So I'm here now between you and your lunch and maybe let's do another session of stretches That's kidding Well, I'm I'm from your friend and card. So it comes more naturally. I'm not here for that I'm here today to talk about As a practitioner, we're often faced with the choice of what database to choose for building that mix system of yours right and and what I want to share here is essentially learnings from my experiences from 2010 building other than building infrastructure services at lip-guard and where I work currently which is cure for 10 and Health phase about building data stores for for health care, right? So the there's a problem with with my title, right? It says sequel and no sequel that that's a very common accepted way of referring to relational and non-relational systems because sequel just simply says what is a query language that? you use right it doesn't define a class of systems and and we'll get to that but in general so the intent is Help make our choices between relational and non-relational the new sequel no sequel Whatever you want to call it or whether you need to choose a polyglot data stores to get your job done So let's start with the landscape this again from one of the research Outputs so you see this it's a the purpose of putting this up is saying that this your choice is just way to get right between in premise and and hosted systems and roughly classified between relational non-relational grid or caching zones and some of them being in premise and and Let's say hosted so that really leaves us leaves us void for twice But the harder problem is with every single vendor out there claiming that their solution is the best for your Choice, how do you make that decision of what database to choose? Okay, so let's start out with some very basic ways of how you'd start looking at Database choices and this is primarily my talk is going to be more Oriented words in premise choices right with some things that you can pick even from from those two solutions So let's start off with some of the over the board of the very obvious considerations that you make So first and foremost is the kind of data manipulation Language or the sequel or no sequel choice that you're trying to make right so a query language of sequel it might seem like That it's something of the last few decades But trust me it is very relevant and why so because even spanner there's a few recent paper that says how spanner is becoming a More sequel system right so sequel as a query language of choice. It's not bad Right, so you you want to make your choices of saying hey is my data more and amenable for sequel like queries Now that's one choice that you would make or you would say is it most suitable for a key value style operation, right? get over or Even differently if you're looking at some kind of draft very capabilities and in my talk today I'll be able to give you examples of some of these cases from real life where you will see that it is quite relevant And it's quite natural to to look for a query language support that you would like to have and Another dimension is to look at bulk processing both in loading and data export and this can be for any number of reasons You're trying to see your database. You're trying to export the data out. Take it somewhere So it's good to get a first-hand view of saying is that database choice of yours going to give you bulk data exports or The next one is asset properties, right? So asset Let's look at one auto asset properties.  What does that mean to database choice, right? So if you look at a Thomas city, it talks about can be roughly translated into transaction support Consistency would talk about Ordering whether you're going to be Across if there is replication is it across replicas is it going to be eventually consistent? Is it going to be strongly consistent? Data stillness and also durability talks about how durable is the data and can it survive crashes, right? So now when someone says that is it asset one dot o compliant Then you can say that you get the following properties or you can expect the following properties from your data store Now more recently there's another proposal or in fact implementation of another Set of properties called the asset 2.0 How many of you have heard of asset 2.0 here? Right, right now asset 2.0 is more about his choice when typically is a matter of choice when you're trying to achieve scale and more precisely when you're trying to achieve higher throughput, right? And in an asset 2.0 system where you say that a data can be Across replicas can be associative commutative and the data gets relayed in a manner that's idempotent and and the data nodes themselves are distributed, right? What does this mean? It typically means Transaction support is a little limited and what I mean by this is if you see in the asset 1.0 world You could say that multiple inserts across multiple tables Sorry insert across multiple tables in a single instance is transactional, right versus in a 2.0 world It is probably limited to saying that inserts only to specific records are transactional not saying that there are in databases that offer that But typically right it means that transaction support is is limited There is a relays relaxed ordering, right now One of the reasons why Spanner has all this fancy infrastructure for GPS and atomic clocks It's just to guarantee ordering and because they claim that they're a globally consistent Datastore and you want all replicas to converge and converge in time Right, so with relaxed ordering you get higher throughput and that also leads to another type You can get that up called CRDT's which are conflict replicated Sorry conflict free replicated data types and there is ready support for this in a in a in a open source system like we add Right where those conflicts get thrown up through the application and application can then solve how to can decide how it wants to resolve those those conflicts and at least once delivery guarantee I Very recently read that Kafka supports exactly once delivery semantics that is Very hard or pretty hard to achieve right just guaranteeing at least once delivery semantics itself is is is fairly complex Right and what that means is with at least once delivery semantics What do you get us mostly eventually consistent data stores, right? And this also can lead to higher availability. So you would start considering 2.0 Properties when you're trying to achieve Large scale, otherwise if the 1.0 properties work well now, that's fine Moving on What do you expect in wire protocols, right? So wire protocols most of them are custom protocols on top of DCP IP some of them work on GRPC and there are very few that even work on on say it's HTTP Not much of a material difference in when your choice in the choices that you're making but it's good to be aware of What it is, right now support for popular database protocols and why is this relevant so if you look at Cockroach TV they give you Support for being used by other postgres drivers and this is primarily because for that you're trying to make a shift from Postgres to cockroach TV. You could pretty much seamlessly use it and and not make too many changes on your application later Right, so it is good to be aware or let's say if I were to consider cockroach TV I would say that hey it supports postgres and I've been using postgres So it's good as a matter of choice as an end user Right or for that matter memcache for a few years. It is always Couchbase has been supporting memcache D as a protocol Right, so you could talk to couch base at the back end but using the memcache Or for that matter standard interfaces, right? So in the Java already JDBC is like a standard and you have JDBC for all kinds of interface Right Apache Hive has a JDBC driver. You have for fetch means you have Phoenix which gives a JDBC driver Or if you look at witness, how many of you have heard of witness? Any of the Google YouTube guys, okay, so witness is a my sequel scale solution built by YouTube and Google and We came across this in Flipkart when we tried to scale my sequel and this does give you a sequel interface on top of an under the underlying my sequel base storage, but what it lacked was a JDBC driver and While we are in Flipkart our team built and compliment contributed a JDBC driver for witness So it basically allows you to scale my sequel Impromise so it means that across a number of instances of you're trying to build any of your custom sharding solutions This is a another viable option, right? But just a case in point where just building that JDBC support opened it out for wider adoption within our company where most of our instances where you've seen my sequel, right? So you could say that okay, it now has a compatible JDBC driver and then you can just shift on to that So it's good to look for that as well. So on schema So I sometimes hear this right like like schema is evil, right? My system is not able to scale because it is it is relational It is very schema defined and therefore it's a problem, but the truth is if you really look at Number of systems that really need schema less Backends that you can count them like they're very few Right. So either there's past missus past metric or you're trying to look to build entity value Entity attribute value storage like for example, if we started off in Flipkart our catalog used to be Something if you're trying to store Let's say a diaper and an iPhone 6 on the same catalog system We started off with an av store, but then just that couldn't scale and then later we build something else Right. So for these kind of system arguably you have a need for a schema less system and you say that okay There are a lot of changes so frequent changes you would go and use such a schema less store, right? So I'm here there might be fans here or document databases like MongoDB and they would argue that it works very well For this kind of requirement, right? Now, what do you lose if you don't have schema right and and very interestingly though? I think as of 2017 Mongo has unknown support for Schemas in their database, right? Why that is so because in the absence of schema understanding the data becomes incredibly hard and What becomes even worse is you have the wrongly typed data going into any of these Fields and then when you're trying to make sense of this data when you're querying it becomes next to impossible So you're you're actually making those the hard You're doing all the hard work when you're querying the data. So schema itself is not is not bad You'd be able to be near to really need to be convinced that if you're going for schema less wire You're going for schema less and be prepared to pay the price for going schema less or there's an in-between part So for the ones which use column data stores They require and and you and you require column indices for example, right? So if you look at a database like Hesbays or let's say Cassandra, they allow you to define indices on top of those column families Why because you're trying to query them you're trying to Make that more efficient then this like kind of an in-between world where you're trying to optimize on on both storage It's a schema. Therefore is it's not even and it is perfectly okay to Expect or look for schema support in the database that you're looking for Cap theorem, right? I'm sure by now all of us will be aware of what's kept here But there's an interesting point about not taking it in an absolute literal sense And there's a debate about saying is CP really achievable or not and and so on But what I like is in one of these papers and those references are there like I found that it is one good example of a fundamental trade-off Between safety and liveness in fault-prone systems. That's exactly what cap theorem. That's right It's trying to define when you say safety it's talking about consistency and liveness It's talking about availability and when you say fault-prone systems It says that when network patterns can up can occur, right? So that's the way