Career

Gartner nous dit que 20 % des organisations vont utiliser l’IA pour virer plus de la moitié de leur management intermédiaire d’ici fin 2026. En face, Sam Altman déclarait à Sydney le 26 mai qu’il était “content de s’être trompé” — l’apocalypse emploi qu’il annonçait, ben finalement, elle n’a pas eu lieu. Les deux ont raison. Et les deux passent à côté du sujet. L’IA ne supprime pas massivement les postes. Elle supprime les étages. Elle redessine l’organigramme sans que personne ait validé le plan. Et ça, on ne le verra pas dans les résultats trimestriels de 2026 — on le verra quand les organisations ne tourneront plus en 2032. ...

Oui, c’est un peu provocateur, vu le nombre de recruteurs qui se trouvent sur Linkedin. Cependant, la question m’a été posée plusieurs fois ces derniers temps, et je me suis dit que mes réflexions pourraient servir, et surtout que je suis intéressé par les avis de la communauté, y compris les fameux recruteurs :-) Précisons bien, je parle d’une situation où je suis en poste, sans avoir annoncé la moindre volonté de changement de job, et je suis contacté par un recruteur pour une opportunité qui pourrait m’intéresser. Prenons l’hypothèse que la proposition est bien ciblée, et que donc, je sois potentiellement intéressé en réalité. Si c’est une offre mal ciblée, passons :) ...

Lorsque l’on évoque le sujet des “IA” de manière générale, on entend beaucoup de banalités, pas mal d’inquiétudes. Et en fait, beaucoup de méprises et d’incompréhensions. Les cas les plus visibles sont les voitures autonomes par exemple, ou bien les tentatives de systèmes semi-autonomes dont le comportement dérive très vite. Je voudrais essayer de rendre ces problématiques un peu plus claires, en synthétisant mes lectures et recherches diverses. Tout d’abord, posons les bases. Je n’apprécie pas beaucoup le terme IA, car il est très vague. Dans l’esprit de certains, une IA est un système doué de conscience, avec des niveaux de compréhension et de raisonnement au moins similaires à un humain. Dans la réalité du quotidien, ce que l’on entend par IA s’étend depuis un système de décision automatique mais figé (comme une brosse à dents qui détecte si les dents sont assez propres) à des systèmes relativement autonomes, dans un domaine limité (comme des voitures). Mettons que l’on s’occupe de tout ce scope-ci, les systèmes autonomes, en incluant tout ce qui permet d’automatiser tout ou partie d’un processus. Ces systèmes sont la plupart du temps très loin de l’IA et ne sont souvent que des robots capables de suivre des arbres de décision pré-établis. Mais certains sont plus complets ou autonomes. Une fois l’incompréhension sur la terminologie posée, j’aime bien définir les différents cas d’utilisation de ces systèmes, dans le monde professionnel principalement. En premier on retrouve les systèmes d’assistance, déjà très répandus. Ce sont les “robots” que l’on active à notre initiative, pour effectuer une opération complexe à notre place. Par exemple nous avons les systèmes de traduction automatique de génération précédente. Ils nous permettent de vérifier une traduction ou une compréhension de manière générale, en allant bien plus vite qu’avec un dictionnaire. Le contexte n’est pas forcément pris en compte, pas plus que les double-sens et les expressions locales (géographiquement ou liées à un jargon métier). Ensuite nous avons les systèmes complémentaires. Ce sont des systèmes qui travaillent avec nous, en parallèle, et qui viennent nous proposer des suggestions pour nous aider dans notre travail. Leur capacité d’analyse est souvent assez large et profonde. Cela leur permet de suivre des opérations sur un spectre et une profondeur que nous ne pouvons souvent pas atteindre sans de très longs et couteux calculs. Dans le domaine de la surveillance vidéo, la reconnaissance faciale pour des systèmes de type CCTV permet de retrouver un individu dans des flux multiples, puis de reconstituer son parcours dans le temps et l’espace. Enfin, arrivent les systèmes que je qualifie de remplacement. Dans les plus simples on retrouve les chatbots ou callbots qui permettent de traiter de nombreuses demandes de manière automatisée, sans intervention humaine. Pour les plus complexes, nos fameuses voitures autonomes sont de bons exemples. Ce sont ces dernières qui inquiètent, pour plusieurs raisons: • La sécurité des personnes