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  • HIPAA & HITRUST
  • TOGAF EA Framework
  • Databricks-Fabric-Snowflk
  • Kubernetes - Docker
  • Technical Full Stack 2025
  • RAG / Vector DB LangChain
  • ML & Transformers
  • Graph Neural Networks
  • AEM Jira SQL Python
  • No-Code AI Worflows
  • Model Context Protocol
  • Azure, AWS, GCP, GitHub
  • AI Agents
  • APIs / Tools
  • Azure AI Foundry
  • Azure Data Fabric
  • Transform Sub-quadractic
  • TensorF PyTorch LangChain
  • AGI - SAI - 2027

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Jira vs Rally

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 Jira | Tray Documentation (Jira Query Language, Slack AI Agent...)


 Jira vs Rally: What Are the Main Differences? 


 Jira | Issue & Project Tracking Software | Atlassian 


 Jira | Tray Documentation 


 Story vs Epic vs Task: What's the difference in Jira? - YouTube 


 What is Scrum? The Scrum Methodology Explained 


 The difference between Kanban and Scrum 


 Explore apps for Atlassian products | Atlassian Marketplace 


 Master Your Workflow with Jira Kanban Boards | Atlassian 


Rally and Jira are two prominent project management tools designed to support agile methodologies and help teams refine their workflows. Both tools have their unique strengths and cater to different types of organizations and project needs.


Key Differences


Flexibility and Customization


Jira is known for its flexibility and extensive customization options. It allows teams to create custom workflows, integrate with over 3,000 apps, and use various agile methodologies such as scrum, kanban, and hybrid approaches. This makes Jira suitable for a wide range of projects beyond software development, including business process management and cross-functional team collaboration.


Rally, on the other hand, focuses on providing extensive agile project management features for large enterprises. It excels in enterprise environments with tools for capacity planning, aligning work with strategic business goals, and supporting iterative development and continuous improvement. Rally's features include portfolio kanban, release tracking, and risk management, making it ideal for large organizations deeply embedded in agile methodologies.


Pricing


Jira offers transparent pricing with multiple tiers, including a free tier for up to 10 users, and standard and premium tiers with clear pricing information2. This makes Jira accessible to teams of all sizes, not just enterprises.


Rally does not list its pricing information publicly, requiring potential clients to contact Broadcom's sales teams for a quote2. This approach can be tailored to clients' specific needs but may be inconvenient for those seeking immediate pricing information.


Integrations


Jira has a vast integration ecosystem with over 3,000 apps and add-ons available through the Atlassian Marketplace1. This broad range of integrations adapts Jira to many project types and enhances its functionality across various industries2.


Rally offers around 40 integrations, including tools like CloudBees, Git, and Jenkins2. While this is sufficient for many enterprise needs, it is not as extensive as Jira's integration capabilities.


Security

Both tools offer robust security features, but Jira provides more comprehensive options, especially in its Premium and Enterprise plans. These include advanced admin controls, SSO, SCIM for user provisioning, encryption, data residency options, and more2. Rally also offers enterprise-grade security features, including data encryption and compliance with industry standards2.


Collaboration

Both Jira and Rally support collaboration with features like real-time status tracking, custom dashboards, and integration with communication tools like Slack2. Jira's integration with Atlassian products like Confluence and Bitbucket further enhances collaboration, providing a unified environment for teams to work together seamlessly2.


Conclusion

Choosing between Rally and Jira depends on your organization's specific needs and preferences. 


Rally is better suited for large-scale agile implementations with a strong emphasis on aligning work with strategic business goals. 


Jira offers extensive flexibility and customization, making it suitable for a wide range of project types and industries2. Consider your team's size, project requirements, and integration needs when deciding which tool to use.

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Rally vs. Jira: Feature comparison

Agile support


Winner: Tie

Rally provides robust support for agile methodologies, including scrum and kanban boards. With Rally, your teams can plan sprints, manage backlogs and track projects and portfolio progress with real-time updates. The agile metric charts offered by Rally include Throughput, Flow Efficiency, Flow Load, Flow Time and Flow Predictability. With such agile boards, Rally can handle large volumes of tasks and users, doubling down on its suitability for enterprise-level agile implementations​.


In addition to being highly customizable, Jira’s agile boards can be integrated with sprint planning tools like version management, backlog grooming, story points and scrum boards, among other capabilities. With Jira, you’ll get scrum, kanban and hybrid methodologies with detailed tracking and reporting capabilities that include agile report features like cumulative flow diagrams and control charts​.

