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Debugging K8s With K8sGPT in Your Internal Developer Portal
- AI can be used to proactively identify potential system degradations and provide instant guidance on remediation, which can sometimes cut your average incident resolution time by 50%.
- K8sGPT is an AI agent designed for Kubernetes (K8s) environments that provides quick recommendations, reduces resolution times, and transforms traditionally reactive processes into proactive ones.
- To create an automated workflow to enrich your internal developer portal with a real-time view of failing Kubernetes workloads, you would need to integrate Kubernetes cluster, internal developer portal, K8sGPT, AI LLM, and communication facilitator.
- K8sGPT leverages natural language processing to interpret Kubernetes data and provide actionable recommendations. It currently supports 11 different types of AI backends.
- Using AI to enrich your internal developer portal can help you centrally manage SDLC data and achieve cross-domain insights with potential automated remediation.
- HolmesGPT is another emerging open source AI project that complements and extends K8sGPT's functionality and offers AI-driven insights supporting also Kubernetes and other flexible deployment architectures, along with multiple AI models.
- One of HolmesGPT's standout features is its ability to understand and respond to natural language queries.
- HolmesGPT extends its analytical capabilities to a wide range of platforms and tools, including PagerDuty, OpsGenie, Prometheus, and Jira.
- Ultimately, the goal is to create cross-domain workflows, simplify the troubleshooting process, reduce time-to-resolution, and achieve better service quality.
- Internal developer portals, empowered with AI, can provide refined, contextual information and streamline problem-solving processes, reducing the time it takes to locate issues and figure out how to fix them.
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