Scaled Agile SAFe-DevOps Dumps

The primary benefit of value stream mapping is that it provides insight into organizational efficiency and value flow. Value stream mapping is a lean technique to analyze, design, and manage the flow of materials and information required to bring a product or service to a customer. It uses a system of standard symbols to depict various work streams and information flows, and to identify value-adding and non-value-adding activities. Value stream mapping helps the organization to gain insight into the current state of the delivery process, such as the lead time, cycle time, throughput, quality, and waste. This insight can help the organization identify bottlenecks, dependencies, handoffs, delays, and inefficiencies that affect the flow of value. Value stream mapping also helps the organization understand how the flow of value can be improved by applying the principles and practices of DevOps, such as culture, automation, lean flow, measurement, and recovery. By improving the flow of value, the organization can increase customer satisfaction, reduce costs, accelerate time-to-market, and enhance business agility

The correct order of activities in the Continuous Integration aspect is: Develop, Build, Test end-to-end, Stage. Continuous Integration (CI) is an aspect of the Continuous Delivery Pipeline that automates the development, testing, integration, and validation of new functionality in preparation for deployment and release. CI is the second aspect in the four-part Continuous Delivery Pipeline of Continuous Exploration (CE), Continuous Integration (CI), Continuous Deployment (CD), and Release on Demand. CI consists of four activities, as shown in Figure 1:

• Develop – This activity involves implementing stories by refining features from the ART Backlog, coding, testing, and committing the work product into the source control system. Testing in this activity tends to focus on unit and story-level testing and often requires test doubles to replicate other components or subsystems that are not readily available or easily tested.
• Build – This activity involves creating deployable binaries and merging development branches into the trunk. Building in this activity includes compiling, linking, packaging, and verifying the code and components. Building also involves applying code quality and security checks, such as static code analysis, code coverage, and code review.
• Test end-to-end – This activity involves validating the solution end-to-end, including the functional and nonfunctional aspects, such as performance, usability, reliability, and security. Testing in this activity requires integrating the code and components with other subsystems and services, and using test environments that resemble the production environment as much as possible. Testing also involves applying automated testing tools and frameworks, such as regression testing, integration testing, system testing, and acceptance testing.
• Stage – This activity involves hosting and validating solutions in a staging environment before production. Staging in this activity includes deploying the solution to a pre-production environment that mimics the production environment in terms of hardware, software, configuration, and data. Staging also involves applying final checks and verifications, such as smoke testing, exploratory testing, and user acceptance testing910

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In the Scaled Agile Framework (SAFe), after features are defined and designed during Continuous Exploration, they move into Continuous Integration. Here, they are further broken down into smaller, implementable parts known as user stories. These stories are then developed, tested, and integrated into the existing codebase. This process ensures that new features are developed in a systematic and efficient manner, with regular integration and testing to maintain quality and readiness for release.

In addition to Continuous Integration, two other aspects of the CDP are Continuous Deployment and Continuous Exploration. Continuous Deployment automates the migration of new functionality from a staging environment to production, where it is made available for release. Continuous Deployment enables the ability to release value at any time, in a sustainable way. Continuous Exploration focuses on creating alignment on what needs to be built, using design thinking and hypothesis-driven development. Continuous Exploration enables the discovery of the most valuable solutions for the customers and the enterprise

Continuous Deployment (CD) is an aspect of the Continuous Delivery Pipeline that automates the migration of new functionality from a staging environment to production, where it is made available for release. CD is a technical practice that enables the ability to release value at any time, in a sustainable way. CD is not the same as Release on Demand, which is the business decision to make the new functionality available to end users. Release on Demand is the final aspect of the Continuous Delivery Pipeline, which enables the delivery of value to the end user as fast as possible, based on market demand

Ensuring that security controls like threat modeling, application security, and penetration testing are in place throughout the Continuous Delivery Pipeline is an example of Continuous security monitoring. This skill involves the ongoing assessment and oversight of security measures within the pipeline to ensure that the software remains secure against potential threats at all stages of its development and deployment.

