Best Agentic DevOps Tools for Mac

NeuBird is the governed center of agentic operations: one secure, audited connection to your telemetry and your LLMs, with a memory of every investigation, so your engineers, your leaders, and your own agents all start from what the company already knows.

Datadog is the monitoring, security and analytics platform for developers, IT operations teams, security engineers and business users in the cloud age. Our SaaS platform integrates and automates infrastructure monitoring, application performance monitoring and log management to provide unified, real-time observability of our customers' entire technology stack. Datadog is used by organizations of all sizes and across a wide range of industries to enable digital transformation and cloud migration, drive collaboration among development, operations, security and business teams, accelerate time to market for applications, reduce time to problem resolution, secure applications and infrastructure, understand user behavior and track key business metrics.

Nuphos is an AI-native DevOps workspace where engineering teams and AI agents operate production systems together without giving up control. Agents learn your infrastructure, investigate issues, and work across AWS, GCP, Kubernetes, Cloudflare, and the rest of your stack while using fine-grained IAM permissions, human approvals, and full audit trails. Each agent session can be scoped with native IAM roles and short-lived, least-privilege credentials, and anything that changes infrastructure is first proposed as a plan for approval. Agents can inspect resources, open dashboards, read logs, generate plans, request approval, and take safe actions while building memory of services, environments, workflows, runbooks, and operational history. Engineers and agents share the same DevOps workspace instead of jumping between terminals, cloud consoles, dashboards, and documentation.

Autoheal actively investigates alerts, hypothesizes root cause, and proposes mitigating fixes under human supervision. It also automates the postmortem phase completely. At its core is the Production Context Graph (PCG), a continuously updating, living map that connects your infrastructure, application logic, production tools and tribal knowledge in real-time. The PCG is built through autonomous exploration of your observability, cloud and code stack, and iteratively refined by a Reinforcement Learning loop as you use Autoheal. On top of the PCG lies a Multi-Agent Platform of specialized agents that collaborate with humans to solve production problems safely and efficiently. For AI agents focused on production engineering to succeed in real-world enterprise deployments, three crucial gaps must be addressed. The Context Gap: can the AI navigate my organization’s fragmented context? The Trust Gap: can I trust the AI to strictly adhere to my organization’s security policies?