OpenOps
A no-code FinOps automation platform that helps organizations reduce cloud costs and automate financial operations, with built-in AI assistance.
- Source repo
- openops-cloud/openops
- Stars
- ★ 1.1k
- Last updated
- today
- License
- NOASSERTION
- Primary language
- TypeScript
- FA score
- 59/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platform
- Cost
- Free tier plus a paid hosted plan
- Setup effort
- Medium · a few setup steps
- You'll need
- Typical use
- FinOps teams that need to safely de-provision idle RDS instances surfaced by visibility tools, with human approval in the loop
- Not a fit if
- Teams with no cloud spend to govern
- Scenarios requiring fully offline operation with no cloud API access
- Source review
- 59/100 · Major gaps
What does this agent do, and when should you use it?
OpenOps is an open-source, no-code FinOps automation platform for reducing cloud costs and streamlining financial operations. It ships with its own Excel-like database (OpenOps Tables) and visualization system (OpenOps Analytics), plus a library of pre-built workflows designed with input from FinOps leaders. Users build or customize workflows in a no-code editor, covering allocation, unit economics, anomaly management, workload optimization, and safe de-provisioning. The platform natively integrates AWS, Azure, and Google Cloud alongside databases, FinOps tools, communication platforms, and project management tools, and provides human-in-the-loop approval controls across multiple channels. It can be deployed either as a vendor-managed cloud service or self-hosted for free via docker-compose; the source is released under the Apache 2.0 license.
OpenOps consolidates optimization opportunities from native and third-party FinOps visibility tools, suggests practical optimization actions, and executes them through workflows. Users orchestrate workflows in the no-code editor, dropping into code when needed; steps can be tested, workflows are versioned, and every action is tracked in logs. Opportunities are logged centrally in OpenOps Tables with support for approvals, dismissals, false-positive marking, and snoozing; critical approvals go through multi-channel human-in-the-loop controls. Results can be visualized in OpenOps Analytics and acted on via integrations with AWS/Azure/GCP, databases, communication platforms, and project management tools.
- FinOps teams that need to safely de-provision idle RDS instances surfaced by visibility tools, with human approval in the loop
- Cloud architects who want reusable, standardized workflows for cost allocation, tagging, budgeting, and reporting
- Engineering, DevOps, finance, and leadership teams that need to collaborate on cost anomalies in one platform
- Enterprises wanting a self-hosted FinOps platform that bundles a Tables database and Analytics visualization
- Ops teams automating cloud cost anomaly handling while retaining human sign-off on critical actions
How do you install or deploy this agent?
OpenOps offers two installation paths:
- Managed cloud service: see https://openops.com/pricing — no infrastructure required.
- Free self-hosted installation (docker-compose-based), installable locally or in the cloud, per the official quick start guide:
bash
# See the official Quick Start Guide
# https://docs.openops.com/getting-started/quick-start-guideThe Quick Start Guide documents the complete docker-compose installation steps; the README itself does not embed the concrete install commands, so follow the official guide.
How do you use this agent?
Once installed and running, use the OpenOps web interface:
- Connect your cloud account (AWS, Azure, or Google Cloud) plus any third-party FinOps tools, communication platforms, and project management tools you need.
- Pick templates from the pre-built FinOps workflow library (cost optimization, tagging, budgeting, allocation, reporting) or build from scratch in the no-code editor, dropping into code as needed.
- Test workflow steps, maintain versions, and trace every action via logs.
- Manage opportunities centrally in OpenOps Tables (approve, dismiss, mark false positive, snooze) and view results in OpenOps Analytics.
Full documentation: https://docs.openops.com/.
What are this agent's strengths and limitations?
- Bundled OpenOps Tables database and OpenOps Analytics visualization — no separate reporting stack to buy
- Pre-built workflow library designed with input from FinOps leaders, covering optimization, tagging, budgeting, allocation, and reporting
- Human-in-the-loop approval controls across multiple channels, suited to safe cloud resource changes
- Flexible deployment: self-host via docker-compose or use the managed cloud
- Workflow versioning, step testing, and full action logs for audit and traceability
- Self-hosting relies on docker-compose, so you maintain a multi-container deployment
- Cloud integrations span AWS/Azure/GCP, but the source doesn't detail the exact permission and credential setup required
- The managed cloud is a paid plan with premium support and SLAs; the free route leaves operations to you
- The GitHub license field is NOASSERTION even though the README states Apache 2.0 — worth verifying
- Strong workflow customizability means teams must invest effort in designing and maintaining workflows
How does this agent compare with similar options?
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| OpenOps This agent | 59 · Major gaps | Self-hosted serviceFreemium | ★ 1.1k | today | TypeScript | — |
| Auto Browser | 62 · Some gaps | Self-hosted serviceFree + model costs | ★ 793 | 3d ago | Python | OpenAI API · Claude API |
| Flow-Like | 55 · Major gaps | Desktop appFreemium | ★ 960 | 7d ago | Rust | — |
| Budibase | 52 · Major gaps | Self-hosted serviceFreemium | ★ 28k | today | TypeScript | — |
How does FollowAgents rate this agent?
Why each dimension lost points
README explicitly advertises HITL approvals, workflow versioning and action logs (+), but these are promotional claims without code evidence in the provided files; package. shows pinned dependency versions plus overrides patching known vulnerable transitive deps (+), yet the dependency surface is very large (AI SDKs, cloud SDKs, ssh2-sftp, isolated-vm), implying a broad permission footprint. No AGENTS.md or data-flow/secret-handling docs; sensitive-data handling and attribution rest on README claims only — deducted.
Consistent Nx monorepo, complete scripts (dev/start/build), and real unit tests (ai-step, Anodot properties) including a fallback from structured generation to generateText, showing failure-handling awareness; only a handful of test files are visible, so overall coverage cannot be assessed — deducted. Dependencies delivered via lockfile and docker-compose; availability adequate.
Audience and scenarios are well defined (FinOps teams, cloud cost optimization across AWS/Azure/GCP) with multi-channel HITL (+); but trigger precision and capability boundaries (which actions require confirmation, how LLM output is constrained) are not documented in the provided files — deducted.
Full Apache 2.0 LICENSE in repo (+), explicit version 0.100.0, docs portal, contributing guide and SECURITY.md reporting channel; but installation details live outside the repo, no known-limitations section, no CHANGELOG, examples are screenshots only, and registry license metadata (NOASSERTION) contradicts the actual license — deducted.
As a No-Code FinOps platform with bundled Tables/Analytics, a prebuilt workflow library, and centralized opportunity management (approve/dismiss/snooze), marginal value is clear and differentiated; but output usability (AI-step result format, log export) is only asserted, and self-hosting cost is a free docker-compose stack — solid but not fully evidenced.
README claims ('designed with input from FinOps leaders', 'seamless integration') lack sources; facts and inference are not separated. Test files partially corroborate AI-step behavior, but all documentation is external and unverifiable in this static review — deducted.
- Publisher identity is unverified; assessment is based solely on repository content — confirm supply-chain trust independently.
- Very broad dependency surface (SSH/SFTP, cloud SDKs, isolated-vm, database drivers); audit which blocks are actually enabled and apply least privilege before deploying.
- HITL approvals, logging and rollback are README claims only; verify in deployment that confirmation gates are enforced by default.
- Registry license metadata is NOASSERTION, contradicting the in-repo Apache 2.0 license; correct compliance records manually.
- LLM-step output constraints and telemetry toggles are visible only in test files; disable unnecessary telemetry in production and review prompt-injection risk.