To look at it in its in its if you just look at the conjecture that Proof of proposed it is too simplistic to say one is achievable a bull versus Not and therefore there's like kind of two simplistic at face value. There are enough examples where Anyway, CA is impractical because you if you're in a distributed world if you don't go beyond a single node then You know the CA is pretty much But cap availability and cap on consistency is actually a spectrum and is never and not binary and I'll give that as an example right, so if you look at AP reads and AP writes now AP reads in a there are enough examples, right? So you can say that I have a cache so long as the entire system is available It's partition tolerant and I trade-off consistency Acceptable. What's a good example of AP writes? Right I've seen one very good example and probably that affects all of us here is I've read this of the number of users who use Uber and I know their friend of much of you were friends here So they I believe they built a system for for captioning the rights when you complete a right Right when you complete a right when you probably swipe and you say that you're completing the right What is very very important is to capture that right because there's Customers are going to wait the cab driver is not going to wait It's very important that you capture the right and the right can go to any popping up among the available nodes and with mechanisms like hinted handouts finally the data Reaches the eventual state you may not be able to read the data right away, but the right is super important. So AP itself is that we will see that in these two examples of a cache scenario versus like a Uber like example It is a spectrum right and so therefore cap even with cap you go and critique your data sources to see what does it that matters to you Right, so it's it's never a binary Right, and then with that you define your application trade-offs right you impact validate impact on your NFS latency I can give you many examples again if I go back to the Pipkart example, so we have systems where like even on pricing well not so much on pricing But I think definitely on offers we chose to have Availability over over consistency right and we build systems for that and and that's perfectly all right And you will define those trade-offs when you're trying to critique it using cap and that also serves as a good starting point for Considering right Polyglot persistence, so what I mean by polyglot persistence is something like this So this is from So in 2010 2012 when we build the system be when we looked at the data Here so there is the raw biometric data the enrollment data Which is roughly now. I think at 1 billion enrollments. It's probably about a few petabytes Right so that needs to be archived for seven years So that's it's on an NFS and I'll talk about why an NFS versus an HDFS So this is like an archive store the same data first actually comes into HDFS for very high throughput processing The biometric extracts so those are for you who have used your other authentication The authentication is happening against HBase, so that data is in on HBase the master other data is on mysql We have indexes. It's no longer mongo's. It's a little dated But that's again mysql and then we have a query on top Which allows you to do all kinds of searches I'll write in a very secure way on like if you lose your enrollment slip and somebody doesn't have it How do you find your other record, right? So it's the same data or rather extracts of it which sits in a in a highly polyglot Stole and the data progresses through various layers another Concept here is about it's called CQRS only if you've heard of CQRS So it's basically means command and query responsibility separation. So which means that yeah in terms of operations It's like write and get read. Yes, obviously operations are separate But what if your data stores themselves are separate and CQRS essentially promotes that and a number of systems today exists That allow you to realize this and I think the go if I'm right among the more recent frameworks allows you to Gives you first-class support for CQRS Basically what what it says is saying that you have rights going into a data store and from there those those are commands And there is a continuous Update of those changes going into a read store so that you can serve the reads of a completely different Infrastructure and what you're seeing to the right is essentially the system that flip cut has on its for its catalog and this system at peak has served like 10 million reads per second Right, that's the read pipeline and what you're seeing at the bottom which is highly replicated highly distributed cluster sitting on readers and and with virtual buckets managed By the application layer while the rights or the whole data that gets stored sits on HPA is elastic search and gets orchestrated through a through a right pipeline along with you know, right repair happening across these clusters so this is one example of of Basically using the polyglot store Applying techniques of CQRS, right? So that's another Another one where without you having to engineer it yourself now There's an example of some work that I'm currently doing at QFIT, which is we are trying to build a knowledge graph Which will eventually be used for such things like an automated symptom diagnosis System and which can even get into can aid the doctor in in in disease analysis, right? I hate the use use the word AI, but this is basically a data driven diagnosis system Which with no human intervention and that talks about first establishing the graph of the sorts Which kind of says hey, you have flu and flu has conditions like flu as a condition has symptoms like cold body ache headache and so on right so very Naturally represented as a graph and what you're trying to do with this and we built it and this uses Titan as a storage And we chose Titan for multiple reasons right one is It could be packed with Cassandra and Cassandra as we know it is an AP system. So very nicely Maps with what we're trying to do here give more than the staliners of data. What we care about is availability of data works well for single query hops like what we're trying to do here, which is like it once in flu you're trying to travels to let's say cold or body ache and headache and For a system like this you can create very interesting Solutions on top, but here with light and the point I was trying to make was with Titan the underlying storage You have a choice of either Cassandra or Hitch base and for indexing it's on elastic search, right? So it's again polyglot persistence under the food you didn't make a choice, but it's a case where it isn't a single bundled Storage engine so couple of other things to look at this performance benchmarks right in general benchmarks by Vendors are lies lies and more lies Right. Why because they obviously they have a job to sell their databases So they'll try to take the most ideal case of databases and then you know workloads and try to prove that it's right for them But I found that independent benchmarks are very useful like there was a reason benchmark on on graph databases And somebody proved that if you can actually implement a graph For certain workloads on let's say a postgres without even going towards a let's say a Berkeley DB or let's say I think they even pick Neo4j and tighten with Cassandra back in those graph queries actually work better with a relational Datastore at its assets underlying storage, right like Facebook tau Database for example, it's a graph database built on my secret So it does help you might still make your decision or a choice to go with whatever right like I Even after the including this report I would still go with titan over Cassandra, but Why because I don't have to build the underlying graph storage layer on top of let's say my sequel or postgres But it's really good to be aware of these kind of benchmarks and use them in your in your choices operations and maintenance This is interesting right so you look at With all of their engineering pro is they didn't go and build a storage layer for tau, right? They went and build it on top of my sequel same with the LinkedIn guys They build espresso and build it on top of sequel and if you look at their engineering blog and those posts will show you that Both of them built it on my sequel as a storage engine and why do they do that? They say hey, we have expertise managing my sequel as a storage engine We know what to do when you have to replicate data when you have to restore data So we would rather use that to build a storage as the storage engine and then build our whatever layer on top Right, whether it's a document dv in case of the LinkedIn espresso or let's say it's a graph database in case of Facebook and the other important thing is support support either it's paid or whether it's a community and community where Where if it is paid whether it's single-vendor versus multiple vendor and community again the size of the community matters a lot, right? Though you would see that a lot of the databases would claim that they are open source But the only company supporting it would be the guys who created it, right? But that doesn't that really is not doesn't speak too much of a Large community the fourth one is a hosted service right so coming to this So when we chose Titan with Cassandra's a storage Titan interestingly also has Storage implemented on top of Dynamo TV, right? And when if you had to deploy and operate on AWS, then I already have a service that can be managed by someone else Right, so that's a matter of choice in a public cloud. So it says that hey, it really works Right, so so that's some again to look at when you're making the choice You're from here will move on to some of the under the hood consideration, right additional things that you Generally look for in addition to what we're the fairly obvious things That was that database part right so between a relational database and a column the database it helps to understand How is data stored internally and in the storage layer so relational quite naturally if you look at it data stored? Where all the data in a row stored together? So which means if there's going to be a disc seek or transfer it's going to operate at a record level Versus in a column a store all column data stored together and why so because when you're trying to do OLAB queries You're trying to do group by you're trying to do any of those count and any of those aggregate queries More suitable for for a column of storage and that's why very very likely that you'll see most of your OLAB databases Having making a choice of using a column our storage at the underlay layer, right? And it gives better query compression and so on and so forth It definitely helps to know what is the underlying storage engine or the water the storage layer look like for the database of your choice It also comes with a few trade-offs, and I have a case in point like suppose you're trying to do a You're trying to build a data store like let's say Other is fine, but if you look at that data you're trying to retrieve a record at the time a relational store because it uses a Petri kind of a store is probably more efficient than a column a day Document so we have four classes right so you have relational column a document and key value So document is essentially a subclass of the key value store data is organized from a TV to a collection to a Document it sometimes have challenges in in optimizing storage right because they don't have a data dictionary So it is it becomes rather hard to define. How do you optimize it first at a store storage level? Now comes a key value stores oftenly ran often ram based and you see that with key value stores If you really start looking deep how many of them give you high guarantees of data durability And I wouldn't expect them to give that because they are by design They're meant to give you very low latency reads right you're saying that Sub millisecond