GitLab - Detailed Review
Research Tools
GitLab - Product Overview
GitLab Overview
GitLab is a comprehensive DevOps platform that serves as a central hub for managing code, continuous integration and continuous delivery (CI/CD), and project workflows. Here’s a brief overview of its primary function, target audience, and key features:
Primary Function
GitLab is essentially a web-based Git repository manager that integrates various tools and features to streamline the entire software development lifecycle. It allows teams to manage their codebases, track changes, collaborate on projects, and automate the testing and deployment processes through CI/CD pipelines.
Target Audience
GitLab caters to a wide range of users, including individual developers, small and medium-sized businesses (SMBs), mid-market companies, and large enterprises. It is particularly popular among DevOps teams, which consist of developers and IT operations professionals working together to automate and streamline software delivery.
Key Features
Git Source Code Management (SCM)
GitLab uses Git to enable version control, branching, and conflict resolution, making it easier for teams to collaborate and manage their codebases efficiently.
Continuous Integration and Continuous Delivery (CI/CD)
GitLab offers highly customizable CI/CD pipelines that automate the testing, building, and deployment processes, reducing manual errors and improving efficiency.
Project Management
The platform includes tools for issue tracking, time tracking, and project planning, allowing teams to divide tasks, track progress, and prioritize work effectively.
Security and Compliance
GitLab provides features like code vulnerability scanning and compliance tools to ensure the security and integrity of the codebase.
Collaboration Tools
It includes features such as wikis, issue boards, and real-time collaboration tools to facilitate teamwork and communication among team members.
Flexibility and Scalability
GitLab can be self-hosted or used as a Software as a Service (SaaS) solution, making it adaptable to various organizational needs and sizes.
Conclusion
Overall, GitLab is a versatile platform that combines version control, issue tracking, CI/CD, and project management into a single, user-friendly interface, making it an essential tool for software development teams.
GitLab - User Interface and Experience
User Interface Overview
The user interface of GitLab, particularly in the context of its AI-driven features like GitLab Duo, is designed to be user-friendly and intuitive, enhancing the overall user experience.Navigation and Interface
GitLab 16, the latest version, introduces a significantly revamped navigation experience. The new navigation system features a toggle at the upper right corner of the UI, which transforms the left sidebar into a streamlined design. This change aims to make the interface more intuitive and less overwhelming, as noted by user feedback.Ease of Use
GitLab is known for its ease of use, with a user-friendly UI and tools that simplify various aspects of project management and development. The interface is divided into clear sections such as projects, users, groups, and stats, making it easy for users to manage different aspects of their projects from one screen.AI-Driven Features
With GitLab Duo, the AI-driven development tool, users can enjoy a range of features that automate and optimize their workflow. This includes AI-powered code suggestions, real-time guidance across the entire software development lifecycle, and automated routine tasks. These features help developers focus on innovation by handling repetitive and routine coding tasks efficiently.User Experience Enhancements
GitLab 16 includes several user experience enhancements, such as real-time merge request updates and accurate reflections of project statuses. These updates ensure that users have the most current information at their fingertips, boosting productivity and streamlining the development process.Customization and Control
Users and administrators have significant control over the interface and features. For instance, administrators can configure which users, projects, and groups can use AI-powered capabilities, ensuring that the tools are used effectively and securely within the organization.Feedback and Improvement
GitLab places a strong emphasis on user feedback to continuously improve the user experience. The platform aims to integrate feedback mechanisms that allow users to provide input on specific features and aspects of the product, helping to refine and enhance the UI and overall user experience.Conclusion
Overall, GitLab’s user interface is designed to be intuitive, easy to use, and highly productive, making it an effective tool for developers and teams to manage and collaborate on projects. GitLab - Key Features and Functionality
GitLab Overview
GitLab, a comprehensive DevOps platform, integrates a variety of features that enhance software development, security, and operations, with a growing emphasis on AI-assisted functionalities. Here are the key features and how they work, including the integration of AI.Version Control and Collaboration
GitLab provides a web-based Git repository, allowing developers to manage code, collaborate on projects, and track issues. It supports unlimited free private repositories, making it accessible for both individual developers and large teams.Continuous Integration and Continuous Delivery (CI/CD)
GitLab offers powerful CI/CD pipelines that automate build, test, and deployment processes. This automation helps identify and fix bugs early in the development process, reducing errors and ensuring faster and more reliable rollouts.Issue Tracking and Project Management
