Just when political parties participating in the Kawata constituency parliamentally by election thought all was it and hit the ground running with campaigns, sadly they have to start afresh as the contender representing the United Progressive People, UPP Francis Rivenda, has given up the race before the 20th of January 2022.  But Friday, 7th January 2022, Mista Rivenda announced that he could not proceed with the contest. Many I widely consulted with my family and I decided that I would draw. To understand the implications of his decision, we spoke to electoral expert McDonald Chepenzi who said the move will compel the Electoral Commission of Zambia to call for fresh nominations and prescribe the new debt for the election. 52 of the constitution of the Republic of Zambia. This article requires that new nominations are supposed to be done and fresh debt of the election is to be announced. This is the predicament now that the candidates that filed in will have to face. It means that they have to pay new nomination fees, they have to organize new supporters for them to be successful. Actually it's a new nomination that has just been triggered. I think it's very important for political parties and their candidates to be serious. It's not good to punish your fellow participants just because you are not ready and you are just a joker. Let's move away from comedian in the electoral process. It's an expensive process, a dedicated process and it should not be allowed people to just withdraw anyhow as they feel like. In this election, some political parties such as the Patriots for Economic Progress, PEP have been having challenges to memorize resources to conduct campaigns and resulted to asking for contributions from members of the general public and yet they will be compared to pay twice for nominations. One can only imagine the predicament. Certainly this scenario was witnessed in the August 12th general election and caused for electoral forms. Good morning ladies and gentlemen from the press. I would like to welcome you to the garden office of the president of the socialist party. This press briefing is going to be pretty short. It's about Kavwata and the happenings that are going on associated to the by elections. We are 19 days in the campaign period. We have only got 12 days to go. And so far information on the ground is that the socialist party candidate kumrit trefa ngandu is doing pretty well. And the kumrit is seated next to me. Our campaign has been the best organized and the reception of the people of Kavwata to his candidates has been very positive. Some three days ago we started receiving rumors that a candidate is going to withdraw. And that was worrisome. Yesterday indeed we saw a letter and this is already in the public domain that one of the candidates Vibanda Francis has withdrawn from this race. And the understanding of many people is also that these elections will be stopped or postponed because a candidate has withdrawn. In our opinion this is a misuse of clause 52 section 6 of our constitution. This clause was meant for calamities such as death of a candidate just to give a fair chance to the political parties that are participating. This clause was not meant for people that will come into the race and then resign expecting that new elections are going to be held. Our appeal is to the ECZ, the electoral commission of Zambia, that this issue should be treated differently. The campaign should go on if these elections are postponed it will set a terrible precedence for the democratic process in Zambia. Any candidate will wake up and say I'm not standing anymore, I'm withdrawing and that can go on and on. There will be no end to this. Kavwata should not set that precedence. The law should not be misused in any way. The Zambian electoral system deserves to have credibility. It has suffered for a long time and let Kavwata not be one of those that breaks it down. As I said again, this news we did receive some time back and they are quite disturbing allegations involving the UPND in this whole process. And those allegations are that the UPND engineered this resignation and this is serious. This story and these allegations would still doom the Zambian democrats. That story states that this resignation is induced because the UPND is having serious problems selling its candidate. And that they have lined up two candidates whose names we have been given to take over. So when this is postponed and it resumes it won't be the same candidate that the people of Kavwata have rejected. Again at this point would appeal to the investigative agencies to the anti-corruption commission would like to appeal to the police to get on this matter as quickly as possible. If these allegations are true, this is a crime being committed and we shouldn't allow it. We are going to engage the parties affected. We are going to engage the ECZ on this issue because this is an issue that touches all of us. The people of Kavwata have been often by not having a legislator for months now. The legal interests, narrow interests of political parties should not deny that constituents' legal or political representation. This is greediness at its waist and as a socialist party we are touched, we are moved by this situation, by this development. You may be asking why didn't we go straight to those institutions, why are we bringing this open? This is not an institutional issue, an organizational issue alone. This is a matter in public interest. There is no way we are going to appeal only to these institutions quietly. We are beginning the process informing you ladies and gentlemen from the press but also the people of Kavwata that this is what is happening. There is a possibility of your elections being postponed. Your constitutional right to have representation is going to be postponed and for what? For the narrow political interests of those in power. That's why we are bringing it out. We are going to follow it immediately, engage the different parties as alluded to. Our people on the ground are also following up as much as they can, get as much evidence as possible. The idea is to bring this to an end. With your help, your involvement, we should be able to create a better Zambia, better democratic processes for this country. The crime-like behavior that these allegations entail should be stopped and that should be done immediately. Thank you very much ladies and gentlemen.


Test, test. All right, so welcome everybody. This is the Nutanix presentation at the Marketplace Theater. So if you're interested in learning more about Nutanix, please come sit down. My name is Lucas Lundell, and I am the Global Director of Solutions at Nutanix. So I run a team of individuals that writes our best practices, reference architectures for any solutions that our customers use, whether it's SQL, SAP, Oracle, VDI, and general server virtualization. I want to start off with a little bit about my background. Before Nutanix, I was actually a data center architect, and I designed data centers for the federal government and financial services companies with Accenture. I worked in their research and development lab. A bit more about Nutanix. Today, we have over 1,750 customers. We have appliances in 70 countries. And our team has grown to over 1,100 employees. And this is just in the last four years that we've been selling a product. So we've seen some very fast growth in the last four years. We also are very proud of our net promoter score. So net promoter score is customer satisfaction for your support team. So we have over a 91 net promoter score, which is highest in the industry. So this is Gartner Magic Quadrant for integrated systems. Nutanix was placed as a leader in the Gartner Magic Quadrant this year. And it's actually the farthest right company. So it's great recognition from the industry and the growth that we've seen from Gartner. So we're very happy with that. And there's actually a Gartner symposium this week in Tokyo as well. So we're very excited to be participating in both of these events. Now, what does Nutanix actually do for those of you who aren't familiar with our product? In obviously a normal standard enterprise virtualization environment, you would normally have three types of gear.  And then you have your storage, whether it's a NAS or a SAN appliance. Now, you manage each of these pieces of gear separately. They're usually produced by different companies. You're responsible for ensuring you're running the right versions of code, BIOS, any software firmware that runs at every layer. And it's very difficult to scale. So as you fill up an existing storage array, you have to buy a new one. Now, what we've done is we've taken all the intelligence of a centralized storage array and built it into a distributed software system. So we have our own distributed file system that we sell as an appliance, as a building block for the data center. And the reason that we did this is we look at the data centers of companies like Amazon and Google, Microsoft. There's no such thing. Most of these data centers, they don't have centralized storage arrays. They run software on Commodity x86 hardware. And that's what we've done. We've taken that intelligence to the storage array and baked it into a distributed file system for enterprise virtualization. Now, what do we actually sell? So we have an array of different appliances. Each appliance has compute and it has storage. It has memory. So we use two different types of disks on every appliance. So we have SSDs and HGDs. And our software is intelligent enough to auto-tier data between those SSDs and HGDs, depending on frequency of access and what data is the hottest. There's also an in-memory read cache. Now, this single appliance, it does all the storage. The storage pooling, so you add more appliances. It's able to pull all that storage together and present it to whatever hypervisor that you want to use. So we support VM or ESX. We support Hyper-V. And we also support KVM. Now, on each of these appliances, on each of the nodes in a cluster, we run our software as a virtual machine. That virtual machine has access to the SSDs and the HDDs. And those virtual machines