Abhishek Kona

Adam's post is good (and I like this categorization in general), but there are a couple of things that I don't agree with. First, I'd say time-to-recovery is a strength of CfD rather than CfM. Physalia (from our paper "Millions of Tiny Databases" https://lnkd.in/gepZPA2Y) is the CfD system that provides the metadata for EBS (https://lnkd.in/g7R3MgYk) a vastly bigger CfM system. We chose CfD for Physalia specifically to optimize recovery time, because it needs to recover before the larger system can recover. Second, I think the post is making an assumption that CfM systems are f+1 on the dataplane, use the minimal number of replicas, and don't use quorums. Aurora is an instructive counter example (https://lnkd.in/gNrNTPp7).

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Istio Service Mesh: great to see Ambient moving up to Beta, delta xDS becoming the default, and api-gateway becoming a first class citizen in Istio. https://lnkd.in/gYPmnTuj

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"The product went from $0 to $1B in 18 months." In this clip, Shishir Mehrotra (CEO Coda and ex-CPO YouTube) shares a powerful story about how a simple re-frame of the customer problem led to one of YouTube's fastest-growing products. I loved talking to Shishir about the: - Best framework to grow your career - WOW process to fix strategic planning - $100 voting process to think at a higher level Some quotes from Shishir: "The best people create clarity out of ambiguity. They can handle any curveball, pinpoint the real issues, and get results." "Planning is the most hated process in most companies. I believe it should take less than 10% of execution time and follow the WOW curve." "Be selfless, people can spot selfishness from a mile away. Learn to pay it forward and focus on the ideas, not on yourself." 📌 Watch now: https://lnkd.in/g-8kfZh8 Also available on: Spotify: https://lnkd.in/giz_Txcn Apple: https://lnkd.in/gqq6M38r Newsletter: https://lnkd.in/gpJkzJuZ

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According to Gartner® “Infrastructure and Operations (I&O) teams commonly struggle to manage Kubernetes (K8s) clusters at scale due to the talent shortage 🤼 — especially on heterogeneous scenarios (multicluster, hybrid, edge, etc.) or supporting multiple downstream teams. Besides inherent Kubernetes complexities, K8s teams must cope with the increase in the average number of clusters per organization from a few to dozens. As the cluster count grows and spans, the stack becomes more complex and diverse across different infrastructures (cloud, on-premises, and edge). This negatively impacts practitioners’ ability to maintain the clusters and demands more attention from I&O teams." 👉 struggling with managing complex Kubernetes? 🗓 schedule free consultancy => https://lnkd.in/dyErkV_C #angelscloud, #k8s, #Kubernetes, #digitaltransformation #multicluster #cloud

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VendorPM Engineering launches their first ever Tech Blog. Everything can't be perfect but everything surely has a Day 1. And today is our Day 1 of showcasing the engineering innovations that we are planning and continuously doing in the #proptech. Every product has tech debt and cleaning the tech debt along the Roadmap is always an interesting challenge. Our first post covers this topic. More to come soon. https://lnkd.in/gkq6huyn #proptech #proptech-engineering #techcompany #vendorpm

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I recently took Shreyas Doshi's product sense course where we learned the secret to building winning products: There are no secrets Most of us are doing it wrong :D But you can get much, much better at it than you realized If you learn to think correctly The course was dense, intense, and I learned more in 30 hours than in many years of doing product. Fundamentally it taught me what it means to treat making correct product decisions as an actual skill. But you have to jump in the pool and swim - there's no framework that can do it for you. Perfect for product people, founders (there were several great ones in my cohort) and senior Engineers https://lnkd.in/e8KDhv5c

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Managing production software, and especially "root causing" issues, whether at the infra or app layer, continues to be a growing challenge despite the success of companies like Datadog. I have looked at applying deep learning to this problem since 2017 when we worked with Gurashish Brar & Mohit Gupta to incubate Opas.ai. The team was exceptional, and they even hired a great SDR (me 😜 ). We learnt the hard way that it was too early and #AI was just not ready. A lot has changed since in terms of data infrastructure (check out Conviva's Operational Data Platform), causal inference models and LLMs. Jaya Gupta and I are excited to take another whack at this market, which we call #AgentSRE to distinguish from the outdated #AIOps framing. If you are building an #AgentSRE company, ping us. https://lnkd.in/gvBgfN7k