When preparing a DevOps backlog, prioritizing features using WSJF includes two factors: cost of delay and duration/job size. WSJF stands for Weighted Shortest Job First, which is a prioritization model used to sequence work for maximum economic benefit. WSJF is estimated as the relative cost of delay divided by the relative job duration. Cost of delay is the money lost by delaying or not doing a job for a specific time. It is a measure of the economic value of a job over time. Job duration is the time it takes to complete a job. Jobs that can deliver the most value in the shortest duration provide the best economic return. WSJF also considers other factors that contribute to the cost of delay, such as user and business value, time criticality, and risk reduction and/or opportunity enablement

Two of the technical practices that focus on Built-in Quality are pair work and test-driven development. Pair work is a collaborative technique where two developers work together on the same code, one writing the code and the other reviewing it. Pair work improves the quality of the code by reducing defects, increasing knowledge sharing, and enhancing creativity and problem-solving. Test-driven development (TDD) is a practice where developers write automated tests before writing the code, and then refactor the code until it passes the tests. TDD ensures that the code meets the requirements and specifications, as well as improves the design, readability, and maintainability of the code

Canary releases are used to allow incremental release of new functionality to customers. A canary release is a change management strategy for software releases that reduces the downtime and risk of deploying new versions of software. A canary release involves having two identical but separate environments: one is the active environment that serves the user traffic, and the other is the inactive environment that hosts the new version of the software. The release process consists of switching a small portion of the user traffic from the active environment to the inactive environment, after verifying that the new version is working properly. The portion of users who receive the new version are called canaries, as they serve as early indicators of the quality and performance of the new version. The canary release has several benefits, such as:

• It allows for fast and reliable rollback, in case of any issues or errors in the new version, by simply switching back to the active environment.
• It eliminates the need for complex and error-prone migration scripts, as the inactive environment can be prepared and tested in advance, without affecting the active environment.
• It enables testing and experimentation of the new version with a subset of users, by directing some user traffic to the inactive environment, before switching completely.
• It facilitates continuous delivery and deployment, by automating the switching process and reducing the transaction cost and risk of moving changes to production

Identifying the Minimal Marketable Feature (MMF) is part of Lean UX, which is a user-centric approach to designing and delivering products. An MMF is a small, self-contained feature that can be developed quickly and that delivers significant value to the user. It is the smallest unit of functionality that can be released to the market and generate feedback. Lean UX advocates for releasing MMFs as early and often as possible, to validate assumptions, learn from users, and iterate on the product

According to the SAFe DevOps Practitioner 6.0 study guide1, the Critical Flow Properties portion of the DevOps Transformation Canvas captures the flow properties that are most in need of improvement. Flow properties are the characteristics of a value stream that affect how well it delivers value to customers. The Critical Flow Properties portion identifies the flow properties that have the most impact on customer satisfaction and business outcomes, and prioritizes improvement actions accordingly. The Critical Flow Properties portion is based on data from monitoring systems, customer feedback, and business value analysis. Therefore, it captures the flow properties that are most in need of improvement for each value stream.

According to the SAFe DevOps Practitioner 6.0 study guide and handbook, test data management is one reason for test data management. This means that test data management helps teams ensure that the application under test has a consistent and reliable state, by automating the provisioning of data from various sources and formats. The handbook states that "Test data management is the process of automating provisioning of data to an application in order to set it to a known state before testing begins."1 Therefore, test data management enables teams to perform end-to-end testing with confidence and accuracy.

The purpose of value stream mapping is to visualize how value flows from concept to cash and to deliver incremental value in the form of working, tested software and systems. Value stream mapping helps to identify the current state of the value stream, the steps, activities, roles, and tools involved, and the delays, waste, and inefficiencies that can be eliminated or improved. It also helps to create a future state vision and an action plan for continuous improvement

According to the SAFe DevOps Practitioner 6.0 study guide1, root cause analysis is a technique that helps identify and eliminate the underlying causes of problems or defects in the Solution. Root cause analysis can be used to address impediments to continuous delivery by finding and fixing the root causes of issues such as delays, rework, waste, and errors. Root cause analysis can be performed during various phases of the PI, such as during the Iteration Retrospective, during the management review and problem-solving portion of PI Planning, or during Inspect & Adapt (I&A). However, the most effective time to use root cause analysis is during I&A, which is a significant event held at the end of each PI, where the current state of the Solution is demonstrated and evaluated. Teams then reflect and identify improvement backlog items via a structured problem-solving workshop. The result is a set of improvement backlog items that go into the ART Backlog for the next PI Planning event. Therefore, root cause analysis can help teams address impediments to continuous delivery by improving their performance and quality in the next PI.