communicate with each other to form the distributed file system. And on top of that file system, we present it to the hypervisor. And however, using whatever mechanism that makes sense for each hypervisor. For VM, where we use NFS to present that pool. For Hyper-V, we use SMB protocol. And for KVM, we actually use iSCSI. So depending on what hypervisor we're using, we're presenting that pool of storage to the hypervisor in a different way. But on the back end, it's all managed and controlled by our distributed file system. And these are a couple of our enterprise customers, data centers here. What's nice about our solution is you don't have three different types of gear to manage anymore. You have a single building block that scales out as you want to add more compute or storage capacity. You simply add more nodes. And we've had some great success here, some of the customers of ours in every industry. But I want to move on and talk a little bit more about what we're doing with OpenStack. And then also answer any questions that you guys have about our solution. So on top of the KVM hypervisor in particular, we've actually built our own management stack. And this management stack runs on the same distributed system as our file system. So we have our own hypervisor management capability that allows you to create VMs. It allows you to create storage, store files for these VMs, do snapshots, do duplication, compression, high availability. So if a host fails, allow those VMs to start on another host. Motion. So if you're trying to move VMs between hosts, it supports all those capabilities. Now, we also have customers who are very interested in using OpenStack and a lot of the advantages that OpenStack provides. Things like the easy to use interface with Horizon, some of the networking capabilities with Neutron, users in quota management, single sign-on. So what we've done is we've integrated our Acropolis technology with the OpenStack services. And how did we go about doing that? First of all, why did we go about doing that? A couple of the key reasons is our file system has many pieces of functionality that haven't quite been implemented. Things like auto-tiering, so flash and H2D auto-tiering. Things like VM data locality. So when you're running VMs on a Nutanix system, the data for a VM, even if you're using something like Cinder, you're actually using NDFS on the back end. And it allows the data for each VM to sit on the flash tier local to that VM. And in the background, we're also replicating that data to a different node. So unlike Amazon EBS and native implementations, we have the concept of VM data locality. And we've seen that reduce network consumption and also improve performance and scalability of any sort of distributed system. We also have things that will transparently happen within our file system, like compression. You can turn on compression, deduplication, and get all of those benefits without actually having to worry about configuring that within our own file system. In-memory caching is another feature that we have. So there's a lot of things that we're doing in our file system that help scale an open stack infrastructure deployment. Now, how do we go about integrating Acropolis and some of the OpenStack technology? We've actually developed another VM, which we call our Acropolis OVM, that sits in between any OpenStack distribution and Nutanix. So you have this VM. And this VM is able to export a Cinder service and a Nova service and serve as an endpoint for those services. So you'll run an OpenStack VM, which we call an OpenStack controller. You can run one or many of those controllers, depending on the scale of your deployment. You'll run an Acropolis OVM, which handles the integration between the OpenStack APIs and our Acropolis APIs. And that'll allow you to use our file system as a resource provider for both Nova, Cinder, Glance, and Neutron. Now, the OpenStack controller will continue to take the dashboard, the orchestration, quota management, user groups and roles, and SSO. So all of that looks the same. It looks like you're managing an OpenStack environment. You have the OVM, which handles the integration. And then you have our cluster and NDFS, which provides all those basic infrastructure services, along with the features of the file system. Now, this is just kind of the high level of what it looks like. You'll have your OpenStack controller. That exposes all the OpenStack APIs. And then it does RPCs with our VM, which exposes all those services and all the resources that we have within the Acropolis cluster. Now, in terms of how the different services break down and what VM holds primary responsibility for each of the services, this is a map. So as you can see, the OpenStack controller is responsible for Keystone, Horizon, Swift, Glance, Heat, and all the other services. And with Acropolis and NDFS, we expose Nova, Cinder, Glance, and Neutron services through Acropolis. So the APIs look the same as a resource provider for each of those services, even though on the back end within Acropolis, we're using Nutanix technology to manage the clustering and also obviously the storage with our file system. Now, as you want to scale a deployment, like I mentioned, you can have more than one OpenStack controller VM. You can also have more than one Acropolis OVM. And if you want to scale it across multiple sites, you can use load balancers across multiple sites to run a multi-site deployment. As you want to add resources to Cinder or Nova, it's as simple as adding nodes to the Nutanix cluster. So we automatically discover, as you add nodes to the same layer or two network, we automatically discover those nodes. You can go to our interface, which is called Prism, add those nodes in, and we'll automatically register it as a resource through Cinder and Nova so that you can run VMs, provision VMs, either through Acropolis or from the Horizon dashboard. So all of this information, we've actually made available. We have a site called the Nutanix Bible, which goes through all of the details on our file system and on our technology. We're very transparent about the functionality and features that we have. So we've written up our OpenStack integration within the Bible. So if you're interested in more information about how Nutanix integrates with OpenStack, we've made it available at that website, which is just nutanixbible.com. Now, why OpenStack is capable of a lot of these things, a lot of, I think there's a lot of benefits towards using both solutions together and integrating Nutanix with OpenStack. It gives you a very simple building block for building out your OpenStack environment. It's also something that we support. So we have a team. We have support teams located across the globe. We actually have one in Tokyo. This is a solution that's fully supported by Nutanix. So as you deploy an OpenStack environment, we help you with the deployment. We help you with the integration. And it's easy to scale. Now, as I mentioned, with the distributed file system, you get a lot of benefits that don't exist in other distributed file systems, including data locality, snapshots, using our snapshot technology, deduplication, compression, and other benefits of our file system. All right, so that's a summary of our OpenStack integration. I want to leave five minutes. If anyone here, any folks in the audience had any questions, we also obviously have our booth here I think it's T70. And if you're any questions from the audience about Nutanix or OpenStack, NDFS. Sure, for the SDN part, so networking within Acropolis, we've kept it very simple. Within Acropolis, you can create different VLANs. So you have VLANs, you have VLAN IDs. And then as you create VMs and their network interfaces, you can associate those with different VLANs. So it's a pretty simple networking model. The SDN side of it, like switch management and all of that, is not something that we take on. So you can use Neutron, you can use Cisco ACI or any other NSX, NYSERA. All those technologies can work with us because all that we need to run our system is a simple layer two network. So once you have a layer two network, doesn't matter. Yes, because you can run Neutron and whatever Neutron's capable of, you can do. So as long as you give our technology a layer two network at the end of the day, we can function. So we've kind of left it up to the customer to choose how they want to do networking. We haven't done a lot in that area besides simple, when you create VMs in Acropolis, assigning those VMs to a VLAN. That's it. That's all you really have to do. We don't manage the network topology or do any layer three overlays or anything like that. Good question. All right. Yeah, so the way that we expose Acropolis to OpenStack is done in a way that it just looks like a Cinder or a Nova resource. So you can use it with whatever distribution. I mean, we've tested it with Canonical as a partner of ours, Ubuntu. We like that distribution. We have customers using that integration. But yeah, I mean, we haven't found a distribution that doesn't work with this model yet. I can't say we've tested them all. But certainly, we wouldn't preclude you from using any distribution that you want. Sure. How do you do backup? So I mean, there's a lot of ways that we support backup or that folks do backup. I mean, there's snapshots, which isn't really necessary. The question was, how do you do backup with Nutanix? There are third-party backup providers that work with ESX. We're working with other third parties to develop integration with our KVM solution. So I mean, some of the more popular ones, obviously, Symantec, Commvault, Veeam. We're working to support all those solutions with Acropolis. We already support those with Hyper-V and ESX were appropriate. All right, any other questions here? I think I have about a minute left. If anyone else has anything, we also have, if you want to pen and want to get your badge scanned, we have some reference material here that we're handing out. All right, so we're very excited to be here in Tokyo. I appreciate everyone for listening to my presentation. And have a great week here. Thank you very much.