GitLab allows teams to create and manage issues, use multiple Issue Boards for a single project, and define milestones. This feature helps in planning, organizing, and visualizing workflows, ensuring transparency and trackability throughout the development process.Security Features
GitLab incorporates security measures from the outset, enabling teams to shift security left. It includes features like vulnerability scanning for application containers and dependencies, helping developers write more secure code.AI-Assisted Features
Code Suggestions
AI-powered code suggestions help developers write code more efficiently by providing real-time suggestions as they type. This feature enhances productivity and reduces the time spent on coding.Suggested Reviewers
AI automatically identifies the right people to review merge requests, ensuring faster and higher-quality reviews. This streamlines the review process and improves the overall quality of the code.Summarize MR Changes
AI helps merge request authors communicate the impact of their changes more effectively, driving alignment and action within the team. It also assists reviewers in understanding the changes and suggestions made in merge requests.Generate Tests in MRs
AI automates the generation of tests within merge requests, helping developers catch bugs early and reducing repetitive tasks. This ensures that well-tested code is rolled out to production.Explain This Vulnerability
AI assists developers in remediating vulnerabilities more efficiently by explaining the vulnerabilities and helping them write more secure code. This uplevels their skills and enhances the security of the codebase.Explain This Code
AI helps DevSecOps teams get up to speed quickly on code by explaining it, which is particularly useful for new team members or when dealing with complex codebases.Issue Comment Summaries
AI quickly summarizes lengthy issue comments, ensuring everyone is on the same page. This feature is beneficial for keeping track of discussions and ensuring all team members are informed.Value Stream Forecasting
AI predicts productivity metrics and identifies anomalies across the software development lifecycle. This helps teams anticipate and manage their workflows more effectively.Integration and Automation
GitLab can be integrated with various APIs and third-party services, including Kubernetes and other CI/CD tools. The integration with Beam AI, for example, allows for automated workflows, code reviews, issue tracking, and deployment processes, enhancing productivity and efficiency.Packaging and Deployment
GitLab provides features for packaging software applications using supported package managers like Maven, npm, or Helm. It also automates the deployment of tested code to production environments, ensuring reliable and efficient rollouts.Transparency and Trackability
GitLab adds transparency to the development process by allowing stakeholders to track progress, provide feedback, and stay informed about the current status. Features like task creation, milestone definition, and time tracking ensure that all aspects of the project are visible and manageable.Conclusion
In summary, GitLab’s integration of AI and its comprehensive set of features make it a powerful tool for software development, security, and operations. These features not only streamline workflows but also enhance productivity, security, and collaboration within development teams. GitLab - Performance and Accuracy
Performance Evaluation
GitLab employs several mechanisms to ensure the performance of their AI-driven features is optimized:
Continuous Analysis Tool
GitLab has developed an AI continuous analysis tool that automates the collection and analysis of data to assess the performance of AI features, such as GitLab Duo Code Suggestions. This tool measures latency, among other metrics, by automating interactions within the Integrated Development Environment (IDE) and using GitLab CI/CD for CI operations.
Multi-Regional Latency Tests
GitLab conducts multi-regional latency tests using the GitLab Environment Toolkit to ensure that requests are served from a suitable location close to the source of the request. This helps in validating the performance across different geolocations.
Foundational Models
GitLab uses foundational models as benchmarks to evaluate the performance of their AI features. By comparing the performance metrics of new models against these benchmarks, they can assess improvements in accuracy, efficiency, and other relevant criteria. This approach also helps in standardizing evaluation methodologies and ensuring consistent and reproducible evaluations.
Accuracy and Reliability
AI Model Validation
The AI Model Validation Team at GitLab relies on foundational models to validate the correctness and reliability of their AI features. This ensures that the underlying models are accurate and reliable, and any new models introduced show improvements over existing ones.
Model Registry
The GitLab Model Registry provides a centralized hub for data science and development teams to collaborate. This registry allows for versioning models, storing artifacts, and documenting model behavior, which helps in maintaining the accuracy and reliability of the models deployed in production.
Automated Testing and Deployment
GitLab’s CI/CD pipelines automate the testing and deployment of AI models, ensuring that any changes or updates are thoroughly tested before being deployed. This includes features like Vulnerability Resolution, which automates the creation of merge requests to mitigate vulnerabilities, thereby maintaining the accuracy and security of the code.