The purpose of the blue/green deployment pattern is to deploy between an inactive and active environment. The blue/green deployment pattern is a change management strategy for software releases that reduces the downtime and risk of deploying new versions of software. The blue/green deployment pattern involves having two identical but separate environments: one is the active environment (blue) that serves the user traffic, and the other is the inactive environment (green) that hosts the new version of the software. The deployment process consists of switching the user traffic from the blue environment to the green environment, after verifying that the new version is working properly. The blue environment can then be kept as a backup or updated to become the next green environment. The blue/green deployment pattern has several benefits, such as:

• It allows for fast and reliable rollback, in case of any issues or errors in the new version, by simply switching back to the blue environment.
• It eliminates the need for complex and error-prone migration scripts, as the green environment can be prepared and tested in advance, without affecting the blue environment.
• It enables testing and experimentation of the new version with a subset of users, by directing some user traffic to the green environment, before switching completely.
• It facilitates continuous delivery and deployment, by automating the switching process and reducing the transaction cost and risk of moving changes to production

Under the Respond activity in the context of DevOps, the practice of Rollback is often included. Rollback is a key response mechanism used to quickly revert a system to a previous stable state in the event of a failure or issue in the production environment. This practice is critical for maintaining system stability and minimizing downtime.

The Continuous Exploration aspect in SAFe primarily supports the key stakeholder objective of aligning business and technology. This phase focuses on exploring market needs and defining solutions that deliver the most significant customer and business value within the constraints of technology and feasibility. It helps ensure that the development efforts are in sync with business goals and market demands, thereby fostering alignment between various stakeholders..

According to the SAFe DevOps Practitioner 6.0 study guide1, continuous deployment enables release continuously. Continuous deployment is an aspect of the Continuous Delivery Pipeline that automates the migration of new functionality from a staging environment to production, where it is made available for release. Continuous deployment allows teams to deploy small, incremental changes to production continually, enabling them to respond to market opportunities with the highest possible value in the shortest sustainable lead time. Continuous deployment also helps teams to reduce the risk of deploying faulty or incomplete code, as well as to optimize the performance and resource consumption of the system. Therefore, continuous deployment enables release continuously, which is a key business objective for delivering value to customers faster and more reliably.

The reason why it is important to take a structured approach to analyze problems in the delivery pipeline is that it helps ensure that actual causes of problems are addressed, rather than symptoms. A structured approach to problem analysis involves following a systematic and logical process to identify, define, and understand the root causes of a problem, and to propose and evaluate possible solutions. A structured approach can help avoid jumping to conclusions, making assumptions, or applying band-aid fixes that do not solve the underlying issues. A structured approach can also help involve the relevant stakeholders, collect and analyze data, prioritize and categorize problems, and communicate and document the findings and recommendations. Some examples of structured approaches to problem analysis are the 5 Whys, the fishbone diagram, the Pareto chart, and the PDCA cycle

According to the SAFe DevOps Practitioner 6.0 study guide1, scanning application code for security vulnerabilities is an important step in the Continuous Integration aspect of the Continuous Delivery Pipeline. Continuous Integration is the process of developing, testing, integrating, and validating new functionality in preparation for deployment and release. Continuous Integration helps teams to improve quality, reduce risk, and establish a fast, reliable, and sustainable development pace. Scanning application code for security vulnerabilities is one of the ways to ensure that the code meets the quality standards and requirements, and that it does not contain any errors, bugs, or vulnerabilities that could compromise the security or functionality of the Solution. Scanning application code for security vulnerabilities can be performed by using tools such as GitHub Advanced Security for Azure DevOps2, which uses CodeQL to identify vulnerabilities in various languages and frameworks. Therefore, scanning application code for security vulnerabilities is an important step in the Continuous Integration aspect of the Continuous Delivery Pipeline.

According to the SAFe DevOps Practitioner 6.0 study guide and handbook, dynamic code analysis is a technical practice that incorporates build-time identification of security vulnerabilities in the code. This means that the code is scanned for potential security risks during the compilation or execution phase, rather than during the testing phase. The handbook states that "Dynamic code analysis is a technique that identifies security vulnerabilities in the code during compilation or execution."1 Therefore, dynamic code analysis helps teams detect and fix security issues early in the development process.