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𝐒𝐭𝐚𝐫𝐭𝐢𝐧𝐠 𝐒𝐞𝐩𝐭𝐞𝐦𝐛𝐞𝐫 𝐰𝐢𝐭𝐡 𝐠𝐫𝐞𝐚𝐭 𝐧𝐞𝐰𝐬 🎉 My PR in Argo Rollouts was approved and merged last week. This change will be launched as part of version 1.8: https://lnkd.in/ddxhHy4N Here are a few thoughts I’d like to share about this milestone: ⊙ 𝐎𝐩𝐞𝐧 𝐒𝐨𝐮𝐫𝐜𝐞 𝐌𝐞𝐧𝐭𝐚𝐥𝐢𝐭𝐲 Collaborating on open-source projects is very different from working on private projects—it requires a completely different mindset. From defining features and writing tests to refactoring code and crafting PR descriptions, the approach changes significantly. I usually feel quite confident doing these tasks within a team, but when it came to open-source collaboration, I was a bit hesitant about making significant refactors and changes to the code. ⊙ 𝐆𝐢𝐭 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 Branches, rebases, and merges can get really complicated. I wasn’t expecting this to be a challenge for me, but it was. When I was almost done with the changes, I realized that all my commits needed to be signed. Since this isn’t a common practice in the teams I’ve worked with, I struggled to get this done after completing my changes. Amending, rebasing, resolving conflicts, reordering commits… I was so out of practice with these actions that I had to relearn them the hard way. If you’re thinking of collaborating or want to check your Git skills, make sure to cross-check with Learn Git Branching [https://lnkd.in/dhHx_ZUU]. And let me know how it goes! 😉 ⊙ 𝐇𝐚𝐯𝐞 𝐟𝐮𝐧 Even though this contribution was a necessity from my team’s perspective, there were other ways to solve our needs that didn’t involve contributing upstream. But I decided to take on the challenge—not only because I was interested and it could bring value to other users, but also because it’s fun. From my perspective, the idea of having a “team” outside the scope of my company and getting feedback from others on the code sounds pretty fun. Lastly, I was lucky enough to have Thibault JAMET to mentor me during this collaboration. It made the whole experience incredibly valuable. It’s always exciting to learn from colleagues you look up to. So, the next time you’re using a tool and you need a slight change in a feature, think twice—maybe a collaboration could be a good fit. 💡 https://lnkd.in/djGJmZCj #argocd #argorollouts #opensource #collaboration #contribution #git

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🧠 From the intelligence of Andi to the curiosity of AskCodi, 🔮 From the magic of AWS Q to the insights of Bing AI, 💻 From the innovation of Codeium to the conversation with ChatGPT, 🔥 From the collaboration with Cody to the assistance of GitHub Copilot, 🚀 From the intelligence of Google Gemini to the lightning-fast Lightning AI, 🌈 From the creativity of Metaphor to the insightfulness of Neeva AI, 💡 From the coding prowess of OpenAI Codex to the mystery of Perplexity AI, 🔍 From the discovery with Phind to the enlightenment with Quora Poe, 🌟 From the assistance of Replit Ghostwriter to the knowledge of WolframAlpha, 📊 From the security of Snyk Code to the suggestions of Tabnine, 🌟 From the intelligence of Visual Studio Intellicode to the whispers of Whispr AI, 🔎 From the personalization of You to the assistance of my very own... We're asking about it all in the Developer Survey - share what you've worked with and what you want to work with in the future. https://lnkd.in/gdz3ZxKB (post content assisted by AI - which is perfectly meta)

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🚀 2025: The Year of AI & LLM Transformation 🚀 In 2025, we’re going to see businesses across industries building meaningful solutions using LLMs and NLP—tools that are opening up new possibilities. 💼 Text-heavy applications like legal services, customer support (think Zendesk), and marketing are about to be transformed. These solutions will automate complex tasks and generate insights we’ve never had before. But it won’t stop there. 🔧 For engineers, the competition is heating up. The bar has officially been raised. Mastering LLMs, NLP, and AI tools is no longer optional—it’s essential. 🌟 What industries do you think will see the biggest impact from these advancements? How are you preparing for the AI-driven future?

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https://lnkd.in/gdGKdeAW - New project I built using a combination of Replit Agent, Perplexity search API using llama-3.1-sonar & OpenAI API Assistant. You're not sure how to vote on that? Take a quiz about your core values then this app will research it/them and help you decide.

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The Site Reliability Engineering: How Google Runs Production System book is arguably one of the most prevalent and well-known SRE resources out there, but there are many other great options for folks looking to expand on their learning. We recently spoke to Google's Reliability Advocate, Steve McGhee, in our Humans of Reliability interview series. In addition to his interesting anecdotes on the early days of SRE at Google, and his journey to becoming a Reliability Advocate, he also shared a handful of his favorite SRE resources, which we compiled here into a list: https://lnkd.in/gpUVhyRa

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Join us for a conversation with Peggy Rayzis on building a "Developer Intent led" GTM motion! We explore the key drivers that led to the wild success of Apollo Graph QL... followed by an AMA Link to register in comments. Feel free to share any questions

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This is a cool project, and another example of the emerging "replace stateful storage with S3" trend. I do wonder at what point someone will package this sort of thing up into a FUSE filesystem to make it generally usable across existing services. Or maybe every service has unique enough needs that it's better to handle it custom each time. https://lnkd.in/etcVBfVf

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Rule #1 of product development: Assume that everything that can go wrong, will go wrong. 10x more true with AI products 😅 Check out my intro guide on AI evals for more: https://lnkd.in/gUDKa_zt

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An intriguing startup called Fragment is shaking up the ledgering game. 💡 If you’ve ever dealt with tracking customer balances, you know how tedious it can be—Fragment's API aims to simplify that by offering real-time, double-entry accounting without the accounting jargon overload.📊 Founders Thomas Neckel and Omi Chowdhury are onto something big here, especially with their track record of successful startups. With early adopters like TruckSmarter and Nala already onboard, it's exciting to see where this tech goes. 🚀 #Fintech #Startup #Innovation #AccountingTech #TechTrends https://lnkd.in/eUrC-tJE

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