Oh, yeah, what's up guys? It's Chris Pike. My friends call me Ben C. I'm back again guys And today I got an announcement video for you.  I know I sound like that guy from Sesame Street But whatever don't judge me bro, but joking aside. Yeah guys Billion views in the last 30 days that is crazy a billion is a huge number It's so huge that I want to give you guys some context. How much is a billion big see help it make sense. Okay, hold on All right first things first how much is a billion?  You're wrong I built one, but yeah, it's a billion. That's what we're doing. You did that in the last 30 days guys That is over 33 million pardon me views per day or 23,000 views per minute across the network It's crazy a billion is so huge. It actually takes the US government to almost three full Hours to spend the billion dollars. Yeah, they're not real good with their money But yeah, no guys, we're doing a billion views and with that kind of growth We need people to join us and we need people more now than ever So in a previous video George outlined, you know, you could go to the link below And if you want to get involved right up a plan right and tell us what you do You know how you want to get involved the types of skills you have how you think you can help contribute to To freedom. Maybe you want to run a channel. Maybe you want to get involved in recruiting Maybe you want to do who knows what you want to do? I don't know leave a message and you know, let's say Big C sent me and if you said Big C sent me I put you at the top of the pile. I don't know how that works and that's probably wrong But whatever, I mean, I just made that up.   I don't know message us. Let us know get involved This is your boy Big C. I got another video coming up shortly.


What's up everyone? It's your girl Kenzie here from Leighton Sports Cards and I am ripping 2021 Panini Prison Football Hoppy 3 box break number 28 random teams. Here is the look at the random results. You can always find these at LeightonSportsCards.com and link is also in chat for you. All right, here we go. Let's see big QB ink seems a nice color or a black finite trail answer base Niners, Christian Barmore, Green, Scope, Rookie, Dazz Newsom for the Bears to 75, and red wave rookie of Peyton Turner Saints to 149. Dwayne Eskridge, Joe Tryon, we've got Orange to 249, Michael Brocker as Lions, and Terri Kill Brilliant, Patrick Jones, Mearsmith, Marseille, we've got Cam Newton on the blue wave to 199, Patriots, and Silver, Otto of LaDanian, Tomlinson, LT, pretty chargers there, Milo, nice one, Tray Nixon, Josh Palmer, we've got Terrell Davids on the purple isa 225, and fireworks rookie Devontae Smith, Tommy Trembl, Kaderius Tony rookie, Giant, red wave rookie, Audie Yingbo to 149, Colt, Silver all out, Austin Eckler, Nico Collins, Tray McKinney to 175, LaDaria Sneed, Chiefs, Silver rookie, Seth Williams, Veronica Lewis, got Najee Harris rookie, Elijah Mitchell, blue wave to 199, of Grady Jarrett Falcons, and emergent rookie Jalen Waddle, Dolphins, Terri Brightwell, Justin Fields, rookie base, got Purple Isa 225, Hardy Nickerson, Bucks, and Silver for Shard Paramon, ever since you said that, we've been pulling him, I don't think I've ever pulled three of those. We've got Orange Wave to 60 at Oliver Bills, and new recruits, rookie Kyle Pitts, Frank Darby, Nishan Wrights, Orange, rookie to 249, Dymie Brown Washington, and Silver, Lamar Jackson. Like there are very few athletes I don't like that I would like if I saw them in person, I would say I don't like you, and for Shard Paramon is one of them. Jaycee Horne, Sewell, the 125 landed Collins football team, Justin Jefferson fireworks, last factor, Fox one, Felipe Franks, Zach Wilson, rookie, got Orange to 249, Jonathan Taylor, and Silver, Miles Gaskin, Dolphins. He was just like we draft him in 2015 out of central Florida, and he's one of those guys that only had his draft stock rise because he ran a crazy fast 40. And I mean, if you look in history, that never works over drafting somebody. Joey B. And Kyle Strauss, rookie, Gabrielle Cox, Orange Wave, rookie to 60, Pete Werner, and Wildcard Coins. Then he wouldn't stay healthy, and like he missed his entire rookie season with like a leg injury. And then when he finally got healthy, like eight games into the next season, he couldn't catch. Got Chuba Hubbard, rookie, Demetric Felton, Hyper, Dalvin Cooke to 175, and Hype, CH. We had to wait like four years before it made like financial sense to release somebody who's never played because he's terrible. God, oh, I can like just hearing his name just frustrates me. Jacob Harris, Chris Evans, we've got DK Metcalf to 199. We've got Purple Power, RPA, Jaylen Waddle, boom! Ego Dolphins, Chris M. That is 33 of 49. Congrats on the Waddle Mag that. Exactly, exactly, Randy. Herbie Second Air, Savin Collins, Monty Rice, Red Waves 149, OBJ, Anna Merchant, Givante Williams. But at least like when Blackman was staying out of trouble and was healthy, he was good, like Rashad Perriman never been good. We've got Rondell Moore, Kylin Hill, Blue Wave to 199, AJ Dillon Packers, and Silver Pete Warner for the Saints. But I could see like Jed's fans being more frustrated at Blackman because of how high they drafted him, like Rashad Perriman was 27. Yeah, Jamar Chase, rookie, Javon Holland, rookie. We've got Purple to 225, Miles Sanders, Eagles, and Russell Wilson, the brilliance. Low rig, Trace Sermon, Purple, Chris Jones, 125, Chiefs, Silver, Landon Collins. That he was, Randy, that he was. Jaylen Kamp, Remandry Stevenson, Illumination, Short Print, Russell Wilson, Seahawks. There you go, Seattle, Sea Birds there, John M. Nice, we'll mag that, and a Tom Brady fireworks. So like Brady color, and this is a hard pole. Berry. Muzerike, Greg Nusa, we've got Blue Waves to 199 on Muzerike, and Silver Lavante David. Jaylen Phillips, Eric Stokes, we've got Orange to 249, Kenan Allen Chargers, and New recruits, Tray Lance, Ricky. I didn't look at when, ouch, when that field pole. I'm curious if that was like the first week of release. I think it was, I think, um, the red box at June 6th. Micah Parsons, Rookie Cowboys, Terrace Marshall Jr., got Rookie Hyper to 175, Eric Stokes Packers, all out in DHOP. Yeah, we had the Waddle Arcade, and Wilder. Jamar Jefferson, Jaylen Waddlebase, Purple Power, Kenan Allen to 49 Chargers, and Silver, Cooper Cup. All right, last box. Kirby's Second Air, Greg Russo, Chamon Davis, Rookie to 249, Brock Lesnar for the Vikings, and Aaron Jones fireworks. Yeah, the color blasts are one in about every 10 cases or so. Kurt Warner, Henry Thomas, Murray Rogers, Orange to 249, Levante, David Bucks, C.D. Lamb to 60 on the Orange Wave. We've got red to 149, Leonard's Ploy, purple to 225, Marcus Colston, and Silver, Rookie of Dihommy Brown. There's a colorful pack there, that's for sure. There you go, Washington. Kyle Trask, Rookie, Bucks, Jabro Cox Cowboys, Hyper to 175, Ed Oliver Bills, Purple Power, 249, Darnell Mooney Bears, Blue Wave to 199, Akeem Hicks Bears, got Orange to 249, Joe Montana, Niners, and Emergent Rookie, Trey Lance. I don't know. Looks like it might. Got Shuba Hovered Rookie, Metric Felton, Orange, Michael Carter to 249, nice one there, Jets. We've got Forest Camo, Mark Burnell to 15, Jax, Purple to 125, Curtis Martin Jets, Silver all out, Kyler, Jacob Harris, got Chris Evans, Red Wave, Ryan Fitzpatrick to 149, Washington, and Mark Burnell, Silver. Obsidian is one per case, J.D., so it's more common in Obsidian than it is in Prism. That's why the Prism ones go usually for a little bit more. Got Cornell Power Rookie, Jared Dokes, Purple to 225, Jamal Adams, Seahawks, Silver, Joe Thysman, so the Mongas and Stinglass, they say about one in ten, or Colorblast one in ten, Stinglass about one in five, Peyton Turner, Sante Samuel Jr., Blue Ice to 99, Damien Harris-Pats, Slamar Jackson Brilliance. Yeah, no problem. Couldn't think of what the third shortcut was. Tyson Campbell, J2 Felly, Tyson Campbell, Purple to 125, Jax, Silver, Plexigirl Burris, another not-so-smart player, shoot himself in the leg, Kelvin Joseph Rashad Bateman, Purple to 125, Devin White-Bucks, right, C.D. Lamb, what in Prism? The ones you're looking for, the Colorblast, Mongas one in ten, and Stinglass one in five, Snakeskins, like a case head, Illumination, those are other short prints. Sam Ellinger, Tylin Wallace, Prism to 175, Jordan Brooks, and Jalen Waddle, Silver Rookie. Dolphin's having a nice break here. Retail is like what, green is a short print, super short prints like red or blue usually, Seth Williams, Kenneth Gainwell, Purple to 225, John Arcelovich, Jr. Packers, and Brink, C.D. Lamb. So I think, Josh, I think it's gravity feeds, like the single packs of the checkerboards. And then, a little Herbert Quay-Pay, Red Wave to 149, Devin Collins-Carnals, and Flashback, Purple, Power, Tenny, and Tenny, Vinny, Testa Verity, Jets to 25 on that one, that's sick. You go Jets, we'll bag that. After the recap, I'll explain it as best as I can, Josh. Give me one second here to set up the random for the wild card points, three and two, five times, again, whatever team is on top after five times, we'll get the wild card points. Good luck, everyone. One, two, three, four, nine-ers, nine-ers. We had the Dami Brown, Silver, Auto, Washington, Lydani, and Thomelson, Silver, Chargers, Red Wave to 149, Peyton Turner, Saints, and the Testa Verity to 25, Purple Power Jets, the Illumination Short Print, Russell Wilson, and Purple Power RPA Jalen Waddle to 49, 33 to 49. Congrats again on all the hits, everyone. Thanks for hopping in, and we've got some more football coming up.