et des données, ett donc la fiabilité des systèmes. Cf les accidents de voitures autonomes, • L’emploi, si ces systèmes étaient à même de remplacer des emplois, • L’explicabilité, pour pouvoir décortiquer la chaine de décision lorsqu’une anomalie est signalée et pour détecter les biais. Je ne vais pas pouvoir entrer dans des détails avancés pour répondre à chacune de ces inquiétudes, un livre n’y suffirait pas. Je peux néanmoins donner quelques pistes de réflexion. En ce qui concerne la fiabilité des systèmes, il y a une chose qui me frappe dans toutes mes discussions au sujet des “IA” : tout le monde s’attend à ce que ces systèmes soient parfaits. Une voiture autonome ne devrait jamais avoir d’accident. Un système de prédiction ne devrait jamais se tromper. Un automate devrait toujours effectuer la bonne action. Question naïve : à quoi compare-t-on ces systèmes? Formulé autrement : • Est-ce qu’un conducteur humain est infaillible? Quelles sont les statistiques d’accidentologie des humains? Des “IA”? • Lorsque l’on demande à un système de traiter des formulaires de manière automatique, quelle est l’alternative? Si je demande à un modèle de reconnaître des écritures manuscrites pour faciliter mon travail, est-ce que je suis fiable à 100%? • Si je mets en place un système de caisses intelligentes qui reconnaissent le contenu d’un plateau repas, le système pourrait être fiable à 99% (par exemple). Connaissez-vous le taux d’erreur d’un opérateur humain? Indice : il est plus élevé que 1% :-) Petite note au sujet de la gestion des erreurs, l’idéal lors de manipulation de modèles est de bien gérer les seuils d’acceptabilité. En d’autres termes, un modèle d’IA vous indiquera toujours ce qu’il pense être la bonne information ...

Wow, it has already been almost a month since I started! My new playground covers IoT and AI, and I am supposed to have a broad understanding of both. Regarding IoT, my recent background helped me grow a solid groundwork for that. I am fairly comfortable with the concepts, and with the involved technologies. Moreover, I have a colleague whose sole purpose is to understand and build IoT solutions, so my bases are well covered. When it comes to Artificial Intelligence, the coast is less clear. First, it is not a domain where I have any background, neither in the theory (math, bio science…) nor practical (any implementation of AI). Second, AI is the 2018 version of the Cloud in 2014 : everyone wants to do it, but not one has a clear definition of what we are talking about. Last but not least, the very term AI covers almost anything, from a chatbot to augmented reality to self-driving cars. My process has been a bit convoluted so far. First thing I have tried was to register for e-learning (MOOC or otherwise) sessions on the topic. I have tried several, from OpenEDX to Microsoft AI school, to Google and Tensorflow. The content ranged from very high level, which was mostly too high for me, to algebra (which was a bit too deep for me). Then I tried to read about the market. So I read a lot of whitepapers, from Microsoft, from DataIKU, from Forrester etc. This was rather useful, as it gave me basic understanding of where the situation was. I recommend Dataiku Machine Learning Demystified : https://pages.dataiku.com/machine-learning-basics-illustrated-guidebook But still, I felt I was stuck in the theory and could not find the practical applications. After some discussions with my usual suspect, Microsoft, I did have a look at their business uses cases and testimonies. I have to admit, some of them were pretty interesting… however there is absolutely no information about the architecture or implementation of the solution, which left me wanting. I finally found two Microsoft websites who did a good job of describing architectural templates, along with potential uses cases. https://azure.microsoft.com/en-us/solutions/architecture/?solution=big-data https://docs.microsoft.com/en-us/azure/architecture This is where I started digging, and it made my mind spin with all the possibilities. You will have to wait a bit for the outcomes, and follow what SCC will be doing on this market in the coming weeks ;) Last note, one of the smartest guy I have met at Microsoft, Frederic Wickert has started an AI business, and is writing, in French, to help debunk AI for us. I definitely recommend reading his posts!

