# Agent 37 vs Datadog

Agent 37 records 180,030 monthly visits with +24.2% month-over-month growth and Free Trial, Contact for Pricing pricing. Datadog records 5,175,760 monthly visits with -4.8% growth and Freemium, Free Trial, Paid, Contact for Pricing, Free pricing.

| Metric | [Agent 37](https://openaitools.app/tool/agent-37) | [Datadog](https://openaitools.app/tool/datadog) |
| :--- | :--- | :--- |
| Website URL | https://www.agent37.com | https://www.datadoghq.com |
| Categories | AI Coaching, AI Agent, AI Developer Tools, Large Language Models (LLMs) | Log Management, AI Monitor, AI Agent |
| Pricing Model | Free Trial, Contact for Pricing | Freemium, Free Trial, Paid, Contact for Pricing, Free |
| Monthly Visits | 180,030 | 5,175,760 |
| MoM Growth Rate | +24.2% | -4.8% |
| Primary Market | Paraguay | United States |
| Direct Visits | 72,672 | 2,745,846 |
| Review Score | 4.3 | 4.7 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Agent 37

Agent 37 is a cloud infrastructure product aimed at people who need somewhere real for AI agents to run. Instead of a chat window, every customer gets a sandbox: an isolated Linux container with CPU, memory, persistent disk, an optional public HTTPS URL, and outbound network access. The company positions itself primarily on price, claiming its sandboxes cost roughly 94% less than most competing providers and publishing a comparison table against AWS, Daytona, E2B, Modal, Vercel, and others. Billing is prepaid and metered by the minute — vCPU, memory, and disk each have their own unit rate — with no subscription fee.

Beyond raw compute, Agent 37 ships a layer of agent-specific conveniences. You can start from a ready-made harness such as Claude Code, Codex, OpenClaw, OpenCode, or Hermes, or bring your own Docker image. Agents keep their files across sleep, stop and restart cycles, and can be given cron schedules so they run unattended and simply report results. Model access can come from the platform gateway (Claude, OpenAI, Gemini, Grok) or from your own API keys, and integrations cover services such as Gmail, Slack, Notion, and GitHub through a Composio-based connector catalog, plus metered access to paid tools like web scraping and people/company data.

Security is a major part of the pitch: sandboxes are isolated with gVisor, hosts have no public hostname, ingress goes through Cloudflare with API-key authentication, and outbound traffic is restricted to the public internet. The company states it does not collect prompts, files, or terminal sessions, holds SOC 2 Type I, and is working toward Type II. It also offers startup credits and a free personal agent tier for individuals who just want an agent of their own.

**Pricing & Plans:** Prepaid, pay-as-you-go compute metered per minute with no subscription or minimum. New accounts get a $5 starter credit once a card is on file, and the company advertises up to $10,000 in credits for startups. Exact unit rates are published on the pricing page and change over time, so confirm current figures there.

- **Per-minute sandbox billing:** Pay for vCPU, memory and disk separately while the sandbox runs; when it sleeps or is deleted the compute meter stops and you are left with disk cost only.
- **Ready-made agent harnesses:** Launch Claude Code, Codex, OpenClaw, OpenCode, Hermes, Grok or your own Docker image, each in its own tenant-isolated sandbox.
- **Persistent workspace and scheduling:** Files survive sleep, restarts and weeks of inactivity, and agents can be attached to cron-style schedules so work runs unattended.
- **Networking and custom domains:** Expose individual ports publicly, attach your own domain, or keep everything behind an API key on an authenticated URL.
- **Integrations and metered tools:** Connect 1,000+ apps such as Gmail, Slack, Notion and GitHub, and buy one-off capabilities like scraping or enrichment from the same balance.

**Strengths:** Aggressively low per-minute pricing with an explicit public comparison against major sandbox providers; Persistent disk and scheduling make it suitable for real agent workloads rather than one-shot tasks; Strong isolation story (gVisor, firewalled egress, no public hostnames) plus SOC 2 Type I; Flexible model and tool sourcing: platform gateway, bring-your-own keys, or pay-per-use tools

**Limitations:** Prepaid balance model means you must top up in advance and monitor spend across many sandboxes; Persona pricing and plan details are only available after contacting the team for the white-label and enterprise tracks; Documentation and benchmark claims are largely self-published, so independent verification is limited

[Profile (Markdown)](https://openaitools.app/tool/agent-37.md)

## Datadog

Datadog began as a hosted infrastructure-monitoring service and has grown into a broad platform spanning observability, application security, digital experience and service management. Its core promise is a single, consistent data model: metrics from agents and cloud integrations, distributed traces from instrumented services, logs from collectors, real user monitoring from browsers and mobile apps, and synthetic checks from managed locations all land in the same graph, so a spike in latency can be tied to a specific deploy, container, database query or error log without switching consoles.

On top of that foundation, Datadog layers AI-assisted workflows. Bits AI acts as an investigation and chat assistant, an agent builder lets teams compose automation, and dedicated AI Observability and LLM monitoring views track model latency, cost, token usage and agent traces. Security surfaces such as Cloud SIEM, Cloud Security Posture Management, vulnerability management and code scanning share the same telemetry, and software-delivery features cover CI visibility, test optimization, feature flags and DORA metrics.

Datadog is aimed at teams running cloud-native, multi-cloud and Kubernetes-heavy estates, from startups to large enterprises. It is a paid, usage-metered service with a free trial and generous free allowances on many individual products, and it ships official SDKs, an MCP server, OpenTelemetry support and an integrations directory covering AWS, Azure, Google Cloud, databases, queues and popular frameworks.