But hey, if I had a nickel for every time I made a cool yamcha come back. Oh, I'd be four. I'd be four. I'd have no nickels. How's it going, everybody? Dato missed the intro. Do you hear rushing through it now? But we're in a right game with Krillin. I going up against Vigito, Berlin. Go. Oh, you already know that Yamsha is always on deck, my boy. Oh, man. Damn, I could have Krillin timed him. Don't worry, we'll get one this game. I told you we get one. Uh, nice. He could have definitely teched out of that. But who cares when we get the kill? Am I right or am I right? Let's go. Oh, well, I'm glad that hit Super Dash. No Super Dash. Damn, look at the reach. Krillin versus Broly is not a matchup you want to be having as Broly. Please hit. Nice. All right, so we're going to get the hard knockdown here. I'm pretty sure this is an easy dragon rush. Yep. I tried deflecting there. I think either that or you just got caught, but good stuff. Nonetheless, we do pick up the knockout on Broly. Everything's looking pretty good here. It would be a miracle if we lost this match. Uh, again, Super Dash Yamsha is just too nice on this. Oh, no, our down heavy does not go off. He's going to go ahead and get the punish on us. Biggest of Yikes. Now we're going to get a lot of damage to the fate. Actually, I never mind. OK, nice back dash and we're in there. Catch him. Oh, no, oh, that could have been bad. Dragon run. Oh, yeah, we sparking up. Hell, yeah, we sparking up. Let's go. That was I did not know what I wanted to do there. Could have gone five destructive disc, but we'll just take the hard knockdown. This might be another place to. Uh, could it be Krillin time already? Get another hard knockdown. What's the mix up this time? Dragon run, beautiful coverage. I'll give it up. I'll give it up. That was pretty good coverage. Uh, if you guys can't tell, I'm desperately trying to get back to Majin, by the way. That's why we're playing my main team, not really joking around, just kind of talking about what's happening on screen. So hopefully, you know, that's OK with you guys. I just focused on. Yeah, look at those points. Oh, are you joking my way to victory? Let's go. Oh, OK, Yamsha just didn't feel like playing that. That time. Wait, whoa, oh, he reflected it. OK, oh, beautiful. He knew I was going to do it. He saw Yamsha come up. He was like, yeah, right, guy. Oh, that's fine. Get me down there. Oh, we out of here. Hmm, bad barrier. Who do I look like approaching you carelessly? I can we optimize this? Oh, no, I had the wrong button. That's why. Nice. Can we optimize this?  But oh, mama, mama. Wow, look at this damage, dude. I might have to pop sparking.  I don't understand. Knock me down. Should I wake up level three? Bad choice. Oh, I'll take it, dude. If that's what you're going to punish me with, you know, that's on you, man. Nice. All right, let's get Krillin back out here. Bring him down. Destructo this for the knockout. The reason we bring Carolina, not Goku is because Krillin's assist is not going to help as much as a comment. Now, unfortunately, miss, but delay it just to get that reflect out. Oh, damn, this is going to be big damage. Oh, my goodness. Oh, beautiful uppercut. Oh, man, taking some blue life off of Goku as well. That is not necessarily what you want to see. Oh, nice. Level one into level one, maybe. No. Oh, no. Wow, we might lose this game now because I've simply made too many mistakes. Level one. Yep, into level one, probably. Yep. All right. Well, I did make a lot of mistakes this game, especially with Goku there. I just got hit twice, which you really can't afford to do. But hey, if I had a nickel for every time I made a cool yamcha come back. Oh, I'd be four. I'd be four. I'd have no nickels. Some would help. Oh, what are you doing? What are you doing? Giving me a chance to come back, huh? I see you. A little bit of a charity donation. You heard I didn't have any nickels. You knew you wanted to donate. Let's go. It's not going to get through a sparking, but I do have. What's he going to wake up with? What's he going to try to cheese me with? No, no, no, no, no, no, no.  No, I forgot he had sparking. How could I forget? I forgot the spark. I always forget when they super dash on me on sparking. I'm like, oh, super dashing raw. All right. All right, all right, all right. Let's calm down. Let's calm down. Let's calm down. I messed up my combo, but I know Krillin time, but that's fine. Let's just do some standardized testing here. No, he was still reflecting. And somehow I messed that up pretty heavy. Oh, yeah, that felt pretty good. I don't know why a mesh lights there like it works. No, he hit me with the lights, the dancers' legs. Dude, let me live. Let me live. You know you want to. You know you want to. Oh, all right, I'll give it up. I'll give it up. I'll give it up. I'll give it up. Get off of me. Wow. OK, I thought he was just going to reflect again. All right, get off of me. No super dashing through that, but that's OK. I don't want Goku out here. Nice. I'm glad we reached him. Oh, come on. That was baloney. Oh, yeah, that was not nice. That was not good. Tech down. All right, it doesn't matter. Oh, level three. Will he do it? He opts to not. Wow, that was unfortunate. Massive unfortunate. He can't get, he can't tag us out though. Nah, he wanted to though. Nice. Don't want to waste any bar unnecessarily. Nice again. Let's go. One bar. We still have three to spare, which is pretty good for us. The game's looking pretty even right now. It's going to come down to who gets the first hit with Goku. And the winner of that is us. Down we go. Just max out the damage here.  It is just rough for me out here. He could kill, he could kill. That was fortunate for us. Ah, ha, ha, ha, ha, ha, bing, bing, bing, bing, bing, bing. Please kill. It's not going to. Oh, it might, it might, it might, it might. We have to predict Sparking. Well, we didn't get it. We didn't get it, but he unfortunately didn't react properly to that at all.  Come on, try something fresh next time. Oh no. No, okay, popping it. Oh, get off of me. Oh, what? Nice. Whew. He won't see me panicking like that again. I'm not on my watch. Let's do that again sometime. Yeah, let's do that again sometime. I definitely agree. Right now. In fact, let's do it again right now. Delay it just a little, try to catch that reflect. You see, it did work out for us there. Can we kill? The answer's probably not. Delay it again, catch the deflect, and we're on our way. It's a matter of reading what he wants to do on defense. You got to condition them. This is an orange square, so we might finally get that pink square back. No!  No, I had corner position and everything. Not on my watch. All right, let's keep him down here. We're gonna get him down into the corner, is where we put the pressure on. Okay, that is not what I wanted, but damn it, he did go with the reflect on that one. Yeah, I would have sworn he'd switch it up, but he didn't, and that's just something we got to deal with. Oh no. Nice, we get the beam. Goku, unfortunately, did not do much there. Boom, we react to those. Why don't you go ahead and fall into this? Bend it upwards, bring it back down, that's a knockout. Now all we have to deal with is Broly with sparking, but that really shouldn't be too big of a deal for us, honestly.  Yamcha. Goku. No, I tried a solar flare him again. No, nice beam amount, that's gonna be it. Please, geez, look at the healing. Oh, I tried a destructor disc on Wake Up. Not a great option, in fact, not even a decent option, or good, or okay. It's just bad, but please, please. Okay, well, he tacked and didn't block, so that was the only way that was gonna kill him, but man, we got him. All right, and maybe that'll give us our pink square. Let's go ahead and check that out. We did not rank up, unfortunately. I did cop that sweet L in the second game, because of all those mistakes I made, let's see. Drum roll, please. Well, I'm gonna go ahead and wrap up today's video here. If you guys like these ranked videos, please go down in the comments and let me know your favorite moment of this ranked video while you're down there, and if you're new to the channel, make sure to hit the like button and subscribe. If you wanna keep up with all the other videos, there's also some videos up on screen right now that you can feel free to click on if you missed out on any of them, or if you just wanna watch something on the channel again. I'm Dr. Adoya, and I'll see you in the next video.


