Quickstart

Fastpath >>>>>

The shortest path to querying your logs with an AI assistant: create a source, assign its streams to a workspace, and connect your assistant via MCP. Use the Dstl8 CLI to on-board at warp speed.

Terminology

• Source — A connection to a platform you want to pull logs from (e.g. an AWS account's CloudWatch, a Kubernetes cluster). You can add multiple sources of the same type with different credentials.

• Stream Type — A kind of log stream produced by a source, e.g. a CloudWatch Lambda log group, or a Kubernetes Deployment or DaemonSet.

• Stream — A specific instance of a stream type, e.g. one Lambda function or one pod.

• Workspace — A boundary that controls user and data access. Streams are assigned to workspaces to make them queryable. Every organization starts with a Default workspace.

1. Create a source and validate streams

Pick a platform and add it as a source:

• AWS CloudWatch — if your logs live in CloudWatch Log Groups.

• Kubernetes — install the in-cluster agent to collect container logs and cluster events.

• Other sources (Vercel, Supabase, OTLP, GitHub) — see Sources.

New sources start as Pending. Within a couple of minutes the source should transition to Healthy and streams will appear with their inferred stream types.

Validate: expand the source card on the Sources page — you should see streams listed under STREAMS. If nothing appears after a few minutes, re-run Test Connection from the source's actions menu (gear icon).

2. Assign streams to a workspace

Streams must be assigned to a workspace before they're queryable. Every organization starts with a Default workspace — the fastest path is to assign everything to it.

1. On the source card, open the actions menu (gear icon) and select Assign Streams.

2. Check the Default workspace to assign all streams from this source, or drill in to select specific Stream Types or individual streams.

3. Click Save.

The source card now shows 1 workspace receiving streams.

For splitting streams across multiple workspaces (e.g. prod vs staging), see Assigning streams to workspaces.

3. Connect your AI assistant via MCP

Dstl8 exposes an MCP endpoint per organization that lets Claude (or any MCP-compatible assistant) query your logs, incidents, and anomaly tools directly.

1. In Org Settings → Organizational Info, copy your MCP endpoint — it looks like https://<org_id>.app.dstl8.ai/mcp.

2. In Org Settings → API Tokens, create an API token and copy it (it's only shown once).

3. Configure your client. Per-client setup guides:

   • Claude Code

   • Claude Desktop

   • Cursor

   • Codex

   • ChatGPT

Full reference: MCP Integration.

4. Ask a question

From your configured assistant, try:

• "What's going on in production?"

• "Any anomalies in the last hour?"

• "Summarize recent errors across my streams."

If you get a grounded answer referencing your actual services and log patterns, you're set.