# Cloudcraft vs Hava vs Cloudeval AI: which diagram tool, when? > **TL;DR:** Cloudcraft, Hava and Cloudeval AI all draw cloud diagrams, but they answer different questions. Cloudcraft designs diagrams and, inside Datadog, shows live infrastructure with ops overlays. Hava auto-documents connected AWS, GCP and Azure accounts with version history and change alerts. Cloudeval AI reviews an Azure ARM or compiled Bicep change in the pull request, before deployment. *By Prateek Singh, founder of Ganak AI Labs. Updated 6 October 2026.* "Which cloud diagram tool should we use?" usually gets answered with a feature checklist. That's the wrong frame. Tools that all draw a nice picture often solve different problems. A better split is the three questions teams ask, at three different times: 1. **"What does it look like?"** You're designing, presenting or onboarding someone. 2. **"What's running, and what changed?"** You're documenting, auditing or debugging the live estate. 3. **"Is this change safe to ship?"** A pull request is open and nothing is deployed yet. That third job is pre-deployment review: checking a change's design, cost and security before it ships. Cloudcraft, Hava and Cloudeval each lean toward a different question. *Disclosure: I'm the founder of Cloudeval. The Cloudcraft and Hava sections stick to what their own sites say, with links. Prices change, so check before you buy.* ## What is Cloudcraft best for? Design and live diagrams in Datadog Cloudcraft is now part of Datadog and comes in two forms. **Cloudcraft in Datadog** is a live, read-only view of AWS, Azure, GCP, OCI and vSphere resources ([Datadog docs](https://docs.datadoghq.com/datadog_cloudcraft/)). You can switch overlays for infrastructure, observability, security, cloud cost and APM (AWS only, preview). The [Cloudcraft homepage](https://www.cloudcraft.co/) pitches alerts, logs, security findings and costs on a diagram that updates as your infrastructure changes. Some overlays need other Datadog products, such as Cloud Security for the security overlay. It's free with any Datadog subscription ([pricing](https://www.cloudcraft.co/pricing)). **Cloudcraft (Standalone)** is a diagramming tool for AWS and Azure, with 3D views of your environments ([docs](https://docs.datadoghq.com/cloudcraft/)). Two features stand out for design work: * **Live and snapshot diagrams.** A live diagram updates from your account. A snapshot is static and fully editable, and you can add components from the Design tab ([docs](https://docs.datadoghq.com/cloudcraft/getting-started/live-vs-snapshot-diagrams/)). * **Blueprints**, which hold "your diagram, a budget, and all the documentation you attach to individual components" ([docs](https://docs.datadoghq.com/cloudcraft/getting-started/create-your-first-cloudcraft-diagram/)). Connecting an Azure account to standalone Cloudcraft needs a Pro subscription ([docs](https://docs.datadoghq.com/cloudcraft/getting-started/connect-azure-account-with-cloudcraft/)). **Where it shines:** whiteboard-quality design diagrams, budgeting a proposed architecture and, on Datadog, ops context on the live picture during incidents. ## What is Hava best for? Auto-generated diagrams and drift alerts [Hava](https://www.hava.io/) connects to your AWS, GCP and Azure accounts and generates interactive diagrams "grouped by VPCs or resource zones." Its homepage lists: * A **security view** of security groups, route tables and connections, to help catch public access to internal services and overly permissive rules. * **Cost forecasts** by VPC, region, instance, tag or project. Hava says plainly that it "isn't a replacement for billing platforms." * **Versioning.** Hava polls your cloud config, archives old diagram versions and lets you compare them over time. * **Alerts** when infrastructure changes. * Exports to Visio, PNG, CSV or JSON, embeddable diagrams and a self-hosted option. For automation, Hava publishes a GitHub Action, [`teamhava/hava-sync-action`](https://github.com/teamhava/hava-sync-action), to "synchronize and export a diagram after you have deployed changes to your environment". It writes a PNG to your repo. Every [Hava plan](https://www.hava.io/pricing) includes unlimited diagrams, daily sync and 3, 6 or 12 months of history. The two-week trial includes Teams features, with exports off. **Where it shines:** always-current documentation of what's deployed across several clouds, with history and drift alerts. ## What is Cloudeval AI best for? Reviewing a change before deploy Cloudeval can start from the template in your pull request instead of a connected account, before anything is deployed. ![Cloudeval Quick Project Creation dialog importing a GitHub-hosted ARM template URL, with stages for connection, file import, stack resolution and diagram and report generation](https://mintcdn.com/ganakailabs-db727e50/vC9eAljPn_70oJmO/assets/images/projects/github-url-consumption-progress-light.png align="center") *Importing a GitHub-hosted ARM template into a project.