Nigeria is the largest producer of cassava and you can as well tell that Nigeria is the largest generator of these cassava peels. These peels decompose over time and emit methane gases into the atmosphere. You can be sure that some of these peels, some people still park them and feed to their livestock. They are unaware of the hazardous health impacts on their livestock. In 2022, I was privileged to be one of the trainees in Illry Nigeria. Where I was trained on how to convert this wasted methane emitting cassava peels to quality feed ingredients. In practice, this process involves getting fresh cassava peels that are first sorted to remove foreign materials and then they are grated to reduce the particle size. After grating, it goes through a rapid dewatering process on the hydraulic jack. Now, after this, this gives us an intermediate product. This intermediate product can be called the HQCP cake. This will have to go through another loosening process. It goes through the pulverizer and it will have to go through another process of sieving where we have a separate product of a fine, it's a fine product and then there's a coarsed product. This fine product is for that ride either by sun drying or on rainy days we have a two star. The HQCP production process helps to reduce to the barest minimum the cyanide and the flatoxin levels in the cassava peels. This can also eliminate the emission of methane gases into the atmosphere. A few of the factors that could help to scale up this innovation First of all most would have been better access rules through the raw materials. Next would have been electricity. Currently the factory is run on generator. We haven't been privileged to get public power supplied down to the factory. Next would have been an efficient drying process that doesn't have a negative impact on the climate. Lastly is finance. The good means to do the process of HQCP are not cheap at all. So if we will get finance from the government or if we have anybody that could help to sponsor the production because from our production we can tell with our return on investment we can be able to generate this finance over time.


Good evening friends. I welcome you all to the hindu newspaper analysis brought to you by the Shankara A.S academy. Today's date is 3rd January 2024. Here are the list of news articles which we are going to discuss today. So, let's get into discussion. The rules related to citizenship amendment act CAA might be well introduced before the upcoming Lok Sabha elections. See, the citizenship act was approved in 2019. According to an official, Hindus from Pakistan who arrived legally in India can now apply for citizenship in an online mode. These individuals will be considered eligible for applying despite their expiry documents. See, this is the crux of the article. In this context, let us understand some important provisions of the Citizenship Amendment Act. See, the Citizenship Amendment Act was enacted to grant citizenship to certain migrants in India. This act had made some amendments in the Citizenship Act 1955 to meet this purpose. Okay, now let us see the key provisions of the Citizenship Amendment Act 2019. Firstly, this act aims to grant citizenship to the people belonging to six religions who came from Afghanistan, Bangladesh and Pakistan. See, these six religions includes Hindu, Sikhs, Buddhists, Jainists, Parsis and Christians. Here note that the act does not apply to the Muslims who migrated to India from the Afghanistan, Bangladesh and Pakistan. The act says that people belonging to these six religions from three countries who entered India on or before December 31, 2014 will not be treated as an illegal migrants and so they will be granted citizenship in a due course. So, let us see the second Secondly, the Citizenship Act 2019 relaxed the requirement of naturalization criteria. Generally know that 11 years of staying in India is required to get Indian citizenship through the process of naturalization. But the CEA 2019 relaxed this 11 year requirement to just five years. So, if the people belonging to the six religions and who stayed in India for five years, they can be granted citizenship through naturalization process. Thirdly, the act says that people belonging to the six religions shall deem to be the citizens of India from the date of their entry into India. This means the status or citizenship status, the status can be granted once they accuse citizenship. The act further means that all legal proceedings against such people with respect to the illegal migration will now be closed. Basically, this act aims to grant citizenship to those who face religious prosecution in Afghanistan, Bangladesh and Pakistan. Moreover, it also aims to protect such people from the legal proceedings of illegal migration. And finally, the act mentions that the provisions of CEA 2019 shall not be applied to illegal migrants who are living in the tribal areas of Assam, Meghalaya, Misoram or Tripura. Moreover, the act mentioned that it is not applicable to the areas which are being covered under inner line permit as notified under the Bengal Eastern Frontier Regulation Act 1873. See, these are all some of the provisions of the act. Now, let us see the some of the concerns regarding the CEA. First concern is that it is said to be against the fundamental rights. Know that the critics argues that it is the violative of Article 14 which guarantees right to equality to people. Moreover, know that Article 14 is applicable to both the citizens and foreigners. The act also contradicts the principles of secularism which get enshrined in the preamble of the constitution. Secondly, this act is discriminatory in nature. India has several other refugees that includes Tamil from Sri Lanka, Hindu Rohingyas from Myanmar. See, they are not covered under this act. Thirdly, the problem is with the difficulty in administration. See, it is very difficult for the government to differentiate between the illegal migrants and those who are actually persecuted. Lastly, it might hamper the bilateral ties between our neighbouring countries. See, this act throws the light of the religious oppression that has happened and is happening in these countries. So, it may worsen our bilateral ties with the neighbouring countries. See, this is all the concerns regarding the CEA. So, in our discussion, we basically, in the first part, we saw about the various provisions of the act and in the second part, we saw some important concerns regarding the CEA-A Amendment Act 2019. See, with these 11 points, let us conclude this discussion and take up the next news article for our analysis. The editorial here is about the GST collection. The article says that though the GST collection has increased, our government needs to stay very cautious. See, this is about the article. In this context, in our discussion, let us try and solve the main related question related to GST. Look at the question. The GST was promised to be the most significant indirect tax reforms since independence in India. Examine the performance of GST in India over the past six years. See, the directive word is Examine. When the question has said I have to go to Examine, you have to do a detailed and in-depth analysis of the topic. Know that you have to discuss the various aspects of the subject matter. In the case of this question, you have to write about the various aspects of the performance of GST. See, this is how we have to approach this question. Now, let us look at the syllabus. This question can be asked in GSPaper 3 under the topic of Mobilization of Resources. Okay, now let us start answering the question. In the introduction, you can write about the basics of GST. See, GST is an indirect tax which has replaced many indirect taxes in India. Before the GST regime, we have had different indirect tax structures in our country. The introduction of GST was a very significant step in the field of indirect tax reforms in India. Guys know that GST has replaced 17 indirect taxes. These indirect taxes were consolidated into one GST. The amalgamation of a large number of central and state taxes into a single tax reduced to the ill effects of cascading or double taxation in a major way. Moreover, it also paved the way for a common national market. Guys know that the taxes subsumed under GST were central access duty, additional access duty, service tax, additional customs duty, special additional customs duty, value added tax, central sales tax, entry tax, luxury tax, octroy and purchase tax. The 101 Constitutional Amendment Act of 2016 was introduced to implement the GST regime. This amendment had also introduced Article 246A, 269A and 279A in our constitution. See, this is a very brief introduction about GST. You can use some points mentioned here in your own introduction part. Now, this is with the introduction. Now, let us dwell into the body part of the answer. Here, we have to write about the performance of GST. We can divide this body into two parts. One is the positives of GST and second is the hurdles. First, let us look at the positives. Here, you can mention about the revenue collection. Guys, look at this graph. As you can see that, except during the pandemic years, where the GST collection has plateaued, the GST collection has consistently increased in the other years. This shows two things. One is that GST registration has increased. See, it has increased from 1.03 crore in April 2018 to 1.36 crores in April 2023. This increase in registration has in turn increased the tax base and it amped up the formalization of Indian industries. The other thing is that, due to the simplicity of the GST regime, the tax complaints has also increased. As per the recent report, pre-GST non-compliances of more than 55% has been reduced to the meagre number