then diffuses into the blood capillaries, where it enters the transport system. Carbon dioxide is transported in the blood from tissues to the capillaries of the lungs. The final route is to come to the lungs capillaries from where it has to diffuse out to the environment. This transport of carbon dioxide occurs in three different forms as carboxyhemoglobin by binding two plasma proteins and as bicarbonate ions. So there are three methods to transport carbon dioxide into the blood. We will discuss these three methods in detail one by one. The first we shall discuss the transport of carbon dioxide as carboxyhemoglobin. Hemoglobin's protein, that is, globin protein, its amino group binds carbon dioxide to it and as a result carboxyhemoglobin is formed. About 23% of carbon dioxide is carried in this bound form with the hemoglobin. 7% carbon dioxide, blood may be binded with plasma proteins and transported while the major portion that is 70% of carbon dioxide is carried in the plasma as bicarbonate ions. How do bicarbonate ions form? We will discuss this in detail. When carbon dioxide is included in the blood in the capillaries of the plasma, it combines with water to form carbonic acid. Carbon dioxide is added with water to form carbonic acid. This carbonic acid is an unstable compound. So it splits quickly and it ionizes to produce hydrogen ions and bicarbonate ions. So till the blood comes out of the tissue, the carbon dioxide is mostly bicarbonate ions. So the carbon dioxide throughout its circulation is in the form of bicarbonate ions. In the lungs, all these reactions occur in the reverse order. That is, bicarbonate ions combine with hydrogen ions to form the carbonic acid. The carbonic acid splits into water and carbon dioxide and the carbon dioxide thus generated in the lungs diffuses out from the capillaries to the alveolar space from where it is delivered to the environment through exhaled air.