or sub two millisecond reads they largely try to keep the data and memory So which means then then when you do a write it's quite likely that writes get batched and then get they get flush to disk And if you say replicas if you're trying to say is an a i require a key value store, which is Going to give me very high durability You know guarantees where the durability is down to disk and is also distributed then imagine the cost of doing that right It has to do an rpcs send the data across nodes and also do a flush to disk Most of them while they do probably might give you the way to Tune that kind of durability key value stores are Better suited for mostly in-memory read writes with kind of batched flushes to the disk So data organization now this is another interesting topic Where if you look at the number of relational stores they organize data data in more like of a b3 format and a more in more recent times would say a lot of these databases Trying to use the log structured format right and why log structured format it is for multiple reasons It started off as being log structure for having very high Uh throughput writes like like a hh base or a kassandra. They started off using a log structured formats for Doing the writes, but interestingly databases like even rocks db or level db, right use a log structured format The reason being most of them are built for storage on ssds and on ssds with write amplification and and your write cycles that you have Uh a log structured storage format is better suited and gives you more life as compared to in place updates That you would probably see in a relational store, right and log structured also means that your data is mostly keyed By the primary key. So that's why if you see a hh base or a kassandra retrieval by the primary key super easy secondary Indices even though they've they've provided the lookups are in just as fast. So we'll we'll talk about that later, but Uh, generally it's also good to see that what is underlying data organization on this Uh, you'll see more and more recent databases having, uh, you know ellison trees Next one is on replication and consensus. So replication is so if you're trying to see that you have a globally replicated Completely consistent database, then it means that you're trying to say that somewhere that the replication is possibly I don't know not read it in detail, but probably spanner replication is probably it is like sink replication Versus a number of the databases that we know uses a sink replication Right and number of replicas the number of copies of the data that you have guaranteed writes Hinted handoffs. So all of these are attributes that if you get to read about mostly the open source databases The white paper the engineering blogs for them You will get to see these common things emerging, right? And it always helps to make sense for the kind of guarantees that you can get from the database Or whether it's a single master read, right? Like for example, hitch base achieves consistency by being a single master of read Right, which means it's a single copy of data always Is is the read and write all reads and write just go to that On consensus it's used in leader election and I know that There's this talk of paxos. So now in on paxos if I say how many of us have heard of paxos show of hands please How many of us understand paxos Not me, right incredibly complex as a consensus protocol and Yeah, and and what you would see is that there are newer protocols like raft Which are also employed for doing this consensus and leader election. It does help to understand replication What is the kind of consensus protocol in use because you'll see that sometimes because of the wrong choice of a consensus protocol The database can actually be Can perform very badly or perform very poorly when it comes to the safety guarantees And if you care to look at it look at jebson tests again show of hands who's heard of jebson tests It's about Very interesting. Just read up jebson tests. Probably you'll you'll not sleep at night, right? You might have chosen a database and if you read the jebson test results, you'll see that. Oh my god What did I choose but the good part is what standard started off as just a critique of those databases Today you have a number of databases actually come and claim saying that my database has crossed as basically uh I hear to all of the jebson tests, right and there are even enough example Jebson basically started off by the work of one single guy kyle kinsbury So look it up and do read about jebson test results for for the database that you're trying to Running out of time. So, uh, you're also trying to look at data export and restore like primarily if you have Strong rp on rto, you know requirements and and a dr scenario Look for tools that that provide full export versus incremental Snapshot tools for restoring from export and all these things start to matter when you're looking at very large database sizes, right? Like multiple terabytes of data you're trying to optimize and you're trying to ship data like here I had a point about uh large-scale data migration So there's a reference of when we did the flipkart data center migration We actually took disks in a truck, right? It was the fastest bandwidth throughput that we could ever get for transferring data from point A to point B right, so, uh, so it does matter to look at these tools for for uh data transfer and and migration, right Another aspect is the meantime to recovery, which is really the time that you take to let's say promote a hot standby to a master Let's say in a mysql scenario and thought In bitters as an example is like a click off a button You can promote a mysql standby to a master by the click off a button Now that says something about how you can manage and keep your operations running, right? So it's good to detect failure and validate and promote to a new master or leader cost Disk memory ratios So going back to an aadhar again, we stored the data on uh after we moved out of hdfs and moved to disk because To keep such a large cluster operational the amount of compute that you would have to dedicate to hdfs is Is more so instead it is cheaper to move it to to an nfs filer, right? So it's good to look at those uh examples and the amount of data that you can hold in memory and the kind of ratios that you can have Now power consumption you will see that in very large data centers when they say that we'll give you ssd disk They're actually doing themselves a favor because it's it's more power efficient to run ssds than to run spinning disk, right? And if you look at glacier store and there are some references there Very very interesting like like the facebook the way they store photos Not all disks in the rack are even powered up, right? They try to optimize that because it's super Critical when you're trying to create such large dense storage Last one is on to look for some db specific optimizations If you really see you're trying to look at how effectively can you use memory and and reduce access to disk or optimize access to disk, right? So if you look at memory, so it all translates to data blocks or block cache buffer pools It's there are enough guidelines around How much buffer pool size you want to give to a mysql instance or in case of hbase? Like what is the size of the block cache because it reduces primarily reduces this guy? provides lower latency reads and also potentially lower latency because of high data locality Of reference, right? There are a few references To go read up more on that but effectively what you're trying to do is try to keep data and optimize for keeping data in In in in memory as much as possible and not hit this and if you do have to hit this techniques like bloom filters right saying which of those data blocks actually contain the data Either you have indexes or you have optimistic data structures like bloom filters, which again tell you that hey There's a good possibility that this data Exists in this block, but it can be you can get a false positive, but never a false negative Right, so these kind of optimizations and if you read again about databases, they'll say that there is support for Let's say in hbase support for bloom filters at a column family Right, and you know why that is for they're just trying to optimize on the on the disc seek and and the data blocks that you have to So that just a couple of things but in essence what it means is the kind of Leavers that you have in order to minimize the access to disc and specifically disc seek times more than transfer and and the kind of levers that you can You know employ as an user And that actually takes me to the end of this name definitely not a comprehensive list but a bunch of Things that you can look at both over the board and under under the board when you make your next database choice some references I mean It's there all over the talk. So interesting leads if you go and start looking into each one of them We'll be able to relate to the various topics that have covered in the last 30 minutes So with that i'm done open to any questions If anybody has a question, please raise your hand And we'll get you in line Wow, it's an entire auditorium without a single question. Oh wait, there's a question right It's almost lunchtime you could almost leave Hi, um, hello check at the last At the last here Can you hear me? Yeah, yeah, okay. So, um, I just have one question or I don't know more like a feedbacker. I want to ask So at one point you talked about lsm Structures, right and you said we prefer lsm For the better lifetime of ssd Because compared that to like in point updates in place of time place updates Can you explain how exactly that happens? I mean because With lsm you generally have a process that comes Along with it called the process of compaction Where you end up rewriting the files by taking deltas over again Whereas in place updates is all about doing random, right? Yeah So random writes actually results in right amplification, right? Whereas in when you do when you do the compaction the way you describe it in in an lsm It writes larger blocks. So the right amplification is significantly reduced The back sauce protocol we are talking about and where you said raft and xab are also maybe Might have listed as three protocols, but raft and xab are just variations of practice So we just need to keep that in so raft is just a way to simplify Back sauce Yeah, I just as an end user found it got too easier to even make an attempt understanding raft Back sauce maybe higher I don't know. It's so incredibly hard But the point more was to see what is the strength of the replication protocol So if a database were to come and tell me that They use back sauce for both leader and replication I know that those cases have done some very serious engineering work Whereas let's say I know elastic search used to use a replication protocol, which was very fault-prone And and that was came out in in the jet centers I'd like to thank you very much We will have a q and a


raise your right hand or repeat after me. Eyes, take full name. Eyes, take full name. You saw me swear. You saw me swear. That I will support and defend. That I will support and defend. The Constitution of the United States. The Constitution of the United States. Against all enemies. Against all enemies. Foreign and domestic. Foreign and domestic. And then I. And then I. Will bear true faith. Bear true faith. And allegiance to the same. And allegiance to the same. I will obey the orders. I will obey the orders. Of the President of the United States. Of the President of the United States. And the orders. And the orders. Of the officers. Of the officers. Of the officers. According to regulations. According to regulations. And the Uniform Code of Military Justice. Uniform Code of Military Justice. Oh my God. Oh my God. Do you feel pretty good? Yes sir. Shit. That should absolutely feel very, very good. There's a lot of people around the world. Look at the country that said that.