The combination of customizability and out-of-the-box nature of Jira makes it an attractive option for software development teams or teams with similar agile workflows.


 

Gantt charts

Winner: Jira

Although it’s not outrightly labeled a Gantt chart, Rally has a Timeline view that gives its users the ability to visualize their portfolio items over a time-based view. Its Timeline view can be used to prioritize and schedule work, so you can visualize the plan data of multiple teams and how work relates across multiple schedules and teams.


Jira also offers a Timeline view as one of two native Gantt chart capabilities. The Timeline view offers Gantt charts for team-level management and is available in all plans, including the free plan. You can use it to visualize the timing, duration and dependencies of the tasks in your projects.

The second Gantt offering, known as Plans, is for organization-level management, allowing for much more complex visualization of organization-wide initiatives, dependency tracking and priority management. However, it’s only available from Jira Premium onwards.


 

Task management

Winner: Tie

Rally is great for task management, particularly for large teams. Rally describes itself as a single system of record for enterprise agile management, meaning its approach to task tracking, sprint planning and backlog management is not only detailed but also comprehensive. Its robust reporting and analytics tools provide lots of insights into team and portfolio performance and project progress. As a result, it’s highly suitable for complex, large-scale projects​.


Integrations

Winner: Jira

Even though Rally offers third-party integrations, they aren’t as vast as Jira’s. It integrates with about 40 tools, including CloudBees, Jira, Git and Jenkins ServiceNow, though a number of its integrations are through OpsHub.

On the other hand, Jira is known for its extensive integration capabilities, offering over 3,000 apps and add-ons through the Atlassian Marketplace. This broad range of integrations adapts Jira to many project types. Some key integrations include development tools like GitHub, Bitbucket and Jenkins, as well as business applications such as Slack, Trello, Salesforce and Confluence.


Security

Winner: Jira

Rally offers enterprise-grade security features, including data encryption, secure user authentication and compliance with industry standards like AICPA SOC, ​​ISO/IEC 27001:2013 and FISMA. It provides robust security controls suitable for large organizations handling sensitive data​.

On the other hand, Jira provides comprehensive security features, particularly in its Premium and Enterprise Plans. These include permissions, advanced admin controls, SSO, SCIM for user provisioning, encryption, data residency options and MDM, among others. Jira’s Enterprise plan also provides additional security measures such as audit logs, data BYOK encryption and more, opening up different levels of security for teams and organizations with different data security needs.


Collaboration

Winner: Tie

Rally acts as a central hub for teams to collaborate on planning, prioritizing and tracking work and other agile best practices at a synchronized pace. Its users can visualize their work across views like list, timeline and board. It also offers features such as real-time status tracking, custom dashboards and iteration planning. It integrates with tools like Slack and GitHub to streamline communication and data flow.

Jira supports collaboration with its detailed issue and project-tracking features, customizable workflows and real-time notifications. Integrations with Atlassian products like Confluence and Bitbucket further enhance collaboration, which provides a unified environment for teams to work together seamlessly​.


Choose Rally if . . .

  • You need a focused agile solution.
  • Your organization is of enterprise scale.
  • You need enterprise-grade security.
  • You need enterprise-level capacity planning tools.

Choose Jira if . . .

  • You prefer straightforward pricing information.
  • Your teams use agile workflows but aren’t enterprise-level.
  • You want highly flexible and customizable agile workflows.
  • You prefer a vast integration ecosystem.



Epics, Stories, and Tasks

 

In Jira, Epics, Stories, and Tasks are key components used to organize and manage work. Each serves a distinct purpose and operates at different levels of granularity within a project.


Epic

An Epic represents a large body of work that can be broken down into smaller, manageable pieces such as Stories or Tasks. It is typically goal-oriented and spans multiple sprints or iterations. Epics are used to track high-level objectives or features that require significant effort and coordination across teams.


Example: If you're launching a new website, the Epic could be "Launch New Website," encompassing tasks like designing the layout, writing content, and developing the site.


Story

A Story, or user story, focuses on delivering value to the end user. It describes a specific feature or functionality from the user's perspective, often following the format: "As a [user], I want [capability], so that [value]." Stories are smaller than Epics and are typically completed within a single sprint.

