Best DORA Metrics Tools for Asana

Jira is a project management tool that allows you to plan and track the work of your entire team. Atlassian's Jira is the #1 tool for software development teams to plan and build great products. Jira is trusted by thousands of teams. It offers a range of tools to help plan, track, and release world-class software. It also allows you to capture and organize issues, assign work, and follow team activity. It integrates with leading developer software for end-toend traceability. Jira can help you break down big ideas into manageable steps, whether they are small projects or large cross-functional programs. Organize your work, create milestones and dependencies, and more. Linking work to goals allows everyone to see how their work contributes towards company objectives, and to stay aligned with what's important. Your next step, suggested by AI. Atlassian Intelligence automatically suggests tasks to help you get your big ideas done.

Faros AI combines all your operational data from multiple sources and enhances them with machine learning signals. The Faros AI Engineering Operations Platform allows you to harness this data so you can accelerate productivity, and better manager your engineering operations. With Faros AI, engineering leaders can scale their operations in a more data-informed way — using data to identify bottlenecks, measure progress towards organizational goals, better support teams with the right resources, and accurately assess the impact of interventions over time. DORA Metrics come standard in Faros AI, and the platform is extensible to allow organizations to build their own custom dashboards and metrics so they can get deep insights into their engineering operations and take intelligent action in a data-driven manner. Leading organizations including Box, Coursera, GoFundMe, Astronomer, Salesforce, etc. trust Faros AI as their engops platform of choice.

Hatica provides actionable analytics and workflows that empower engineering teams to be their best. Combine git, project and collaboration data to gain insights into dev workflows that will help your engineering teams do their best work. Track Pull requests metrics from open through deployment, along with code-review metrics, to identify bottlenecks or opportunities for improvement. Metrics such as deployment frequency, MTTR and change failure rate can be used to measure DevOps performance. A centralized dashboard that displays aggregated activity and metrics from git, project management and CI/CD tools, which act as a proxy for progress and performance, allows you to view the data. You can gain insight into the allocation of effort by engineering teams to align them with business goals. Hatica consolidates all work activity and progress in a central dashboard, giving visibility into where your teams are working and what they are facing.

Weave is an engineering intelligence platform that helps organizations measure software delivery performance, developer output, code quality, AI adoption, and the economics of AI-assisted development. It analyzes engineering activity from AI prompts and token consumption through commits, pull requests, reviews, deployments, and production outcomes. The platform combines AI-specific measurements with established engineering frameworks such as DORA and SPACE to provide a unified view of software development performance. Token intelligence shows how spending is distributed across AI models, providers, engineers, and development tools while evaluating efficiency and quality alongside raw consumption. Organizations can use these metrics to compare AI-assisted output with historical baselines and identify where AI is contributing to measurable improvements or unnecessary costs. Weave Router automatically classifies prompts and sends them to models selected for an appropriate balance of cost, latency, and output quality. The router can work with AI providers including Anthropic, OpenAI, and Google while learning from feedback at both the user and organizational level. Wooly provides an AI interface for asking questions about engineering performance, AI usage, deployment bottlenecks, and team effectiveness using connected internal records as evidence. Weave is intended for engineering executives, development managers, platform teams, AI transformation leaders, and enterprises seeking greater visibility into the productivity and financial impact of AI coding tools.