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https://kubernetes.io/docs/tasks/administer-cluster/manage-resources/memory-default-namespace/ LimitRange If you mention the limits but not the requests then pod is assigned limit value as the request(for both memory and cpu) Make sure to have limits set for atleast memory and requests as well. You can set a default memory and cpu limit for a namespace as well. These are namespace scoped. A LimitRange provides constraints that can: Enforce minimum and maximum compute resources usage per Pod or Container in a namespace. Enforce minimum and maximum storage request per PersistentVolumeClaim in a namespace. Enforce a ratio between request and limit for a resource in a namespace. Set default request/limit for compute resources in a namespace and automatically inject them to Containers at runtime. Reference - https://kubernetes.io/docs/tasks/administer-cluster/limit-storage-consumption/ ...

There exist quite a number of RAG techniques aiming to improve chatbot systems to have better accuracy and relevance to questions being asked. Some of the popular techniques are - RAG Fusion Multi query Native RAG Stepback prompting Hierarchical indexes Document summary index + LLM rerank HyDe Query decomposition Refer to research paper with different RAG techniques compared are graded - https://arxiv.org/pdf/2404.01037 Here is how they compare to each other and what are the benefits and problems of each technique being used for implementing RAG based systems. ...

So I have been working on GenAI applications for past few months and decided to build something using RAG. I could not think of some interesting resources so I decided to take my own blog content as the data to build my RAG chatbot on. Please note that the following content is going to be almost same as my medium blog - https://medium.com/@varunarora1408/building-rag-chatbot-on-my-personal-blog-ff89ac772c69 So, here was the rough idea that came to my mind to create this application- ...

Pod Scheduling Flow in Kubernetes Open above image in new tab Pod scheduling is a core component of Kubernetes that manages how and where pods are placed across the cluster’s available nodes. The process ensures that each pod meets its requirements, such as resource allocation (CPU, memory), affinity rules, and node availability. Let’s break down the pod scheduling request flow, along with key details based on the provided diagram and Kubernetes principles. ...

Node affinity and taints/tolerations are Kubernetes features that allow you to control where and how pods are scheduled onto nodes in a cluster. They serve different purposes but can be used in combination to achieve more advanced scheduling requirements. Node Affinity: Node affinity is a feature that allows you to specify rules for which nodes your pods are scheduled on based on labels assigned to nodes. It can be used to influence pod placement based on node characteristics such as hardware capabilities, geographic location, or other custom attributes. ...