Depending on how you consider things, it is the third time that it happens to me. Being able to design, under certain limits, your own job, is an amazing opportunity. I will not go into too many details as some of it is work in progress, but the process was amazingly energizing and I wanted to share a bit of that energy. For my current job, I met my future boss on the recommendation of a former colleague. We discussed many things, from ITIL to Managed Services, and also public cloud and the need to get dev and ops team closer. We went through those kind of talks several times, at least four if memory serves. We went from a job which look like an Ops engineer/ITIL practitioner, to something closer to an Azure tech lead. In my previous position I also had the opportunity to be offered a promotion, and been able to discuss some of the content and responsibilities of the future role. I was also able to step down when time came for me to admit that it was not an ideal position, for me or for the company. Which was really appreciated, at least on my part. And once again a few weeks ago, I was called out of the blue by a colleague’s boss. He started to discuss his own future and what he was trying to design. He wanted to build something new, and was searching for a partner to build that together. And in that scheme, he discussed a position very similar to my dream job, and offered it to me. I almost fell off my chair. At that point I was ready to accept, without having any more details about the exact role and responsibilities, or even the salary. That’s where my future boss started to ask me what I would include or exclude from that job description, and how I could make it my own. My mind just froze. It took some time for me to recover and start thinking again. After some lame jokes, we discussed the position, and what we would like to build together. It took us several meetings and calls to see through the fog, as we are really going to build something new together, and we cannot rely much on what exists around us. The last funny thing to happen was that my next interview was with the CEO of the company, who was convinced by the both of us in less than 35 minutes. I could not believe my luck in getting there. Anyway, that’s it for the bragging post. I really needed to write that down to make it real (even if I signed and will start by the end of the summer :) )

Yes, another post with an obscure reference for a title. After some time discussing tech subjects, I was of a mind of going back to something that has often been misread in the past by IT teams and IT management. And by that I mean : business. Yes, again. Do not misunderstand me, I am still a technologist, and I love learning about technology, finding out the limits and possibilities of any enw tech that is coming out. I am not a sales person, nor a marketing person. However I have been exposed to many well crafted presentations and talks over the years, and what often came out of even the most interesting ones was that : “our tech is fantastic, buy it!” All right, I love that tech. Be it virtualisation, SAN, VSAN, public cloud, containers, CI/CD, DevOps… choose whatever you like. But technology is not an end to itself in our day to day world. Whatever matters is what you will do with it for your company or customers. I will take an example. An easy shot at someone I admire. Mark Russinovich, CTO of Azure, and longtime Windows expert (I would use a stronger term if I knew one :) ). A few months ago, during a conference, he had a demo running where he could spin up thousands of container instances in a few seconds, with a simple command. First reaction : “Wow!” Second reaction : “Wooooooowwww!” Third reaction : “How can we do the same?” Fourth reaction (probably the sanest one) : “Wait, what’s the point?” And there we go. What was the point. For me, Mark’s point was to show how good Azure tech is. Which is his job, and this demo made that very clear. But Mark did go further, as he usually does, during his speech and encouraged everyone to think about the usages. Unfortunately, most of the people I have discussed with seem to miss the point. They see the Wow effect, and want to share it. But few of us decide to sit down and think about what the use case could be. And that is the difficult, and probably multi-million dollar question : how to turn amazing technology into a business benefit. Never forget that, apart from some very lucky people, we are part of a company that is trying to make money, and our role is to participate to that goal. We should always think about our customers, internal or external, and how we can help them. If doing that involves playing with some cool toys and be able to brag about it, go for it! But that is not the other way around. PS : to give one answer to how we could use Azure Container instances for the real world, especially the kubelet version of ACI, try and think about batch computing, where you would periodically need to spin up dozens or hundreds of container instances for a very short time. Does that ring any bell for you? PPS : I could not find the exact session from Mark I am describing here, but there is an almost identical session from Corey Sander and Rick Claus there : Azure Container Instances: Get containers up and running in seconds