Limitations and Areas for Improvement
Third-Party Services
While GitLab focuses on optimizing the performance of their own components, they acknowledge that third-party AI services can contribute to overall latency. However, integrating these services into their performance testing is challenging and may not yield significant benefits.
Continuous Monitoring
To maintain high performance and accuracy, GitLab continuously monitors and updates their benchmarks and evaluation frameworks. This involves regularly updating benchmarks and evaluating models against historical baselines to rapidly identify and assess new models.
In summary, GitLab’s approach to performance and accuracy in their AI-driven features is centered around continuous analysis, benchmarking against foundational models, and ensuring seamless collaboration between data science and development teams. While there are challenges related to third-party services, GitLab’s methodologies are designed to maintain high standards of performance and reliability.
GitLab - Pricing and Plans
GitLab Pricing Structure
GitLab’s pricing structure is designed to cater to a wide range of users, from individual developers to large enterprises, and is segmented into several tiers. Here’s a detailed overview of each tier and the features they offer:
Free Tier
- The Free tier is available at no cost and is suitable for individual contributors and small teams.
- It includes essential features such as unlimited public and private repositories, issue tracking, CI/CD pipeline tools, and a Git repository manager.
- This tier is ideal for personal projects and small teams, with no credit card required.
Premium Tier
- The Premium tier is priced at $29 per user per month, billed annually. This is a recent increase from $19 per user per month, effective April 3, 2023.
- This tier is targeted at teams and directors, offering advanced features like code quality and security tools, merge requests with approval rules, team planning, and advanced CI/CD capabilities.
- Additional features include code ownership, protected branches, agile planning tools (roadmaps, epics, boards, and milestones), and release controls such as multiple approvers and approval rules.
Ultimate Tier
- The Ultimate tier is the most comprehensive plan, priced at $99 per user per month, billed annually.
- This tier is aimed at executives and strategic organizational usage, providing all the features from the Premium tier plus additional advanced security and compliance tools.
- Key features include dynamic security testing (SAST and DAST), compliance frameworks, audit events, and advanced analytics and visibility tools such as value stream analytics and contribution analytics.
Pricing Methodology
GitLab uses a value-based pricing approach, focusing on the value proposition that their innovations provide to customers. This includes factors such as development cost reduction, revenue gain due to decreased time to market, improved reliability and security, and greater collaboration.
Additional Considerations
- GitLab offers discounts for nonprofits and educational institutions. Interested parties should contact the sales team to inquire about eligibility and discounted pricing.
- The pricing model is designed to be transparent and flexible, allowing users to bring their own Kubernetes (BYOK) and avoiding opaque premiums on infrastructure costs.
By offering a range of tiers, GitLab ensures that users can choose the plan that best fits their needs and budget, whether they are individual developers or large enterprises.
GitLab - Integration and Compatibility
Integrating GitLab with Other Tools
Integrating GitLab with other tools and ensuring its compatibility across various platforms is a key aspect of its functionality, making it a versatile and efficient tool for software development and project management.Integration with Project Management Tools
GitLab integrates seamlessly with a wide range of project management tools. For instance, integrating GitLab with Jira allows you to track Jira issues directly within GitLab, automate builds and deployments based on Jira project updates, and refer to Jira issues by ID in GitLab commits and merge requests. Similarly, GitLab can be integrated with other project management tools like Trello and Asana. The Trello Power-Up for GitLab enables you to visualize GitLab issues on Trello boards, while Asana allows you to track GitLab projects directly within Asana.Integration with Communication and Automation Tools
Besides project management tools, GitLab also integrates with communication platforms such as Slack. This integration enhances team collaboration by allowing you to receive notifications and updates directly in your Slack channels. GitLab’s CI/CD (Continuous Integration/Continuous Deployment) capabilities are another significant integration point. By integrating GitLab CI/CD with your existing tools, you can automate the entire build, test, and deployment process, streamlining your workflow and reducing manual work. This can be done with tools like Jenkins, which can be set up as part of your CI/CD pipeline.Authentication and Security Integrations