Example: For the website launch, a Story could be "As a user, I want a responsive homepage so that I can access it on any device."


Task

A Task is a specific piece of work required to complete a Story or Epic. It can also stand alone for non-user-facing work. Tasks are more granular and focus on actionable steps that contribute to the overall project.

Example: For the Story about a responsive homepage, Tasks might include "Design the homepage layout" and "Implement responsive CSS."


Key Differences

  • Scope: Epics cover large goals, Stories focus on user-centric features, and Tasks handle specific actions.
  • Timeframe: Epics span multiple sprints, Stories are completed in one sprint, and Tasks take a few days or less.
  • Hierarchy: Epics are at the top, followed by Stories and Tasks. Subtasks can further break down Tasks or Stories.


Practical Use

  • Use Epics to manage large projects or features, such as "Migrate to the cloud."
  • Use Stories to define user-focused requirements, like "Enable users to reset passwords."
  • Use Tasks for technical or operational work, such as "Set up database backups."

Understanding these distinctions helps teams plan effectively, prioritize work, and maintain clarity in project management.


 Effectively managing Jira Epics involves clearly defining epics, breaking them into manageable user stories, prioritizing based on business value, visualizing progress with Jira features, and fostering team collaboration through regular reviews and automation.


1. Understand What an Epic Is

An Epic in Jira represents a large body of work or a significant feature that can be broken down into smaller user stories or tasks. It typically spans multiple sprints and helps organize complex work into manageable parts, aligning efforts with strategic goals.


2. Create and Define Epics Clearly

  • Naming: Give your epic a clear, descriptive name that reflects its purpose.
  • Summary & Narrative: Add a meaningful summary and description explaining the goal, scope, and expected outcome.
  • Scope boundaries: Define what the epic covers to prevent scope creep.
  • Establish clear completion criteria or definitions of done to know when an epic can be closed.


3. Break Down Epics Into Stories

  • Divide epics into smaller, actionable user stories or tasks.
  • Each story should represent a testable feature or deliverable achievable within a sprint.
  • Use story points or other estimation methods to assess effort and complexity.
  • Group related stories for easier tracking and prioritization.


4. Prioritize Based on Business Value

  • Use prioritization frameworks like MoSCoW or weighted scoring.
  • Focus on high-impact stories first, aligning with business goals.
  • Maintain a prioritized epic backlog to plan sprint work effectively.


5. Visualize and Track Epic Progress

  • Use Jira’s Epic Panel, Timeline view, and Roadmaps to plan and monitor epics.
  • Set start and due dates to manage timelines.
  • Utilize Jira reports like Epic Report, Burnup Charts, Velocity Charts, and Cumulative Flow Diagrams to visualize progress and identify bottlenecks.
  • Use swimlanes on boards grouped by epics for clearer work segmentation.


6. Collaborative Management and Regular Reviews

  • Hold regular backlog refinement sessions to update priorities, add acceptance criteria, and remove obsolete items.
  • Foster open communication via daily standups and collaborative tools within Jira.
  • Assign clear ownership of epics and stories for accountability.


7. Automate Routine Tasks

  • Use Jira Automation to:
    • Auto-close epics when all child issues are completed.
    • Notify stakeholders about status changes.
    • Update fields and transitions automatically to reduce manual effort


8. Close Epics Properly

  • Mark epics as "Done" once the main objectives are completed.
  • It’s acceptable to leave irrelevant or deprioritized child items open.
  • Conduct retrospectives to capture lessons learned for future epics.


Bonus Tips

  • Avoid making epics too large or too small; aim for meaningful bodies that deliver value within a reasonable timeframe (often 6 months to a year).
  • Use custom fields and labels for enhanced categorization.
  • Leverage Jira add-ons like Structure or Salto to create hierarchical views for deeper insight.
  • Review and update your epic roadmap regularly to keep everyone aligned.


