Ivan Martoš

Understanding the Risks of Long-Lived Kubernetes Service Account Tokens From the content: The popularity of Kubernetes (K8s) as the defacto orchestration platform for the cloud is not showing any sign of pause. This graph, taken from the 2023 Kubernetes Security Report by the security company Wiz, clearly illustrates the trend: ...[Read more]

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Sometimes to fix a problem somebody has with a Kubernetes app, I have to change some Terraform to update EKS, and I have to update the shared Helm charts our apps depend upon, and I have to get it all to deploy via ArgoCD, and I have to test it using git branches because I don't want to merge something that's broken, and so I have to update the branch variables in some other Terraform, and I'm working in 4 or 5 different repos all in separate branches and I have to make Jira tickets to track all of this so I don't forget where I am in the process, and this is what it all looks like in my mind.

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💚 We extend our gratitude to Vadim Tkachenko and Percona for their detailed exploration of Coroot's capabilities in Kubernetes observability. 🔗 Read the full article here: https://lnkd.in/eBpN8qZN Discover how Coroot enhances visualization and diagnostics in Kubernetes deployments 👆 #Kubernetes #Observability #DevOps

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Grafana has significantly advanced the field of observability, enhancing the quality of service. What's even more impressive is that it's an open-source product. Given the widespread adoption and prevailing trends surrounding Kubernetes, it's imperative for technology professionals to consider the automation of observability. This approach represents the future of cloud observability and instrumentation practices, marking a significant evolution in how we manage and understand cloud environments. "If you write it, you run it, and you should be on call for the software you write—that's a very important philosophy," says Torkel Ödegaard. This is the spirit that organisations should keep in mind. As a solutions provider, I continue to observe that many developers and operations professionals operate independently, adhering strictly to traditional role definitions. However, it is essential to recognise that DevOps represents a culture and set of practices, rather than a distinct role. This perspective has been extensively discussed in numerous articles and presentations. So, do your organisation use #Grafana Stack? Or do you use other SaaS solutions? Leave a comment and I would love to hear more about your perspective. Check out this article to learn more: https://lnkd.in/eGGGgSHh

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Is write once, run once becoming a reality? Does #WebAssembly / #WASM present an alternative to creating and maintaining secure and optimised containers to run application services? #kubernetes #cloudnative https://lnkd.in/eEAUHeDm

New Post: How to Set, List, and Remove Taints on Kubernetes Nodes

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If you’re using Kubernetes, you can build out your environment based on your own reality. The beauty of k8s is the extendable API. If you think about it from just a programmatic perspective, that means your environment can look any way you want. You can also build ON TOP of Kubernetes to create your own environment. Here’s a great example I saw at KubeCon. #kubernetes #devops #platformengineering

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🔊 𝐃𝐢𝐯𝐢𝐧𝐠 𝐢𝐧𝐭𝐨: 𝐆𝐫𝐚𝐟𝐚𝐧𝐚 𝐀𝐝𝐚𝐩𝐭𝐢𝐯𝐞 𝐌𝐞𝐭𝐫𝐢𝐜𝐬 📊 We're proud partners to Grafana Labs and today we dive a bit deeper into their 𝘈𝘥𝘢𝘱𝘵𝘪𝘷𝘦 𝘔𝘦𝘵𝘳𝘪𝘤𝘴 𝘧𝘰𝘳 𝘎𝘳𝘢𝘧𝘢𝘯𝘢 𝘊𝘭𝘰𝘶𝘥 - what is it and what difference can it make for your business? 🤔 We know the feeling: you have praised observability in your organization (as you should) and onboarded multiple teams to an observability platform - great! What can go wrong? Everything is amazing, until the first bill comes in... WHAT? How did it become so much?😅 We hear you. 🔍 You're managing a sea of metrics, In which only a fraction truly matters. As metric cardinality grows, so does your cost to store and retrieve the data. 💸 Grafana constantly look for ways to make observability more cost-effective and that is why we're digging deeper into their 𝗔𝗱𝗮𝗽𝘁𝗶𝘃𝗲 𝗠𝗲𝘁𝗿𝗶𝗰𝘀. With it, we allow you identification and elimination of unused time series data through aggregation. It filters out the noise, focusing only on what's essential. This innovative feature intelligently sifts through your data, retaining only the critical metrics you need 💪 💡 𝑻𝒉𝒆 𝒓𝒆𝒔𝒖𝒍𝒕? Significant cost savings, streamlined telemetry and enhanced performance without compromising on observability. It's like having a superpower for your observability stack! So, next time, you don't have to try and hide the bill from your financial department.... You can proudly show it 😎 and continue gaining benefits from observability. Dive into the future of 𝗚𝗿𝗮𝗳𝗮𝗻𝗮 𝗔𝗱𝗮𝗽𝘁𝗶𝘃𝗲 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 - For more details how it works, read below 👇 PS. Curious about our partnership with Grafana Labs? Don't hesitate to reach out! https://lnkd.in/gkNrPdKY

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Monitoring Kubernetes Service Topology Changes in Real-Time https://buff.ly/3UFfhsq Horizontally scalable data stores like Elasticsearch, Cassandra, and CockroachDB distribute their data across multiple nodes using techniques like consistent hashing. As nodes are added or removed, the data is reshuffled to ensure that the load is spread evenly across the new set of nodes. When deployed on bare-metal clusters or cloud VMs, database administrators are responsible for adding and removing nodes in a clustered system, planning the changes at times of low load to minimize disruption to production workloads.

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Monitoring Kubernetes Service Topology Changes in Real-Time https://buff.ly/3UFfhsq Horizontally scalable data stores like Elasticsearch, Cassandra, and CockroachDB distribute their data across multiple nodes using techniques like consistent hashing. As nodes are added or removed, the data is reshuffled to ensure that the load is spread evenly across the new set of nodes. When deployed on bare-metal clusters or cloud VMs, database administrators are responsible for adding and removing nodes in a clustered system, planning the changes at times of low load to minimize disruption to production workloads.

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This article recounts the journey to Kubernetes 1.0, covering the project's early days, lessons learned from Borg and Omega, the evolution of the API, and key features added during the years. More: https://lnkd.in/eF6BGUnA

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In this episode, we talk with Marvin Beckers from Kubermatic about KCP - a CNCF Sandbox project that provides a horizontally scalable control plane for Kubernetes-like APIs. https://lnkd.in/gez2JWgF

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influxql-to-m3-dashboard-converterOverview A tool to migrate Grafana dashboards based on InfluxDB source to Prometheus source ( like Prometheus, M3DB, Cortex ... #devopskhan

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