Ansible vs Modal
Side-by-side comparison of AI visibility scores, market position, and capabilities
Q4 2024 automation revenue up 15-16% YoY; 2025 H1 automation grew 15%; Red Hat contributed 3.5 percentage points of organic software growth; Red Hat annual run rate $6.5B (doubled since IBM acquisition); CAGR mid-teens over 5 years
About
Ansible is an open-source IT automation framework originally created by Michael DeHaan in 2012 and acquired by Red Hat in 2015, which was itself acquired by IBM in 2019. Ansible was built to solve a fundamental problem in IT operations: configuration management and infrastructure provisioning required specialized scripting knowledge, complex agent installations, and brittle, hard-to-audit procedural scripts. Ansible introduced an agentless, YAML-based declarative approach — Playbooks — that allowed IT teams to describe the desired state of their infrastructure in human-readable files, executable from any control node over SSH without requiring software installed on managed hosts.\n\nAnsible's automation framework handles configuration management, application deployment, cloud provisioning, network automation, and security compliance enforcement. The platform integrates with major cloud providers (AWS, Azure, GCP), virtualization platforms, networking vendors (Cisco, Juniper, Arista), and hundreds of enterprise applications through a library of community and certified Ansible Collections. Red Hat Ansible Automation Platform extends the open-source core with enterprise features including a web-based UI (Automation Controller, formerly Ansible Tower), automation analytics, content management, and enterprise support — the commercial layer IBM monetizes alongside the free open-source offering.\n\nAnsible has over 1 million deployments globally and is the infrastructure-as-code standard across enterprise IT, networking, and cloud operations teams. Red Hat reported automation revenue growth of 15 to 16% year over year in Q4 2024, driven by expanding Ansible Automation Platform adoption as enterprises accelerate infrastructure standardization and cloud migration. Its agentless architecture, vast integration library, and position as a trusted Red Hat/IBM enterprise product give Ansible a durable position in the IT automation market against competitors including Puppet, Chef, and Terraform.
Serverless GPU cloud platform for AI/ML with Python-native deployment and per-second billing; developer-favorite scaling from zero competing with Replicate and Beam for AI compute.
About
Modal is a serverless cloud computing platform purpose-built for AI and machine learning workloads — providing on-demand GPU compute that scales instantly from zero with per-second billing, container management, distributed training support, and a Python-native developer experience that makes running ML workloads in the cloud feel as simple as running code locally. Founded in 2021 in New York City and backed by Redpoint Ventures and other investors, Modal has grown rapidly as AI development has accelerated demand for flexible, developer-friendly GPU infrastructure.\n\nModal's developer experience is its primary differentiator — engineers write Python functions decorated with @modal.function() and deploy them to the cloud with a single command, with Modal handling container building, GPU provisioning, auto-scaling, and execution. The platform supports training jobs that need distributed compute across multiple GPUs, model serving endpoints that scale to zero when unused (eliminating idle GPU costs), and batch inference jobs that process large datasets. The per-second billing model means developers pay only for actual compute time, not provisioned instances.\n\nIn 2025, Modal competes in the AI infrastructure market with Replicate, Beam, Banana, and major cloud providers' managed ML services (AWS SageMaker, Google Vertex AI, Azure ML) for serverless GPU compute. The market for AI-specific cloud infrastructure has grown dramatically as the number of ML engineers deploying models to production has expanded — traditional cloud providers require significant DevOps expertise to use GPU instances effectively, while Modal's Python-native approach reduces the barrier to entry. Modal has attracted a strong developer following among AI researchers and ML engineers building production AI applications. The 2025 strategy focuses on growing the developer community, adding enterprise features (dedicated GPU capacity, private networking, compliance), and expanding the hardware options available (H100 GPUs, custom accelerators).
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