There we are, I have finally given my talk about Kubernetes and Azure. It was both more and less than I expected. It was more easy, once I got there, into the position of a speaker than I expected. My fellow speakers were very kind and supportive, which helped with the pre-stage flutters :) It was also easier because the room was of a reasonable size, and I was not on stage in front of 500 people. And it was less deep dive than I expected, which also allowed me to relax a bit. I could get a feeling about the audience before going there, which let me into the dark regarding their needs and expectations. Let’s set the stage. The event took place at Microsoft’s Building 20, which is a Reactor (https://developer.microsoft.com/en-us/reactor/). So the building is definitely designed to host events comfortably. That helped a lot, as we even had someone from the A/V team to help us and ensure all the screens and microphones would be working correctly. And yes, the free coffee might also have been a huge help :) The room was large, without any raised platform for the speaker, but with multiple repeat screens all around. I was the third speaker, so I definitely had some time to review my slides and demo setup a few times. I did setup the demo environment the night before, to avoid any deployment issue at the last minute (which did happen 2 days before while I was practicing). Once again, having a scripted demo ensured that I would not forget any step, or mess up some command line options. I did have a few issues during the talk. First the mike did stop working at some point, failed battery. I kept on speaking without it, as the room was small enough to let me speak louder for a short time and still be heard. The support guy came shortly to replace the battery, so no big issue there. My remote clicker did work perfectly, but not the pointer part. That’s a shame, because it made it more difficult to point out at a precise section of a slide or demo. Afterwards I found out why, and I should be able to avoid that particular issue in the future. I did not get as much interaction as I hoped I would. I thing that it was mostly due to my anxiety, which prevented me to behave like my normal self and be engaging. What I would change for the future. First, for a set event like this one, I would practice in front of a camera, or a mirror, to actually see and listen to my speech. That would probably ensure that I would keep the correct pace and articulation. And also make sure that the flow of slides is comprehensible. Second, I would work more to know the expectations of the public. It turns out that my talk was way too technical and fast it should have been. While discussing with the attendees afterwards, I realized that I did not get many of the points through, probably because I went too fast over those. This brings me back to the interactions point above : would I have been more comfortable and interactive, I could have grasped that during the session and corrected it. Third, I should probably think about learning a bit more about controlling my voice and projecting it. I realized that during the week leading to the event, as I had to speak in a loud environment, and present/discuss the same kind of subjects. Labs A word on the hands-on labs we had in the afternoon. I just was glad to have stayed for that part. First because I had never been on the proctor side before, and it’s really fascinating to see a problem through the eye of someone with a different mindset and culture. I really learned a lot, and realized a lot during these 2 hours. Second, because it showed me the areas where my presentation had been lacking, and how much I had not been clear enough to be understood by everyone. I think these discussions with the attendees were the deeper feedback and improvement tips that I could get. For the record, the container labs we used are there : https://github.com/Azure/blackbelt-aks-hackfest/ That’s it for now. This first talk has unlocked something and made me realize that I should talk at every occasion I can, and that I love it, at least when it’s done ;)

I’m writing this a bit ahead of time, as I plan to write a follow-up to compare what is planned against what will have happened. As the title suggests, I will be hosting my very first public session on the 21st of April. I am taking part in Global Azure Bootcamp https://global.azurebootcamp.net, a worldwide community event where experts from around the world gather locally to share their experience and knowledge on Azure. I would probably have preferred to be involved in an event in France, however I am in Seattle that week, so my event of choice will be directly @Microsoft in Redmond. This will an occasion for multiple first times for me : first time on my own as a public speaker, first participation in Global Azure Bootcamp, first time presenting fully in English, and first time presenting in Redmond of course :) So, big step far out of my comfort zone. The aim of this post, as stated above, is to record what I did to prepare for the event, and afterwards, write down what have gone right and wrong, and how I can progress and do better. I have chosen the topic of containers & Kubernetes on Azure for two reasons : first I am rather comfortable with the subject, and second a colleague, Jean Poizat, https://www.linkedin.com/in/jean-poizat-0a97bb/, did already build a slidedeck and demo which I could expand from. Obvious first then : I have a chosen familiar grounds and existing