Blog topic
Practical AI-for-Kubernetes writing: intent compilers, plan gates, and honest product limits. 39 articles.
Muhtalip Dede7 min readHow to compose kprompt with kagent without collapsing the layers: kagent hosts Agents-as-CRDs via MCPServer / RemoteMCPServer; kprompt ships read/plan-only MCP tools that return a typed PlanResult and never auto-apply. Validated against kagent quickstart + first MCP tool docs.
Muhtalip Dede5 min readkagent (CNCF Sandbox / Solo.io) is a Kubernetes-native agent runtime — Agents as CRDs, MCP, A2A, mesh. kprompt is an AI Runtime for cluster ops: PlanResult → approve, plus Observe notify. Is kprompt a kagent alternative? Only for the ops job — decision guide.
Muhtalip Dede4 min readUse kprompt against GKE the same way you use kubectl — get-credentials, aliases, plan-before-apply — plus Gemini BYOK. Optional Observe agent on the cluster; no Marketplace SaaS, no kubeconfig upload.
Muhtalip Dede4 min readUse kprompt against Amazon EKS the same way you use kubectl — update-kubeconfig, aliases, plan-before-apply — plus Ollama or cloud BYOK. Optional Observe agent on the cluster; no Marketplace SaaS, no kubeconfig upload. Native Bedrock preset still deferred.
Muhtalip Dede3 min readLooking for a kagent alternative? Map by job: kprompt for plan-before-apply day-2 + Observe notify, kubectl-ai for NL kubectl REPL, K8sGPT for diagnosis, ARK for agent apps as CRDs — plus when to keep CNCF kagent.
Muhtalip Dede4 min readagentgateway (Linux Foundation) is an AI-native proxy for LLM, MCP, and A2A traffic on Gateway API. kprompt is an AI Runtime for cluster ops: PlanResult → approve, plus Observe notify. Is kprompt an agentgateway alternative? Only for the ops job — decision guide.
Muhtalip Dede3 min readLooking for an agentgateway alternative? Map by job: kprompt for plan-before-apply day-2 + Observe notify, other AI/MCP gateways for LLM traffic policy, kagent for Agents-as-CRDs — plus when to keep Linux Foundation agentgateway.
Muhtalip Dede4 min readUse kprompt against Azure Kubernetes Service the same way you use kubectl — az aks get-credentials, aliases, plan-before-apply — plus Azure OpenAI BYOK or Ollama. Optional Observe agent on the cluster; no Marketplace SaaS, no kubeconfig upload.
Muhtalip Dede4 min readThree Kubernetes AI layers that share vocabulary and confuse buyers: AI Runtime (kprompt PlanResult ops), AI Gateway (agentgateway LLM/MCP/A2A data plane), Agent Platform (kagent Agents-as-CRDs). One hub, honest jobs, deep links.
Muhtalip Dede4 min readkprompt mcp serve exposes read and plan tools to Cursor, Claude Desktop, and other IDE assistants over stdio. Mutations return a PlanResult and never auto-apply. IDE interop, not an agent platform.
Muhtalip Dede2 min readStarting from zero with kind is easy. The real challenge is attaching kprompt to a cluster you already run: bind existing Prometheus, read-first insight, optional MCP — install last.
Muhtalip Dede3 min readWhy unsupervised auto-remediation is not the destination. Observe by default, Autopilot propose-only, reality anchors, and investigate → plan → approve → verify as the load-bearing loop — not a fleet of agents that apply because the model sounded sure.
Muhtalip Dede2 min readRead-only service topology as typed nodes/edges — Ingress, PVC, Secret/ConfigMap names, reverse impact — not a Secret CMDB or chat “who depends on what” folklore. Honest degraded when OTel/mesh are missing.
Muhtalip Dede3 min readNamespace dependency facts that bias Observe without becoming root-cause proof. Local or in-cluster stores — never cloud dumps as fake authority — with AG-034 confidence caps.
Muhtalip Dede3 min readIncident chronology as typed EvidenceRef[], not chat folklore. Events, rollout revisions, and HPA in one Investigation artifact — with honest degraded[] when Prom/OTel/mesh are missing.
Muhtalip Dede4 min readChat is a line; ops is a gated graph. Fan-out where edges are real, independent verify (not same-session soft-agree), PlanResult → approve → verify — without becoming a free-form agent fleet.
Muhtalip Dede10 min readMap of Kubernetes AI / k8s AI tools by job: K8sGPT (and Kubegpt-style searches) for diagnosis, kubectl-ai and kprompt for NL CLIs, Kagent for in-cluster agents — honest mutation contracts included.
Muhtalip Dede3 min readA plain-language map of Kubernetes AI: analyzers like K8sGPT, intent CLIs like kubectl-ai and kprompt, in-cluster agents, and what belongs in CI vs on your laptop — for searches like kubernetes ai, k8s ai, and k8s ai tools.
