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DevOps & SRE notes

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Post #2182 10.7K
Learning from unexpected service failures can be a catalyst for long-term improvement, as Tines software engineer Shayon Mukherjee shares in this blog post. The story reveals how a Redis upgrade exposed a hidden point of failure in their webhook system, ultimately leading to stronger resilience and more comprehensive testing practices.

https://www.tines.com/blog/engineering-incidents-improvement/
Tines Tines | Intelligent workflow platform Build and orchestrate intelligent workflows and agents, on the platform security and IT teams love.
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Post #2179 9.31K
Designing a robust network architecture for K3s multi-cluster environments can be challenging, especially when integrating Layer 2 and BGP routing on Unifi UDM devices. In this guide, David Elizondo walks through practical considerations and strategies for planning private RFC 1918 address spaces and achieving effective communication between clusters using tools like Cilium and native routing.

https://medium.com/@david-elizondo/planning-a-k3s-multi-cluster-network-with-l2-and-bgp-on-unifi-udm-ae4480a7b4f7
Medium Planning a K3s Multi-Cluster Network with L2 and BGP on Unifi UDM In my journey to rebuild my Kubernetes Lab to use a multi cluster design, I needed to put some thought into where in my network, services…
Post #2178 9.12K
As the complexity of modern software systems grows, the meaning and practice of "observability" have become increasingly muddled. In this personal essay, Charity Majors argues that it's time to "version" observability—differentiating the traditional metrics-logs-traces approach (Observability 1.0) from a new, more flexible model built on wide, structured log events (Observability 2.0).

https://charity.wtf/2024/08/07/is-it-time-to-version-observability-signs-point-to-yes/
charity.wtf Is It Time To Version Observability? (Signs Point To Yes) Observability 1.0 is the hard way; observability 2.0 is SO much easier. Want data? Toss it in. Want to ask a question? Ask it. Don't care about format or cardinality.
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Post #2175 7.9K
Optimizing autoscaling in Kubernetes involves much more than just monitoring CPU and memory, as this blogpost by Cristian Sepulveda demonstrates through a practical application workflow. By leveraging KEDA to scale based on real-world metrics like message queue length, teams can achieve faster, cost-effective scaling tailored to specific application needs.

https://medium.com/@csepulvedab/how-to-optimize-autoscaling-in-kubernetes-using-metrics-based-on-application-workflows-7f899fdef4d9
Medium How to Optimize Autoscaling in Kubernetes Using Metrics Based on Application Workflows One of the key advantages of using Kubernetes in modern infrastructure is the ease with which we can scale computing resources. Both the…
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Post #2174 7.71K
The challenge of making artificial intelligence more transparent is at the heart of Andrew Mallaband's exploration of the "black box" dilemma. This insightful editorial delves into the real-world implications of explainability in AI systems.

https://www.linkedin.com/pulse/explainability-black-box-dilemma-real-world-andrew-mallaband-ogvae/
Linkedin Explainability: The Black Box Dilemma in the Real World The software industry is at a crossroads. I believe those who embrace explainability as a key part of their strategy will emerge as leaders.
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Post #2169 6.53K
Enhancing workload isolation and security in Kubernetes environments is critical for protecting sensitive operations and preventing container breakouts. This blogpost explores how Kata Containers combine the efficiency of containers with the robust security of virtual machines, enabling secure deployments on Amazon EKS with minimal configuration changes.

https://aws.amazon.com/blogs/containers/enhancing-kubernetes-workload-isolation-and-security-using-kata-containers/
Amazon Enhancing Kubernetes workload isolation and security using Kata Containers | Amazon Web Services Containers have become the dominant method for deploying and managing applications in recent years. Their widespread adoption is attributed to numerous advantages, such as isolation, efficient hardware use, scalability, and portability. In situations where…
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Post #2168 6.37K
Optimizing Kubernetes cluster networking is essential for modern applications requiring scalability, low latency, and efficient resource utilization. This blog explores how LoxiLB leverages eBPF technology to enhance load balancing, observability, and security while overcoming the limitations of traditional proxy-based solutions like kube-proxy.

https://www.loxilb.io/post/loxilb-cluster-networking-elevating-k8s-networking-capabilities
LoxiLB LoxiLB Cluster Networking: Elevating Kubernetes Networking capabilities Since the inception of microservices and distributed applications, Kubernetes reigns supreme, providing a robust platform for deploying, managing, and scaling containerized applications. At the core of Kubernetes lies Kubernetes cluster networking, a sophisticated…
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Post #2165 5.44K
Managing stateful workloads in Kubernetes often comes with challenges, particularly when scaling storage dynamically. This article introduces the PvcAutoscaler, a custom solution developed by City Storage Systems to enable volume expansion, shrinking, and modification for StatefulSets, improving cost efficiency and operational flexibility.

https://techblog.cloudkitchens.com/p/swapping-disks-in-kubernetes
techblog.atoms.co Swapping Disks in Kubernetes for Fun and Profit Introducing the PvcAutoscaler at City Storage Systems
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Post #2164 5.25K
Securing multi-cluster ArgoCD setups requires innovative approaches to authentication and token management to avoid long-lived credentials. This post explores how OpenUnison, kube-oidc-proxy, and ArgoCD's credential plugins can be combined to create a centralized, secure GitOps platform that spans multiple Kubernetes clusters.

https://www.tremolo.io/post/securing-multi-cluster-argocd
www.tremolo.io Securing Multi-Cluster ArgoCD Learn how to securely integrate ArgoCD with remote Kubernetes clusters with short lived tokens based on ArgoCD's Kubernetes identity..
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Post #2162 4.7K
Post #2161 4.48K
Deploying OpenAI Whisper for streaming audio transcription on Amazon EKS with Ray Serve combines cutting-edge ASR capabilities with scalable infrastructure. This blogpost outlines the architecture, tools, and processes needed to create a distributed ML inference solution that supports dynamic workloads and autoscaling with Kubernetes.

https://aws.amazon.com/blogs/containers/host-the-whisper-model-with-streaming-mode-on-amazon-eks-and-ray-serve/
Amazon Host the Whisper Model with Streaming Mode on Amazon EKS and Ray Serve | Amazon Web Services OpenAI Whisper is a pre-trained model for automatic speech recognition (ASR) and speech translation. It has demonstrated strong ASR performance across various languages, including the ability to transcribe speech in multiple languages and translate them into…
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