All the openness. None of the assembly.

The Assembly Required Problem

Six tools. Six configurations. One observability goal.

• Loki, Tempo, Mimir, Pyroscope, Alloy, Grafana: Grafana ships these as six separate open-source projects, each with its own repository and release train. Self-host and assembling them into one platform is your job.
• Assembly tax: configuration, upgrades, scaling, cross-signal correlation, and on-call for the monitoring system itself.
• Platform engineering bandwidth: for teams that need to ship features, not manage observability infrastructure, the assembly tax is real.
• Self-hosting also reduces the AI, and Grafana says so: "Core chat, dashboarding, querying, and navigation workflows remain available, while Grafana Cloud-dependent features such as investigations, infrastructure memory, and Grafana Cloud MCP connections are hidden" (source, verified 2026-08-19). The open-source path and the full Assistant are not the same product.

What If It Came Assembled?

One platform. Fully managed. Still OTel-native.

• Same commitment to open standards: no proprietary agents, no vendor lock-in. Your OTel instrumentation works with any compatible backend.
• Single, managed platform: traces, metrics, logs, AI, and 3D topology in one product, not six tools you wire together.
• Capabilities dashboards cannot deliver: spatial topology and an AI assistant that fixes code.

Architecture: How We Differ

Unified platform vs composable stack.

DeepCube and Grafana share the same commitment to open standards and OpenTelemetry. The difference is what happens after data ingestion. Grafana gives you the best dashboards in the industry. DeepCube gives you a 3D spatial environment where your services, relationships, and telemetry live together, plus an AI assistant that can diagnose issues and fix your code.

Grafana Cloud is fully managed, and we will not pretend otherwise. The assembly does not disappear, it moves to the invoice: Grafana Cloud is sold as 17 separately priced product lines, each with its own meter and its own free-tier limit, and you decide which ones to turn on (source, verified 2026-08-19). Each meter carries its own independent free limit, for example 50 GB of logs per month, 2,232 Application Observability host hours, 3 active visualization users and 3 active AI users, so the free tiers do not pool. DeepCube is one platform at one per-node price, and there is nothing to select.

AI: Tessa vs Grafana Assistant

Human on the loop.

Tessa connects the telemetry of the environment you are viewing to your connected codebase. Add your repositories as workspaces, and Tessa traces a production issue from the 3D topology straight to the source file, then makes the fix.

Your code stays in your workspace. You review the changes. You commit when ready. Tessa does the work; you own the outcome.

Grafana's equivalent surface holds a different set of things. "Grafana Assistant Workspace is a full-page Assistant experience", and its context picker takes "data sources, labels, metrics, dashboards, entities, and skills" (source, verified 2026-08-19). A repository is not on that list. The one Grafana surface that did reach local files is being retired: "Grafana Assistant CLI is deprecated and will be removed in a future release. Use gcx instead", and its file reach was read-only by design, "Run the tunnel so Assistant can read local project files and, optionally, run approved shell commands on your machine" (source, verified 2026-08-19).

Grafana Assistant helps you write queries, understand anomalies, and investigate incidents within the Grafana dashboard. Valuable for teams who live in Grafana, and Grafana scopes it themselves: "Grafana Assistant brings a purpose-built LLM to Grafana so operators, developers, and SREs can troubleshoot issues, manage dashboards, and answer product questions in minutes" (source, verified 2026-08-19). It does reach a codebase, through the gcx CLI and an MCP server, but Grafana's own pricing FAQ puts the code reasoning on your side of the line: when your own coding agent uses gcx or the Cloud MCP server to query Grafana, "the reasoning happens in your agent's model, and no Grafana AI tokens are consumed" (source, verified 2026-08-19). So when the investigation is done you still context-switch to your IDE to make the fix. On Cloud Pro it costs $20/active AI user/month on top of your existing Grafana costs, with the first 3 users free, and it is included on Grafana Cloud's free plan. Tessa is in the price of every DeepCube plan with no AI seat and no per-user AI charge, and goes from diagnosis to code fix in one conversation.

Pricing: The Full Picture

Scenario: 40 nodes, 10 engineers.

Grafana Cloud's pricing appears transparent, but the multi-dimensional billing model (per-signal, per-user, per-feature) adds up. Here is what a production deployment looks like.

Run Both. Migrate Gradually.

Same telemetry, two destinations, zero re-instrumentation.

• Dual-destination: Your OTel Collector fans out telemetry to both DeepCube and Grafana simultaneously.
• Both platforms are OTel-native: migration is straightforward. Add an exporter, see your data in DeepCube's 3D topology, and decide which experience your team prefers.
• Keep your Grafana dashboards: DeepCube adds spatial topology and AI on top. You do not have to abandon existing dashboards.
• Exit guarantee: If DeepCube is not right for you, change one endpoint URL. Your instrumentation stays exactly the same.