My name is Jin Bo-wen. I'm the training manager at NCI. Even though I work here for about eight years, the new role of a training manager just to start the beginning of this year. In this talk, I would like to share the new training strategy that we established this year some thoughts about how do we measure the impact. I think you would all agree with me that digital skill is one of the key elements here to underpin the integrity of research and this has been addressed in the NCI the next five years roadmap and training is one of the area that we want to focus and help the research community. At the beginning of this year, I've done quite intensive consultation internally external stakeholder one-on-one interviews plus hundreds of response from user survey about what the requirement on the training basically the message is quite consistent across all stakeholders saying that yes we need training at all different level across different topic and we actually identify a couple of gaps in this exercise. The first one is that we know the technology moves really fast but we also observe the community pick up the technology at a different pace. Some of them are falling behind and we are thinking why is that? I think it's quite obviously that some people may not even know that exists and sometimes people may think oh I know it's coming but I don't see the immediate impact on me so there's no motivation to pick up and learn those things right away and also I think in the e-research two weeks ago some some people raised about the question how the Haas community pick up the AI. I think that's a good example to show that they wanted to get on top of those technology but they don't know how and where to start with so I think that's where we can help. The second the gap we identified is the missing fundamental computation skill in many science domain students. If we look at the university curriculum programming and command line and parallel computing are not offered as a formal requirement in the graduate program but people need it so they have to learn by themselves or they attend the course that for example NCI or POSI or Intersect offer to those university sectors. The third gap is that I found the requirement on training is quite heterogeneous. I think that's very obvious because we help we serve across multiple domain the data coming in different formats and they use different workflow and libraries. I feel that the introductory level courses can only go that far to get people on board but if you want to further help people to scale up to the next level to intermediate even advanced I found they specialized the training example and customized training workflow to the domain science is really helpful for people to pick up things right away. Based on those gaps I developed a quite end-to-end learning journey where all the learning components identified in that curriculum from absolute beginner in the stock training to become an expert. Basically we have all these learning components built as a framework and people can pick up the relevant parts to themselves to learn things. Now let me shift to the impact parts and see how how we see that the training help user community and I think the first one would be a great outcome that people feel now I can do it before I can't and then they might suffering from difficulties or frustration why my code doesn't work or why my code take ages to finish. With the training on parallel for example they can run things at scale and of course I think in the end from learning and teaching experience it's all about building confidence and I think training is a good way to help all the students and researchers building confidence adopting new technology and I don't know regardless whether they realize or not by introducing the new tool and new platform we actually gradually change their workflow and if they adopting the new tools they change the new environment they basically working in a faster mode and I found that especially the group who intended to adopt those latest technology and apply to their research domain more quickly often help to put themselves in a more competitive position to have a higher chance to win the grants and publish high quality journal articles in those tier one research articles in a much faster mode and of course I'm passionate about training because we I feel that this is a two-way communication through that training we hear exactly what people's need and we address those needs through the training material we build a trust and supportive community with each other one of the way to quantify those impact is the environmental impact on the job efficiency so if we think about after training people can run 10 times faster than they used to be then it can be translated as an electricity bill that can be further interpolate as how much carbon dioxide emission generated by the research community that is a quantified environmental impact that we've done through the training course now I'm going to shift from the the metaphor of animal picture to the real science here by sharing another observation about the impact which I see that the training community really inspire the cross disciplinary research leverage I will use two real examples to explain what do I mean by that the first one is signal processing so the picture here shows you an oil reservoir where high fluid of high speed fluid was injected into the well and forced the rock open fracture fractures that fracture allow the trapped oil come out of the reservoir when the fracture happened it's actually a small earthquake so the signal is like this it's an impulse signal on the right hand side it's a human body's nerve impulse the signal is very very similar look like the micro seismic event the commonality of the technical issue behind those two different scenarios are that they both suffer from very big overwhelming noise as a background interfering the signal so it also means that consequently the same knowledge or technology of signal to noise ratio improvement can be applied to two different scenario but working on the same type of time series of data the second example is about image if we think about an image in the computer science it's basically represented as a matrix with x and y as the position of the pixel and the third column could be the color scale from 2 to 255 and in the colorful image it's a combination of the RGB but still it's a matrix but to scientist that matrix means completely different things in different domains this one is a brain scan in the medical science and this example is the satellite image and this example is a climate model the paper published in Nature last year the commonality between those examples are that image either have a low resolution or some part are missing especially in this climate model some area like the remote area in the polar or in middle of Pacific Ocean we often suffer from the sparsity of the data and using the deep learning neural network technology we can actually reconstruct those image with a higher resolution or backfill the missing bit so the technology behind are really similar so the main point is that by bringing the different community together and they watch each other and see oh I've used this technology maybe it can be applied to my research and that's I think the motivation and impact to the research community through this training forum now the question is how do we quantify them I didn't see I I did a quick analysis in the beginning of the consultation process and see how many tickets are there and what they are talking about so I used a natural language processing technique to analyze those texts and classify by topic so I identify a number of most frequently asked questions so through that classification I got a pretty good idea to understand what is the daily question from the user support group and then we can address how to help to answer those questions by offering training courses or good documentation and of course I mentioned about system log about the job efficiency that as another quantified in measurement but I also want to throw something here the idea of a knowledge graph how to measure the long-term impact of the training by introducing the new tools and accelerate researcher with advanced training courses how do we impact the whole research life cycle here I use this node to represent user organization brands publication and collaboration each node can be identified with a persistent identifier and I built this model early on when I was a data collection manager at NCI we wanted to see the impact of the data collection so on the left hand side you can see the graph that we built is composed by the creator of the data and data collection themselves and the publication that sides the data and we wanted to see the dynamic ecosystem of the data impact between the people and the publication system and then we augment this graph with international database with ORCID so that we can see further down the track what is the impact of the data collection the reason I want to quote this work is that can we build such a kind of graph to measure the impact through the whole research life cycle by introducing an excellent training program so finally I want to just wrap up with back again with my animal theme today is that I really believe a collaboration is a key words so recently we announced a collaboration in partnership with intersect that they can help us to offer introductory courses to our user that response is I am totally overwhelmed with hundreds of seats or booked out within just three days and I feel deeply passionate about training I saw Claire is there I remember in my previous days working together with Claire offer training courses with people we always get feedback and that's the passion and love that I want to bring to the community of course translating those passion and love into practice I think quality is one of the keywords making sure that the tutorial that we created has quality and that's really make a big difference when we're marching together we also want to make sure that nobody is falling behind especially for people who don't know where to start I think we have a key role to play and help each other with that I'm going to finish with the general email address training dot NCI at AU.edu.au please reach out if you have any comments idea and intention to collaborate with us and by the way we're also recruiting a few training offers as a casual position to help us with that I'll stop and hand back to Anastasia thank you


Are you feeling overwhelmed about where to apply for university? The truth is, I felt really overwhelmed when I was going through this and it's something that a lot of students face. The reason is that this is such a huge topic and there's really a lot of different factors that go into it. My best advice would be to do a lot of research into what kinds of universities you're looking at, what would work well for you and what fits your personal circumstance. Chances are, what you're thinking about when applying to university is going to be really different than your friends and other people who are doing the exact same thing. Try to keep an open mind as much as possible and take in as much information as you can from talking to other people and doing your research online.


Thousands of ex-Vagna fighters to join Chechen unit Ramzan Kadyrov, the Akhmat Special Forces unit from the Chechen Republic, will absorb 3,000 ex-Vagna private military company fighters, the regional head Ramzan Kadyrov has announced. A renowned Wagner commander with the call sign Ratibor will also join the elite Chechen unit. After now deceased, Wagner chief Yevgeny Prigoshin's failed mutiny attempt in June 2023, the Russian authorities gave the group's members the choice of either signing contracts with the Defence Ministry or moving to Belarus. In a post on his telegram channel, Kadyrov wrote that Russia's Defence Ministry had already allocated the necessary number of vacancies to accommodate the newcomers in Akhmat. He added that arrangements and formalities will be sorted out in the near future and the ex-Vagna fighters will soon see action. The Chechen leader hailed the fighters as experienced and very effective warriors, who have proven their metal in Ukraine. He described the incorporation of such troops into Akhmat as a strategically important step toward beefing up the country's defence capabilities. We are united by a single purpose to defend the motherland and its interests. I am convinced that this decision will very soon have a considerable impact on the way the special military operation progresses. Kadyrov concluded, in February, the commander of Akhmat, Apti Alodinov told the Russian media that there were three separate units composed of former Wagner private military company fighters in his detachment. Akhmat is a part of the Russian National Guard, which is an internal military force that reports directly to the President and the head of the National Security Council. The Wagner group played a key role in seizing the city of Bakhmut in Donbas last May. Russia rebuilt its military after suffering tremendous losses in Ukraine, U.S. official. Russia has been successful in rebuilding its military after suffering tremendous losses during its full-scale invasion of Ukraine, a U.S. official has claimed. According to Defense Post media outlet, speaking during an event hosted by the Center for a New American Security, U.S. Deputy Secretary of State Kurt Campbell stated that they have been monitoring Moscow over the last few months to assess if it has regained its strength. He said invading forces have almost completely reconstituted. Thanks to the significant surge in its defense spending since the war broke out in February 2022, the support of its closest allies in China, North Korea, and Iran has also helped Russia endure economic and military setbacks in the last two years, Campbell stated. We've really seen the People's Republic of China start to help to rebuild Russia's defense industrial base, essentially backfilling the trade from European partners, he remarked. As of March 2024, Russia has likely suffered more than 350,000 casualties in Ukraine due to Kiev's heavy resistance according to a UK Ministry of Defense Intelligence report. The average daily number of killed and wounded Russian soldiers currently stands at 983, the highest since the invasion began. Additionally, Moscow has reportedly lost 2,619 of the nearly 3,000 tanks it initially deployed to Ukraine. US intelligence officials previously claimed the invading forces might need a decade to fully recover considering the enormous losses it had sustained. But Campbell's latest assessment fuels speculation that Russia is recuperating faster than expected and on schedule for its alleged plan to attack a NATO member by 2026.