* * **Inputs:** ARM JSON, Bicep compiled to ARM JSON, and AWS CloudFormation JSON or YAML as a static beta. For what's already running, live Azure comes in through Cloud sync with a least-privilege, resource-group-scoped custom role ([support matrix](https://docs.cloudeval.ai/trust/supported-clouds-and-iac?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=support)). There's no live AWS or GCP connection. * **Output:** architecture and dependency views, cost estimates, Well-Architected and validation results, and findings tied to the affected resource. Findings draw on 1,650+ checks. Not every project runs every check, and unsupported areas show as `Not assessed` instead of passing silently. * **In the PR:** a GitHub Action posts one result comment. It can fail the job on thresholds you set for Well-Architected score, high-risk findings, validation and monthly cost. * **Handoff:** the CLI exports diagrams as PNG, JPEG or SVG, which also works for CI or agents. ![Cloudeval cloud evaluation report overview with posture score, critical risk count, run-rate cost, savings, maturity score and priority decisions](https://mintcdn.com/ganakailabs-db727e50/Q5sxR4Wz8SD3FHrz/assets/images/reports/cloud-evaluation-overview.jpeg align="center") *Posture, critical issues, cost and priorities on one screen.* It isn't a freeform design canvas, an observability overlay or a multi-cloud live inventory. PR diagram diffs and snapshot drift comparison are planned, not shipped yet ([interfaces and workflows](https://docs.cloudeval.ai/trust/interfaces-and-workflows?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=roadmap)). **Where it shines:** the gap between "the template is valid" and "the template is deployed", when a reviewer wants the shape, cost and risk of a change. ![Cloudeval architecture view with issue badges, dependency labels, cost status and project-aware AI chat](https://mintcdn.com/ganakailabs-db727e50/Q5sxR4Wz8SD3FHrz/assets/images/workspace/ai-chat-architecture-preview.jpeg align="center") *Architecture view with issue badges, dependency labels and cost status.* The difference is the link from a finding to what it affects. This 48-second clip shows it: %[https://www.youtube.com/watch?v=ozl0jQhoXqM] ## How do Cloudcraft, Hava and Cloudeval AI compare? This maps what each tool is built for, from each vendor's own description. It's not a scorecard. | | Cloudcraft | Hava | Cloudeval | | --- | --- | --- | --- | | Primary question | What does it look like? What's happening now (in Datadog)? | What's deployed, and what changed? | Is this change safe to ship? | | Starts from | Connected accounts (live) or a hand-built design (snapshot) | Connected cloud accounts | A template in a PR, or a live Azure sync | | Providers (per vendor) | In Datadog: AWS, Azure, GCP, OCI, vSphere. Standalone: AWS, Azure | AWS, GCP, Azure | Azure, plus AWS CloudFormation (beta) | | Design and editing | Snapshot diagrams, Design tab, blueprints with budget | Not the focus of its main pages | Markup on generated diagrams, not a freeform canvas | | Change over time | Diagram version history | Version history, diagram comparison, change alerts | Per-commit PR reviews. Drift and graph diff are planned | | Cost | Blueprint budgets, Cloud Cost overlay in Datadog | Cost forecasts | Monthly cost estimate and an optional budget gate in the PR | | Security signal | Security overlay (needs Datadog Cloud Security) | Security view of groups, routes and exposure | Findings with evidence from 1,650+ checks | | CI/CD | Not covered here | GitHub Action and CLI to sync and export after deploy | GitHub Action that comments and gates before merge | | Pricing (per vendor page) | Free with any Datadog subscription | From $59/month | Free 7-day trial (150 credits), Basic $19/month, Pro $49/month | ![Cloudeval report treemap grouping findings by resource type, with Virtual Machines, Storage Accounts, Load Balancers and Virtual Networks as the largest tiles](https://mintcdn.com/ganakailabs-db727e50/7G2QBGQbVygbrIBs/assets/images/reports/report-current-treemap.png align="center") *The treemap shows where findings cluster by resource type.