of less than 20%. It is these two things that has resulted in the increase in GST collection. See, this is the first major positive. Secondly, due to the simplification of the tax structure under GST, the ease of doing business in India has improved a lot. This has spurred the economic activity which resulted in employment generation. Thirdly, GST with its one nation, one tax mantra has enhanced the interest rate trade in our country. Lastly, by incorporating the innovative ideas like input tax credit and other innovations like EVA bill, the GST regime has brought down the evasion of taxes. Here, EVA bill is nothing but an electronically generated permit which is very needed for an interest rate or interest rate transportation of goods worth more than 50,000 rupees. See, these are all some of the positive aspects of the GST regime. Now, coming to the hurdles. Though it is widely stated that GST is a one nation, one taxation regime, there exist a multiple tax rates under the GST. Know that GST rates in India for various goods and services are being divided into four slabs, that is, 5%, 12%, 18% and 28%. See, this has further complicated the procedures. Second hurdle is with respect to the structure of this GST. See, GST is a destination based taxation. So, the states like Tamil Nadu and Gujarat with a lot of manufacturing capacity are losing their own revenues. The third issue is with a compliance burden. See, many MSMEs are not able to cope up with a complicated compliance burden associated with the GST regime. See, the fourth hurdle is with respect to the technical issues associated with the GST N interface. See, this has also impacted the eva bill generation in India. And fifthly, while implementing the GST regime, the union government climbed that as the GST addresses the issue of various cascades of taxes. So, the N consumer will experience a reduction in prices. But this did not happen in reality. So, to address this, union government even appointed national anti-profiting authority to ensure that the GST rate reductions were being passed on by the firm to the consumers. But sadly, this also did not result in the reduction of the prices for the N consumers. Lastly, certain sections of the economies climbed that the increase in GST collection is not due to the increase in tax base or compliances, but mainly due to inflation. For example, year on year growth in the GST collections in March 22 was 14.7% in nominal terms. But when it got adjusted to inflation, it has drastically come down to 3.7%. See, these are some of the hurdles that GST regime currently faces in India. Now, having done the body part of the answer, let us come to the conclusion part. In the conclusion part, you can mention some important points to improve the GST regime. The points can be simplifying the GST filing mechanism. Second point is creating a unified tax lab under the GST regime. Third is to bring petroleum and electricity under the GST regime. Fourthly, addressing the glitches in the GST interface. And finally, ensuring that national anti-profiting authority achieves the mandate which is being given to it. So, you can write these points in your conclusion. See, in our discussion, we have seen the performance of GSTs and in the second part, we saw about the various hurdles in the present GST regime. So, with these learned points, we have come to the end of the discussion. So, let us finish this and take up the next news article for our analysis. Take a look at this news article. The annual nesting season of the olivaridly turtles has started this month. But sadly, nearly eight olivaridly turtles were found dead in Chennai over the past three days. It is widely believed that the oil spills which happen during the cyclone mick jam is the cause of the death of this turtle. But the wildlife warden ruled out the spillage as a reason for these deaths. See, this is the crux of the news article given here. In this context, let us quickly go through some of the important facts about the olivaridly turtles. See, olivaridly turtles are the smallest and most abundant of all sea turtles found in the world. They inhabit the warm waters of Pacific, Atlantic and Indian oceans. Know that name for this sea turtle is because of the color of its shell. They have an olive green colored shell which is hot shaped and rounded in appearances. Now, let us see the physical features of this turtle. See, the turtle grew to a height of about 2 feet in length and 50 kilogram in weight. Know that males and female turtles grow at the same size. However, females have a slightly more rounded carapace when compared to male. Now, let us see the consumption pattern of this turtle. See, the turtles are carnivorous. It means they are meat eaters and they mainly feed on jellyfish, shrimp, snails, crabs, molluscas and a wide variety of fishes and their eggs. Remember, these turtles spend their entire lives in ocean and migrate thousands of kilometers between feeding and mating grounds in the course of a year. But one of the important features about this turtle is that the female turtle return to the very same beach from where they first hatched to lay their eggs. During this phenomenal nesting, up to 6 lakhs and more females emerge from the water over a period of 5 to 7 days to lay their eggs. This unique kind of mass nesting is known as Aribada. In other words, Aribada is a phenomenon in which thousands of females come together on the same beach to lay eggs. Olive Ridley along with their cousin, Kemp's Ridley, are best known for this unique mass nesting pattern. They usually dig a conical nest about one and a half feet deep within their hind flippers and they lay their eggs in this conical nest. See guys, the coast of Orissa in India is the largest mass nesting site for the olive ridley. It is followed by the coast of Mexico and Costa Rica. After about 48 to 65 days, the egg begins to hatch and these beaches will be swamped with crawling olive ridley turtle babies. Okay, now with this basics, now let us see the threads for the olive ridley. Know that the hatching survey will rate of olive ridley is very low due to the risk of predation. It is estimated that approximately one hatching survey to reach adult hilt for every thousand hatchlings that enter the seawater. Maybe this might also be the reason why aribada happen in which a single female can lay 80 to 120 eggs and sometime even twice in a season. See lastly, let us see the protection status of the turtles. The olive ridley turtle is listed as vulnerable under IUCN status. It is also under appendix 1 of sites and appendix 1 and 2 of the conservation of migratory species or CMS treaty. This is all about this discussion. In this discussion, in the first part we saw some basic facts about olive ridley and in the second part we saw about threads and the conservation status of the turtles. With this learned points, let us conclude this discussion and take up the next news article for our analysis. Look at this news article. It talks about the government's decision to scrap the free movement regime, FMR along the Myanmar border. So from now onwards, if people living in border area wanted to cross over Indian border, they would require visas. The border areas have been already surveyed with the help of drones. So around 300 kilometers of the border will be fenced sooner. See this is the crux of the news article. In this context, let us quickly go through the free movement regime or FMR in a prelims perspective. See, FMR was implemented in 2018 as a part of ACT East policy. As you all know, the border between India and Myanmar runs for 1643 kilometers in the four states of Mizoram, Manipur, Nagaland and Arunachal Pradesh. The FMR facilitates the migration across the Indian-Myanmar borders. It is actually a mutually agreed agreement between India and Myanmar. So, FMR allows the tribes living on the both sides of the border to travel up to 16 kilometers inside the other country without visa. Moreover, they can even stay for up to two weeks per visit. So we have to know why it was implemented. See, the border between India and Myanmar was demarcated with the British in 1826. Since independence, this unfenced border is the official border line between the two countries. But the problem is, this border effectively divided people of same ethnicity and culture into two countries without their local assent. For example, know that in Manipur's more region, there are villages where some homes are in Myanmar and some homes are in India. In Nagaland's Mon district, the border actually passes through the house of chief of the village, splitting even his own home into two countries. So, since the people in the region have strong ethnic and familial ties across the border, it was very essential to conceptualize the FMR to facilitate people-to-people contact. Know that, apart from this, FMR was conceived to provide impetus to their local trade and business. See, the region has a long history of trans-border commerce through customs and border huts. So, it facilitates the sustenance of local livelihoods. For border people in Myanmar also, Indian towns are very closer for business, education and health care than even the towns in their own country. See, this is all about the FMR. Currently, government is in the plan to scrap the FMR due to various reasons like illegal immigration, drug trafficking and insurgency. Moreover, following the Myanmar's military coup in 2021, over 40,000 refugees have entered Mizoram and around 4,000 have entered Manipur. This increases the security concerns as well as for India. Know that, already Manipur has suspended FMR since 2020 due to COVID pandemic. So, now the government is going to scrap the entire FMR regime across the northeastern states. See, this is all about the discussion. In