material, to limit the amount of work needed. This however presented a challenger : start from slides which I did not write, and get familiar with those, before rearranging & completing those to my purpose and comfort. A word on how I got out of my comfort zone : a nice kick in the back end! I saw on some social networks few friends and colleagues getting ready for GAB in France, which prompted me to start collaborating, at least to give a hand. Once I realized I would be in Seattle at that time, I contacted the local event owner Manesh Raveendran, https://www.linkedin.com/in/maneshraveendran/, to offer my help, in broad terms. It took me a while to be able to suggest the session I will be presenting, and I almost chickened out a few times. But once Manesh wrote me in, that was it, I had to make this work! The next step was to get very familiar with the presentation and with the associated demos. I started presenting to myself, but out loud and standing. This allowed me to work my speech, content and speed, and fine tune the slides. I also quickly incorporated the demos, to work out how to time things, and how to work around a failing demo. I started 10 days before the set date, with the slides & demo mostly ready. I allowed a minimum of a deck run every two days, that I would then adjust depending on my comfort and accuracy. During these dry run, I would keep a piece of paper next to me, to write down whatever thoughts/questions or clarifications were needed. These would affect either the speech or the slides, and even the demo. In between these runs, I would review the slides as much as I could every day. I did not spend as much time reviewing the demo, as Jean had provided me with a solid script that would mostly run by itself, on my cue. The few manuals demos were quite simple, and worked every time. I was also lucky enough to meet with several architects during that time, who were kind enough to give me their feedback on my slides, and even to let me rehearse in front of them, and give me their impressions and advice. That was a big help, and a great comfort as showtime loomed closer :) I am now a few hours from the actual session, I will submit this post and start writing the follow-up right after the session. Stay tuned! PS : the program for the Redmond event is there : https://www.azurecommunityevents.com/#/event?181C8806AFB7-4142-B0D3-B1858E9E8956

Catchy title, isn’t it? It could have been copied from a Management magazine, or CIO Monthly. Note to self : check before getting a copyright infringement lawsuit. What I wanted to write about is mostly how to deal with the fast pace of innovation in the IT cloud business. And mostly, how I deal with it, in my specific role, and how I dealt with it before. As IT pros, we need to always keep an eye on the market, to check emerging technologies, to check where the existing ones are going and which ones are dying. This serves two purposes : • Keep our company and infrastructure up to date • Keep our own profile up to date, or at least on the track for the future In french we have an expression for that : “veille technologique”, which would roughly translate to “technological watch”. In some french schools this subject is taught. It mostly describe how to identify the proper source of information to track, and how to track those. The sources are mostly tech websites and influencers. The tools are more diverse : RSS feed, Linkedin, Twitter, Facebook, Reddit… In my previous position, as an infrastructure consultant & architect, I had to keep up with a limited set of technologies, mostly around databases and virtualization. My watch was purely technical, and dealt with detailed evolution of some component : which new feature was available in the latest version of Vsphere ESX, what capabilities was expected in the future release of Oracle DB etc. In that scenario, using RSS feeds, and attending some virtual events from the software editor was enough. I could keep up with the innovation pace by investing something along the line of one day per month of my time. Today, if I consider my CTO-like role, the job is more complex. The scope I have to watch is much broader. If you consider only Microsoft Azure and the services it may provide, it is already almost impossible to keep up. For example, if you use the blog posts “Last week in Azure” which only relate to official news from the Azure blog, you get around 30 news per week (https://azure.microsoft.com/en-us/blog/last-week-in-azure-week-of-2018-02-12/). If you want to dig into each announce, and find out how it might affect you, this will take more time than you have in a week :) And that does not count anything outside of official Azure news. If you add some specific content creators, from Microsoft or not, which post also every week, and then also add news and tendencies around DevOps… you get the point. I forgot the podcasts, and videos… The main risk, as the title stated, is innovation burnout, or innovation overload. From what I have seen with colleagues, partners and customers, most of them do not want to keep up with that mass of information. Fortunately, I love learning new stuff, and I love information. Here is how I am currently working to get the most relevant information in my mind, and keep up with the news stream. I have separate tools for separate needs, and most important I do not use them at the same pace : ...

