Authors

Authors

Authors

Ajinkya Wadekar

SRE @One2N

Akshay Srivastava

SRE @One2N

Chinmay Somani

Drasti Kaurav

SRE @One2N

Harsh Mishra

SRE-Intern

Hrithik Sawant

SDE

Jaideep Khandelwal

Founder, CTO @One2N

Kalpesh Deo

Lead Software Engineer

Mihir Bhagwat

SRE @One2N

Mohit Kumar

Software Engineer @One2N

One2N Team

Saurabh Hirani

Principal SRE @One2N

Saurabh is a systems engineer who cares about what he builds and automates what he can. If you have an idea, I will craft a story for you.

Siddharth Shashikar

SRE @One2N

Sitaram Shelke

SRE

Spandan Ghosh

Content @One2N

Spandan likes tinkering and reverse engineering stuff…

Checkout our latest posts

November 8, 2024 | 7 min read

Karpenter vs Cluster Autoscaler: A Comprehensive Guide to Kubernetes Node Scaling

Rahul H Bhatia

SRE @One2N

October 8, 2024 | 9 min read

Exploring Retrieval-Augmented Generation (RAG): Enhancing LLMs with External Knowledge

Harsh Mishra

SRE-Intern

September 19, 2024 | 10 min read

Storing Sparse Data Efficiently: A Deep Dive into ClickHouse and Schema Design

Amit Sadafule

Lead Software Engineer

August 30, 2024 | 6 min read

Setting Up CloudWatch Alerts for EKS Clusters: Insights and Solutions

Mihir Bhagwat

SRE @One2N

August 19, 2024 | 5 min read

Eliminating bot-tlenecks - spin machines from containers

Ajinkya Wadekar

SRE @One2N

August 5, 2024 | 3 min read

Maintaining Multiple GitHub Accounts on a Single Machine

Saurabh Hirani

Principal SRE @One2N

Blog

Checkout our latest posts

November 8, 2024 | 7 min read

Karpenter vs Cluster Autoscaler: A Comprehensive Guide to Kubernetes Node Scaling
Discover the key differences between Karpenter and Cluster Autoscaler for Kubernetes node scaling. Learn how each tool handles dynamic workloads, node provisioning, and cost optimization to choose the best solution for your cloud-native environment.

Rahul H Bhatia

SRE @One2N

October 8, 2024 | 9 min read

Exploring Retrieval-Augmented Generation (RAG): Enhancing LLMs with External Knowledge
Discover Retrieval-Augmented Generation (RAG), a technique that enhances Large Language Models (LLMs) by integrating external knowledge bases to provide more accurate, up-to-date, and contextually relevant responses. RAG combines information retrieval with generative AI to address issues like hallucinations and outdated training data, ensuring LLMs stay relevant and current. Learn how RAG works and its benefits

Harsh Mishra

SRE-Intern

September 19, 2024 | 10 min read

Storing Sparse Data Efficiently: A Deep Dive into ClickHouse and Schema Design
Learn how to efficiently store and query sparse data using ClickHouse. Discover the differences between OLAP and OLTP, optimal schema designs, and best practices for avoiding nullable columns. Explore real-world examples and performance metrics to optimize your data management and analytics workflows.

Amit Sadafule

Lead Software Engineer

Blog

Checkout our latest posts

November 8, 2024 | 7 min read

Karpenter vs Cluster Autoscaler: A Comprehensive Guide to Kubernetes Node Scaling
Discover the key differences between Karpenter and Cluster Autoscaler for Kubernetes node scaling. Learn how each tool handles dynamic workloads, node provisioning, and cost optimization to choose the best solution for your cloud-native environment.

Rahul H Bhatia

SRE @One2N

October 8, 2024 | 9 min read

Exploring Retrieval-Augmented Generation (RAG): Enhancing LLMs with External Knowledge
Discover Retrieval-Augmented Generation (RAG), a technique that enhances Large Language Models (LLMs) by integrating external knowledge bases to provide more accurate, up-to-date, and contextually relevant responses. RAG combines information retrieval with generative AI to address issues like hallucinations and outdated training data, ensuring LLMs stay relevant and current. Learn how RAG works and its benefits

Harsh Mishra

SRE-Intern

September 19, 2024 | 10 min read

Storing Sparse Data Efficiently: A Deep Dive into ClickHouse and Schema Design
Learn how to efficiently store and query sparse data using ClickHouse. Discover the differences between OLAP and OLTP, optimal schema designs, and best practices for avoiding nullable columns. Explore real-world examples and performance metrics to optimize your data management and analytics workflows.

Amit Sadafule

Lead Software Engineer

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