this discussion, we saw some conceptualized points about the FMR and some problems related facts about the free movement regime. With these 11 points, let us conclude this discussion and take up the next news article for our analysis. This news article talks about the new changes brought to the appointment of Chief Election Commissioner and the Election Commissioners. See, in our news article discussion, first let us understand how both Chief Election Commissioner and Election Commissioner are being appointed currently. And then we shall see about the recent news article which is being given in our paper. Let us get into discussion. See, Election Commission is a constitutional body established directly by the Indian Constitution under Article 324. As per the article, the President has the sole right to fix the number of members in the Election Commission. Currently, Election Commission functions as a multi-member body consists of three action commissioners. Among them, one member is appointed as the Chief Election Commissioner. The appointment of Chief Election Commissioner and other commissioner is made by the President. Know that they hold office for a term of six years or until they attain the age of 65 years. This is how both the CEC and EEC are being currently appointed. See, in March 2023, the Supreme Court, using its power under Article 142, laid down that the CEC and EEC shall be appointed by a committee consisting of Prime Minister, Chief Justice of India and the leader of opposition or the largest opposition party in Lok Sabha. Here note that Article 142 gives the Supreme Court the power to issue any direction for doing complete justice in any matter. So, the Supreme Court issued the order based on the recommendations of two committees. One is Dinesh Goswami committee on electoral reforms 1990 and the second is Law Commission's 255th report on electoral reforms. See, as he said that this appointment mechanism, Chief Election Commissioner and Election Commissioner will be in place until Parliament enacts a new law on this matter. Consequently, the CEC and other EECs, appointment conditions of service and terms of office Act 2023 was enacted. This act said that both Chief Election Commissioner and Election Commissioner will be appointed by the President upon the recommendation of a selection committee. Note that the selection committee will consist of Prime Minister, Union Cabinet Minister and the leader of opposition or the leader of largest opposition party in Lok Sabha. Moreover, this act also provides for a search committee. See, this committee is headed by the Cabinet Secretary. This search committee will propose a panel of names to the selection committee. This is all about the recent Act enacted by the Union Government. Now comes the point of contention. See, numerous petitions have been filed in the Supreme Court saying that the Chief Justice of India has been replaced by the Union Cabinet Minister in the selection committee. See, this change has overturned the previous judgment of the Supreme Court and the appointment procedure gives the government a more control over the process. See, this is what the Hindu newspaper article is written about. So, we have to write for the Supreme Court decision in this matter. See, this is all about the discussion. With this learned points, let us conclude this discussion and take up the next news article for our analysis. Look at this news article. This article highlights the evolution of perspectives on slums in India over a period of years. In our discussion, let us see the points mentioned in the article in a detailed manner. See, this is least important for problems but paramount for your main examination. Okay, let us see the points mentioned in the article. Firstly, let us take up the 1950s to 60s period. India, a newly independent nation, viewed slums as a consequence of partition and population influx. This is mainly due to partition where people migrated and settled near the major cities. The areas these people settled lacked basic amenities. So, during this period, the government viewed slums as an epidemic. At that point in time, the government thought that to address this issue, the only solution available to them is the eradication or destruction of slums all together. However, government intervention was limited as most of the slums were located in the private land. This changed after the slum area act 1956. Know that this act facilitated the involvement of slum and this act provided for the after formal notification of an area as a slum. See, this was happened in 50s and 60s. Now moving on to the next decade, that is 70s to 80s. In this period, the government started viewing slums as a necessary evil. So, due to this change in the position, the government focused on the development of slum rather than the demolition of the slum. Government started its focus on improving the basic amenities in the slum during this era. Government also initiated town planning in this period. Through this, the government pushed the slums to the periphery of the city. Now, let us move on to 80s to 90s decade. See, during this period, the government started to view cities, including the slums, as an economic asset rather than the liabilities. This is because government came to a realization that it is the cities along with the slums acted as the engine of growth in India. Due to this, economic reasoning overshadowed social perspectives. Government started to view the funding provided to the city as an asset rather than the liability. The focus shifted from town planning to broader housing policies. Also, in 1996, national slum development program was launched. Through this program, the union government started providing funds directly for the redevelopment of slum. Okay, now let us move on to 2002 current period. See, the census data 2011 broadened the understanding of slum. This understanding led to the targeted schemes. Also, during this period, based on the statistical information, the government came to a realization that slums which is formed in the urban area is mainly due to urban housing defects and lack of proper planning. So, the government started focusing its policy to address this set issues. Government also focused on giving proper rewrite slum doulas for their upliftment. See, this is all regarding this discussion. Through this discussion, we understand the progressive transformation of how slums are being perceived in India. We also saw how the government solution towards addressing the various issues changed from the complete eradication to technically solve the urban issues. This is all regarding this new discussion. With this, let us move on to the next part of a video that is to discuss the preliminary practice questions. Yes, today I'm having four questions. I'll solve three of them and one will be a quiz question for you to solve. Okay, let us move on to the first question. Consider the following statements with reference to the olive redly turtles. The statement one, their population are distributed across the globe except to polar regions. See, from our discussion we know that statement one is wrong because these turtles are distributed only along the warm waters that is circumtropical distribution. So, the statement one is wrong. See, the statement two, the peculiar behavior of synchronized nesting in mass number is known as aribada. See, the statement two is correct. See, the third statement, Gahirmada beach in Odisha is one of the nesting grounds of the world. See, the third statement is correct because along with Gahirmada beach in Odisha, there are also a few nesting grounds of olive redly across the world. They are along the Ganjamp coast and minor pockets of Corumandel and Sri Lankan coast. So, the third statement is correct. So, the first one is alone wrong. The other two are correct. So, the correct option is option B. See, the second question. In the context of India and neighbour relations, which of the following statement best depicts the term free movement regime as frequently seen in the news. See, out of four options, see the third option. Since it's a very easy question because we have discussed it in our analysis part. See, the third statement is this free movement of tribal across the border on either side of the Indo-Myanmar border. See that this statement is correct as we saw in our news discussion. So, the correct option is option C. See, the third question. Consider the following statements with reference to election commission of India. Statement one, it resolves the dispute related to splits or mergers of the recognized political parties. See, statement one is correct as election commission grants the recognition to the political parties and it also allows the symbols according to the political parties and moreover also it will settle the disputes related to the political parties. So, the first statement is correct. See the second one. It administers the election to the officers of president and vice president. See, this is the basic statement as we know that this is correct. See the third one. It is responsible for deciding the election schedule for the conduct of both general and by-election. See, this is also out of our common sensical knowledge. We can easily say that this is also correct. So, the three statements are correct. So, the correct option is option C. See, this is the quiz question of the day. I will post it in the community section. Interested aspirants can try and answer this question. See, the main question based on today's analysis is also displayed here. Interested aspirants can write and post it in the comment section. If you like today's video, like, comment and share it with your friends. For other updates regarding UPC preparation, subscribe to Shankar IAS Academy. Thank you.