Muhtalip Dede2 min readPractical shortlist of AI tools for Kubernetes troubleshooting: K8sGPT for scans, intent CLIs for explain/plan, kubectl for evidence — with an honest mutation checklist.
Muhtalip Dede1 min readWhat “chat with your Kubernetes cluster” means in practice: local NL CLIs, hosted consoles, and analyzers — and how to keep credentials and apply behind a human gate.
Muhtalip Dede2 min readHow to use AI on Kubernetes Pods safely: explain CrashLoopBackOff and ImagePullBackOff with kubectl, K8sGPT, or an intent CLI — without piping model output straight into apply.
Muhtalip Dede2 min readBest kubectl-ai alternatives by job: kprompt for gated PlanResult, K8sGPT for diagnosis, Kagent for in-cluster agents — plus when kubectl-ai is still the right REPL.
Muhtalip Dede1 min readPeople searching Kubegpt usually mean K8sGPT — the analyzer-first Kubernetes AI tool. How it differs from kubectl-ai and plan-before-apply CLIs, and when each job fits.
Muhtalip Dede4 min readMcKinsey’s ARK is an Agentic Runtime for Kubernetes — CRDs to run agent apps on the cluster. kprompt is an AI Runtime that reasons about the cluster under plan → approve. Same word “runtime,” different jobs. Decision guide.
Muhtalip Dede4 min readWhy kprompt’s category is an AI Runtime for Kubernetes: observe, reason, plan, approve, execute, learn — not a ChatGPT wrapper, chatbot, or silent auto-healer. Honest shipped vs building.
Muhtalip Dede4 min readFor Kubernetes AI, clever prompts lose to curated context: live cluster facts, tool detection, local history, and a typed PlanResult. Why the next leap is what you feed the model — not how you word the sentence.
Muhtalip Dede3 min readAI SRE across kubeconfig contexts: single-context default, explicit read fan-out, per-context mutate approval, aliases, and why we refuse silent fleet --approve or uploading cluster credentials.
Muhtalip Dede3 min readBoth turn English into Kubernetes actions on your laptop. kubectl-ai optimizes for kubectl fluency and agentic chat; kprompt compiles intent into a gated PlanResult — plan, safety, approve — then apply. Decision guide for operators choosing an AI Kubernetes CLI.
Muhtalip Dede2 min readPolicy is code, not LLM vibes. How kprompt’s safety engine hard-denies wipe-class intents, scores risk, forces approval, and why fail-closed is the load-bearing wall of AI SRE.
Muhtalip Dede3 min readPlanResult is the IR of AI SRE: one typed document for humans and CI. Why JSON, what applied means vs verify, how blastRadius attaches, what never gets stored, and how investigate/why must extend the same artifact.
Muhtalip Dede3 min readKubernetes deserves a compiler, not a chatbot. How kprompt turns natural language into Intent → Actions → PlanResult, why Go owns planning and safety, and why the IR must stay reviewable for AI SRE.
Muhtalip Dede3 min readAI kubectl is not enough. Production needs investigate, why, blast radius, and verify — still behind an approval boundary. Why the AI SRE category exists, what failed in classic AIOps, and what we ship first.
Muhtalip Dede2 min readA long-form series on building an AI SRE under an approval boundary — intent compiler, PlanResult, safety, multi-context, investigation, and why we refuse unsupervised auto-remediation. Episode index and honesty rules.
Muhtalip Dede3 min readSchema-focused companion to CI plan gates: apiVersion, plan.actions, risk.denied, result payloads, RouteResult / MultiContextResult, history vs CI artifacts, and hard rules on manifests and API keys.
Muhtalip Dede2 min readHow kprompt’s shipped optimize report works: inventory, Prometheus-backed idle and rightsizing findings, HPA hints, JSON output, and optional follow-up scale/patch plans that still require their own approval. What it is not.
Muhtalip Dede3 min readNatural language → plan → approve is the wedge. The differentiator is thinking about the cluster — investigate, why, timeline, blast radius, verify — still under the same approval contract. Honest shipped vs building vs exploring.
Muhtalip Dede4 min readWhy we compile natural language into a gated PlanResult instead of racing kubectl-ai on agentic chat — same NL CLI lane, different contract: typed plans, hard denies, CI JSON, multi-tool day-2 under one approval loop.
Muhtalip Dede5 min readCompare Gemini, OpenAI, Anthropic, Groq, and Ollama for Kubernetes CLI workflows with kprompt — BYOK keys, air-gapped setups, model speed vs explain quality, and security rules for operators.
Muhtalip Dede6 min readLarge language models change how operators talk to clusters — but they don't replace kube-apiserver truth. A practical map of AI + Kubernetes: use cases, failure modes, and why plan-before-apply matters.