Okay, so yeah. Hi, I'm Josh. Hi, I'm Interpolar Manager for Distro-Tracing at Einstein IBM. Yeah, and today we're going to talk to you a little bit about open telemetry and observability and using the two of them together for healthier software. So today we're going to cover a few topics. First we'll talk about sort of observability broadly and how it differs from traditional monitoring and APM. We'll talk about the components of distributed tracing and how it's a different challenge than what we maybe used to coming from monoliths. We'll introduce the open telemetry project and its benefits and talk about why you might want to use it together with something like Instana. And we'll talk about the different ways of instrumenting your services for tracing specifically. So we'll talk about some automatic and manual instrumentation methods. And then finally, we're going to show you what you can do with all of that data in an observability backend like Instana and how you can actually use the data to gain insights into how your software is operating or failing and remediate it. So first, we want to just briefly talk about what is observability. I'm sure this is the topic that many of you have opinions about. I just want to get us all on the same page for this talk. So to us at Instana, this quote is a paraphrase of the original 1960s paper by Coleman on observability. So it's observability is certainly to understand the interstate of a system by measuring all of its outputs. It's very relevant to microservices because even though we can technically see into the communication between the various services in practice, the complexity of the architectures makes that very difficult. And so with traditional monitoring, you know, you're setting up monitors on known services and how they interact and communicate with your other services. The landscape is shifting too quickly for you to keep up with your manual configuration and how do you, how do you deal with that. How do you gain the insights that you need. And so with observability and especially at Instana we believe that to achieve this complete visibility of your application, you need automation. And so that's why we try to automate as much of the process of gathering telemetry from all of your various services. So it's a complete picture that adapts and changes as quickly as your application does. And that then in turn allows you to answer questions that you didn't know you were going to have when you set up your observability tool, as opposed to just being able to answer questions that you have thought about in advance, which is not enough. So I talked about a little bit about telemetry data. So Yinshi, why don't you tell us a little bit about the signals that we're dealing with. Yeah, so basically there are mainly three types of signals, one is metrics, basically measurement of your services captured in runtime. So you have logs like timestamps data, string data, unstructured on nodes, and then you have traces. Traces is really about give you full picture of how your systems works, and we will focus on traces in this webinar. Yeah. And I think, you know, like I said, like we said earlier, coming from a traditional application where you maybe only have one process running on, you know, one machine. Your logs are in effect your traces, you can go to your logs and you can follow, you can correlate the events happening in the software in the logs with the requests that triggered those events. So distributed tracing is really the art and science of correlating and user requests with processes inside your software, no matter how many services those calls without. Yeah, definitely so it's definitely we people start to do distributed tracing because we move from monolith application to more distributed like complex services, then you does not know like how it attacks in your system right that's why we need distributed trace. So this quote kind of kind of lays out what we're talking about. Specifically, the traces are made up of calls and spans I'm sure many of you are familiar with this terminology we're just going to review briefly. Yeah, so basically a trade trace is a series of calls and calls are like this page said communication between two services, it could be a TV request or database queries, or a message in your cute message queue, and a cause could be combined by spans like access spans, which is basically a request so recorded by your server, because it's enter the your service or exit span which is more like a client request it goes out from your service that's why it's called. access bands and if we combine those two span you will get a cause and also sometimes you will have like intermediate kind of spend like internally in your system, you know, in that service, you have made some, I don't know function costs or something except. Because it kind of an illustration. Yeah, yeah, so basically this is kind of a trace.  And when they miss that request it goes through your API's and the API's internally will cause some awesome also relation authentication to know if that's a user and right if they want to pay you will have to go to payment. You know, some database course and also call external third party external API's to know okay if that's payment is successful or not. So it's definitely a lot of like service or cause going on here. And that's why we need like this free tracing to give you a full picture, say if if customer cannot add their item to their shopping cart you will definitely want to find the root cause very fast and distributed tracing enable you to do this. Yeah, excellent. And so there, there are some components that we need to enable distributed tracing. Yeah, so they are mainly we categorize into three components. So the first one is like instrumentation of your application rights. You need to be able to generate those signals are in concept of distributed tracing like spans, a cause in your application rights to do that, we can use inside as auto tracer which will do it automatically for most cases. Also, also you can use some other SDKs like SDKs provided by Instana open telemetry. And then you need a collector to collect those trace data. It can be pool based or push based. And for that you have, you can use Instana agents or you can also use open telemetry collector. Yeah, by the way, Instana agent is also compatible with open telemetry collector so it can ingest open telemetry data. And then you need to back end right because open telemetry really focus on data collection part of observability to be able to process your data and analyze and maybe making some actions based on the data you need to have back ends. That's what Instana can also provide. Instana provide your whole ecosystem of your observability solution. Yeah, and I think this this highlights a really important portion of open telemetry in general, which we'll talk about in a little bit, which is the portability of the data so if your services are instrumented using the open telemetry SDKs or using open telemetry protocols, then you can just, you know, switch out the Instana agent for the open telemetry collector or vice versa or even run them both if you want to use the collector to kind of direct the data where you will. So that's that's really a huge benefit is, you know, you just you take care of instrumenting your services, and then you know that the rest of the process will be handled one way or another, whether you're choosing a vendor solution or an open source solution. Yeah. So speaking about service instrumentation there are a couple different ways that we can instrument our services with, I would say varying degrees of convenience for the developer. Yeah, so based on here with based on here we categorize them into three markets based on how automatic the instrumentation is. So first you have automatic instrumentation. It basically means you as like owner of the service you don't need to do anything basically like in some environments like Java, because it provides such a functionality of GVM to a dynamic attached to the GVM like from outside through agents. And we just discover it and attach to it and then change some bytecodes and yeah. Traces are generated. That's the first way. And the second way is what we call like semi automatic, like in some environments you still need to do some configuration, right, but not like heavy lifting kind of instrumentation. The rest is already covered by like in Stana. Some cases, maybe Python writes you need to basically specify as this environment variable auto wrap and it will do the rest. By the way, this approach, maybe not needed in Kubernetes environment. Because Kubernetes have this auto trace kind of webhook, right, you can have this mutation webhook already done those, those things need a great detail configuration thing for you. But in like normal host you still need to do some minimal work. And then, like, unluckily in some cases you still need to manual instruments, your applications or SDKs, typically cases would be like C++ which is a compiled kind of language. So you cannot really do that instrumentation in runtime.  Yeah, yeah, definitely. So, so I think for me the key differentiator with automatic instrumentation, and specifically with the Stana auto trace is that you don't, you don't even need to restart your running services. If you have a, you know, if you have a Kubernetes environment like you were mentioning in G and you install the Instana agent. It just, you know, as a sidecar container in the environment, it will detect all of your containers and will detect all of the run times such as JVM that that it's capable of attaching itself to, and you'll start seeing data. So one of our engineers did a test and installed Instana on a completely new host and started seeing the completely populated infrastructure map within about a minute and 20 seconds. So, so that's, that's very fast for Instana to kind of spread out throughout your environment and discover all of the things that they can instrument. With semi automatic instrumentation, it's still very easy. And it's usually just a question of changing, you know, a few lines of config, or adding a single library to your service, and that's, we'll give an example of that towards the end of this talk. Manual instrumentation open telemetry has come a long way and making this a lot easier. You're not worried about trying to emit data in, you know, OTP formats because for pretty much any language that I've had to work with. There's an SDK available from the open telemetry community.  