All right. I guess I'm going to get started since the room is full here and hopefully those of you that are online and Couldn't get in or online and can at least listen or catch the reap Yeah, I think there was about 700 people that registered for the event and when I saw the room I said this is going to be a lot of unhappy people that's fine Yeah, so thanks everyone for joining and coming in person They gave me lots of room, but you guys are pretty crammed in out there. So There's only one person here. I'll explain a little bit about why Pavel's not here and And introduce him. He also was able to pre-record a few sections of the Presentation so you'll hear directly from Pavel My name is Anna Cowell. I work on Yeager. I'm the CTO at Logs. Iow works put them together One of the tools that we offer is Yeager along with Prometheus an open search and so I Spend a lot of time working, but when I'm not working I try to be underwater some photos I've taken recently spend a lot of time diving I live near Miami, Florida and Yeah, a lot of work. I have Pavel's bio. That's why I'm pulling it up and so Pavel Here so Hopefully Pavel's colleagues. He's a senior software. Sorry. All right lots of bikes. Okay So Pavel is Is a senior software engineer red hat working on distributed tracing and observability for modern cloud native applications? Pavel contributes to several CNCF projects including open telemetry and Yeager and Pavel spends a lot of time in the mountains, which is why you see these awesome pictures He's always sending me photos of him skiing and climbing and making his dog do uncomfortable things in the mountains So it's always enjoyable Pavel is great to work with. He's definitely part of the team working on Yeager and Great to work with him there and on open telemetry So you'll hear from Pavel a bit and I'll also talk a little bit through the presentation Today we're going to cover a few different things. I'm going to talk about some of the basics I'm not going to go into a whole tutorial about distributed tracing because You're going to get that in many of the open telemetry talks going on this week I know my colleague Doton is speaking tomorrow about open telemetry But I'm going to go into a few basics just for context because I'm sure many of you aren't Tracing people and you're just trying to see what Yeager can do for you and what this tracing thing is all about And then Pavel is going to go a little bit more deep into Yeager and open telemetry and how they work together I'm going to talk about a really cool feature Probably the biggest Yeager feature that's been built in the last couple of years is how we've integrated Prometheus into Yeager and you can now do application performance monitoring inside of Yeager And it's nice to have the compatibility with the Prometheus ecosystem So I'm going to talk about that and then Pavel will discuss the operator He spends a lot of time and obviously it's super important for those running on Kubernetes or OpenShift To use the operator and so he's going to talk about that And then I'll touch on the roadmap and where Yeager is going for those of you that are using it and want to see kind of What the vision is and then we'll do some Q&A so without further ado. I'm going to jump in here So a few semantics when Yeager was created and it was a project created by Uber and then donated to the CNCF It's one of the few graduated projects of the CNCF. So it's considered mature It's been around for a while. It was actually built around open tracing Which is the predecessor to open telemetry So some of the things in the UI and some of the semantics might use slightly different terminology but I'm going to talk in open telemetry words because that's what you're going to Instrument your applications with and it's by and large very similar to open tracing So the trace is basically think about an end-to-end transaction that's going through a bunch of different microservices And that's what the trace is each of those microservices and the pieces they're executing is a span So even if you're not in a microservices architecture anytime you're calling a service Which is calling a service which is calling a service. You're going to get trace data And the span itself is basically the work that one component is doing in your application And then inside of the span you can have a bunch of different types of data But tags are extremely useful. So if you're running on Kubernetes You can auto populate the data about your Kubernetes infrastructure inside the span So that when you're troubleshooting a problem You might say that a particular pod is having an issue because all of the transactions with that tag are Showing an issue with that pod name So that's what the tags are used for and people stuff all kinds of things into tags You can even like stick a whole log message into a tag. It's not always the best idea, but I've seen some crazy stuff And people also will create a lot of different types of span data related to a trace because it's your code you can essentially Instrument and build out that visibility in any way that you want So open telemetry Supports a lot of different types of instrumentation from SDKs to API's to auto Instrumentation and you'll hear about that in hotel discussions and logs So like another way to look at this visually and I'll show you how it looks in Jaeger is Basically what we call this the root span That's the first part of the transaction up at the top and then essentially can cascade through Asynchronously or synchronously and as these things execute you basically build You know a tree of what the trace looks like and then another way to look at this is over time So as I progress from left to right What are the things that are executing what things are executing at the same time? Where is there potentially blockers? That's really what tracing is useful for and to see where Errors latency or other problems are within the trace itself So in the Jaeger UI here, we're basically just visualizing over time This is a relatively short transaction 700 milliseconds and then you can see where the time is spent But a good example of you know potentially some issues is when you see things that are Stacked up like this that shows that there's potentially ways that you could improve this by threading it or changing your application And then things like errors show up and you can actually drill inside the UI So that's basically how Jaeger visualizes traces And then obviously in this case we're looking at you know front-end service And then you can watch as it goes through the back-end services. So it's just kind of an example So Pavel is going to explain a little bit about Jaeger and open telemetry for a few minutes here in the video and I will Touch on that a little bit later because it is an important part of our roadmap So here is Pavel Hello everyone, my name is Pavel and in this part I will talk about Jaeger and open telemetry first of all I want to explain the differences between these two projects and ecosystem and Then I want to bit more kind of explain or introduce you to open telemetry and Last but not least I want to talk about integrations between these two projects So what is the difference between open telemetry or hotel how we call it and then Jaeger? So open telemetry is all about data collection. It provides capabilities to together Telemetry data from our applications Process it and then send it to to any kind of vendor of our choice On the other hand Jaeger is just a platform it's a kind of a server that you can run on your machine or in the cloud and It has API to ingest but as well query and visualize tracing data and You know before I think 2021 Jaeger ecosystem as well provided the Client libraries that we could use to instrument our applications but this you know part of the ecosystem is now deprecated and the main Purpose of Jaeger is just a platform right now So the server that we can actually deploy somewhere So let's talk about it a bit more about open telemetry I'm pretty sure there is a different open telemetry Presentation at this conference, but just for the Context of the stock I want to introduce you to open telemetry And as I mentioned open telemetry is all about the data collection and data collection is very complex and difficult problem Because if you want to deploy You want to do Observability right then we need to collect as much telemetry data as possible and The problem is that there is too many or not too many but there is many programming languages and There is too. There's too many or many Frameworks in all of those languages and if you want to do If you want to understand what is happening, you know me in our applications we really need to instrument all those frameworks and This is a huge kind of job to To do right because there is just too many of those frameworks and and for example like database clients and whatnot So this is kind of the first part of the open telemetry ecosystem is the instrumentation libraries for, you know, various RPC or database clients for different Languages The second part of the ecosystem is the open telemetry collector, which is able to receive data from those instrumentations The process the data and then send it to Observability platform and the last part of the ecosystem is a specification that basically Standardizes what telemetry data should be collected To be kind of consistent across languages and frameworks so Let's now take a look at the kind of reference architecture when instrumenting The application So on this slide what we see on the other part it's user application process So it's our application in other words and it is instrumented with Some instrumentation API to collect tracing data and then this You know instrumentation Code is then sending this data to the agent and collector and finally data reaches the platform So for the instrumentation API, we used to use the open tracing API Which Yeager clients used to implement But this is not deprecated and we encourage our users to use open telemetry API and SDK to instrument applications and Then for the agent and collector you can still use Yeager agent and Yeager collector But you have as well choice to use open telemetry collector as a replacement, especially for the Yeager agent For the Yeager collector, you still have to use Yeager collector if you want to use Yeager but in some scenarios you can use Open telemetry collector and then send data to Yeager collector, which will store the data to persistent storage So let's Talk a bit more about open telemetry collector because now maybe you are confused. What is the difference between Yeager and open telemetry collector? So all the collector is essentially a pipeline that can receive data in multiple