I have been pushing my team to get certified on Azure technologies for the past 24 months, with various degrees of success. I am quite lucky to have a team who does not discuss the value of the certification, however much they discuss the relevance of the questions. But, as I am now going over almost 15 years of certifications in IT, I feel quite entitled to share my views and opinion. Keep in mind that I work in infrastructure/Operations, and in France, which will probably give some bias to my analysis :) I will start with some general comments on the value of certifications, from a career perspective, and dive into some specifics for each vendor I have certified with over the years. Some of my exams are a bit dated, so please be nice. I will conclude with my general tips to preparing for an exam. As I said, it’s been almost 15 years since my first cert, and I started that one before even being employed, that gives me some insight about the relevance of such investment in my career. I took my first dip into the certification world during a recruitment process with a consulting company. We were two candidates, I was the young guy and the other one was already holding his Microsoft MCP. I felt, at that time, that I could benefit from one myself, and compensate some of my lack of experience with it. As I registered for my first MCP exam, for Windows 2000 (!), I was contacted to get into a kickstart program to get my certification level up to Microsoft MCSE, everything started from there. After a few months, I passed the final MCSE exam (out of 7 at that time) and was recruited, to work on Cisco networking, which had nothing to do with my skills, by the very same company that had interviewed me when I discovered the MCP. I still think that the fact that I went through the certification path did a lot to convince my boss to be of my motivation and ability to work hard. Over the years I refreshed my MCSE with each version of Windows (from 2000 to 2016) and added a few new ones, depending on what I worked on at my positions : Cisco, RedHat, Vmware and Prince2. Even though it was not obvious in my first job, the following ones were pretty clear cases where my certifications held some value to my employer. We discussed the fact during some of the interviews rather openly. And I was in a recruiter’s shoes myself a few times, and here is why I feel is useful regarding the certifications. First it show that you can focus on sometimes gruesome work, for a while. Passing these kind of exams almost always forces you to learn tons of new information, on software or devices that you maybe never handle. Then it show dedication to maintain them over time, when they have at least some value to your current position. And, let’s be candid, it show you can take one for the team, because almost every vendor partnership requires some level of certification. And, as I said, I know for a fact that I had been recruited, at least partly, twice thanks to my certs. On the salary part, I am not definite on the impact of certifications. I do not feel that the cert plays a part there, but I cannot prove or disprove it. That being said, when you take one of these exams, you will experience very different things depending on the vendor, and sometimes on the level of certification. Let’s take a closer look. We’ll start with my longest running candidate : Microsoft. Apart from one beta test ten years ago, I always had some kind of MCQ with them. You may have some variation around that : drag and drop, point and click etc. But, by and large nothing close to a simulator or designer. This had led to a bad reputation a while ago, when you may have had an MCSE (which was like the Holy Grail of Microsoft certification) while having absolutely no hands-on experience with Windows. They have kept the same format for Azure exams, and are taking some heat also, because the exams are deprecated almost as they go out. I am wondering whether they are working on some other way to certify. Cisco had a router/switch simulator for a long time, which had brought some rather interesting exams, for the lowest levels. I only took the CCNA 15 years ago, so I do not know how it goes for higher levels. The only caveat, from my perspective, was that the simulator did not allow for inline help and auto-completion, which you still have in real life. RedHat, for the RHCE exams, had the most interesting experience in my view. The exam was completely in a lab, split in two sections. First you had to repair a broken RHEL server, three times. Then you were given a list of objectives that you had to meet with a RHEL server. You could choose whichever configuration you would prefer, as long as the requirements were met (with SELinux enforced, obviously :) ). You had a fully functional RHEL, with the man pages and documentation, but without an internet access. I still feel to that day that this way let you prove that you really were knowledgeable and had the necessary skills to design and implement a Linux infrastructure. And the trainers were always fun and very skilled. I also certified on Vmware Vsphere for a while and that brought me to a whole new level of pain. The basic VCP level is fine, just along the same lines as an MCP. But when I started to study for the next level, VCAP-DCD (which stands for Vmware Certified Advanced Professionnal-DataCenter Design), I had to find some new ways of preparing and learning. You see, where a usual exam requires you to learn some basic stuff by heart (like the default OSPF timers, or the minimum Windows 2000 workstation hardware requirements) it was still a limited scope. For this exam, you had to be able to completely design a Vsphere infrastructure, along the official Vmware guidelines, form all of the perspective ...