You know, it can't find the code paths like it can with the semi automatic method, but really all you need to do usually is get in there and you know maybe add some direct excuse me decorators to your request handlers. You know, maybe some function calls to create new spans when you're starting an asynchronous request, but it's really a lot better than it used to be. So we're talking about open telemetry a lot. So let's talk about some more. What is open telemetry and and why do we care. Yeah, so a little bit about history. So in the telemetry is a merge of two opens a project one is open tracing and another one is open census. Open telemetry right now is a since they have incubating projects, and it aims to provide a vendor not your toolkit for harvesting your traces metrics and logs. Yeah, that's that's basically the hottest topic in open observability industry, I would say. Yeah, definitely. And so, so why would you want to use it. Yeah, so as we already talked before it's provide your like unified formats based on the open telemetry specifications. So you have like data probability among different vendors from and it can avoid vendor looking right if you you can just instrument your application use open telemetry and send it to whatever back ends, it would be right you can use open source base one or you can use commercial one like in style now. And it's, yeah, it's also like a common conventions across different technology and language, because right now people use like different languages mean a single system right by using open telemetry you will have like unified approach. So that's what open telemetry really shines to provide a standard way and to avoid vendor looking basically. Yeah, and I think I think it's really amazing, you know that the open telemetry project is able to achieve this. That there's such a unified vision throughout the entire community I think that's that's really kind of the promise of all open source right is that you could have this, this one way of doing things that is open and portable and then you have your choice of vendors to back that up. So it's really the best of all worlds. And I think another perspective probably my personal perspective, it's to have such standards is also great for like for the earth like different vendors already have like a similar approach but basically they are repetitively done similar things. But if you can have a standard ways and you can save some like energy even in, don't know, build your codes in different ways that's also quite eco friendly, I will say. Yeah, it's more sustainable right and it's, it's easier than trying to wrangle, you know, 15 different teams using 15 different exciting new technologies for their particular stack. It's just way better. Maybe you can save some energy effort to this so we can go to Mars. One day. Yeah. So the, the open telemetry is CNCF incubating, as you mentioned. It's fairly stable, you can see here, the only portion that isn't completely stable is the logs API and SDK. But, but we're using them, right. Yeah, yeah, right. So metrics are traces. We are instant agent can already ingest them and logs it will be supported. But since it's still in a unstable kind of phases right now, and the community is really awesome they really aim to deliver it this year or next year. But yeah, eventually, when it's stable, we will support it. Allow me to introduce my friend Stan. So Stan, Stan is our automation expert and intelligent assistant at at it's not not really you don't actually have to talk to a robot. I know that can be an annoying experience for some of us, especially, but but yeah, it's really just about it's about the automation and the intelligence that we can add to your data. So that you can get to the root cause of your issues quicker, and, and also improve the overall performance of your services and applications. Yeah. So auto trace is definitely like one of most important superpowers than half right in standard have. And what's great about so our goal for auto trace is really to minimize your efforts to let you gain the maximum observability in your services. So it can automatically discover your service right if if it's in Kubernetes if it's a normal host if it's in container and so which processes that it's that Java application or NodeJS Python, etc. And it will collect those informations and when we auto instruments your application, those information will be correlated as later in the demo you will show you will see that's like a full context we provide. And in Santa auto also provide you a automatically created dashboard right so you'll see okay how things goes, and you don't need to create your own dashboard but still you can customize it. And we also based on like I said since Dana is also backends for observability which open telemetry does not provide or not aim to provide. So we can utilize the data we get and do do data processing and analysis based on the data like trace data or metrics data. We can set some alerts for you automatically like okay this this traces it's it's gone for for some sometimes probably you have some host changes. And because in Santa also correlate is this information it can also also say okay there is a one host that's maybe full of storage or something like that. So you can get to your like root cause more quickly. Yeah, that's, that's what's in Santa auto trace aim to provide. Yeah, absolutely so kind of an example of the smart alerts and the anonymity detection that she's talking about in a previous example. We had an application with a messaging queue in between two services, one of them is processing user requests and the service on the other side of the messaging queue is handling rights to the database. So, you know, a little chaos engineering we take down the messaging queue, and instead is going to going to create several alerts for that it's going to notice that the requests on the front end service are failing or coming back with with the error codes, you know, however that front and service handles the message to being down, and it's going to notice that the back end service is no longer receiving requests it's going to notice that the database is no longer receiving the same volume of traffic that it was. And I kind of sort all of those issues together and and create an incident for me so that I can zero in on you know rather than having to deal with any one of those things separately. I can see the complete picture of all of these issues and kind of from those data points. That's enough for for me as a developer and also for for instance I kind of go, you know the problem is probably with this messaging queue that sits in the middle of all these things. And so I can get to that, you know, very very quickly and we'll show that in a little bit. So if auto tracing is so awesome, then why do we even need open telemetry, you know, well besides all of the reasons that we mentioned before, with with data portability and sustainability and and you know saving effort. There are a few reasons that you would want to use both of these things together. So the first one you mentioned open telemetry does not provide an observability back end. So you could self host something like Jaeger. You know, there are other tools out there, but none of them are really going to come with the intelligence and the expert knowledge that is built into Instana. And as far as I've seen none of them come close to the convenience of Instana as far as setup. Instana supports most technologies but as we mentioned at the beginning of the talk observability really requires that we have a complete picture of everything happening within our application. And so we want to make sure that no services are left uninstrumented and and open telemetry can be a huge help in that regard. We can use it to to instrument the things that that Instana hasn't gotten to yet that are maybe a little older or a little more esoteric. And then we can also use it as a migration path for legacy systems, as we're trying to bring them into our observability framework. And also like some companies they have self invent some framework right it's can we cannot know you have your sets so in that case you're probably also needs SDK to instrument your application. And so to kind of give you a picture of what that math looks like. On the left we have some of the technology supported by the Instana sensors. And on the right we have the open telemetry libraries. Yeah right so basically we for for those that could be technically there are no limitations will aim to provide your auto trace rights. Like I said we really want to minimize your efforts to get your observability rights in. In some cases like we talked about before like in C++ or us where you can have a kind of compiled language, you probably needs to do some manually instrumentation, and because you don't want to be in window locking, you can use open telemetry SDK. And also another example would be caucus right so caucus is really a hot topic in JVM areas, it provided it provides two ways to deploy application one ways, like normally a kind of bytecode and drawing JVM things like that. And another way is that it can use GraphVM to combine to binary. In the later case it will gain you some like super fast, super fast like loading time and warm up time will be low, but since it does not provide this attachment kind of mechanism normal JVM provides. We cannot auto trace that through our JVM auto tracing, then you'll also maybe you want to consider use open telemetry to provide the traces. Yeah, definitely. So, so right so using, you know, using the JVM you're firmly in, at least with Instana, you're in the fully automatic category with the JVM because we can attach to the bytecode and inject what we need to and follow those code paths to detect your endpoints. With the native binary, which in my experience is just so much easier to work with. You can build an open container image which is, you know, so easy to deploy just anywhere compared to, you know, Java jar. And it also like as you mentioned the runtime performance just in some quick examples that I ran, it was two orders of magnitude faster to process requests using the binary versus the JVM for the same code base. So that's great, but we're giving up that dynamic environment where we can just attach and discover what we need to. And so yeah, we would need to include some library but thanks to the open telemetry project we're still in that semi automatic category, we're not having to go in and you know decorate all of our request because we just installed the open telemetry library, the open telemetry library is, you know, specific extension for the corpus framework. And so it knows exactly what what methods need to be instrumented and what it needs to do. So setting this up as just an example. And, and one of the things that you can find on our website we should actually probably link to this I'll make sure that goes out. Our open telemetry robot shop so we have an example application called robot shop which is a simple, you know, make or services e commerce store using a variety of languages. And then we have a variant on robot shop robot shops little brother hotel shop. And so hotel shop is fully instrumented with open telemetry protocols. We're still using the Insta agent as the collector portion. So you can also run the open telemetry collector if you want to. But getting back to to corpus so so to instrument corpus, we install this extension. We install the Insta agent