GitLab supports integration with various authentication providers, including LDAP, SAML, and OpenID Connect. This allows for secure and centralized user authentication across different platforms. In terms of security, GitLab can be integrated with several security partners such as Anchore, Prisma Cloud, Checkmarx, and others. These integrations help in identifying and mitigating security vulnerabilities within your application.Compatibility Across Platforms and Devices
GitLab is compatible with a variety of operating systems and devices. Here are some key points:Web Browsers
GitLab supports major web browsers like Mozilla Firefox, Google Chrome, Chromium, Apple Safari, and Microsoft Edge.Server Requirements
GitLab can be installed on Linux servers and requires specific storage, CPU, and memory configurations. It also supports PostgreSQL as the database, which needs to be tuned correctly for optimal performance.Cloud and On-Premises
GitLab can be deployed both on-premises and on cloud platforms, ensuring flexibility in deployment options.DevOps Pipeline Integration
In a DevOps environment, GitLab plays a central role in bridging the gap between development and operations. By integrating GitLab into your DevOps pipeline, you can create a unified workflow that streamlines the entire development lifecycle. This includes automating tasks, enhancing collaboration, and providing a clear picture of the development process. In summary, GitLab’s integration capabilities are extensive, allowing it to work seamlessly with a variety of tools and platforms, thereby enhancing productivity, automation, and security in software development and project management. GitLab - Customer Support and Resources
Support Options
GitLab offers various levels of support depending on the subscription plan you have:Standard Support
Included in Legacy GitLab self-managed Starter plans, this provides ‘next business day support’ with a response time of 24 hours (24×5).
Priority Support
Available with self-managed and GitLab.com Premium and Ultimate purchases, this includes tiered response times. For example, emergency issues are responded to within 30 minutes (24×7), highly degraded issues within 4 hours (24×5), and medium impact issues within 8 hours (24×5).
To contact support, you can open a support ticket on the GitLab Support Portal. It is essential to select the appropriate severity and priority for your issue, as these help the support team understand the impact on your organization.
Documentation and Resources
Before reaching out to support, GitLab encourages users to search their extensive documentation. The documentation is published on https://docs.gitlab.com and includes guides for various GitLab products, such as GitLab, GitLab Runner, and Omnibus GitLab. This documentation is also available within the application by adding `/help` to the URL.
For AI-specific features, users can leverage AI-assisted tools integrated into GitLab. For instance, AI can summarize comments on issues, helping users quickly understand the content and take action faster. Additionally, AI can answer queries and point users to relevant documentation and tutorials using large language models trained on GitLab documentation.
UX Research and Feedback
GitLab also conducts UX research to ensure their AI solutions meet user needs. This involves identifying user problems, collecting baseline data on how users currently solve these problems, and gathering feedback on trust, usability, and the overall user experience with AI features. Users can participate in surveys and provide feedback to help improve these AI-powered features.
Insights and Reporting
For users on the Ultimate tier, GitLab provides insights that allow you to create custom reports and interactive bar charts to analyze data such as issues created, merge request times, and triage hygiene. This feature helps in monitoring and optimizing project and group performance.
By leveraging these support options, documentation resources, and AI-driven tools, users can effectively manage and optimize their use of GitLab’s products.
GitLab - Pros and Cons
Advantages of GitLab
Comprehensive DevOps Platform
GitLab offers an all-in-one solution that includes version control, CI/CD pipelines, project management, issue tracking, and more, all within a single platform. This integrated approach streamlines development workflows and reduces the need for external tools and integrations.
Self-Hosting Options
GitLab allows users to host the platform on their own servers, providing more control over repositories and data. This is particularly valuable for organizations prioritizing data privacy and security.
Free Private Repositories
GitLab’s free plan includes unlimited private repositories, making it a cost-effective option for small to medium-sized teams or individual developers who require private code repositories without additional costs.
Built-In CI/CD
GitLab provides native CI/CD pipelines, enabling automated testing, code review, and deployment processes directly within the platform. This simplifies the setup and configuration of CI/CD workflows.
Enhanced Security Features
GitLab offers robust security features, including fine-grained access controls, mandatory code reviews, Static and Dynamic Application Security Testing, Dependency Scanning, and Container Scanning. These features ensure a secure development environment.
High Customizability
GitLab is highly customizable and can be adapted to meet specific development needs. Its open-source nature allows developers to modify and extend the platform to fit their unique requirements.