By following these best practices, Jira Epics become powerful tools that streamline agile project management, enhance visibility, and improve team collaboration, ensuring successful delivery of large 


 Jira Task vs Story vs Epic: Unraveling the Hierarchy of Agile Work Items 



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AEM

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 Adobe Experience Platform Agent Orchestrator | AI Orchestration Tool 

 Product Support Agent | Adobe Experience Platform 



Adobe Experience Manager (AEM) is a comprehensive content management system (CMS) that optimizes the authoring, management, and delivery of content and digital media. Key features include:


  • Centralized Dashboard: A sleek interface that provides a high-level view of all projects. 1

  • Cloud Service: A scalable platform that supports omnichannel content delivery. 1

  • Digital Asset Management: Integrates digital asset management with content management to enhance brand engagement. 1

  • High-Performance Page Creation: Empowers marketers and developers to create high-performance pages across various digital properties. 1

  • Dual Functionality: Functions as both a CMS and a digital asset management system. 1

  • AEM consistently outperforms its competitors by bridging the gap between content creation and personalized customer experiences. 1

  • 5 Sources

AdobeAdobe Experience Manager — what it is and how it worksAdobeAdobe Experience ManagerView all
 

AEM Agents

  Engage human-centered AI with Adobe Experience Platform Agents 


Human creativity isn’t going anywhere — and we’ve always understood this fundamental truth at Adobe. That’s why we believe the real opportunity for enterprise AI is not to replace talent, but to scale your best talent. Despite the noise around AI taking over, the Adobe 2025 AI and Digital Trends report revealed that 69% of senior executives plan to invest more in talent.

For decades, we’ve built the technology that the world’s leading brands use to tell their stories, express their identities, and design experiences that stand out. With the announcement of our Adobe Experience Platform Agents at Adobe Summit 2025, our human-centered AI approach is expanding to unlock more potential for creativity and strategic marketing. By integrating generative models and new agent capabilities into everyday creative and marketing tools, we're enabling teams to enhance their expertise and skills while providing more opportunities to create customer experiences with greater creativity, strategy, and innovation.


How teams engage with each other is evolving.

Creative and marketing teams are being asked to do more — both as individual teams and close partners. And with new AI advances, teams are seeking ways to gain new efficiencies and enhance customer intelligence.

Adobe Agents are purpose-built for how creative, marketing, and technology teams collaborate. Powered by Adobe Experience Platform, these agents draw from customer data and content to ensure every action they take is smart, relevant, and expertly aligned with business goals.

They do more than just handle tasks. Thanks to Adobe Experience Platform Agent Orchestrator, they can coordinate across systems and workflows to help teams deliver outstanding experiences faster than ever. Best of all, these agents are flexible, letting you tailor their capabilities to meet the unique needs of your team or industry.


Adobe Experience Platform Agents

Grounded in real-time customer experience data and content.

Agents are powered by Adobe Experience Platform and its semantic understanding of journeys, content, behavior, and performance signals. Actions are context-aware and aligned with business goals.

Designed for orchestration at scale.

Agents do not operate in silos. Through Adobe Experience Platform Agent Orchestrator, they coordinate across workflows, applications, and systems to deliver results in real time.

Extensible by design.

The agent framework supports a wide range of use cases. Customers, partners, and developers can build, configure, or integrate agents to match the specific needs of their teams and industries.

Human-AI collaboration is the future.

We understand that when it comes to orchestrating customer experiences, collaborating with other business units is only one aspect of the work. We envision a future where human-AI collaboration supports unprecedented potential and empowers individual practitioners to push boundaries as they execute their work better and faster.

With Experience Platform Agents, this vision becomes a reality, as teams are equipped with trusted AI partners that collaborate seamlessly, offer proactive intelligence, and act with precision across dynamic workflows. The following five foundational pillars are redefining how creative and marketing teams create, strategize, and innovate allowing them to transform customer experiences with new, bold ideas.

1. Trusted partnership.

Experience Platform Agents act as trusted teammates by working alongside marketing and creative teams to surface insights and suggestions while acting within designated Adobe workflows. For example, the Data Insights Agent transforms complex data into rich visualizations via natural language queries that practitioners can explore, refine, and adjust in real time, keeping humans in control while accelerating impact.

2. Proactive, always-on intelligence.

Imagine agents that never rest, continuously monitoring data, audience, and campaign metrics to proactively surface alerts and insights before problems escalate. Far from replacing marketers, these agents ensure their work remains efficient and impactful. For example, the Audience Agent will be able to identify duplicate, overlapping, or stagnant segments and deliver notifications directly to marketers, who can then act swiftly and effectively.

3. Action-oriented execution.

Experience Platform Agents go beyond suggestions — they take action while always keeping practitioners in control. Under the user’s oversight, the Site Optimization Agent can detect issues such as engagement drop-offs or SEO inefficiencies and implement fixes seamlessly within the site management experience.