which I'll show how that process in a little bit but it's a one liner. And we modify one config key for our Insta agent, and it's not it does support updating config the get. So this is very easy to do. If you have a you know if you have a lot of hosts that you want to enable this on setup kit ops and take care of that. And then we just need to, you know, unfortunately we are going to have to add some configuration to our corpus application and in this case we will have to rebuild it and redeploy it. We can't just, we can't just do this in place on production. But this is, this is a very minimal change to have to make to an application to get full full tracing of all of your endpoints. It's that easy. Okay, so let's let's show it time for a live demo. Yay. Okay. Um, so I was still looking at the correct screen everyone can see hotel shop. Yeah, I can see it. Okay, excellent just making sure because. So, here is hotel shop running in one of our QA environments, you can kind of already tell just from looking at the golden signals here that, and this is actually a good time to point out. So it's Donna, you know, we, we really like to highlight these Google S3 golden signals and you're going to see these and a lot of use these three, these three signals, right, which is throughput error rate and average latency. So, this is a demo environment, it's probably under provisioned. And you can kind of see that just, just right from this dashboard. One thing I do want to mention about this dashboard is, I didn't build this, no one built this, we installed the install agent on our hosts, and based on the data that was coming in, we get this dashboard. We build custom dashboards if we want. But for the most part we don't need to, and it's not just about this one dashboard that we're looking at here which is in an application perspective, which we'll talk about. It's all of the dashboards throughout and starting you'll see me clicking around from, from, you know, services and entities. They're all automatically generated, and they're, they're designed to give whatever your team is whatever your particular slice of the service is that you're interested in. Whether it's, you know, SLIs and SLOs for a specific service, whether it's infrastructure and overall health of the hosts.  I promised that I would show the installation so let's get into here. And, oh no I'm in a demo environment so I can't show that, but it's a one liner. It's, it, if you go here in an environment where adding new agents is allowed, you'll see the list of supported technologies and types of hosts that we can install on so you can see these Docker right your containerized environments open shift VM where Tanzu, and we'll have specific instructions for each one of those but it's, it's just one command that you're going to copy in all of these cases. And then we can also support, you know, installing the agent directly on your hosts, whether it's Mac or Linux, or Windows hosts. In the case of Mac hosts, like maybe you want to run the install agent and your local development environment, and that's something that we'll be talking about in the future as part of shift left, but really there's there's no limit to where you can install it. Installing it in a containerized environment is incredibly easy. We have Helm chart or operator or whatever your chosen, you know tool is, we can provide that. And, and if you do it through the dashboard that one liner is going to be pre populated with your, your keys that are needed to connect to your tenant. So getting back to the actual data. So this right now what we're looking at we call this an application perspective. And what that is is so go to the list of all of our applications. And it's really just a collection of filters on the services right so if we look at this tab this is these are all the services reporting to this environment. And so, I'm obviously not interested in all of these there might be, you know, services here that are completely unrelated to my application, or that just aren't the responsibility of my team and so I need a view that excludes those and includes the ones that I care about. The application perspective comes in, and we can define this with just a couple of filters. So in this case, all we're doing is filtering on the Kubernetes cluster and anything running in that cluster is going to come into this application perspective. So, so getting back to the application perspective. You can see we have our golden signals we have our top services. We also have our time perspectives over here. So this is a really important part of your debugging and, and troubleshooting journey in it's Donna. So, you know, from experience that a lot of the times when you're trying to debug something, you might be correlating, you know, logs from one service metrics from another platform, like from atheists, and, and maybe you have traces somewhere else. And so you're kind of trying to zero in on okay well this is the time window, when this problem occurred. You know, it's just that we're having the problem.  You know, trying to trying to keep all of this data in sync across these different services and zero in on. Well, what is the issue in this in this giant haystack with inside application perspectives. You can choose any timeframe. You can also use releases if, if your CI tool is reporting releases. And this is going to be sticky as you navigate throughout the Insta dashboard. So you know if I choose last 10 minutes, that's going to stay as I navigate to other pages through to other applications, which is fine for just this, but where it really comes in handy is say I want to zoom in on. Well, there's an error spike right there. Let's zoom in on that and see why that happened. Then I can do that. This is going to bring us to our unbound analytics feature. So this is sort of your place to, to filter through and, and you know you can see we have all of these manual filters on the side that I can use to find the specific calls or traces that I'm interested in. And you can use this manually, but you can also get to it the way that I just did by by being on a screen choosing some data, zooming in on it and getting the filters pre populated for you so you can see exactly what you care about. Now this environment is not that interesting because we actually I think our low gen is broken so I'm going to switch over to our regular robot shop, which has a little bit more, more stuff going on. We'll go to the last hour, the time deal. So you can see there are a lot of JS errors happening here. But nothing that's really causing oh well that's interesting there's a there's a huge spike in the load time right there. So let's zoom in on that and see if we can figure out what was going on there. Looks like the issue got resolved by now but we'll pretend that it hasn't yet. What's happening. Oh yeah. Okay, so let's let's specifically look at traces during this time frame. And let's see the error. Okay. Erroneous traces 100% that's smelly. So let's see what's going on here. So we can see all of these requests are timing out after about two seconds it looks like. And I'm going to zoom into one of them. So, so here's a view of a particular trace. This is a problematic trace in this case. We can see the logs associated with this trace. We can see the calls we can see the end user information from, you know, the end user monitoring which is a JavaScript tool that you can stall on your front ends. And there's also a tool for mobile applications so you can get this this information from native apps. And, and this is going to be correlated with any of the back end traces that can be associated with this end users requests. So this is really a huge help in in figuring out exactly what's going on and who's affected. And then scrolling down we can see this Gantt chart, kind of similar to the one that we were looking at earlier. So this is is our complete trace and we can see that it's terminating in this connection failure. Let's open that up and see what's been on here. Oh, okay. So it's failing to connect to the database. And yeah, that's, that's probably at this point we kind of know what we what we need to know. The database has a 100% error rate.  But either way we know what we need to do next which is get this database service back online. So the traffic can continue to flow. Now that was a troubleshooting journey where we kind of saw something, you know just through through one of our workflows we saw something anomalous on a graph and we zoomed in on it to try and find the issue. But you'll notice Instana actually already knew about this issue before we saw it, and was ready to alert us if we had any kind of alert and channel setup. So, like I said earlier, you know you kind of got Instana it's noticing all of the changes that happening in your environment. So this could be things like a configuration change, or it none happens during this time window but a configuration change a service coming online or going offline. Anything that's going to affect the Instana agent, maybe a new container gets deployed. Anything like that. Then, you know, as those as things go outside of the normal band of healthy, it's not going to raise issues. Now these aren't necessarily actionable. But we want to collect all of them and make sure that we have all of them, because there might be a bigger problem that these are going to be part of the picture and figuring out what that bigger problem is. So we want to make sure that we have all of the abnormalities logged and tracked for you. And then we can kind of sort those and see okay actually we do have a big problem. We have an incident occurring a sudden increase in the number of erroneous calls. Okay, if we scroll down to the related events we can see, Oh, well the root cause of this was a signal on the my SQL service. So again, you know, this the second path getting through to to this point took me two clicks. I could do that in 30 seconds, I can see okay. My SQL services the problem signal that that's, that's bad that's probably malicious actor so we need to do something about that. And that is sort of the power of the both the navigation and the intelligence built into Instana and what we can do with your traces. Another important thing to mention is that Instana does not sample traces. So if you're using an open telemetry collector, you can, a lot of the open telemetry libraries will have a configuration variable for your sampling coefficient. It's going to be up to you if you're using open telemetry, but I would leave it set to one. And that's how the Instana sensors operate is just no sampling whatsoever everything gets reported, which means any communication between any service internal or external is going to be detected and and will become part of the map. What those zero, what that zero sampling enables us to do is create the real time dynamic dependency graph. So I'm going to go back to back to regular timeframe that incident that we were looking at has been resolved. And this environment