Dashboard tour

Once a billing source is connected, the dashboards are where you read your spend. This page tours the main views so you know where to look for what.

The CloudQuell all-sources Overview dashboard, showing total spend, forecast, savings and anomaly KPIs, top movers, and a daily cumulative cost comparison chart.

The sidebar is organized into three groups: Dashboards at the top, Insights (the analysis views — Reports, Savings, Commitments, Anomalies, Tags, Alerting), and Manage (org-wide configuration — Allocation, Budgets, Cost centers). A scope picker at the top of each view selects the provider and integration the view reads from, and it stays put as you move between views. A Cost view control in the same bar switches every source to one cost basis — credits, taxes, or amortization — for the session; by default each integration keeps its own cost settings.

The Dashboards menu adapts to what you have connected. With one kind of source it goes straight to that dashboard; once your sources span more than one category — cloud platforms, AI platforms, or a data warehouse — it leads with an org-wide Overview, groups providers under clickable category headers (Cloud, AI), and lists each provider beneath.

The Overview (all sources)

When your organization has more than one category of source connected, landing on the dashboard opens the Overview — every connected source in one ledger roll-up. It surfaces:

Total spend (MTD) — across every source, compared to the same days last month, with a forecasted month-end.
AI platforms share — what portion of total spend is direct Anthropic / OpenAI platform usage.
Sources — how many sources are connected, with a “data through” freshness stamp per source.
Monthly and daily cost by source — stacked charts, one color per provider; click a segment to open that provider’s own dashboard.
Top services across sources — the biggest line items this month, labeled Provider · Service.

Spend that your cloud provider bills — like Claude on AWS Bedrock, Azure OpenAI, or Gemini on Vertex AI — counts as cloud spend here (it’s on your cloud invoice), so every number reconciles against the bills you actually receive. Bedrock, Azure AI Foundry, and Gemini / Vertex AI are also visible in the AI Spend view below, as a lens over those same cloud rows — shown there for comparison, never counted a second time.

The Cloud dashboard

The Cloud dashboard — opened from Dashboards (or automatically as your landing view when cloud is your only source category) — is the home of your day-to-day cloud cost picture. At organization scope it combines every connected cloud provider (AWS, Azure, Google Cloud); pick a provider in the Dashboards menu or the scope picker to focus on one. It’s available on every tier and pulls from the single cost ledger. It surfaces:

KPIs — headline numbers, including month-to-date spend versus the previous month.
Spend trend — how spend is tracking over time, so you can see direction at a glance.
Top movers — the services (and accounts) whose spend changed most, so the biggest swings surface first.
Per-account breakdown — spend rolled up by each linked account or subscription.

The AI platforms dashboard

With an Anthropic or OpenAI integration connected — or with Amazon Bedrock, Azure AI Foundry, or Gemini / Vertex AI usage on your cloud bill — Dashboards also offers the AI Spend view: token-level cost by model, token type (including cache reads and writes), workspace/project, API key, and service tier. With more than one AI source it opens on All AI with a per-source split; the buttons narrow to one source.

Cloud-billed AI appears here as a lens, not as an integration. Three sources are billed by your cloud, so their rows already live in your cloud spend and are counted there exactly once:

Bedrock — Amazon Bedrock, from your AWS bill: by model, token type, tier, routing, linked account, region and tag.
Azure AI Foundry — Azure OpenAI, the other models Microsoft sells through Foundry (DeepSeek, Grok, Llama, Mistral, Phi, Microsoft MAI), and Claude bought through Azure Marketplace, from your Azure bill: by model, model developer, token type, deployment type, tier, subscription, region and day. Provisioned throughput (PTU) and Marketplace Claude show as their own buckets, not per model.
Gemini / Vertex — Google Gemini / Vertex AI generative usage (Gemini, Claude and other Model Garden models, Imagen, Veo, embeddings, grounding, provisioned throughput), from your GCP bill: the same breakdowns, by project and serving scope. Gemini 1.x / PaLM-era usage shows dollars but no token counts.

The AI Spend view reads those same rows so you can see them beside your direct Anthropic and OpenAI usage. Nothing is ingested twice, and there is nothing to connect: each button appears on its own once your cloud bill shows that usage (and only if your plan includes that cloud). Non-model services — Azure Speech, Translator and Vision, or Vertex AI training, notebooks and Vector Search — stay in cloud spend only. Because those dollars sit on your cloud invoice, the All AI total is an analytical figure and is never added to cloud spend. Selecting a cloud-billed source, or All AI while it includes one, disables the scope picker — the cloud-billed half spans every connected account, subscription and project, and a total that narrowed only its direct half would be a half-truth. To narrow Azure AI Foundry or Gemini / Vertex, use the Subscription or Project filter instead; or pick a single direct provider to narrow again.

Two numbers to read carefully:

Effective $ / 1M tokens divides only the spend that actually bought tokens. Non-token charges — server tools, provisioned capacity, guardrails — are in the total but not in that rate, and a note tells you how much of the spend the rate covers.
Data through dates a blended figure by its oldest source. Cloud billing data settles a day or two behind the direct provider APIs, so an All AI total is complete through the cloud-billed side’s last day; later days are partial, not missing.

For the full reporting surface — pivoting by product family, usage type, or tag, and saving or exporting a view — head to Reports under Insights in the sidebar (see Cost reporting).

Where everything else lives

Each sidebar entry goes deeper on one part of FinOps.

Under Insights:

Reports — build detailed pivot reports, save them, and export to CSV. See Cost reporting.
Savings — rightsizing, idle-resource, and commitment recommendations with dollar estimates. See Savings.
Commitments — Reserved Instance and Savings Plan utilization and upcoming expiries. See Commitments.
Anomalies — spot unusual month-over-month and week-over-week swings and investigate the drivers. See Anomalies.
Tags — how much of your spend carries cost-allocation tags, and where the gaps are. See Tag coverage.
Alerting — rules and notification channels that push cost and budget events to Slack, Microsoft Teams, or email. See Alerts.

Under Manage:

Allocation — assign spend to cost centers with allocation rules. See Cost allocation.
Budgets — set targets and watch actual-versus-forecast pace against them. See Budgets.
Cost centers — define the cost centers that allocation assigns spend to. See Cost centers.

Organization-level administration — settings, members, billing, integrations, notification channels, and cost settings — lives behind the Admin entry at the bottom of the sidebar.

Reading spend with an agent

You can also query all of this in plain language by connecting an AI agent through the CloudQuell MCP server — ask “why did our RDS spend jump last week?” and the agent answers from your live data.