Everyone, save here, we're late in sports cards. You've been 22, Panini, select football hobby, six box, half case break, number 54, pick your team style, read off the list of our names and our teams. Onward G Patriots, Chris F. Saints, Dan M. Jets, Daniel D. Bills, Garrett C. Browns, James P. with the Colts, Jeffrey H. Steelers Niners, and Panthers. Joe H. with the Ravens, Joel B. with the Dolphins, John W. Lyons, Joseph M. Raiders, Capelle O. with the Bucks, Kevin H. Packers, Chiefs, and Commanders. Kurt W. with the Bears, Larry K. with the Titans, Matt P. with the Cardinals and the Broncos. That is Michael Z. Falcons, Rory C. with the Giants, Russell P. Charger Seahawks, Ryan C. with the Bangles, Sam A. Eagles, Steve S. Vikings, Vito C. Rams, Will M. Will M. O. with the Texans, Will Z. with the Jags, and William M. I. with the Cowboys. Good luck, everybody. Let's do it. Here we go. Box one. Nice, artistic selections. Bailey Zappi, right off rip. Super short print, nice one there for the Pats. Take that for sure. Canine, Silver Josh Jacobs, and Logan Thomas. That one should be fine. Purple to 75, Alec Pierce with the Colts. White, Silver, Isaiah likely, Ravens Rookie, and Damian Pierce. Desmond Ritter Rookie. Parsons, Silver Brand Nia, and Barry Sanders, feel the blow. What's up, Thomas? Joe Burrow, 52 is 75. Jumbo, Malik Willis, white jersey card for the Titans. Subah, Jack Sandborn, and Jalen Hurts. That is gonna be a Davis Mills to 75 for the Texans. We've got Harrison Bucker, Super Bolado, nice one there for the Chiefs on card, and Dante Forman, I love the Super Bolados. I need to get the Suggs, dude. I need it, I need it. Drake London Rookie. Redemption is gonna be Breesaw, Prime Selections Prism Signatures for the Jets, nice one there, congrats Jets. Luke Fortner, Tri-Colored, Jonathan Taylor to 249. Silva, Kade York Rookie, Patrick Zartan, Damian Pierce to 149. Silver, Pierre Strong Jr., yo, Pierre, you wanna come out here? There's a Rashid Shakid, light blue to 99. J.J. Watt, Silver Mahomes, and Fred Warner. Silver, Terry McLauren, and Chris O'Lave. Picket, Neon Icons, Silver Russ, and Chris O'Lave, Field Level Rookie. Last pack of Box One, Sauce Gardener Rookie. Silver, Traylon Burks, Silver Dolphin Cook, and Camakers. Box two, here we go. Can I pick it, Sensations? Silver, Adam Feelen, and Damian Pierce, Field Level. There's a Bloop, Deron Harmon to 99. The Raiders, Silver, Nick Benito Rookie, Ace, Garrett Wilson. Silver, Marcus Davenport, Field Level, to a tag of ILO. Silver, Seyquan, Tony O'Gibson. Gonna be T.J. Watt, 29 of 99, on the Sparks Jersey Guard, Bronze, and Steelers. Silver, Baker, and Luke Fortner. Tri-Colored, Terry and Davis Price, 249. Three of 99, Drake London, Prime Selections, Jumbo Jersey Auto. Congrats on that, Falcons. Drake London. Silver, Givante. Silver, Nicholas Petit-Farre. Well, also just got suspended for a game. Or no, maybe it was PED, something. I don't know, we got suspended for something. Remember seeing that, I'm like, I remember that guy from Select. There's Kyler Murray to 149, right? No, 199. Silver, Watson, PS2. Auto, Romeo Dobbs to 199. Rookie, Auto for the Packers. Apparently, I don't know if it was you I was talking to, it was you or Sean, and I was like, Chris Olave, Rookie. Apparently, he's like, Jordan loves go-to guy. Who, on summer leave? Who was? Romeo Dobbs. He's like, apparently, his go-to guy. All right. Talanoa, Hofunga to 149. Silver, ETN, and Dante Forman, and Camp, at least, and that doesn't really take that with a grain of salt, but. Yeah, but you didn't gain real good, go-to guy you trust. True. Purple, Jemo to 75. Jemo Draftings, Silver, Tyler Algier, and that's Stafford. Malik Willis, Silver, Sensations. Silver, Tegan, Quiriano, and Chase Claypool. Yeah, that's pretty common. There's some guys who have clean autos, but a lot of guys, yeah, a couple lines, maybe a letter, we're lucky. Or you get George Pickens, who's just a line. I like the color there, Tida. See, this is counter-intuitive. The idea of putting a filler is to replace a hit, so you can't pack search, but with this, there's a hit and a filler, so it's like, double negative. I thought the fillers were for like, to negate like, patch cards, not necessarily hits. Yeah, no, it's to negate patch cards, exactly. This is a tie-died patch card? I say a spiller, 3 of 25. Okay, yeah, okay. It's recolored RPA for the chargers. Dang it, filler. I know, right? See, no, because they're like this. They know that, right? You know what I mean? It's just like backwards. God, it's working against the purpose. Yeah, true. Kind of Walker. I've noticed that in a few selects. Like, see, there's a filler, but no hit in there, too. It's got more silver. Make you think there's something there, but it's not. There it goes. Kind of Walker, Lamonte Smith, and Malcolm, I know Aiden Hutchinson, that's what that was. Hutch. That is Tetsum and Ritter, fair. Jamin Ramsey to 99, light blue. Silver, Brian Asamoah, rookie, Daniel Jones. Jimmy the intern, man. Jimmy the intern, man. Yeah, he's a good guy. Michael Pittman to 199, right? Yes. Leighton Van Der Ash, 24 or 49. Purple jersey off for the Cowboys, XRC. Silver, George Pickens. Silver, Miles Garrett, and Deandre Swift. XRC is gonna be defense three, witherspoon. Javon witherspoon, right? No, Devin witherspoon. No, no, no, no. Will Anderson, Devin witherspoon. Tyree Wilson, that's who it is. So going to the Raiders, Tyree Wilson. Yes, Anderson first, Devin witherspoon second, and Tyree Wilson third. Defense three, that's on that there, Raiders. Tri-color, Cam Taylor, Britt to 249. Silver, Bilish Jones, and Channing Tindall. Tindall, Tindall. Drake London, Red to 99. Stingley, Silver, Cam Juergens rookie. J.K. Dobbins, J.K. Alvay. During the day of the prize. White, Damian Pierce, sweet level to 35. Silver, Watson, AJ Terrell. Joe Burrow, Silver, sweet level. Kenny Pickett, field level rookie. Stavon Diggs, 31 to 49 on the Jurrs card. Nice one there for the Bills. Daniel, I believe that is. Silver, Drake London, and Josh Jacobs. Last pass here of box three. Will soon be a memory, Donnie. Yup. Silver, Brian Robinson, Jr., and Cooper Cup. Wow, Patrick Mahomes color wheel. That is nasty. Hell yeah, man, that's going to the Chiefs. That's sweet. Oh boy, Kansas City. Who's got the Kansas City Chiefs? Kevin H, let's go Kevin. Mahomey baby, color wheel number four. Mahomes, Silver is Desmond Ritter. Who? I don't know, some guy, some two-time Super Bowl champ. Joe Burrow, 299, Brian Agnew. Silver, Justin Herbert, base. Silver, Chris O'Lavey, and Kenny Pickett, field level. Goldaroni, Brock Purdy is 10 of 10. Kenneth Walker, going to the Seahawks on the Gold Rookie Patch Auto. Congrats, Seattle, Siebert's picking that one up. That's kind of gross. Love the Seahawks from the inside of the numbers. That little pattern they have, so cool. Safe one. Johan Dotson, 94, 99. On the Rookie Swatches jersey. Silver, Jake Ferguson, and Terry McLauren. Oh, I agree, I totally agree with you, Soul. There's Snoop Conner to 35, Rookie. Silver, Alec Pierce, Rookie. O'Lavey on top, Alec Pierce. Silver, Christian Watson. Silver, Damon Clark, Derek Young, nothing. He typed something in his paper. He's got nothing. There's Marchand Lattimore to 149. Silver to Rob Bernard, Rookie. I'm just going to make an executive poll, do it. Okay. Kenny Pickett. I will send them your way. Mike Evans and Cooper Cup. I'll say you are looking. I don't like it when I get fired. It's like, tomorrow, Scumman is like, ah man, a mag back at it, Walker, let me go. Kevon Tibodeau to 199 for the Giants. Silver, Chris O'Lavey. It's out of the night to 249. Nice one here, Super Bilotto is going to be John Taylor Crome, that's going to the Niners. Got San Fran, Snoop Conner. Silver, Kobe Bryant, and Drake London, Rookie as well. If I could talk to you about it, I'm going to have some words. What's up? So if I could talk to you about it, I'm going to have some words. Like, this is the last straw, Donnie. You're like, let me, let's take a moment history, shall we? There was a Desmond Ritter. Illuminations this one time. There was a James Martin moment. Uh, Palo, what is it, for one in one vaude? I have not. I have not. Do you want to shoot me a pic? Red, Kyler Murray to 99, is it nasty? Silver, Darren Gland. Dante Forman. There's no bathroom breaks, unless you're bringing