AI-Powered Workflows
GitLab incorporates AI throughout the software development lifecycle, supporting tasks from coding and testing to security, documentation, and governance. This helps in reducing cycle times and improving developer productivity.
Platform-Wide Governance
GitLab ensures security at scale with automated guardrails that secure the software supply chain. It allows customers to set granular policies and rules that automate compliance.
Disadvantages of GitLab
Slower Interface
Some users have reported that GitLab’s interface can be slower compared to other version control platforms, although the performance is continually being improved.
Complexity for Small Projects
GitLab’s extensive features can feel overwhelming for small projects or individual developers who may prefer a more streamlined and lightweight version control solution.
Considerable Learning Curve
Mastering all the features and capabilities of GitLab may require a significant learning curve, especially for those new to DevOps practices and continuous integration.
Frequent Bugs
Users may encounter frequent bugs throughout the software lifecycle, which can require active management.
Limited Integrations
Although GitLab offers various integrations, it may not have the same extensive integration options as some other version control platforms like GitHub.
By weighing these advantages and disadvantages, users can make an informed decision about whether GitLab aligns with their specific needs and preferences.
GitLab - Comparison with Competitors
Unique Features of GitLab Duo
- Comprehensive Lifecycle Support: GitLab Duo offers a wide range of AI-powered features that span the entire software development lifecycle, including planning, authoring, reviewing, testing, and deploying code. Features like Code Suggestions, Code Explanation, Test Generation, and Vulnerability Resolution are integrated directly into the GitLab UI and IDE extensions, making it a holistic platform for developers.
- AI Impact Dashboard: This feature allows users to measure the effectiveness and impact of AI on their software development lifecycle metrics, providing valuable insights into how AI is enhancing their workflow.
- Self-Hosted Models: GitLab Duo Self-Hosted enables users to host their own language models, giving them more control over data privacy and security. This is particularly useful for organizations with strict compliance requirements.
- Continuous Analysis Tool: GitLab has developed a continuous analysis tool to validate AI feature performance, focusing on metrics like latency and user-centric insights. This ensures that the AI features are continuously improved and optimized.
Potential Alternatives and Comparisons
Market Research and Analysis Tools
While GitLab Duo is focused on software development, tools like Quantilope, Brandwatch, and Morning Consult are geared more towards market research and consumer insights. These tools use AI for survey design, social media listening, and predictive analytics, which are not directly comparable to GitLab Duo but highlight the diverse applications of AI in different fields.
Academic and Research Tools
For academic and research purposes, tools like LitMaps, Inciteful, and Elicit offer features such as generating literature maps, finding related papers, and optimizing database searches. These tools are more specialized in aiding research processes rather than software development and do not offer the same level of integration as GitLab Duo within a development environment.
Development Platforms
When comparing GitLab to other development platforms like GitHub, GitLab stands out with its complete, packaged platform approach. GitLab includes features like continuous integration, time tracking, and backups out-of-the-box, whereas GitHub relies more on third-party integrations. However, GitHub’s marketplace offers a wider range of integrations, which might be appealing to teams looking for more flexibility in their toolset.
Summary
GitLab Duo’s unique strength lies in its comprehensive support across the software development lifecycle, integrated AI features, and the ability to self-host language models. While other tools excel in different areas such as market research or academic research, GitLab Duo remains a powerful choice for development teams seeking to leverage AI to enhance their workflow. If you are looking for a more flexible integration ecosystem, GitHub might be a consideration, but for an all-in-one development platform with built-in AI features, GitLab Duo is a strong contender.
GitLab - Frequently Asked Questions
Frequently Asked Questions about GitLab’s AI-Driven Product Category
What is GitLab Duo and how does it integrate AI into the software development lifecycle?
GitLab Duo is a suite of AI-powered features that assist users across the entire software development lifecycle. It combines AI capabilities to enhance team collaboration, reduce security and compliance risks, and increase efficiency. GitLab Duo includes features like code suggestions, suggested reviewers, summarizing merge request changes, and explaining vulnerabilities, all integrated into the DevSecOps platform.
How does GitLab Duo improve code authoring and review processes?
GitLab Duo offers several features to improve code authoring and review. For code authoring, it provides code suggestions as you type, generates tests for your code, and helps refactor or fix code issues. For code review, it generates summaries of merge requests, suggests reviewers, and summarizes all comments in a review. These features aim to make the development process more efficient and streamline code reviews.
