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Middleware

Crystal-clear visibility into engineering productivity to spot bottlenecks, align teams, and deliver software faster.

Quick Info

Starting at $0
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Overview

Middleware is a comprehensive platform designed to enhance engineering productivity and streamline software delivery. It addresses the common challenges of unpredictable software development by offering crystal-clear visibility into the entire engineering flow, from planning to deployment. By unifying data from various SDLC tools like Jira and Git, Middleware provides a holistic view of operations. The core value proposition of Middleware lies in its ability to transform scattered data into actionable insights. Its 'Cockpit' feature allows teams to customize and monitor their most critical metrics and KPIs, ensuring everyone is aligned on what truly matters. The platform also offers 'Project Flow Metrics' to highlight blocked, spilled, or dropped work, enabling teams to proactively clear impediments and accelerate delivery. This leads to faster bottleneck resolution, reduced reporting time, and significantly improved project predictability, ultimately helping teams deliver better software faster and with greater confidence.

Pricing

Community

$0

  • DORA Metrics
  • Support: Email + GitHub Issue
  • Integration Priority: Low
POPULAR

Standard

$39 Per user /per month

  • Project Insights
  • Bird's eye view of org efficiency
  • AI Reports
  • Project Roadmap
  • Playbook & Slack Automations
  • Support: Slack Channel
  • Integration Priority: High

Pros & Cons

Pros

  • Provides a unified view of the entire software development lifecycle
  • Helps identify and resolve engineering bottlenecks 2.6x faster
  • Significantly reduces time spent on creating reports (87% reduction)
  • Improves project predictability by 3x
  • Open-source, offering transparency and community contributions
  • Aligns engineering and business goals through clear metrics

Cons

  • Requires integration with existing SDLC tools, which might involve setup time
  • Effectiveness is dependent on the quality and completeness of integrated data
  • May have a learning curve for teams new to engineering productivity metrics
  • Specific advanced customization options are not detailed in the provided content

Use Cases

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Best For

  • Improving software delivery predictability
  • Identifying and resolving engineering bottlenecks
  • Aligning engineering and business teams on delivery goals
  • Measuring and reporting on engineering productivity
  • Optimizing project flow and reducing context-switching
  • Gaining visibility into blocked or delayed work across sprints

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