**Pricing & Plans:** Usage-based SaaS pricing. New customers get a free trial, and many individual products include free tiers or allowances (for example, a handful of free hosts, limited custom metrics or log ingestion credits). Beyond that you pay per host, per ingested log volume, per indexed span, per monitored synthetic test and per security seat, with annual commitments typically discounted. Enterprise and consolidated-bundle plans are quoted by sales.

- **Unified metrics, traces and logs:** Agents, cloud integrations and OpenTelemetry collectors feed one platform where metrics, distributed traces, profiles and logs can be pivoted between without context switching.
- **AI-assisted investigation:** Bits AI, an agent builder and LLM/AI-agent observability help teams triage alerts, explain anomalies and monitor model latency, token spend and agent traces.
- **Security in the same data model:** Cloud SIEM, cloud security posture management, vulnerability management, workload protection and code scanning correlate threat signals with the telemetry you already collect.
- **Digital experience and delivery:** Real user monitoring, session replay, product analytics, synthetic and mobile testing sit alongside CI visibility, test optimization, feature flags and DORA metrics.
- **Alerting, SLOs and automation:** Metric, log and trace monitors, service-level objectives, event management, on-call schedules and workflow automation turn signals into coordinated action.

**Strengths:** Very broad product coverage from infrastructure, APM and logs through to security, RUM and software delivery; Strong integrations and OpenTelemetry support across clouds, runtimes and languages; Shared data model makes cross-signal correlation practical in one interface; Reliable alerting, dashboards, SLOs and collaboration features for on-call teams

**Limitations:** Costs can climb quickly because pricing is granular per host, per log volume and per span; The breadth of the catalogue means onboarding and configuration take real effort; Some advanced AI and security modules require separate purchases, which complicates budgeting

[Profile (Markdown)](https://openaitools.app/tool/datadog.md)

## Frequently Asked Questions

### How do Agent 37 and Datadog compare in monthly traffic?

Agent 37 has 180,030 monthly visits, while Datadog has 5,175,760. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Agent 37 has a month-over-month growth rate of +24.2%; Datadog has -4.8%.

### How does pricing compare?

Agent 37: Free Trial, Contact for Pricing. Prepaid, pay-as-you-go compute metered per minute with no subscription or minimum. New accounts get a $5 starter credit once a card is on file, and the company advertises up to $10,000 in credits for startups. Exact unit rates are published on the pricing page and change over time, so confirm current figures there. Datadog: Freemium, Free Trial, Paid, Contact for Pricing, Free. Usage-based SaaS pricing. New customers get a free trial, and many individual products include free tiers or allowances (for example, a handful of free hosts, limited custom metrics or log ingestion credits). Beyond that you pay per host, per ingested log volume, per indexed span, per monitored synthetic test and per security seat, with annual commitments typically discounted. Enterprise and consolidated-bundle plans are quoted by sales.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [RunPod](https://openaitools.app/tool/runpod) | 2,881,043 | +5.9% | Paid | The AI developer cloud for GPU pods, serverless inference and clustering | [.md](https://openaitools.app/tool/runpod.md) |
| 2 | [Modal](https://openaitools.app/tool/modal-com) | 1,196,021 | +30.2% | Freemium, Contact for Pricing | Runs serverless Python containers optimized for AI model inference and batch jobs rather than persistent agent sandboxes. | [.md](https://openaitools.app/tool/modal-com.md) |
| 3 | [Browserbase](https://openaitools.app/tool/browserbase) | 283,597 | -8% | Freemium | Cloud browsers and web APIs for AI agents | [.md](https://openaitools.app/tool/browserbase.md) |
| 4 | [Arize AI](https://openaitools.app/tool/arize-com) | 249,028 | +3.2% | Paid, Contact for Pricing | Specializes in tracing and debugging production LLM applications, but does not provide general cloud infrastructure metrics or log management. | [.md](https://openaitools.app/tool/arize-com.md) |
| 5 | [Vectra AI](https://openaitools.app/tool/vectra) | 150,359 | -1.1% | Contact for Pricing | Provides advanced AI-driven threat detection for cloud networks, but focuses purely on security rather than general application performance monitoring. | [.md](https://openaitools.app/tool/vectra.md) |
| 6 | [Coder](https://openaitools.app/tool/coder) | 149,417 | -12.8% | Free Trial, Contact for Pricing, Free | Self-hosted infrastructure platform for provisioning secure cloud development workspaces and governing AI coding agents. | [.md](https://openaitools.app/tool/coder.md) |
| 7 | [Maxim AI](https://openaitools.app/tool/maxim-ai) | 121,351 | +10% | Contact for Pricing, Free Open Source | Evaluate, monitor, and govern your AI applications in production | [.md](https://openaitools.app/tool/maxim-ai.md) |
| 8 | [Thunder Compute](https://openaitools.app/tool/thunder-compute) | 102,147 | -29% | Paid (per-minute instances, per-second sandboxes) | Low-cost cloud GPUs with per-minute instances and per-second sandboxes for AI workloads. | [.md](https://openaitools.app/tool/thunder-compute.md) |
| 9 | [PromptLayer](https://openaitools.app/tool/promptlayer) | 85,899 | -4.6% | Free Trial, Contact for Pricing | The collaboration layer for AI engineering teams | [.md](https://openaitools.app/tool/promptlayer.md) |
| 10 | [Confident AI](https://openaitools.app/tool/confident-ai) | 83,400 | -3.3% | Freemium, Paid, Contact for Pricing | Standardize LLM evaluation, observability, and red teaming across your whole org | [.md](https://openaitools.app/tool/confident-ai.md) |

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Source: https://openaitools.app/compare/agent-37-vs-datadog

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)