Reduce a giant toolstack to one simple #opensource tool, self-hosted with zero-code setup. Pivotal instigator of the #DevOps movement Kris Buytaert shares why he loves Coroot: t.ly/p7l4_ #Linux #FOSS #softwarelibre #monitoring #observability #Cloud #Agile #Vagarant #Scrum #kubernetes #docker #SRE #IaaC #tech #Devsecops
Coroot
Software Development
Palo Alto, California 1,305 followers
Instant observability with no-code setup. Improve uptime in seconds with AI-powered root cause analysis.
About us
Coroot solves the problem of time-consuming root cause analysis. It handles the full observability journey for your team - from collecting telemetry automatically with zero code setup (thanks, eBPF!) to simplifying the role of SREs and DevOps everywhere with instant root cause analysis powered by AI. View metrics, logs, profiles, and traces in a single dashboard - with customizable SLOs that transform alert fatigue into a single notification, connected to the work messaging platform of your choice. Accurately identify the root cause of over 80% of outages, and eliminated blindspots with a comprehensive Service Map of your entire system, dependent services, and databases. We believe that simple, quality observability should be an innovation everyone can afford to benefit from: which is why our core software is open source 🐧🐝
- Website
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https://coroot.com
External link for Coroot
- Industry
- Software Development
- Company size
- 2-10 employees
- Headquarters
- Palo Alto, California
- Type
- Privately Held
- Founded
- 2021
- Specialties
- Observability, AI-powered Root Cause Analysis, Open Source, Enterprise, and eBPF
Locations
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Primary
Get directions
Palo Alto, California 94306, US
Employees at Coroot
Updates
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👨💻 🔥 Thanks #DevOps & #SRE Pro Abdullah Salman Hameed for sharing your experiences with Coroot and deciding "Coroot is the best observability choice thanks to eBPF!"
Building a Modern Observability Stack: Lessons from Production Over the past few weeks, I've been deep in the trenches setting up a comprehensive monitoring infrastructure for our production environment, and I wanted to share some insights from the journey. The stack centers around Coroot, an open-source observability platform that's been a game-changer for understanding our distributed systems. What makes it powerful is how it connects the dots between metrics, logs, and traces without drowning you in complexity. Here's what the architecture looks like: Core Components: Prometheus for metrics collection and time-series storage ClickHouse for efficient log and trace storage with intelligent retention policies cAdvisor for deep container-level insights Blackbox Exporter for endpoint health monitoring Node agents for system-level observability Key Design Decisions: I implemented aggressive data retention policies to keep storage manageable. Logs are retained for 3 days, traces for 3 days, which strikes the right balance between debugging capability and infrastructure costs. Resource limits were carefully tuned for each component. Prometheus got 4 CPUs and 6GB RAM to handle our query load, while ClickHouse received 4 CPUs and 8GB to manage the data ingestion efficiently. In total, we have 16 GB RAM, 8 cores, and 500 GB of storage. Everything runs containerized, which makes deployment reproducible and scaling straightforward. The entire stack can be brought up with a single command, which is invaluable when you need to replicate environments. What I Learned: The difference between monitoring and observability is real. Having metrics is one thing, but having them contextualized with service dependencies and performance patterns is what actually helps you solve problems at 2 AM. Setting up proper health checks and resource constraints from day one saves headaches later. The monitoring system needs to be reliable, because it's your eyes into everything else. Data retention isn't just about storage costs. It's about finding that sweet spot where you have enough history to debug issues without drowning in data that's no longer actionable. The observability space has matured significantly. Tools like Coroot, combined with the Prometheus ecosystem, give you enterprise-grade capabilities without enterprise-grade complexity. For anyone building out their monitoring infrastructure, my advice: start with clear retention policies, implement resource limits from the beginning, and invest time in understanding your service dependencies. The service map visualization alone has helped us identify bottlenecks we didn't know existed. I think Coroot is the best choice in the 20s thanks to EBPF. The setup needs some hard work to implement, but it's an enjoyable journey. Thanks to Coroot #coroot #SRE #DevOps