According to the SAFe DevOps Practitioner 6.0 study guide1, when prioritizing improvement items, the steps with short Active Time and high %C&A in the future-state map should be the main focus. Active Time is the amount of time a step spends on performing work, while %C&A is the percentage of capacity utilization of a step. The future-state map shows how the Value Stream will look like after implementing improvements, based on customer feedback and business value. The improvement items are ranked by their impact on flow efficiency, customer satisfaction, and business agility. The steps with short Active Time and high %C&A in the future-state map indicate that they are bottlenecks or waste sources that need to be eliminated or reduced as soon as possible. Therefore, they should be prioritized for improvement actions.

Trunk-based development is a version control management practice where all developers work on the same trunk of shared code. The trunk is always in a releasable state, which means that at least once a day, developers must integrate their changes to the trunk. This is accomplished through short-lived feature branches related to project tasks. Trunk-based development is a common practice among DevOps teams and part of the DevOps lifecycle since it streamlines merging and integration phases. It also enables continuous integration, which is the practice of merging all development versions of a code base several times a day. Trunk-based development has several benefits, such as:

• It reduces the complexity and conflicts of merging long-lived branches
• It improves the quality and consistency of the code by enforcing frequent testing and validation
• It accelerates the delivery and deployment of new functionality by minimizing the transaction cost and risk
• It fosters a culture of collaboration and transparency among developers 

According to the SAFe DevOps Practitioner 6.0 study guide and handbook, the metric that reflects the quality of output at each step in the Value Stream is Percent Complete and Accurate (%C&A). This metric measures the relative cost of delay divided by the relative job duration, which indicates how efficiently the value stream delivers value to customers. The handbook states that "Percent Complete and Accurate (%C&A) is a metric that measures the relative cost of delay divided by the relative job duration."1 Therefore, %C&A helps teams identify and eliminate any waste or inefficiencies in their value stream.

Mapping the value stream helps accomplish two actions: to gain insight into organizational efficiency and to understand how the flow of value can be improved. A value stream is the series of steps that an organization uses to implement solutions that provide a continuous flow of value to a customer. Mapping the value stream involves identifying the steps, people, inputs, outputs, tools, and metrics involved in delivering value from concept to cash. By mapping the value stream, the organization can gain insight into the current state of the delivery process, such as the lead time, cycle time, throughput, quality, and waste. This insight can help the organization identify bottlenecks, dependencies, handoffs, delays, and inefficiencies that affect the flow of value. Mapping the value stream also helps the organization understand how the flow of value can be improved by applying the principles and practices of DevOps, such as culture, automation, lean flow, measurement, and recovery. By improving the flow of value, the organization can increase customer satisfaction, reduce costs, accelerate time-to-market, and enhance business agility

The Respond activity in the SAFe DevOps Health Radar is about proactively detecting and resolving production issues before they cause business disruption. It requires two skills: cross-team collaboration and version control. Cross-team collaboration enables faster resolution of incidents by involving the right people and teams. Version control enables tracking changes and restoring previous versions of the code or configuration if needed

According to the SAFe DevOps Practitioner 6.0 study guide and handbook, the Release activity is triggered by a business decision to go live. This means that the Solution is ready to be delivered to end users and customers, based on the validation and testing done in the previous activities. The handbook states that "The Release activity is triggered by a business decision to go live."1 Therefore, this activity involves releasing value to customers on demand, while also measuring and learning from the feedback.

According to the SAFe DevOps Practitioner 6.0 study guide1, feature toggles are useful for decoupling deployment from release. Feature toggles are a technique that allows code to be turned “on” or “off” without needing additional deployment. Feature toggles enable teams to experiment with different features, validate their assumptions, and learn from their failures without affecting the rest of the system. Feature toggles also help teams to reduce the risk of deploying faulty or incomplete code, as well as to optimize the performance and resource consumption of the system. Therefore, feature toggles are useful for decoupling deployment from release, which is an aspect of the Continuous Delivery Pipeline that releases new functionality immediately or incrementally based on business and customer needs2.