your coffee in there. Pam Juergens. Devonte Smith to 99 on the Sparks Jersey Guard. Silver, Devonte, and Luke Fortnance here. This Palo downtown looks like. Ooh, that's so sick. That's wild. That's really cool. That's really cool. I love it. I love it. I love it. That's so sick. Silver, Drake London. Silver, Cam Thomas, Fred Warner. That's kind of like a person-to-person paradise. Some people like Select Better, some people like Prism. It's more a personal preference, I would say, than anything. Silver, Garrett Wilson. Tony O'Gibson. Because you're looking for different things in both, too. Silver, Malik Willis. Like, I personally take Select Over Prism. Fair, yeah. I mean, there's certain aspects I like in one over the other, too. To 199, that is Boye Mafe. 96 to 199, Malik Willis. Rookie Jersey Auto for the Titans. Nice one there. Like, the Color Blast and Prism are nice. The Mongos are sweet. Like, there's really good short prints in Prism. David Bell to 249. Like, I think I prefer the Prism case hits over. Uh, Tyler Linderbaum over Select Case hits. Color Wheel, 36. Color Wheel is, that is, that is, that is, that is a work of art. Silver, Josh Pascal. Uh, no, no staying glass in this one, only staying glass in Prism. I would, I also like the Autos in Prism better. That's fair. That's fair. RPA's in Select, but Prism base and... Orange, Jalen Hurts to 49. So, uh, Prism. Yeah.  You know, it's just the one car, like the one line, but... I do like how you get multiple shots in Select to pick it up, and, like, the field levels are huge. Vante Smith. Brian Robinson Jr., 6 of 25. Uh, nice. Tideye, rookie jersey auto for commanders. Tideyes are nice too. The Tideyes are sick. Tideyes and the Whites are really good. The Whites are super clean. Super clean. Chris Olave. I, I like Optic too, Vaughn. Optic is pretty awesome. Optic is awesome. Optic football I really like. Silver CD-Lan. Silver Jonathan Taylor, Chase Claypool. I mean, Optic really just has a downtown, right? A rookie short, like, short stuff. Yeah. Derek Stingney to 199. I'd probably put that in three. Fair. Silver TDP and Matt Stafford. Yeah, I agree with that soul. That's not really something that's, like, like marker calendar for when I agree with that. Mandre. Silver Johan Dotton, sweet level rookie. Silver Darren Waller, Reese Hall rookie. There's Najee Harris, field level blue to one, not 49, just to 49. Silver Zonovan Knight and Derek Stingney. My Tideye coming off here. It's going to be Garrett Wilson, 16 of 25. On the select draft swatches, swatches. Ice one there for the Jets. Bateman and Damon Clark. Traylon Burks. Silva, Damian Pierce. And Jason Kelsey. This is a warping word on this one. Chris Olave. That Prescott. Nicholas Petit-Farré to 99. We've got 38 of 99. Romeo Dobbs for the Packers. Classic system bad. Usually it's, I don't think it's standalone anymore, though. I don't think it's its own product. Maybe it is. I don't know, to be honest. I don't remember. Silver Jalen Hurt, snapshots. Derek Stingney, silver rookie. Bailey Zappy, base rookie. Purple Jalen Ramsey to 75 for the Rams. Silver DJ Moore, JC Horn. Silva Najee Harris, snapshots. Jason Kelsey, silver. And Cam Thomas, AJ Brown. There's 72 of 75. Malik Willis, blue auto for the Titans. Congrats, Tennessee. Malik Willis, second Malik Willis to the break. Oh, is it really? Plates and Patches is coming back. That's one of my favorite products. Plates and Patches, freaking awesome. Mack Jones, green. Zion Johnson to 49. Silva Cooper-Cup and Jonathan Taylor. Yeah, I didn't even think about that, actually. So, all that makes sense. Ooh, green. Last pack, green. Allen Robinson, nice A-Rob. Three at five, going to the Rams. Congrats, Rams on the green. Kavon Tip-Dope, silver fedarian. Mathis and Robert Hood. Let's do a quick recap here, guys. We have Tyree Wilson, going to the Raiders. Bailey Zappie, artistic selections. A. Garrett Wilson, Devonte Smith. Jahan Dotson, Stephon Diggs. T.J. Watt. Malik Willis, Malik Willis again. Romeo Dobbs. Brian Robinson, Jr. Malik Willis again. John Taylor, Leighton Vander Esch. Isaiah Spiller, Romeo Dobbs. Drake London. Brees Hall, Harrison Bucker. The Gold RPA, Kenneth Walker, 10 of 10. For the Seahawks. And then a color wheel, Patrick Mahomes. For the Chiefs on the Super Short Grant. I'll do it for the break, guys. Thanks again for the film. Coming up next is Pinini 1.


This is an overview of highlights from OpenStack's user survey, the seventh survey we've conducted since April 2013. Our goal is to better understand attitudes, organizational profiles, use cases, and technology choices across the community's various deployments. This user survey represents more than 1,600 community members and more than 1,100 different organizations. That's 25% more organizations and 22% more individuals than last time. Although only 36% of the same people answered both this survey and the last one, we've surveyed nearly 2,500 community members over the last two survey cycles. The results are surprisingly consistent, suggesting we have a representative cross-section of the community. The users answering this survey spanned the globe, 76 countries. We also saw consistent representation from companies of all sizes, demonstrating that OpenStack is an enterprise-grade solution, but it's also strongly used by startup and midsize organizations. 47% of users told us they have more than one role or function in the way they work with OpenStack. The most prevalent answer on this list is new this year, Cloud Architect. Also new on this list was the CIO slash IT manager role. Five projects have been adopted by 90% of clouds. In the last survey, the top six projects adoption ranged from 78% to 85%. Now the range is 83 to 97%, an increase of 5 to 12 points. For the second survey in a row, containers lead the list of emerging technology of greatest interest to users. The container service Magnum is also at the top of the list of projects of interest. This list suggests where OpenStack's growth will be in the future. Some OpenStack releases are more strongly adopted than others. This chart shows the popularity of Icehouse relative to Havana, for example. While in the last survey, most deployments were on the three most recent releases, in this survey, many more upgraded to the two latest releases at the time of the survey, Liberty and Kilo. Most clouds use a lot more projects than just OpenStack's core services. Nearly 50 deployments in production or QA testing phase run more than 15 different OpenStack projects. You can look at this spike at the end of the chart as the sum of the long tail of clouds using many, many projects. A typical cloud runs nine projects. This cycle saw major shakeup with business drivers as standardization has become a top priority for virtually every user. Six months ago, only 60% of users said standardizing on the same open platform and APIs that power a global network of public and private clouds was a top five consideration. OpenStack has become the standard for enterprise infrastructure as a service. OpenStack's net promoter score climbed steadily over the past three surveys. A net promoter score 41 is top of the charts good, considering that the industry average for software is only about 19. We think the NPS trend is a key indicator of increasing user satisfaction. We also see highest results from those with deployments in production or QA, suggesting that those who use OpenStack fully are most satisfied. Also among all users, we saw clear trend toward an increasing NPS score. When asked for the primary reason for their score, the positives were community support, avoiding vendor lock in, consistency, stability, and the importance of open source. On the negative side, complexity, difficulty in deployment, inconsistency, and a lack of stability were cited. You can read more comments verbatim in the user survey itself. Finally, we looked at the proportion of clouds in production to those in proof of concept or QA testing phase. The number of clouds in production or full operational use grew to nearly two-thirds of all deployments and increase of 33% in just 12 months. Special thanks to the OpenStack user committee. I'm Heidi Joy Trethewey, Senior Marketing Manager for the OpenStack Foundation. I hope you've enjoyed this digest of the user survey and that you'll dive into the full report for more.