* ## Can you use Cloudcraft or Hava with Cloudeval AI? Yes, and that's often the most practical setup. This pipeline reviews on the pull request, then refreshes documentation diagrams after deploy. ```yaml # .github/workflows/infra.yml (sketch: wire in your own deploy job) on: pull_request: push: branches: [main] permissions: contents: read pull-requests: write issues: write jobs: pre-deploy-review: # Question 3: is this change safe to ship? if: github.event_name == 'pull_request' runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: ganakailabs/cloudeval-action@v1 with: access_key: ${{ secrets.CLOUDEVAL_ACCESS_KEY }} project_id: ${{ secrets.CLOUDEVAL_PROJECT_ID }} mode: review post_pr_comment: true upload_artifacts: true # deploy: ... # your existing deployment job refresh-docs-diagram: # Question 2: what's deployed now? if: github.event_name == 'push' # needs: deploy runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: teamhava/hava-sync-action@v1 with: source_id: ${{ secrets.HAVA_SOURCE_ID }} hava_token: ${{ secrets.HAVA_TOKEN }} environment_id: ${{ secrets.HAVA_ENVIRONMENT_ID }} view_type: infrastructure image_path: docs/architecture.png # commit docs/architecture.png in a follow-up step if you want it in the repo ``` The Cloudeval job needs the repo linked through the Cloudeval GitHub App. The Hava job needs a connected Hava source. On Datadog, Cloudcraft's live diagram replaces the second job, outside CI entirely. ## Which cloud diagram tool should you choose? Ask these in order: 1. **Designing something new and presenting it?** Cloudcraft's snapshot diagrams and blueprints. 2. **Already paying for Datadog?** Cloudcraft in Datadog is included. 3. **Need always-current docs and change history across AWS, GCP and Azure?** That's Hava's core pitch. 4. **Changes reach production through pull requests, and nobody checks design, cost and exposure there?** That's the gap Cloudeval targets. Some teams answer "yes" to two. That's fine, because the tools mostly don't compete for the same moment. ## Frequently asked questions ### What is a good Cloudcraft alternative for Azure? It depends on the job. Hava is built for always-current documentation and change history of deployed Azure, AWS and GCP accounts. Cloudeval AI reviews an Azure ARM or compiled Bicep change in a pull request before it ships. See the longer [Cloudcraft alternative for Azure pre-deployment review](https://cloudeval.ai/compare/cloudcraft-alternative?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=faq). ### Does Cloudcraft support Azure? Yes. Per Datadog's docs, Cloudcraft (Standalone) covers AWS and Azure, and connecting an Azure account needs a Pro subscription. Cloudcraft in Datadog covers AWS, Azure, GCP, OCI and vSphere. ### Is Cloudcraft free? Cloudcraft's pricing page says it's free with any Datadog subscription, with unlimited users and diagrams. Standalone Cloudcraft has Free, Pro and Enterprise plans, and connecting Azure needs Pro. ### How much does Hava cost? Hava's pricing page lists Professional at $59/month (3 cloud accounts, 1 user), Teams at $249/month (10 accounts, unlimited users) and custom Enterprise pricing. Check the page before you buy, because pricing changes. ### Can you use a diagram tool and a pre-deployment review tool together? Yes. They run at different moments: review the change on the pull request, then refresh documentation diagrams after deploy. The workflow sketch above runs both from one GitHub Actions file. ## Takeaway "Cloud diagram tool" covers at least three jobs: designing, documenting what's live and reviewing a change before it ships. Pick the tool by the question you need answered, and when. A diagram of production won't warn you a PR is about to double the bill. A PR gate won't help you whiteboard next quarter. If pre-deployment review is the missing piece, read the criterion-by-criterion [comparison of Cloudcraft and Cloudeval for Azure pre-deployment review](https://cloudeval.ai/compare/cloudcraft-alternative?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=cta). **Related on cloudeval.ai** * [Compare Cloudeval with other cloud review and diagram tools](https://cloudeval.ai/compare?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=related-compare-hub) * [Hava.io alternative for reviewing Azure changes before deployment](https://cloudeval.ai/compare/hava-io-alternative?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=related-hava) * [Lucid Cloud Accelerator alternative for Azure pre-deployment review](https://cloudeval.ai/compare/lucidscale-alternative?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=related-lucid) * [How to generate an Azure architecture diagram automatically](https://cloudeval.ai/answers/how-to-generate-azure-architecture-diagram?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=related-diagram) > **Try it** > > Want to see a template as a reviewed diagram before it ships? Open the [Cloudeval app](https://cloudeval.ai/app?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=try-app) and follow the [diagrams and workspace views guide](https://docs.cloudeval.ai/guides/results/diagrams?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=try-docs). > **About the author** > > **Prateek Singh** is the founder of Ganak AI Labs and builds Cloudeval AI. > > [cloudeval.ai](https://cloudeval.ai/?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=author) | [Docs](https://docs.cloudeval.ai/?utm_source=hashnode&utm_medium=referral&utm_campaign=diagramming-vs-predeploy&utm_content=author) | [YouTube](https://www.youtube.com/@GanakAILabs) | [GitHub](https://github.com/ganakailabs) | [LinkedIn](https://www.linkedin.com/in/prateekkumarsingh/)