4. Goal-driven precision.

Every agent is specifically skilled and focused on executing goal-driven workflows with unmatched precision. Take the Adobe Content Production Agent — currently under development — that will interpret marketing briefs to generate audience- and channel-relevant content, build comprehensive understandings of your brand for consistency, and provide real-time feedback so pieces stay sharp and on-brand.

5. Multi-agent collaboration.

The power of Experience Platform Agents multiplies when they work together. Leveraging upcoming updates in Experience Platform Agent Orchestrator, agents will coordinate across workflows, share context, and align with user goals. For instance, the Adobe Data Insights Agent identifies bottlenecks in the journey canvas and will be able to partner with the Journey Agent, once available, to recommend adjustments and simulate potential optimizations — mirroring the dynamics of high-performing, collaborative, human teams.

AI teams can trust.

Responsible AI isn’t a feature of Adobe’s AI solutions. It’s the foundation.

Adobe takes a practical approach to put the right guardrails and safeguards in place so that teams can confidently work with all types of AI. When it comes to agentic AI, data safety, precision, and transparency are at the core of everything we do. We believe that when working with agentic AI, all business data should be safeguarded with strict security and privacy controls, AI should deliver precise answers, and the technology should be explainable and trustworthy. As each Experience Platform Agent becomes available, these will remain the foundation for their development.

Learn how to evaluate AI solutions for responsibility and how to encourage the adoption of AI solutions in your organization in our guide, The AI Inflection Point.

Creativity + Marketing + AI.

Experience Platform Agents are built for a new era of work where AI is powering creativity and marketing execution to help teams move faster, work smarter, and stay in control. Agentic AI will never replace human expertise. It’s here to help experts create more capacity so they can focus on creative solutions that will drive greater business impact than ever before.

The future of AI is human led. Adobe Agents make that possible — and we’re just getting started.

Learn how Adobe Experience Platform Agents are shaping a future where human ingenuity and AI innovation converge.

Anoop Sahgal is a product marketing executive with experience leading go-to-market strategy, messaging, and sales enablement and currently serves as Head of Product Marketing for AI across Adobe Experience Cloud, and is responsible for the enterprise AI narrative across Adobe’s Experience Cloud portfolio.



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Jira -JQL

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JQL functions | Jira Cloud | Atlassian Support 


jira jql functions - Search 


Jira Query Language (JQL) functions are powerful tools that allow you to perform advanced searches and filtering in Jira. Functions in JQL are typically used to dynamically retrieve data based on specific criteria. Here's a quick overview:


Key Features of JQL Functions

  1. Dynamic Queries: Functions can return results that change over time, such as issues updated recently or assigned to a specific user.
  2. Flexibility: They can be combined with fields, operators, and keywords to create complex queries.
  3. Parentheses: Functions are written as a word followed by parentheses, which may include parameters.


Commonly Used JQL Functions

Here are some examples of built-in JQL functions:

  1. currentUser()
    • Returns issues assigned to or reported by the currently logged-in user.
    • Example: assignee = currentUser()

  1. membersOf("groupName")
    • Finds issues assigned to members of a specific group.
    • Example: assignee IN membersOf("developers")

  1. startOfDay(), endOfDay(), startOfWeek(), etc.
    • Used for date-based queries.
    • Example: created >= startOfWeek()

  1. issueHistory()
    • Retrieves issues that the current user has interacted with.
    • Example: issueHistory()

  1. project()
    • Returns all issues in a specific project.
    • Example: project = "MyProject"

  1. filter("filterName")
    • Uses a saved filter to retrieve issues.
    • Example: filter = "My Saved Filter"


Advanced JQL Functions (e.g., ScriptRunner)

If you use plugins like ScriptRunner, you can access additional custom JQL functions, such as:

  • hasSubtasks()
  • linkedIssues(issueKey)
  • epicLink()

These functions allow for even more granular control over your queries.


Tips for Using JQL Functions

  • Combine functions with operators like AND, OR, and NOT for complex queries.
  • Use parentheses to group conditions for clarity.
  • Save frequently used queries as filters for quick access.

Let me know if you'd like help crafting a specific JQL query! 😊


EditPerform AnalysisTime complexitySpace complexityChange LanguagePythonC++JavaC#JavaScriptTesting ToolsGenerate test dataIntegrate test casesMore ActionsPerform code reviewExplain the codeAdd error handlingMake code compilableRecreateCopyExport 


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