Supercharge Kubernetes Debugging with k8sGPT.pdf

Oct 23, 20240 likes40 views

Nilesh Gule

Slide deck used during the Microsoft Reactor Bengaluru session

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Supercharge Kubernetes Debugging with k8sGPT.pdf

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Programming

@nileshgule
CNCF Landscape – Application & Databases

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CNCF Landscape – CI CD, Streaming & Messaging

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CNCF Landscape – Security & Compliance, Automation, Registry, Key
Management, Storage, Networking, Runtime

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CNCF Landscape – Scheduling, Service Mesh, Observability, Chaos,
Optimization

@nileshgule
k8sGPT filters
• ReplicaSet
• Node
• Pod
• CronJob
• Service
• Ingress
• Deployment
• StatefulSet
• MutatingWebhookConfiguration
• ValidatingWebhookConfiguration
• PersistentVolumeClaim
• Gateway
• HTTPRoute
• HorizontalPodAutoScaler
• PodDisruptionBudget
• NetworkPolicy
• Log
• GatewayClass
Active filters Unused filters

Summary
• k8sGPT improves debugging experience with Kubernetes by scanning and finding issues,
also provides possible solutions in simple language
• Supports multiple backends
• Integrations allows extensions to external tools and services
• Remote Caching helps to store and retrieve frequently accessed data
• Automate k8sGPT related activities using Kubernetes operator

References
https://www.youtube.com/@nilesh-gule
https://github.com/k8sgpt-ai/k8sgpt
https://docs.k8sgpt.ai/
https://landscape.cncf.io/

Nilesh Gule
ARCHITECT | MICROSOFT MVP
“Code with Passion and
Strive for Excellence”
nileshgule @nileshgule Nilesh Gule
NileshGule
www.handsonarchitect.com
https://www.youtube.com/@nilesh-gule

Source Code & slide deck
Cloud Native Ninja
https://github.com/NileshGule/cloud-native-ninja
https://speakerdeck.com/nileshgule/
https://www.slideshare.net/nileshgule/

This document discusses continuous integration and continuous deployment (CI/CD) with Docker and Kubernetes. It begins with an introduction to the presenter and an overview of previous parts of an AKS learning series. The document then covers CI/CD topics like building pipelines in Azure DevOps, deploying containers to an AKS cluster using kubectl and Helm, and references additional resources. Code demonstrations are provided for CI with Build Pipelines, continuous deployment to AKS with kubectl and Helm, and a release pipeline.

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Slidedeck is related to the presentation done for Azure Singapore user group about Monitoring Kubernetes with Prometheus and Grafana on 19 August 2021. Covered Prometheus Architecture, installation using Prometheus operator, Service Monitor, Pod Monitor, Alert rules. Live demo included Prometheus and Grafana integrations for Spring Boot and .Net Core application. Monitoring for infrastructure / messaging platforms using RabbitMQ is also covered. Youtube video recording - https://youtu.be/t8uenUoI4Mw https://www.meetup.com/en-AU/mssgug/events/279925499

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The document discusses Apache Spark, a unified analytics engine for large-scale data processing. It introduces .Net for Apache Spark, which provides .Net language bindings for Spark. It also mentions using the MovieLens dataset with Spark on Azure Synapse Analytics. Key components of Spark include RDDs, DataFrames, SparkSession, and transformations/actions. The document provides an overview of Spark and demonstrates it through a movie recommendation example on Azure Synapse Analytics.

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Cloud, Containers, Kubernetes (YOW Brisbane 2018)bridgetkromhout

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Cutting the Kubernetes Monorepo in pieces – never learnt more about gitStefan Schimanski

Kubernetes uses a monorepo approach for development and testing. For Golang vendoring by 3rdparties we publish subdirectories as separate Github repositories (like k8s.io/client-go, k8s.io/apimachinery, k8s.io/api, etc.) continuously every night, while keeping all history, all Github merge commits and while rewriting commits with Godep-save updates to express dependencies. Sounds easy? It's not! Implementing this was the best learning experience of git and git internals and the topic of this talk.

Portable Multi-cloud Microservices with Dapr .pdfNilesh Gule

In graph we trust: Microservices, GraphQL and security challengesMohammed A. Imran

In graph we trust: Microservices, GraphQL and security challenges - Mohammed A. Imran Microservices, RESTful and API-first architectures are rage these days and rightfully so, they solve some of the challenges of modern application development. Microservices enable organisations in shipping code to production faster and is accomplished by dividing big monolithic applications into smaller but specialised applications. Though they provide great benefits, they are difficult to debug and secure in complex environments (different API versions, multiple API calls and frontend/backend gaps etc.,). GraphQL provides a powerful way to solve some of these challenges but with great power, comes great responsibility. GraphQL reduces the attack surface drastically(thanks to LangSec) but there are still many things which can go wrong. This talk will cover the risks associated with GraphQL, challenges and solutions, which help in implementing Secure GraphQL based APIs. We will start off with introduction to GraphQL and its benefits. We then discuss the difficulty in securing these applications and why traditional security scanners don’t work with them. At last, we will cover solutions which help in securing these API by shifting left in DevOps pipeline. We will cover the following as part of this presentation: GraphQL use cases and how unicorns use them Benefits and security challenges with GraphQL Authentication and Authorisation Resource exhaustion Backend complexities with microservices Need for tweaking conventional DevSecOps tools for security assurance Security solutions which works with GraphQL

DevSecCon Singapore 2018 - in graph we trust By Imran MohammedDevSecCon

The document discusses using GraphQL to retrieve data from the GitHub API to build a secret scanning tool. It provides an example of using the GitHub REST API to get a list of repositories, which returns a large amount of nested JSON data in one request. It then suggests using GraphQL could retrieve the same data through multiple targeted requests to get 1) a list of repositories, 2) list of branches for a repository, 3) scan the code in a branch, and 4) analyze for secrets, in a more efficient manner.

Put iOS and Android on the same Wavelength with Serverless MicroservicesNeil Power

This was a talk presented at AnDevCon in Washington DC, July 2017. For products that are delivered on the Web, iOS and Android, there have been myriad approaches to reducing development time and the duplication of work. Sharing code between major platforms has, in some ways, felt like the search for the holy grail - hope remains, but as of today, has yet to be found. As long as there have been multiple platforms, there has been a desire to write once, deploy everywhere. In this class, we will look at accelerating cross-platform development by harnessing serverless microservices. At Hootsuite, our serverless experiment uses AWS Lambda functions. This class will cover the motivations of using AWS Lambda compared with other mobile cross-platform solutions. We will also examine the benefits and drawbacks of this approach to cross-platform development. Lastly, you will learn how Hootsuite worked to automate the deployment and versioning of its AWS Lambda function, including its integration it into our existing continuous integration pipeline. We also share the lessons learned after having an AWS Lambda deployment on iOS and Android running for many months as well as the experimentation with Amazon API Gateway to create an endpoint which invokes the Lambda function, enabling the function to be used by our web-based products as well.

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