vikshana-graft-app, developed by Vikshana, is a Grafana App Plugin that converts observability signals into plain-English answers for dashboards, metrics, logs, traces, and alerts. It translates natural-language prompts into actionable queries and provides modes for short answers or deeper multi-step troubleshooting. The app includes searchable chat history and a prompt library, integrates with the official Grafana LLM Plugin, and supports both hosted and local model providers. Graft targets DevOps engineers, SREs, and platform analysts who need faster incident triage without mastering PromQL or LogQL.

What tasks can you actually use it for?

Graft enables conversational investigation inside the monitoring UI. The tool accepts natural-language questions and maps them to observability artifacts so teams can check dashboards, fetch metric series, inspect logs, examine traces, and review alerts from a single chat interface. The two interaction modes separate quick lookups from extended troubleshooting sessions, letting engineers switch between concise answers and stepwise analysis during incidents.

How accurate are the outputs for observability work?

Response reliability depends on the chosen language model and query context. The app returns context-aware explanations alongside links to relevant Grafana panels, but the factual correctness of narrative outputs follows the underlying model’s behavior. Teams should validate critical findings against raw panels or queries, because model-generated summaries reflect patterns in the model rather than guaranteed instrumented truth.

What inputs and environment does it require?

The plugin runs inside Grafana and requires specific platform configuration. Installation needs Grafana version 10.4 or later and a configured Grafana LLM Plugin to connect to a model provider. Graft reads the instance’s configured data sources and dashboards, so it operates on whatever metrics, logs, and tracing backends are already present in the monitoring stack.

How it fits team workflows and where it falls short

Graft suits teams that maintain a current Grafana deployment and can manage model selection. Its open-source codebase and support for local inference make it attractive where data locality matters. Community feedback notes practical value for reducing query friction, while teams without a managed LLM or older Grafana versions face integration work before benefits appear.

Graft is a practical option for observability-first teams with a managed Grafana stack

The app suits DevOps and SRE teams that can operate a maintained monitoring platform and select or host an LLM, delivering conversational access that speeds investigation. Expect usefulness to scale with the quality of the connected model and the stability of your dashboards. For mission-critical findings, verify narrative outputs against raw instrumentation and panels rather than relying on generated summaries alone.