Hey guys, thank you so much for those of you that joined in last night's GCSE revision live while an over Creative writing and how to write a model response for the June 2020 exam Now don't forget guys that this Sunday at 5 p.m. I'll be hosting a GCSE English masterclass Answering the creative writing question for the November research exam


So we are going to start our business plan like our company's name is F2C India So any guesses by anyone who would like to decode this F2C India? Anyone from the batch? That's a good question Any guesses anyone come on fast? Okay, so it's like farmers to consumers in India Farmers are targeted and consumers are also targeted here So next our headquarters will be in Bangalore because of the major IT sector and the population density And then we will go to Hyderabad and Chennai and our B plan is mainly focused on the metropolis and cities Next slide please Okay, like introduction we are going to procure vegetables and fruits directly from the farm gate like clusters of farmers and Fios unlike like other companies who are going to Mondays and all Our application will be like we will order from app and at least before 10 to 12 hours You will get your order like at night if you will order you will get your order in the morning We are focusing on B2B2C model and our target is mainly like eliminating the multi multiple chains There should be zero wastage and tech enable supply chain in India. So it's our main motive. Next slide please So here are our team members like Myself CEO and the MD and other members like Usha Svita as the HHA head Vishabhna sir is the tech head other sir is the finance head and Setupati sir is the supply chain head We are loaded the portfolio according to their interests and strength Next slide please So this is the mission vision and values like mission is to inspire the healthier communities by connecting people to Real and valuable fruits and vegetables and our values is like inclusiveness We respect people value diversity and are committed to the quality and To the people and our vision is like to build India's most efficient and largest supply chain platform and improve the lives of Producers business consumers and farmers in a meaningful manner. So my team members will continue from here So good evening, sir, and we are the market research accordingly like for procurement India is divided into two segments like government procurement and private procurement and we have gone through various reporters such as KPMG PWC and Government of India's report and startup India report So here we can see is India is holding 17 by 5.5 percent of worst population in just 2.4 percent of the area So what we need is we we have to cater these many population by Meagher amount of a geographical area. So first focus is on that Again, we are we have considered Malthusian concept which is saying that the population is growing at exponential rate and we have to produce and Supply chain should be standard. So that is the key point for us Malthusian theory like Malthusian disruptions So missing forward and backward linkages are our main concern like as KPMG report says 9 to 10 billion Produce is expected to last by 2025. So this is also focus and there are many Okay, there are many like us in backbone of a value chain like we already discussed and to overcome these like KPMG report I already said that 1% of what market potential is only tapped by startups So we are going because of that into this this market potential to tapping this market potential Which is huge potential showing huge potential, which is 24 billion by 2025 and it's only 1% of it is So gets to be filled by our F2C is a test of traceability like there are cancer development in various areas like urban areas because of what because of use of a severe based cultivation of a fruit and vegetable and And people are consuming that and because of which they are they are facing various health issues such as cancer and Other issues. So we are going with the traceability and we are using RFID sort of a technology Which is used in nowadays in the transportation and vehicle Segmentation, so we are using that technology so that it can be like less costlier and it is viable so quality we are focusing with the government of India's and Food episode size rules and regulations. We are going with that quality and fresh fruits and vegetable are generally They're chemical composition and all the parameters. We are going to discuss in the quality So we are focusing morally more on traceability and quality because of a health issue And it is main motto of converting our B2B or B2C to B2B to B C So we are accepting model B2B to C. So that is our main motto because of which Then there are transportation losses which we are going to minimize by incorporating various value chain supplies such as cold storage And we are out in tier two tier one cities, which are our main factors and fresh product We are supplying because of which we want our customers to Give order prior to their consumption because we are not believing that the fruits can be fresh by Again more than 24 hours. So we are moving towards the first process. Next slide So these are the products where which we are focusing on like vegetable in vegetable We are focusing on onion, potato, tomato, brinjal, chili The cucumber, carrot, cabbage and in fruits there are various fruits. We are considering as of now But we want to expand in this also So packaging and pricing we are focusing on packaging and pricing based on the segmentation based on the area and segmentation based on the kg how many kg you want so We want to segment that based on the Based on the quantity the customer want then back stress and Hamper, which we are using going to use such as Ninja card is using this technology They are using crates to transport from village to B2B But we are using this technology to transport it from B2B and also B2C. So the fruits are Fruit and vegetable are more fresh to the consumer and health should be taken care of And less price as compared to the local market as As we have seen the various government reports that because of middleman there is hike in 40 percent of the cost So what we are doing is we are eliminating disrupting this chain by eliminating middleman And we just transferring this 10 percent to the farmer to fulfill goal of doubling farmers income and And also transferring 10 percent to businesses as well and 20 percent we are investing in our own F2C So we are using that 40 percent in our okay. Thank you. Next My colleague will take care of Good evening batch mates and sir and here we are going to deal about the how operation will be going to take place um in in normal supply chain former cells and Majorly the In the Mondays, but the and the middleman will purchase that then it goes to the industries or retailers Which includes a multiple loading and unloading and wastage is also high there and After that some of the highly perishables gets wasted Due to the delay of the delivery timings. So to overcome this multiple transportation we made operation like At present there are multiple Computators who are operating just by purchasing the Mondays and delivering to the customers But we are we are bringing the new innovative like we will be procuring from the farm gates itself Where the we have the we will be collaborating with the fpo's And we will be giving the set of parameters how the quality should be there and what are the demanders that that is needed for us based on the past records And we will be procuring from the farm gate and we will be bringing the those to the warehouses And from warehouses, we will be creating the some some of the distribution centers in the metropolitan city majorly our plan and our Pilot project will be start in the metropolitan city because the population density in the metropolitan city is comparatively high and they they are the people interested in the digital market digital way where because we are introducing the mobile application for the ordering of the Foods and vegetables that's why the operation model is distributed in the metropolitan city And what are the target markets like hotels restaurants and the education institutes and the supermarkets and hypermarkets are our sole markets because the they have the high buying power and due to this we can eliminate the multiple Loading and unloading and we can eliminate the wastages by our company itself And how how the channel will work majorly it will be a mobile operation by the mobile application And we will be getting the orders from the mobile application by the order in the mobile application itself from the customers And we have the two ways of ordering like is the any Customer is a big business holder like any retailers They have to order in advance so that we inform the farmers so that they can harvest according to the demand needed through the fpo and When if it is a normal customers will we can we can get the orders before the Six to six to eight hours and we can deliver within the time of the delivery And this is the and the advantage of this application is in major cities of india like mumbai there there are the recorded highest number of cancer patients because Of the growing vegetables and vegetables on the sewages. That is the reason for the high Cancer patients. So we are adopting the