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      • S1- Recurring high rework rate
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      • S6- High technical debt on Sonar
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      • S9 - Unreviewed Pull Requests
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      • S12- High Lead Time For Changes (DORA)
      • S13- Low Deployment Frequency (DORA)
      • S14- High Change Failure Rate (DORA)
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      • OOBEYA-2.0.8 - Release Notes
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  • INTEGRATIONS
    • Integration Catalog
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    • Installing An Addon
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  • ADMINISTRATION
    • User Management, Single Sign-On, Auth Settings
      • Microsoft Entra (Azure AD) Integration
      • LDAP / Active Directory Integration
      • Importing a New User From LDAP / Active Directory
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      • Adding a New User
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      • Understanding Roles in Oobeya
    • License Management
      • Updating The License Key
  • DEVELOPMENT ANALYTICS - GITWISER
    • Git Analytics - Metric Definitions
      • Coding Impact Score
      • Impact Ratio (team-level)
    • Setting Up Development Analytics And DORA Metrics
    • Git Analytics Exclusions
    • Setting Automated Reanalyze For Gitwiser
    • Deployment Analytics (DORA Metrics)
    • Merging Contributor Accounts
  • DORA Metrics
    • DORA Metrics Introduction
      • Lead Time For Changes (LTC)
      • Deployment Frequency (DF)
      • Change Failure Rate (CFR)
      • Mean Time To Restore Service (MTTR)
    • Failure Detection (For Change Failure Rate & MTTR)
    • How To Calculate DORA Metrics for GitHub
    • Updating Team Scorecard configuration to display DORA Metrics
    • How To Start Deployment Analytics (DORA Metrics) For An Existing Gitwiser Analysis
  • Project Analytics - AgileSpace
    • Agile Analytics - Metric Definitions
    • Agile Board Analytics Intro
    • Starting an Agile Board Analytics
    • Board Overview
    • Sprint Reports
    • Update the Agile Board Analytics
  • QUALITY ANALYTICS
    • Total Code Quality Index (TCQI)
  • Guides
    • Azure DevOps Guides
      • How To Calculate DORA Metrics for Azure DevOps
      • Best practices for integrating Oobeya with Azure DevOps Scrum Boards
  • PROFILES
    • Introduction
    • Adding A Profile
    • Developer Scorecard
    • Adding A Related Account Information To Oobeya Profile
  • Team Health
    • Adding A Team
    • Team Scorecard
    • Project Analytics (Scrum Teams) Widget
  • Test Quality Report Widget
  • CUSTOM DASHBOARDS
    • Adding A New Dashboard
    • Adding A New Widget
    • Updating And Deleting Widgets
    • Adding Jira Sprint Progress Widget
    • Adding Jira Board Metrics Widget (Metrics With JQL)
  • SUPPORT
    • Support Request Workflow
    • Customer Success & Support Guide
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On this page
  • Why is this a symptom?
  • Possible Causes
  • Improvement Areas
  • Detection Method

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  1. TEAM INSIGHTS & SYMPTOMS
  2. Symptoms Catalog

S13- Low Deployment Frequency (DORA)

This symptom refers to a situation where software changes are not deployed to production frequently. It indicates a potential bottleneck or inefficiency in the deployment process.

Why is this a symptom?

Low deployment frequency (DORA) refers to a situation where software changes are not deployed to production frequently. This symptom indicates a potential bottleneck or inefficiency in the deployment process. Teams may face challenges in delivering changes to production environments, which can result in slower software delivery cycles and longer lead times for deploying new features or bug fixes.

Impact: Reduced agility in delivering value to users, slower feedback loops, and delayed realization of business benefits.

Level: Team Level, System Level

Potential Complications: #slow_delivery, #slow_time_to_market, #poor_customer_satisfaction, #inefficiencies, #delay_in_delivery, #high_lead_time

Possible Causes

  • Inadequate resource allocation: Insufficient resources, such as limited team capacity or lack of infrastructure, can lead to delays in deploying code changes.

  • Complex and lengthy deployment processes: Cumbersome and time-consuming deployment processes, involving multiple manual steps or dependencies, can hinder the frequency of deployments.

  • High technical debt: Accumulated technical debt, including code that is hard to maintain or modify, can slow down the deployment process and reduce frequency.

  • Limited test automation: Insufficient automated testing practices and reliance on manual testing can prolong the deployment cycle and decrease the frequency of releases.

  • Ineffective release management: Poor release coordination, insufficient planning, or inadequate release management practices can result in delays and infrequent deployments.

  • Lack of collaboration and communication: Inadequate collaboration and communication between teams involved in the deployment process can cause delays and reduced frequency.

  • Risk-averse culture: A risk-averse culture that prioritizes stability over speed can lead to cautious deployment practices and lower deployment frequency.

  • Inefficient code review and quality assurance: Lengthy or ineffective code review processes, coupled with inadequate quality assurance practices, can delay deployments and decrease frequency.

Improvement Areas

  • Enhancing infrastructure and resource allocation: Ensure sufficient resources are allocated to support frequent deployments, including robust infrastructure, suitable hardware, and adequate team capacity.

  • Streamlining deployment processes: Identify and remove unnecessary steps, automate manual tasks, and simplify the overall deployment process to increase efficiency and speed.

  • Reducing technical debt: Address technical debt by refactoring code, eliminating code smells, improving code quality, and adopting best practices to make the codebase more maintainable and deployable.

  • Increasing test automation coverage: Invest in automated testing frameworks and tools to improve test coverage and reduce the time required for manual testing, enabling faster and more frequent deployments.

  • Implementing effective release management practices: Develop a well-defined release management strategy that includes clear planning, coordination, and communication to enable smoother and more frequent deployments.

  • Cultivating a DevOps culture: Foster a culture of collaboration, shared responsibility, and continuous improvement across development, operations, and other teams involved in the deployment process to promote a faster and more frequent release cycle.

  • Prioritizing stability and reliability: Balance the need for speed with a focus on stability and reliability by implementing robust monitoring, error tracking, and incident management practices to minimize risks associated with frequent deployments.

  • Optimizing code review and quality assurance: Streamline code review processes, establish clear guidelines, and ensure thorough quality assurance to expedite the review cycle and enhance the overall deployment frequency.

  • Leveraging deployment automation tools: Explore and adopt deployment automation tools and technologies, such as continuous integration and continuous deployment (CI/CD) pipelines, to streamline and accelerate the deployment process.

Detection Method

Oobeya detects this symptom if the Deployment Frequency metric is less than the specified threshold in the selected period.

Formula: (deployment_frequency) < (threshold) in the selected period

Example: In the past 3 months, the Deployment Frequency metric is less than 0.2 days.

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Last updated 1 year ago

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