What AI-assisted features are available for security and operations teams?
For security and operations teams, GitLab Duo includes features like “Explain This Vulnerability” to help remediate vulnerabilities more efficiently, “Generate Tests in MRs” to automate repetitive tasks and catch bugs early, and “Explain This Code” to help teams quickly understand code. Additionally, it offers “Vulnerability Explanation” and “Vulnerability Resolution” to learn about and fix vulnerabilities.
How does GitLab Duo ensure user privacy and security?
GitLab is committed to protecting user privacy and security. The AI-powered features are designed with a customer-centric approach, focusing on privacy first. This includes containing customer intellectual property and source code within GitLab’s cloud infrastructure, ensuring that sensitive information is secured.
What is the AI Impact Dashboard in GitLab Duo Enterprise?
The AI Impact Dashboard is a feature of GitLab Duo Enterprise that measures the effectiveness and impact of AI on software development lifecycle metrics. It provides insights into how AI features are used and their impact on cycle time, deployment frequency, and other key metrics. This helps organizations understand the value and efficiency gains from using AI-driven tools.
How can users access and use GitLab Duo Chat?
GitLab Duo Chat is available in the GitLab UI and IDE extensions. It allows users to write and understand code, get updates on project status, and learn about GitLab by asking questions in a chat window. Users can refine their prompts to get more accurate results, avoiding short or yes/no questions and providing specific context for better assistance.
What are the different tiers and offerings for GitLab Duo features?
GitLab Duo features are available across different tiers, including Premium and Ultimate. Features like Code Suggestions, Code Explanation, and Test Generation are available in both Premium and Ultimate tiers. More advanced features, such as the AI Impact Dashboard and Value Stream Forecasting, are part of the Ultimate tier and GitLab Duo Enterprise add-on.
Can organizations self-host the language models that power GitLab Duo features?
Yes, organizations can self-host the language models that power GitLab Duo features through GitLab Duo Self-Hosted. This option allows them to host the models in their own environment, supporting features like Code Suggestions and Chat. This is particularly useful for organizations with strict data privacy and security requirements.
How does GitLab Duo help in planning and managing work?
GitLab Duo includes features to improve workflow while planning work, such as Issue Description Generation, which generates more detailed issue descriptions based on short summaries, and Discussion Summary, which summarizes lengthy conversations in an issue. These features help teams stay aligned and manage their work more efficiently.
What kind of support does GitLab provide for its AI-driven features?
GitLab provides extensive documentation and support for its AI-driven features. Users can access tutorials, watch overviews, and learn more about each feature through the GitLab documentation. Additionally, GitLab continuously updates and improves these features based on user feedback and iteration.
GitLab - Conclusion and Recommendation
Final Assessment of GitLab in the AI-Driven Product Category
GitLab has made significant strides in integrating AI and machine learning (ML) technologies into its DevSecOps platform, particularly through its initiative known as GitLab Duo. Here’s a comprehensive overview of what GitLab Duo offers and who can benefit from it.Key Features of GitLab Duo
GitLab Duo is a suite of AI-powered features that span the entire software development lifecycle. These features include:- Code Suggestions: Helps developers write code more efficiently by providing suggestions as they type.
- Code Review and Summaries: Automates the process of finding the right reviewers and summarizing merge request changes and comments, making the review process faster and more efficient.
- Test Generation: Automatically generates tests for code, helping developers catch bugs early.
- Vulnerability Explanation and Resolution: Assists in identifying and fixing vulnerabilities, making the code more secure.
- Issue Management: Generates detailed issue descriptions and summarizes lengthy conversations, ensuring everyone is on the same page.
- GitLab Duo Chat: A chat interface that helps users get up to speed on project status, understand code, and learn about GitLab features.
Benefits and Target Audience
GitLab Duo is particularly beneficial for several key personas:- Development Teams: Developers can write code more efficiently with code suggestions, generate tests, and refactor code. Features like code explanations and fix code help in improving code quality.
- Security Teams: The ability to explain vulnerabilities and generate merge requests to resolve them enhances security. Features like “Explain This Vulnerability” and “Vulnerability Resolution” are particularly useful.
- Operations Teams: Tools such as root cause analysis for CI/CD job failures and value stream forecasting help in optimizing the deployment and operational phases.