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Kerno.io – Developer-first monitoring that makes sense

Hacker News

Kerno.io – Developer-first monitoring that makes sense

Hey HN! Anibal, Sean, Vlad, Maxi and Karim here we're the co-founders of Kerno ( https://www.kerno.io/ ). We're building a zero-hassle tool to help developers monitor and troubleshoot their services in a way that makes sense. No complex rollouts, no custom infra, no tons of instrumentation, no sidecars… none of that! Just a minimum effort, out-of-the box, highly contextualized and interactive experience so you and your team can focus on shipping! We basically scan your cluster resources, build usable abstractions on top of all the kubernetes craziness, identify monitor your service interactions and backtrace errors on demand to understand end-user impact and prioritise what to work on. We plug into your code versioning and CI to know who is who and who is working on what to give you back the time wasted in figuring that out (and we know that can take a while sometimes!). We then ping who we think might have introduced the issue, who “owns” those systems, and who owns the systems being impacted by them. You get this through a desktop app in real-time and are quickly taken to a fully contextualized and correlated event and telemetry data down to the potential problematic lines of code. As our platform gets smarter -and we need you for this!-, Kerno aims to bring to near-zero the time to figure out not only what’s happening in any given service, but who should be brought into the loop and what, who and how is it impacting your overall service. Now, let’s talk about tech a bit > Zero code instrumentation. Our agent runs as a DaemonSet leveraging eBPF. > Hassle-free and almost instant. Deployments in sizable clusters take as little as 30 seconds. Two commands tops (no worries, scripts, and Helm charts are published on GitHub if you want to have a look, of course) > As light as it can get. We are talking as little as 0.125 CPU and 64MiB per node depending on your nodes’ size! (currently running at < 5% CPU in our highly-stressed test environments). > Low overhead, all across. We are minimalistic with data. We collect, process, and transmit data based on events of interest (from an error being detected to a user requesting N samples). We only transmit and store data in our cloud to provide a top user experience (it’s a hybrid approach). > No billing surprises. Since we don’t base our business on charging for data ingestion and storage, pricing is quite predictable, allowing us to offer you flat pricing for the service. We price the service by unique workload, ignoring replication and associated resources (like configmaps or network services). > Data is secure at all times. We capture and manage trace storage encrypted in your cluster. Relevant logs are transmitted to the user on-request through a blind encrypted tunnel to facilitate access to all features. A few current limitations: > We only officially support EKS & GKE for now, but we are working on support for other managed Kubernetes services and AWS ECS. > TLS support is currently limited to common gateways (like Nginx). If you are using TLS or HTTP/2 for intra-cluster comms, no problem, we are getting there real soon! > GitHub and GH actions bound for now, but we are working hard towards supporting other large Git and CI services! So… that’s it for now. We are really happy to put Kerno out there! And look very much forward to hearing from you all! Please let us know your thoughts and questions in the comments.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: agent, user, context · Missing: mac, agents, macos
86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: nginx, ide, io · Missing: https docs, excited, just released
79%79% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, soon · Missing: plus, intuitive, reviews
26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce, smart · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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