traceable so that we'll deliver the healthy fruits and vegetables and this is how our channel distribution is operating and we will be operating completely on the mobile application and And we also gives the trackings to the customers and as well as the payment for the farmers will be completely digital more so that the farmers can be get benefited as well as the consumers And the advantage is to customers will be handled by the usha And edges of customers. They will be getting the high quality products with less price Our products are delivered home quickly with fresh fruits and vegetables Even qr codes are present such that customers can scan it and have a detailed information regarding the fruits and vegetables Next slide please coming to promotions and publicity plans. There are personal selling advertising event marketing trade shows and discounted products In personal selling we can sell the products after meeting face to face with customer such that we can give detail information and encourage them to buy In advertisement we promote a product of fruits and vegetables in attempt to induce potential customer to purchase the product Event marketing it is a strategy to promote product real-time engagement online Or offline and companies can participate as host participants and sponsors trade show like Exhibition where our products are showcased and demonstrate our products and services As we are mainly concentrating on metropolitan customers. This will be more useful for us discounted products Because people prefer buying things on sale discount serve as a ploy to attract more people to our services next slide Funding requirements as it's a startup. We mostly prefer risk-free funding. We will add our investment in rent We concentrate on angel investor anyone interested in our B plan and invest in our B plan and to even eliminate risk We will add him as partner. We would raise our funds by taking up bank loans and even we consider government programs that offer startup capital Good evening everyone and as per the new msme definition by government of india our startup is a Small small enterprise and this is the amount we invested so far in the in f2c india Like in in different sheds like like for logistics where we are following rental based warehousing for promotion and the miscellaneous like the salary for that Drivers then packaging and for buying stairs next slide And this is the growth projection by the year 2025. We are we are planning to serve Consumers of one lakh in numbers with the for help of farmers in number 10,000 And with the target of fun free tennis 2010 us and we are working at the profit percentage of 10 percent next slide Coming to the conclusion f2c is attempting to solve the decay for problem In agriculture because this operation through modern technology the technology we are using in the mobile application or RFID This radio frequency identification and the board strap my SQL these are the softwares which is used for the traceability and for web designing and app development and after that in our business farmers are getting better prices and we are also solving some of the existing problems like food waste it Comparing to traditional model. We are reducing the food waste by 26 and eliminating information barrier among the farmers And the distribution inefficiency among farmers and easy handling of cash And the customers are benefiting through 100 percent traceable traceable food and retailers are getting fresh producers and reducing the intermediaries by using the modern technologies and We are working on the process of tapping the untapped market potential of 24 billion so far The existing companies have covered 1 percent of market so far. So we are on the positive side That's it sir. Thank you Great job. Congratulations exactly 15 minutes I have a clock is started at 515 if you all did that's phenomenal job. Congratulations. Thank you very much


Hey everyone, welcome back to another Adobe Illustrator slash After Effects tutorial. We use both products, or both products, but actually this is more After Effects than anything. Guys, real simply, I'm going to show you how to animate a .ai or a .adobe illustrator file. Basically, you create a really cool thing in Adobe Illustrator or a really ugly thing like I did right here, and then I'm going to put that inside of After Effects and normally you can only just move it around a little bit. You can move it scale, size, position, etc., etc., but I'm going to show you how to turn it into a vector layer inside After Effects and move the various little points around. It's awesome, trust me, let's get this ball rolling. The first step here is I've gone ahead and just made a very simple Mickey Mouse Adobe Illustrator drawing and I just used the pen tool and again this is just for demonstration purposes. The second step is we go into Finder, you take your .ai file, your Adobe Illustrator file, and we're going to drag and drop that bad boy into After Effects. So let's go ahead and do that. Boom! The next step, if you're following along, is you want to create a new composition. So I'm just going to create Comp 2. Notice it's 1920 by 1080, that's just standard HD for video, but again this can be any size, guys. We're just teaching the technique here. And then I'm going to hit OK. Now I've got a new composition and it's got a white background. You can change the composition. When you create it, you can always change the background color depending on what colors your Adobe Illustrator file is. But I've gone with black and white because that's got the best contrast. Alright, the next step is I'm going to drag and drop this bad boy right on top here and boom! Now we've got the Adobe Illustrator file. The vector file is loaded up and it's in here. Now when I move across the timeline in After Effects, nothing happens. Now here's where it gets interesting. If you're just an illustrator or better yet if you're an animator or a wannabe animator, you can do your work inside an Illustrator, put it in After Effects and then we can create a vector file inside After Effects that has movable points and movable properties that a lot of people don't know how to do. So let's just go ahead and show you how to do that. Before I do that, I'm just going to drag and drop, move this around here. I can go ahead and do some basic movements to this thing. So if I want to make it bigger, move it to the right, move it to the left, up and down, all that other stuff, this can all be done here. But if I want to move the points and parts of the line here or the drawing, we've got to make another change. So real simply here, you want to click on, left click on example.ai or whatever file you're using, then you want to right click on top of it, go down to create and here's where the magic happens. Create shape from vector layer. Watch what happens. When we do that and we zoom in, you're going to see that it looks like there's a line running through it. And more importantly, when we go ahead, you'll see actually, well I got you, you're going to see that this created something called example outlines. I'll just expand that a little. And the original example.ai, or our original Illustrator file, lost the eyeball and the eyeball went to example outlines. So basically that means it's replaced it and now we've got this instead of the original file. All good. I hope you're following along with me. The next step and this is where it gets a little tricky is you want to click on the new layer, the new example outlines or whatever it's called in your Illustrator there or your After Effects. Drop it down, go down to group one, go down to path. Now when I click on path and I hover over it, you're going to see here that it's got points. These are manipulatable points that you can now go ahead and change. Watch. Right? There we go. We made a change. Go ahead a little further here and I'll just do an example. We made another change. You're going to notice that what was originally a static drawing has now become manipulatable over time and space. This is how you go ahead and take Adobe Illustrator drawings and stuff like that and make them animatable. If I was to go ahead and drop this down a little more, you're going to see the stop watch and when I click on that stop watch, this now says, okay, this path is now open for animation. So at zero seconds, this is where we're at. Let's go ahead to like, I don't know, something like three seconds, somewhere around three seconds. Sure. And we're going to move. Nope, never mind. You got to go ahead. This is actually quite tricky, but you have to be clicked on path and let's see if I got it. There we go. I got it on top of one of those points and now I'm going to move it down and I'm going to just distend it very strangely just to show you kind of what I'm working on. And I'm going to move this one over down at five seconds. And here's what's happened. I'm going to go back to now fit. We're going to move to the beginning and I'm going to hit space bar. And you're going to see here that the static Adobe Illustrator file that we drag and dropped in now can be basically animated and changed over time. This is an awesome technique for those of you that are getting into animation. I hope this video helps. I got a ton of more cool stuff coming up. All right. Thanks for watching. Cheers.


