Best FinOps Tools for AWS Lambda

Sedai intelligently finds resources, analyzes traffic patterns and learns metric performance. This allows you to manage your production environments continuously without any manual thresholds or human intervention. Sedai's Discovery engine uses an agentless approach to automatically identify everything in your production environments. It intelligently prioritizes your monitoring information. All your cloud accounts are on the same platform. All of your cloud resources can be viewed in one place. Connect your APM tools. Sedai will identify and select the most important metrics. Machine learning intelligently sets thresholds. Sedai is able to see all the changes in your environment. You can view updates and changes and control how the platform manages resources. Sedai's Decision engine makes use of ML to analyze and comprehend data at large scale to simplify the chaos.

Cloud Custodian empowers users to oversee their cloud assets through a system of filtering, tagging, and executing various actions. Utilizing a YAML domain-specific language, it allows for the creation of rules that help maintain a cloud infrastructure which is not only secure but also optimized for cost efficiency. By streamlining the process, it replaces complex cloud-specific scripts with more straightforward syntax, ensuring that policies are effectively applied across your infrastructure. The tool is compatible with major public cloud platforms such as AWS, Azure, and GCP, with additional support for Kubernetes, Tencent Cloud, and OpenStack currently in beta. It actively enforces security measures by seamlessly integrating with the control plane of cloud providers, enabling real-time remediation of issues. In addition, it features comprehensive metrics and reporting capabilities. Users can schedule resources to be turned off during non-peak hours to minimize expenses, while also identifying and removing unused assets by analyzing utilization metrics. Tagging capabilities allow for easy management of underused resources. Furthermore, Cloud Custodian can be executed in various environments, whether locally, on an instance, or in a serverless format through AWS Lambda, providing flexibility in deployment options. This versatility makes it a vital tool for efficient cloud resource management.

NudgeBee is an enterprise-grade AI Agents and Agentic Workflow platform purpose-built for SRE, CloudOps, DevOps, and platform engineering teams running complex cloud-native environments. The platform ships pre-built AI Assistants that work on day one, no model training, no prompt engineering. The AI SRE Agent handles incident triage, alert enrichment, root cause analysis, and remediation guidance. The AI FinOps Assistant delivers continuous Kubernetes and cloud cost optimization with right-sizing, spot instance, and abandoned resource recommendations. The AI K8sOps Agent provides natural-language interaction with clusters for workload checks, upgrade guidance, and maintenance operations. Alongside these, NudgeBee's visual no-code Workflow Builder lets teams automate any custom operational process. It supports 20+ action categories including native AWS, Azure, and GCP CLI nodes, kubectl execution, database queries, LLM-powered nodes, Agent-to-Agent (A2A) calls, and MCP server integration, all with built-in approval gates and audit logging. Key technical differentiators: NudgeBee uses a live semantic Knowledge Graph to ground AI answers in real infrastructure topology. It queries observability data in place, zero data ingestion, zero egress cost. A single workflow can span multiple clouds, Kubernetes clusters, ticketing tools, and communication channels. 49+ integrations across Kubernetes, AWS, Azure, GCP, Prometheus, Datadog, Dynatrace, Jira, ServiceNow, Slack, GitHub, ArgoCD, and more. Enterprise-ready: RBAC, MFA, immutable audit trails, BYOM (GPT, Claude, Gemini, Bedrock, Ollama), self-hosted deployment, SOC-2 Type II, and ISO 27001 certified.