is set up to sort of deploy that and then, you know, roll back the deployment because of the incident being automatically And that's another thing that you can do with Instana is you can combine our intelligence with automated tools so that some of these issues can get resolved with minimal or no human interaction or intervention. But getting back to our application perspective. So here we have the application dashboard that we started at. And if I click here to dependencies, we're going to see something generated by that dynamic graph that I was just talking about. So this is all of the communication happening inside the robot shop application within the last five minutes, we can see all of the calls we can see all of the services we can see all of the databases. None of this was configured, nowhere did I have to go in and edit some YAML file and say oh this service talks to the service and the service is called this. This is all just automatically detected and and built for us and it's updated in real time. So as services come offline or online. This is going to get updated. And this always up to date graph is what enables us to do things like if you if you zoom in on a specific service, like say the cart. We can see the complete stack of for this service so we can see the application, the endpoints that it provide the application that is a part of those are the filters that we talked about at the beginning. We can see the four endpoints that it provides. We can see that it's running in a Kubernetes cluster we can see all of our Kubernetes metadata that we could ever want here. We can zoom into any of these entities and see the specific configurations for them. And then we can get down to the infrastructure level and see the specific hosts that these pods are running on. So that's, that's the power of the dynamic graph is that we can sort of correlate all of the activity within your application with the related services and infrastructure from the front end user all the way down to bear metal. And speaking of bear metal, the last thing I want to show you running at a time there's there's a lot to show. So this is our infrastructure view. So kind of coming zooming out from the perspective of an application developer to, you know, ops or an SRE. So this is kind of an overall view of all of the infrastructure reporting into this host. And right now it's sort of it's separated by zone. There's custom defined zones, you can see we have our, our hotel demo, we have our robot shop demo. But I can also change this and I can, you know, change the perspective to be by container instead of by host so you're all of our containers running in those zones. And then I could, for example, say, Oh, well what Kubernetes namespace is, is the container running. And so I can just kind of sort and filter this view. Going back to the host of you. I can zoom in. And you can see that each one of these towers is is a specific host. So these are three Linux hosts running this Kubernetes cluster. And I can kind of mouse over them and see all of the services is as pancakes they're kind of difficult to see but you can see all of the processes and all of the containers that those processes are running in. And I can open up the dashboard for any of these. I don't want to make sure that we have time for questions. Oh, I do see that there are questions. Okay. So switching gears, and I'll leave the demo open as we answer some questions in case there's anything else we want to show. I guess that enabling open telemetry for son agent will consume more memory and CPU at the agent. How much impacts will we have at the agent enabling this option in she can you answer that. So we definitely aim to minimize the impacts when we design the agent so for open telemetry to enable this it's just expose a endpoint right so it should it would be minimal. So still have concern you can like you like, I think you mentioned it's in Kubernetes right you can limit the resource for agents like home, many units of CPU it should limit and how many unit of memory. You can limit sets in Kubernetes. Yeah, so should not be a problem. Our agent is very lightweight and you only need one instance of the agent per node. So depending on the size of your nodes it's it's it can become an almost unresolvable impact on. Yeah, I think that also answers him a new air question right it's installed as a demon sucks. Right. Yes. Okay. So Zia asks, does open telemetry or install cover overall asynchronous workflows, e.g. an end to end order fulfillment. How an order performed in various stages. Yeah, so I think it's really depends on which framework it is right so it's it's really case by case because there are tons of frameworks out there. And if we say okay we support this frameworks and if you have asynchronous handling there we will still support the correlations there. But yeah, it's really depends which framework you are using. Yeah, and I would say, you know, for for some of those asynchronous tools that you might be using in there like Kafka or MQ we handle that I think out of the box correct engine. Yeah, and open telemetry is just going to require some some minor instrumentation. Yeah, you define the beginning and ends of your spans in your asynchronous processors, and you may need to put some trace context messages in order to get that to your downstream services. And since there is another one, Raina, Kamala, Instana, trace contains Instana and open telemetry spans. Yeah, that's a good question. We support it. You can limit and mix it and it will get correlated but there are some limitations because open telemetry internally it use W3C trace context and it's only defined for for HTTP calls, right. And if that's message queue there are no defined thing, but since then we support correlations through some message queues. For more detail just check out documentation. But we definitely support the mix of Instana and open telemetry spans. So Zia also asked does open telemetry and Instana handle any time synchronization or clock queue issues in low latency. I'm not sure that I understand that question. Yeah, I guess that's like some low level thing. I think it really depends on which runtime it is. And I mean if you have further questions like how specific, if you can specific question later or get in touch with us. We can get our engineers for SME to answer those questions. Yeah, definitely definitely reach out to either one of us and we can put you in touch with people who can answer that question. That does remind me for anyone who thought that my demo was too short. We do a live demo every Tuesday and I believe that the link will be in the chat so I definitely encourage all of you to sign up for that if you if you're hungry. Okay, so the next question is, which SDK we need to use for NodeJS REST API to have open telemetry traces and metrics deployment. So if you want to use the open telemetry SDK just go to the open telemetry project. They have a list of supported languages so you just click on NodeJS and they would show you the preferred packages to use. But Instana Auto Trace also works great with NodeJS so you could skip that and just use Instana. Yeah, and another one is Instana Auto Trace for open telemetry. I mean if that's, I guess that's similar to the previous run right so you can mix Instana Auto Trace and open telemetry. If both Instana and OTEL is enabled on a service, will Instana agent avoid instrumenting something that's instrumented by OTEL and just use the OTEL data. You know the answer to that. I believe the answer is yes that Instana will leave it alone because we do detect agents from some other observability tools and and halts our operations if those agents are protected. Now that's a that's a configurable thing though so if you're trying to do something really specific, you can probably override whatever the default is. Yeah so agent provides configuration like in a YAML file or you can use it's GitOps so just disable some Instana sensors. Okay, how is open telemetry different than Grafana? So Grafana would be one of the tools and organizations contributing to open telemetry and that you would use open telemetry with. I know Grafana provides a dashboard tool that I've used quite a lot. I think Instana dashboards are a little bit more convenient than you know editing YAML files to create a dashboard, but maybe that's a matter of preference. But yeah you would use Grafana sort of as the back end similarly to how you would use Instana and you would be still using open telemetry if you wanted to. Yeah so open telemetry is really scoped to data collection. So it's just let you create those data but how to illustrate it and how to analyze it. You need to another tool. Okay and finally we have a question about Instana self-hosted in a cloud platform. So I assume this means the Instana back end is being self-hosted which is something that we do support, we do support on-premise installations in the cloud or even in air-gapped environments. We also are very excited to have open shift support for Kubernetes for on-premise coming up in the next quarter so. Yeah. Do you know specifically where the logs end up? It starts internally, you don't need to manage separate things to do logs. Yes. It is, I believe it would be elastic search correct but it would be, you wouldn't have to manage it, it would just come with the Helm install for the back end. But you don't need to manage any databases or data storage. It all comes with the back end installation. Yeah so those three signals are native supported by Instana, metrics, traces and logs. Do the SDKs have an impact on our application forms or service latency?  No. We're talking about if there's any difference, it's immeasurable in the end of seconds. By the way, your English is not that great. Yeah, agreed. Okay, so when registering an agent, the console finds out or do I need to register on Instana too? No, so the one liner that I couldn't show you, it will include your agent key and then Instana back end will use that key to associate the agent installation that you've just done with your back end. So you don't need to do anything to tell it about new hosts other than install the agent on the host. Okay, we have about five minutes left. Are there any more questions? Okay, well thank you so much for coming everyone. I hope that, oh here we have one more question. Okay, nope, never mind. Yeah, I hope that you'll check out Instana. You can take it for a spin. We have a 14 day free trial or you can just click on the play with button on our website and get into an environment very similar to the demo environment that I showed here. We also have our live demos on Tuesday. And if you're going to any conferences this fall, we wait see you there. So thank you so much. Thank you. Thank you so much and she and Josh for your time today and thank you everyone for joining us. As a reminder this recording will be on the Linux foundations YouTube page later today. We hope you join us for future webinars. Have a wonderful day.