formats process it and then export the same data to to a different system and Yeager collector is a Lot different because it can only receive data in Yeager or Zipkin format and then store it to Persistent storage supported by the Yeager platform, which is you know Cassandra Elastic Surge Badger or Kafka And open telemetry collector doesn't provide any storage or query capabilities It just receives data process it and then you know Sends it to to platform, which in our case is Yeager So in the auto collector there is it's kind of the functionalities divided into three main components, which is the receiver Then processor to process the data So for example do PII filtering data normalization or even export or can extract Metrics from traces and Jonah will talk about it in more detail and Last but not least export the data to a different system So it's kind of like pipeline very flexible one that allows you to process the data Super cool is that you know a single stream of data you can process it and then exports to For example to multiple systems so you can keep some data in or export it to Yeager that you have deployed locally in your in your Environment, but as well export the same data to To an observability vendor All right, so this is the collector and now let's talk about the integrations between Yeager and Open telemetry So first set of integrations is done in the instrumentations. So especially in the open telemetry SDKs So as I mentioned before the Yeager client or Yeager ecosystem used to provide Yeager clients that we could use to instrument our applications However, those clients are deprecated right now and we encourage users to use open telemetry SDKs and APIs and To better kind of support migration to open telemetry We have done bunch of work on the open telemetry SDKs and so The old LSD case supports the Yeager context propagation header or format. So If you're already using Yeager clients and you are using Yeager context propagation You should be able to deploy new service instrumented with open telemetry and kind of make and use this piece of code that will make sure that the traces are not broken and the context propagation works across the old and new services and And The second integration in the hotel SDK is that there is Yeager email sampler implementation So if you are using Yeager sampler Yeager email sampler, you should be able to use it with open telemetry SDKs as well now Let's talk about open telemetry collector and Yeager integrations So in the hotel collector, there is Yeager receiver that can receive Yeager data in pretty much all supported formats Then Then there is Yeager exporter that can export Data to Yeager This as well Yeager email sampler extension. So essentially you can just grab your Sampling configuration from Yeager collector and use it in open telemetry collector and last but not least open telemetry collector integrates with Kafka and You can configure it to use Yeager As a payload style and the last integration is in Yeager query component or Yeager query So we have added Yeager v3 query API, which is very similar to Yeager v2 With one major difference is that the payload is not Yeager Type but is it comes from open telemetry and it is open telemetry resource spans. I highly encourage you to take a look at this query API if you want to query Open telemetry data from Yeager platform Okay, thank you very much and this is everything from the Yeager and open telemetry integrations part Cool Thanks, Pavel. Hopefully he's listening, but he has one other section. You can hold the applause till he's actually done But yeah, I mean Pavel's done a lot of work and I'll also talk about where things are going between Yeager and open telemetry because there's definitely overlap The sampling implementation for those that are really into tracing that Yeager allows for is a head-based sampling But it's it can be dynamic and it was built at Uber specifically for them to change Instrumentation dynamically based on load or other types of characteristics But it's predetermined at the beginning of the transaction not at the end like a tail-based sampler So there's actually better sampling methods and open telemetry, but that's a whole nother talk to have So I wanted to talk a little bit about Yeager and Prometheus in the new monitoring tab. That's part of Yeager We're we're always refining it, but it's been out for many months now So if you grab the newest version of Yeager It's in there and what it is is it's basically This moves Yeager from a distributed tracing or debugging UI into a bit more of a monitoring UI and allows you to actually see operationally what's happening with your service and APM is typically a combination of tracing and metrics together so that you can understand when your service is starting to show Errors going up or latency going up or some other characteristic that showing it's unhealthy or having an issue and this opens use cases for monitoring alerting and things like capacity planning as well whether We're going to implement alerting and Yeager still TBD. We'll see There's also a new Capability that we built. It's actually this is the old name is aggregated trace metrics That we called it now. It's called service performance monitoring SPM in the Yeager documentation We renamed it a little while ago But the idea is how do we integrate these two things together instead of building metrics in Yeager? We just said everyone's using Prometheus. Let's make this Part of the way that people Already work and then once it's in Prometheus not only can you visualize it in Yeager But you can use whatever front end you're you're used to using probably Grafana for the UI So the thing that we tried to solve is how do we generate the metrics from the traces? This is where hotel comes in So what we built is a processor when Pavel was talking about the pipeline Your trace data comes in from the application and then we built a processor Which is called the span metrics processor and I'll have a link to that And then the idea is you export the metrics from open telemetry Into any format that you want even if it's not a Prometheus back end you can export it But in Yeager, we only support Prometheus based back ends for the query side And so this means in our case at my company we use M3 DB but if you're using Thanos or Cortex or Victoria metrics or whatever kind of Prometheus back end as long as it supports promql In remote, right? It'll work seamlessly And then the idea is we derive the metrics from the traces automatically And then we're actually able to store them and visualize them So I'm going to show you how this works in configuration this is open telemetry collector sample config and Basically in here You're we're talking about that span metrics processor the up at the top You can actually define what kind of buckets you want and so when you're looking at a histogram Depending on how you want to segment the data and how you want to store it That's totally configurable based on what makes sense for you This is kind of the default buckets for histograms that we've set up and then down towards the bottom is the pipeline where you would Listen for Yeager traces in this case you would process it and create the metrics and then in the case of And then you would basically define the exporter now down here on the bottom we can send it to Prometheus you can send it to whatever back end you want and This essentially will create that and there's a link The presentation in PDF is in the schedule the scheduling app So you can always download it and the link will work that actually goes to the collector code base but this is part of the Contrib collector distribution if you're using open telemetry and So you can visualize it a couple of different ways in this case as an example We visualized it inside of Grafana just to show you how you can use the histograms And then inside Yeager we created a new service called the metric query service and that will query any promql back end that that understands the promql query language and Today it supports, you know, whatever kind of back end. I put a few examples And others can add so if you let's say use influx DB or a proprietary metric solution from a vendor You could actually modify the metric query service To the vendor that you're using or the solution that you're using and and it would still work in the Yeager UI So in the monitoring tab, there's basically a new little tabs that says monitor and then basically we're visualizing You know the top services And then there's a few out of the box Kind of columns that we're looking at here that we've defined It's relatively basic, but at least it starts to get people thinking about how you can operationalize trace data, which Not a lot of open source tools can do so This makes it a bit more useful And we hear great things from users a lot of people have actually Taken that open telemetry piece that we built and they're using it for all kinds of other use cases Because there's a lot of useful data when you create metrics from traces Cool and I'm gonna pass it back to Pavel to talk about the operator He's done a ton of work on this over the last few years And it's it's definitely one of the main ways that people are deploying Yeager and deploying other parts around the Yeager ecosystem, so Pavel's gonna explain a short bit about the operator Hello everyone, it's Pavel again and in this section I will talk about Yeager Kubernetes operator so Yeager operator, it's essentially a Kubernetes operator that you can deploy in your cluster and it will take care of Yeager configuration and installation on your behalf If you are interested in the operator, you can find a source code on Yeager tracing slash Yeager operator or there's as well good documentation on the Yeager tracing.io so first of all like why you should be using the operator instead of plain Kubernetes manifest files and The the answer is the operator is kind of more sophisticated and it's kind of smarter on On how the Yeager deployment should look like and Probably the biggest advantage for the operator is that it will help you with day two activities like upgrades scaling and monitoring of Yeager deployments It's as well the operator kind of as well automatically recognizes what you have installed in your Kubernetes cluster and as well like which distribution of Kubernetes cluster you are using and based on that it will kind of Unlock features that are specific to that API or platform If you are for some reason cannot use the operator then the Yeager operator you can use it as a binary to Generate plain Kubernetes manifest files from the given CR Which brings us to the CR and I'm pretty sure that almost everybody here is familiar with the term custom