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🐝🐧🔥 Thanks Nasi Chaudhari for sharing why you love Coroot! (Check out his channel for more #DevOps tips: https://lnkd.in/eD9C7AKw) Tackle root cause analysis in seconds with #AI and no-code setup: https://t.ly/6pHTZ #observability #opensource #SRE #Linux #eBPF #FOSS #tech #AI #monitoring #kubernetes
Zero config eBPF & AI root cause observability with coroot! #observability
https://www.youtube.com/
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“Observability best practices” starts with functioning monitoring. Learn the difference between these two concepts and common mistakes to avoid: https://t.ly/2H_JM Huge thanks to Co-founder of #DevOpsDays, O11y, Inuits, and pivotal instigator of the DevOps movement Kris Buytaert for joining us to teach you why ‘Everything a Freaking #DNS Problem,’ how to avoid Git-branch nightmares, tips on mastering #scrum, and why the most important #DevOps tool of all is beer. Listen to Episode #3 of The Open Source Observability Podcast wherever you get your podcasts (RSS): https://lnkd.in/esP2_sRR #Linux #FOSS #softwarelibre #monitoring #observability #Cloud #Agile #Vagarant #Scrum #kubernetes #docker #SRE #IaaC #tech #Devsecops
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🐝🐧🎊 Happy New Year's Eve from #Coroot to our global community of #opensource observability heroes! A special thank you from the bottom of our heart to Asker Kakhramanov, Arie van den Heuvel, George Gaál, and everyone who helped our community improve open observability for everyone in 2025. May everyone have (mostly) functioning pods and incident-free evenings in 2026. Maybe you'll be the top contributor next year: https://t.ly/__UBr #observability #DevOps #SREs #AI #LLMs #kubernetes #AWS #Linux #eBPF #HappyNewYear #HappyHolidays
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Happy Holidays! May your on-call pagers in the New Year be silent at 3AM and your days be incident-free 🐧🐝🎊 Many thanks to all the dedicated #opensource Coroot community members in 2025 that contributed code, wrote articles to teach others, and shared their stories with us to help make incident resolution faster for everyone. #HappyHolidays #Coroot #DevOps #SRE #observability #monitoring #eBPF #Linux #tech #AI #softwarelibre #opensource
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🐧🐝👇 Learn how you can quickly pinpoint the root cause of incidents and see the steps to restore system health with Coroot: https://t.ly/M5yC8 #Opensource user? Here’s how to configure it with Coroot Community Edition (10 free incidents monthly.): https://t.ly/ZYb2i #AI #AgenticAI #DevOps #SRE #kubernetes #observability #monitoring #Linux #tech #AWS #cloud
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Coroot reposted this
Adding observability to applications always involves tradeoffs. We know instrumentation has a cost, but how much exactly? This benchmark on OpenTelemetry for Go puts some real numbers behind what's usually just intuition or rough assumption. The article findings: enabling OpenTelemetry tracing added about 35% CPU overhead and pushed p99 latency from 10ms to 15ms. Memory increased roughly 50-80%. I'm curious if these are comparable to what others have seen. These values are not trivial, but also not a dealbreaker for most use cases where visibility actually matters. The article from Coroot is very interesting. I always like reading benchmark cases like this. https://lnkd.in/eeMNVmgS
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☁️ 🐘 Learn how to manage complex cloud environments with #Coroot Co-Founder Peter Zaitsev’s keynote at Prague PostgreSQL Developer Day! https://p2d2.cz/en/ Join January 28th, 15:35–16:25 (GMT+1) to sharpen your cloud-native #postgres observability with topics such as #eBPF, automatic discovery mechanisms for High Availability postgres clusters, and monitoring for #VMs, storage volumes, and network components. #softwarelibre #opensource #freesoftware #DevOps #SRE #kubernetes #observability #cloud #databases #postgreSQL #highavailability
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