Tezal Le Antigua ITTT's Tezal course in Guatemala is located in the city of Le Antigua Listed as our UNESCO World Heritage Site, Le Antigua is a popular tourist destination with fine examples of colonial-era architecture and interesting ruins throughout the city The city is situated 1,500 meters, 5,000 feet above sea level and rests in the shadow of Agua Volcano A visit to Guatemala is like traveling to another world with its historical architecture, ruins of the Mayan civilization and looming volcanoes there is plenty to see and do in Guatemala Le Antigua's position in the central highlands makes it the ideal base for exploring the many interesting and beautiful sites the country has to offer Trips to the Pacific Coast, Lake Etitlán and the Mayan ruins Taikal can all be arranged from Le Antigua With the stunning beauty and fascinating history of Guatemala combined with our excellent course and lifetime job guidance, ITTT's Tezal course in Le Antigua represents excellent value for money There are a large number of quality restaurants in Le Antigua and you'll be spoiled for choice when it comes to tasting the local cuisine The city is also home to several small shops and boutiques selling souvenirs, antiques, traditional crafts and other products In the city center and in the surrounding villages you will find handicraft markets and open-air markets selling a wide range of locally produced items Beyond eating and shopping you can hike a volcano, visit a coffee plantation or go ziplining plus many other exciting activities There's so much to see and do here that you may decide you never want to leave and whether you decide to leave or stay in Guatemala You can be sure that our Tezal certificate will give the skills you need to teach English all over the world By choosing our Tezal course in Le Antigua you are choosing to study in a beautiful city Where every morning your walk to the school will take you past fascinating ruins and historic buildings as you take in breathtaking views of Agua Volcano The training center itself is located in a colonial building with fully updated and modern facilities that classrooms are well equipped and our students are real Spanish speakers who are keen to learn English


Good morning. Good morning, everybody. How you doing? Getting ready for another day right here. I've got a delivery in Vinton, Virginia. First thing tomorrow, we'll go to Auburn, Massachusetts. And then I go over to Beverly, Massachusetts. And then I end off in Bideford, Maine. From there, we'll see what our reload is. It's Labor Day weekend when I'm filming this. I hope you had a good one.  I'm taking my long weekend in two weeks because my wedding anniversary is on that weekend. We got married on September 16th, 2017. So it's going to be our sixth anniversary this year. So instead of taking Labor Day weekend off, I'm going to take that weekend off and a couple extra days there. We're going to go do some special stuff. The last couple of days, I haven't been vlogging too much. The videos were a little shorter. I just put them together and I realized that they didn't have a lot of substance to them. I apologize for that. When you vlog every day, some days are just not as exciting as other days. We've got this covered wagon Conestoga trailer behind us. We call them roll tights. It's a tri-axle. The rear axle is a lift one. So it's not actually on the ground.  So instead of tarping your freight with this load, you need to roll the cover over it, but you load it from the side. I found these truck stops here late last night. I got it pretty late. But we got it done. We're slowly getting our way down there. Tonight, we'll be down in Benton. I still don't know where we're going to be sleeping tonight. Let's figure that out as we go. I'm going to get myself a coffee.  The law says I can start rolling in about 20 minutes, so I better start doing my pre-trip so we can get out there. Have you guys been paying attention? Have you been waiting for another one of these giveaways? We've picked one winner so far. We're going to pick a few more yet by the end of this month, but you've got to watch every video. Today's your lucky day. If you want something from Haas, maybe a hat like this, maybe a mug. I'm not too sure what they're going to send you. If you'd like one, the way you get one, instead of emailing me, don't email me this time because last time you just about broke my phone. That's totally okay. If you want one, go down below to the comments section. Tell me about a Haas product that you bought recently or in the past, and tell me how well it worked for you. Go down below to the comments section right now. Let me know. I'm going to pick one comment, and I'm going to pin the winning comment. If your comment gets pinned, I'll reach out to you and respond to you there, and I'll get a mailing address or we can send something to you. So go down below. Let me know what Haas product you bought or which Haas product you bought when you bought it, and how you liked it. Did it work? Turning Sharker Josh vlogs into some kind of infomercial channel where they're going to try to sell you something every day. That always bugs me. I understand why YouTubers do that because a lot of YouTubers, they do this for a living, right? I wish I could just do YouTube videos for a living, but then I wouldn't be able to drive my truck. And I love driving trucks, so I don't want to be selling you stuff every day, but I will give shout-outs to products that work that I know and that I like. And the people at Haas reached out to me a while ago already and I've gotten to know them. They're really good people. Just like people at Bullsnot. And I'll share with you products that I use that I think you might like too. They're related to my channel, right? I don't want to make a video about trucking and then suddenly turn around and, you know, try to start selling you the beach towels or something. I have people emailing me every day if I want to be sponsored by them. And I said, no, no, no. My channel is not sponsored by anybody but me. I mean, I'm not one of those channels that is trying to sell something all the time.  So if there's a product that comes along like Haas or Bullsnot, a little product placement here, right, for both of them, right? Sure, I'll talk about them. If they reach out to me, we develop a little bit of a relationship, maybe a partnership. It's not a sponsorship. We work together a little bit, right? If I think they have some products that could help you, sure, I'll help them. And you know what, Haas has been nice enough that they want to send you out a couple of hats, a couple of mugs. I think I got a mug in here as well. I can show you it later. Where is it? I can't reach it right now. But they asked me to do a couple of giveaways on my channel here. And I said, sure, we'll think of some creative ways. We'll do four or five in this month. So maybe one per week, but you're going to have to watch every day. You see that way I get you coming back every day if you want a hat. Interstate 74 eastbound. We're just about at the Indiana border. This highway's going to take us straight to Indianapolis. It looks like it's going to take us right through the city. Hopefully we don't hit any big traffic today. I don't have a lot of time to waste. We're going to be go, go, go, go in again. This whole week is sort of going to be a bit of a rush because we have the four drops and I want to get them off as fast as possible because I'd like the opportunity to reload this week yet. I don't know where my reload is going to be. But if I rush and if I hurry responsibly, I should be able to get unloaded Thursday, I think. Because we're going to be in Benton, Virginia tomorrow, which is Tuesday morning. And then Woburn, Massachusetts is another 600 and some miles, 650 miles. So that's a full day driving, 1,050 kilometers. So Tuesday drive all of Tuesday, deliver their Wednesday morning-ish, late morning. And our next one in Beverly, Massachusetts is I think an hour and a half, two hours away as long as there's no big traffic jams.  If everything works properly and all the ducks line up in a row, we can do that. And then we have all of Thursday and Friday to get reloaded. Now remember, because I came down from Canada delivering this freight from Canada to the U.S., the freight I take back into Canada has to be going directly back or the freight I pick up. So I'm not too sure where it'll be or what it'll be, but it'll have to be a load that goes directly back to Canada. I can't pick up in the U.S. and drop off in the U.S. That's very illegal. So we'll be going back north. Maybe there won't be any loads.  I don't know. We'll find out as we go. That's one of the little fun parts of trucking, at least for me. You never quite know what's next. Sometimes that can be a little stressful. Depends if you need to get home for something important. And in a way, it's kind of nice having a little bit of mystery, you know? Something different all the time. I couldn't do a dedicated route where it's the same route over and over and over and over. I just... I guess so bored of doing that. Remember I did city work for over a year there? It was really great. A great position. And it got me home. That was during COVID. And we didn't know what was going on. We thought the world was sending and everyone was dying. Turns out it wasn't as bad as we thought at the beginning. So I was local for a while. I'm doing the same routes over and over and over again. For me, personally, it gets repetitive, boring, monotonous. I like switching it up. Doing something different all the time. Maybe doing the same thing for a little while but then doing something different like this. We went out to Prince Edward Island on our last trip. Now we're going out to Virginia and Maine. Just switching it up a bit. Off the highway and check the GPS. Right through the city of Indianapolis. And apparently I-65 is a freeway that goes right through the heart of Indianapolis. I wanted to make sure it wasn't sending me like... Sending me through downtown like it did in Charlottetown, Prince Edward Island last time. There is a bypass that goes around the city, but if the I-65 is an interstate, it should be a freeway all the way through. And it's Labor Day weekend. There shouldn't be that much traffic on the highway, right? There shouldn't be. It's a holiday. Everyone should be at home. Traffic is in our favor. And nonexistent. I want to go 70 East. I don't know why I followed 70 West. And that'll take me around the south side of Indianapolis back. What highway is this? You gotta pick one there, Karen. This way? Yes, I can. In 600 meters, keep to the right on. I-465 East, I-74 East, I-465 West, I-74 West and then keep to the left in 190 meters. Okay, so I want to turn right from this lane? No, I want to be in that lane. There's nobody beside me. 5 East, I-74 East. Our savior highway. This will save us from our own mistakes. And bring us back to I-70 East where I belong. With the I-70 East people. I-465, shake me back to my people. I'm pretty sure you used to have to keep left. And keep right to go west. Now you have to keep right to go east to left to go west. Where I'm from, there's one main road. Biderweb of interstates just entangled with each other. Gotta make sure you don't miss your turn. You'll end up in Mexico or something. I'm on vacation in Mexico right now. Just saying. I'd love to go sit on a beach there. Continue on this road for 160 kilometers. Celsius outside. 32 degrees Celsius is equal to 89.6 degrees Fahrenheit. Doesn't seem as hot when you say it in Fahrenheit. I don't know why, because it's a bigger number, right? Trucks use left lane. Well then, I'm a truck. Left lane through the construction zone. Gotcha. That construction's already done. It knows what it is, but it is here. Find it here. New York City, though. We'll do that tomorrow. Thanks for hanging out with me, everybody. I'll see you then. Stay safe and be safe.