resource definition and On this slide we see the custom resource definition for the Yeager And it is essentially a YAML file where you can kind of describe How the Yeager Deployment or Yeager cluster should look like and We will take a look at you know parts of this CRD to explain the operator features and the first parts that we will explain is the strategy and There are three strategies right now the first one is only one in only one strategy the Yeager operator will deploy Yeager as a single binary and The single binary will then you know talk to the persistent storage or you can even skip the persistent storage if you will use the in-memory option with Yeager The second strategy is production The production strategy essentially splits Yeager collector and query into two separate deployments that you can scale independently If you will hit scalability limits with this, you know deployment Strategy then you can switch to streaming that essentially splits Or decouples Yeager collector from the persistent storage by putting Kafka in between And this is by far the most scalable Yeager deployment that you can achieve with Yeager operator So now let's take a look how we configure the storage in the CR The storage, you know, you can configure it in under In the CRD under spec.storage node and there are two most important Kind of configuration fields first one is type where you can define which storage type you want to use There is in-memory elastic search Cassandra, Yeager, even gRPC plug-in and Kafka and the second option is the options that is loosely coupled and here we put the The storage related flags for the given Storage that we want to use and you may ask the question, how do we find out which flags the Yeager supports, right? There are kind of two ways that I can think of you can either go to our documentation on YeagerTracing.io or you can run the Yeager collector or the query docker commands or the binaries With the spend storage type set for your storage of choice and use the health flag and it will print you all the supported flags So for example in this CR we are configuring the collector options and here under the option node We can put the all the supported collector options Okay, let's take a look at another Yeager operator feature that is related to Yeager agent and The operator allows you to inject the Yeager agent into your verclodes and For this you have to in the CR you have to set the agent strategy to sidecar which is default by Which is by default so you can even skip it and then if you want to inject the sidecar then On the deployment annotations you have to you know provide this annotation with value either true that will You know choose the right Yeager instance Where the data will be going or you can set it to false to disable injection or you can here specify the Yeager name that And then The Yeager instance with this name will be used to send data to the other agent strategy is demon set and in this strategy Yeager operator will deploy agent as dean on set on every Kubernetes node in your cluster Last but not least the Yeager operator integrates with Two operators. The first one is Kafka Which comes from streams the operator and the second one is elastic search which comes from open shift cluster logging operator and if you have these or let's say elastic search operator installed in your cluster then Yeager operator kind of will recognize that and it will It's able to provision elastic search instance for you When you will be you know creating new Yeager instance and the same for Kafka And the second integration is is monitoring of Yeager operator So Yeager operator itself is instrumented with Prometheus for metrics and open telemetry for traces So it's able to you know emits telemetry data kind of That will give you visibility how the Yeager operator behaves and what it does So thank you very much and this is everything from the Yeager operator part So thank you for that appreciate it Cool, and so I did want to touch on the roadmap I know I'm running up on time, but this is quite brief So I mentioned adaptive sampling Where there's this new sampling type We recently we're still working on this where we're making some good progress and it allows for dynamic sampling control This is something that that we came out with recently an open telemetry which Pavel touched on The service performance monitoring which I touched on that's also a new feature that's key And then we've actually decided as a project to really move towards open telemetry We've gone through deprecation of the Yeager clients and the SDK And that leads me to where we're going from there Which obviously has a lot to do with with open telemetry in the second part here, but We're we're doing some work on the dependency graphs. So those of you that are using Yeager There's kind of three different dependency graphs in Yeager They're all kind of mediocre or let's say not that useful So we're actually going to be normalizing these together and really creating a nice service topology view That's interactive has metrics overlaid on it. So we're gonna really You know improve the way that the that the service graph the topology view looks and what it does and We also are thinking about moving the calculation of that dependency graph Which today actually requires that you deploy spark or Kafka streams Potentially into the open telemetry collector. So there's some work going on there Of how to calculate these topology graphs and we're hoping we can do that in open telemetry and reduce a component in the Yeager architecture and then Secondarily, which is the bigger one is we're actually moving and Pavel's actually already built a POC of this But we're gonna basically implement the Yeager storage exporters inside open telemetry and Create a distribution of open telemetry. That's basically a Yeager collector So the history of Yeager is of open telemetry is that actually was a fork of the Yeager collector That then had the stuff built around it and now we're going to actually bring it back in and make Yeager collector a distribution and Then another piece where there's active work going on is native support for open telemetry line protocol So that'll allow you to write directly To open telemetry for many Anything that supports otlp and we can take it into Yeager natively, so it's definitely more coming And I would at offer questions, but I don't know if I have time for it And I'm gonna put up a few links. Do I have time to take a couple questions? I think I do so Does anyone have a question and I will bring a mic over to you? Hopefully this works. Yeah Yes, a question about the service performance monitoring would it also expose those metrics as Prometheus metrics to be scraped instead of being forwarded Just for simplicity because it's calculated inside open telemetry I don't believe you can scrape a collector, but maybe you can so if you can it would work the same way It's working another question Thanks, is that a strategy for handling long-running background tasks as part of a trace? How do you handle that usually? It can cause You can do it, but the problem is that sometimes it won't visualize properly So it's actually more of a UI problem not a problem with the actual storage of long-running traces And part of it is the UI starts to look weird when you have something running for a week It's like what do you it's going to be like these little teeny things happening? So the UI is not really built to visualize traces that run over like days or many hours But the data in the back end storage is there So you could write your own Visualization and use it totally so there's no plan like to add some kind of linking between traces or It is in the data, it's just not in the UI, so there's no plan to make the UI work with that. Okay If you're using something like open search or elastic search You could do something in cabana or open search dashboards to visualize it And I know the open search team, which is open source. They're building some Trace analytics capabilities that we're gonna be that are going to be compatible with Yeager where it might actually solve that So I would check out open search. They have a trace analytics plugin That might do a good job and you can use it together with Yeager Soon not quite yet right now. There are two formats in the storage But they are gonna support Yeager format It's part of the plan there. So yeah, sure. Thanks Guess one more till they kick me out. I'm gonna keep taking questions. So I'm working on a rather Unusual use case. I'm instrumenting a CLI app that has gRPC plugins And I want to visualize the interaction between the CLI tool and its plugins What would be the minimal Amount of open telemetry and Yeager components and I need to ask the users to have available when they run this thing So they can ship me Spans for debugging for example, like do I need to So you you when you build your tool, which is a CLI tool You would instrument with an SDK in the tool and that would emit the span data Yeah, but the user is off to have something to collect it. What would be the least amount of Yeah, so you I would probably that's gonna be tricky because the user might not be connected to the network Essentially, right, but they could they collect locally and then ship me some sort of like You could do something like that so when Pavel was explaining the all-in-one you connect There's actually a back-end called badger. That's an open source Database essentially that Yeager is compatible with and that actually is stored in a file So you could potentially store it as a badger database locally And then they can send you the file and you should be able to visualize it with the Yeager Query in the UI. So that might work for you. Yeah with Yeager. Sure. Yeah Sounds like a fun project. I guess I'll take one more. Do you mind passing this back? So I don't Thanks So it kind of depends on your back end and that's more of an open telemetry thing We're not going to visualize exemplars inside Yeager UI, but you might get those inside, you know Grafana UI for example, so we're not planning on implementing it in Yeager UI But it's it's supported as long as the exporter you're using supports it within open telemetry But we're not going to visualize it. So And I think yes Yeah, so there's a hyperlink in that monitoring tab that allows you to move from the service Into an example trace of the service. So it's similar to an exemplar, but it doesn't use it from the metric data It's inside the Yeager UI because it knows that those things are linked together I Think that's all the time I have for but I'll be up here or tweet message And I'll try to answer the Q&A that was sent in online Through our slack channel, but thanks everyone for joining