The dramatic monologue is a kind of lyric poem, the second oldest form of poetry in the western world after the epic. But unlike long narrative epics with their heroes and gods, lyric poetry developed as a short meditative poem in Greek culture spoken over chords struck on a harp-like instrument called a lyre to mostly aristocratic audiences. The instrument gave the poetic form its name and in turn is where we derive the term lyrex to refer to the words of a song. From its origins in Hellenic culture all the way through the end of the 18th century however, the voice of lyric poetry was always assumed to be that of the poet, him or herself, offering an elaborate musical rhythms and provocative metaphors, his or her own experiences or thoughts directly to an audience of readers or listeners. Words of the romantic movement in Europe of the 1780s and beyond began to write a different kind of lyric poem called the dramatic monologue. In this type of poem, the poet adopts a persona, a voice or character other than his or her own. Very much like a playwright puts his or her own thoughts into the mouth of characters in a drama. But in the dramatic monologue poem, the voice persona reveals through observations that he, she is most often speaking to an audience other than the reader, addressing another figure in the poem where even one the speaker imagines needs to hear some pressing matter while not actually present at the moment. In the romantic dramatic monologue, the persona usually tells a tale that suggests the struggles and victories of everyday people, often in rural settings and how they might find solace in human ideals like the piece of nature, spiritual fulfillment or loving relations between family, friends or lovers. In Samuel Taylor Coleridge's 1798 poem, The Rime of the Ancient Mariner, for example, an old sailor stops a wedding guest on his way to the ceremony and explains to him what he has learned about devotion, love and respect for all living things, concluding his monologue with the romantic sentiment that, quote, he prayeth best who loves best all things great and small, for the dear God who loveth us, he made and loveth all. In 19th century England, the dramatic monologue form became a staple kind of poem for the generation of English people referred to as Victorians after their queen, who ruled for 70 years. Since the novel was the most popular form of literature during that era, the dramatic monologue appears to have appealed to Victorian audiences' fascination with fictional characters. During this period as well, one poet in particular, Robert Browning, singlehandedly changed the dramatic monologue by introducing personae who were so troubled, delusional or egotistical that as they explained themselves to their audience, they indirectly revealed their misperceptions and failings, which they themselves never appear to grasp. Thus even before the advent of the unreliable narrator in modern fiction, these dramatic monologue personae function in poems in the same manner I explained in a previous video in this series about that other narrational mode. In one of Browning's most famous dramatic monologues, entitled My Last Duchess, a Renaissance Duke is conducting a tour of his magnificent home with a Count's agent who has come to discuss the terms of the Duke's next marriage. The Duke feels compelled to explain to him how he came to lose his first wife, the Duchess of the Poems title. When the pair encounter a painting with a curtain drawn over it, the Duke draws the drapes to reveal a portrait of his former wife. He explains to the agent that his last Duchess never learned that she was to have showed him respect and adoration above all things in her world, as the aristocratic culture of his era dictated. But the Duke explains further that the Duchess had, quote, A heart, how shall I say, too soon made glad, too easily impressed. She liked whatever she looked on, and her looks went everywhere. Sir, twas all one, my favor at her breast, the dropping of the daylight in the west, the bow of cherry, some officious fool broke in the orchard for her, the white mule she rode with round the terrace, all in each would draw from her alike the approving speech, or blush at least. She thanked men, good, but thanked somehow, I know not how, as if she ranked my gift of a 900-year-old name with anybody's gift. In this passage, the Duke indeed reveals himself to be a total control freak. In the next breath, he implies he had the Duchess killed for what he perceived was her insolence. Although the agent never speaks nor judges the Duke, we as readers eavesdrop on their conversation and are allowed to see in the Duke's control of his wife and even over who he allows to view her portrait, that his obsession with being worship goes well beyond the matrimonial assumptions of his era. In this way, readers of the poem are being encouraged to understand the Duke's explanations ironically and through this to grasp Browning's feminist announcement of the Duke's control and abuse of his wife. Browning's update on the dramatic monologue went on to influence how the form was used by most 20th century poets. From T.S. Eliot's influential 1917 poem, The Love Song of J.L. for Prufrock, to Sylvia Plas' 1965 Lady Lazarus, to A.I.'s 1979 Killing Floor, to Rita Dove's 1980 The House Slave. Each of these very different poets recognize that the dramatic monologue allows the writer to imply ironic distance from a persona's observations in the poem. As careful readers, we too recognize that we are being pushed to listen to the persona ironically. And just as with the unreliable narrator, share an understanding of the persona's psychology along with the author, to which the persona remains blind, wrapped as he or she is in misperceptions and delusions about him or herself, other people, and the world.


Welcome to Toffee TV. It is the Everton News Daily. Obviously yesterday evening we got the sad news that Jean-Philippe Gabamann has got a serious Achilles injury. One of the, probably one of the worst injuries you can pick up as a footballer. He's going to be out between six and nine months. He did the injury playing a game of basically full tennis with Andre Gomez apparently, the irony in that. Apparently he'd been looking very strong in the small training sessions and it was completely a completely free injury. And for the third time in his very short Everton career, Tuesday he will undergo surgery on it in London and it's just a massive blow for a player that we'd only just heard this week that. Obviously he was backing some part of training and he was looking forward to being involved in the end of the season and now it looks like he's not going to be obviously back till the latter part of next season now which is, I mean for the player it's an absolute disaster and you know for a player who had such a good injury record before he signed for Everton he's been absolutely cursed by these two injuries and it just seems that both of them have been complete free injuries as well. That's the thing, you look at someone like Andre Gomez and you fully understand how he got his injury and you can see and it's almost like there's a point of blame there but for Jean-Philippe Gabamann to pick up two injuries in training in just two complete strange incidents it is very very sad so he will have his surgery on on Tuesday and for I mean for us I suppose it is it is now about going out and finding a player who can not you know it's not even a case of a place and I mean beforehand it was probably not shorting but you had to him and you had him and another to come in now it you know he he has to just be put to the back of everyone's mind and even I've got to go out and buy a player who can play in that position that we've been obviously missing massively obviously Alan's been in and mentioned a lot of times from Napoli someone like Garnett has been mentioned this week you know there's been rumors of him being saved plus two we're climbing to Paris Saint-Germain but that's a position that Evan are going to have to go and film now desperately and that's going to be first choice and I imagine we'll supersede any other position and unfortunately it's the worst time as well with the economics of the situation we're in now there's not a lot of money floating around and it just sort of if the where of the players obviously we've been the whole Gabriel situation but you can't I can't even think of it and I'm going to spend any money on anybody that is not a sense of a feel to now I really I really just don't see it and we've been really unlucky with injuries you know on to go on to go on to go on to his injury go back once I had two injuries shint hoson um it was a play that we would we were trying to get rid of as well it's just been an absolute disaster um the last few the last few months in terms of injuries and trying to get players out of the club and bring players in so we wish him a speedy recovery and hopefully comes back stronger whenever that is um obviously it was announced yesterday that the Premier League is coming back Evan's first game looks like it's going to be the Mayside Derby on the 20th of June a lot of talk about a neutral venue Evan versus Liverpool is one of the games apparently on the list there's only about six or seven of them and it's the only one Evan who are involved in with the police out or the body who have been looking at getting the games back on have recommended a certain amount of games should happen in neutral venues neutral venues apart from this are off the table Evan will be playing the games at Godderson Park but for the Mayside Derby they are looking at it and saying that it is one that's been um needs to be played on a neutral venue funny funny enough mayside police have come out and said they will provide any police and that is required for any of Everton and Liverpool's home games um so who in fact is providing this information whether it's at a national level whether it's at a government level just to make sure that there aren't any problems um a lot of the games do to actually concern Liverpool um and I don't know whether it's just due to the fact of the games that when they could when they possibly could win the win the title you know whether Evan or Liverpool will be played at a neutral venue if Liverpool can't win the title at that game will have to be decided but at the moment we'll have to wait and see but um it's you know it adds to for me just that nonsense of listen I understand football has to come back but you know for it for for Evan to lose that home advantage even though there's no fans there against Liverpool for a Mayside Derby just shows to me that you know that big fat asterisk put it up there put it up there because it needs to be seen because at the end of the day it's not the competition we signed up for um so yeah Mayside Derby is going to be free to wear as well on tv uh I think it's going to be free to wear on sky so everyone will get to see it which is great for our first game back but the plan is I think the plan is to have games on a saturday then games midweek for you know five to six weeks depending on what else is going on the epic cup is coming back as well and obviously the europeans coming back as well so it'll all be dependent on who you're playing and where you need to fit those games in to get it back but it's no more than hopefully six weeks because apparently after the end of july there are penalties that the teams would have to have to pay back certain amounts of money to the tv stations and they're trying to keep that down as much as possible so there you go um in nonsent transfer news we've been linked with Diego Godin today this this 34 year old centre back from uh into my land use I think you already said on there last summer from let's let's go Madrid we've been linked with Diego, Diego Mottorwell and another experienced centre back it's straight it it's quite funny that we've been linked with two experienced centre backs that we could get on free contacts and now a lot of people out there be gone this is absolutely nonsense but we've only got three senior centre backs at the moment um and none of the three are really experienced and it's just a just an interesting one to wonder if if that has been fearless put out there just to have some experience have a leader at the back that could come in not play every game but could play certain amounts of games just to be that fourth 20 centre back no the fourth 20 centre back but be that fourth centre back that could come in and add some experience and be someone in my stay for a year or two years at the club I'm not saying that's what's actually going on but it just it's it's quite interesting that narrative um and you wonder whether that's something that Carlo Ancelotti's identified at the club that there aren't enough leaders there aren't enough people in the club who have won things who understand what it takes to be to be a winner so I'm not saying those things are true I just find that an interesting narrative that's we've been linked with two players but um we'll have to wait and see we're going to have to be very creative if we're going to try and bring players in this um this this window whenever that window starts and as I said the good Batman thing might have thrown all of those plans up in the air depending on who we were looking at and who we want to bring in so there you go um let me know your thoughts in the comments don't forget to give this video a like join us on page and if you haven't already the link is in the description um the Don Hutchinson video is now on youtube exclusive interview with Don Hutchinson it's an hour on youtube the page inversion is an hour and 35 minutes absolute magnificent interview give us all the details on his time at the club why he loves it so much and why he left the club which just seems to be an absolute terrible decision then yeah if you want to find out more about that watch the interview it's available now thanks for watching toffee tv see you later