SAFe-DevOps SAFe DevOps Practitioner Exam SDP (6.0) Questions and Answers

One of the measurable benefits of adopting DevOps practices and principles is that it results in faster lead time and more frequent deployments. Lead time is the time it takes from the moment a change is requested until it is delivered to the customer. Frequent deployments are the number of times a change is deployed to production. Both of these metrics indicate the speed and efficiency of the DevOps process, as well as the ability to respond to customer needs and feedback.  According to the State of DevOps Report 2020, high-performing DevOps teams have 208 times faster lead times and 106 times more frequent deployments than low-performing teams

According to the SAFe DevOps Practitioner 6.0 study guide and handbook, when development and operations do not collaborate early in the pipeline, surprises are found in deployment that lead to significant rework and delay. This means that the teams may not have a shared understanding of the quality, performance, and security requirements of the Solution, and may encounter issues that were not anticipated or tested.  The handbook states that " When development and operations do not collaborate early in the pipeline, surprises are found in deployment that lead to significant rework and delay. " 1  Therefore, it is important for teams to work together throughout the value stream to ensure continuous delivery.

According to the SAFe DevOps Practitioner 6.0 study guide 1 , a canary release is a type of release on demand that involves making a Solution available to any subset of users, such as a specific team, product, or region. A canary release allows the DevOps teams to test the Solution in a controlled environment and monitor its performance and feedback before rolling it out to the entire customer base. A canary release can help reduce the risk of introducing errors or failures into production and improve the quality and reliability of the Solution.

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.

According to the SAFe DevOps Practitioner 6.0 study guide 1 , 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 needs 2 .

According to the SAFe DevOps Practitioner 6.0 study guide and handbook, recovery is an element of CALMR. This means that recovery is the ability to restore the Solution to a desired state after a failure or incident.  The handbook states that " Recovery is the ability to restore the Solution to a desired state after a failure or incident. " 1  Therefore, recovery is one of the key aspects of DevOps excellence that enables continuous delivery.

According to the SAFe DevOps Practitioner 6.0 study guide and handbook, value flows through Continuous Integration in the Continuous Delivery Pipeline. This aspect involves merging code changes from multiple developers into a shared repository and running automated tests to ensure quality and functionality.  The handbook states that " Continuous Integration is the process of merging code changes from multiple developers into a shared repository and running automated tests to ensure quality and functionality. " 1  Therefore, Continuous Integration enables teams to deliver value faster and more reliably by reducing integration errors and conflicts.

According to the SAFe DevOps Practitioner 6.0 study guide 1 , Lean UX is used in Continuous Exploration to create a platform to continuously explore. Continuous Exploration is the process of creating alignment on what needs to be built, synthesizing Solution ideas into ART Backlog Features, and utilizing WSJF to prioritize a DevOps backlog. Lean UX is a team-based approach to building better products by focusing less on the theoretically ideal design and more on iterative learning, overall user experience, and customer outcomes. Lean UX design extends the traditional UX role beyond merely executing design elements and anticipating how users might interact with a system. Instead, it encourages a far more comprehensive view of why a Feature exists, the functionality required to implement it, and the benefits it delivers. By getting immediate feedback to understand if the system will meet the fundamental business objectives, Lean UX provides a closed-loop method for defining and measuring value. Therefore, Lean UX is used in Continuous Exploration to create a platform that enables teams to experiment with different hypotheses, validate their assumptions, and learn from their failures.

The statement that describes the Lean startup lifecycle is: Define the hypothesis, build a minimum viable product (MVP), continuously evaluate the MVP while implementing additional Features until WSJF determines work can stop. The Lean startup lifecycle is a highly iterative build-measure-learn cycle that has proven to be effective in optimizing the economic value of strategic investments. It consists of three learning milestones: MVP, tune the engine, and pivot or persevere. The MVP is the smallest possible experiment that allows the enterprise to test the assumptions and hypotheses of an epic or a large initiative. The tune the engine phase involves quickly adjusting and moving towards the goal based on the data and feedback gathered from the MVP. The pivot or persevere phase involves deciding whether to deliver additional value or move on to something more valuable based on the validated learning. The Lean startup lifecycle is supported by the SAFe Lean Startup Cycle, which provides guidance and tools for applying the Lean startup principles in the context of SAFe. The SAFe Lean Startup Cycle includes the following steps:

Define the hypothesis – This step involves creating an epic hypothesis statement that defines the initiative, its expected benefits, and its leading indicators.

Build the MVP – This step involves defining, building, and deploying the MVP that tests the hypothesis and delivers the minimum amount of value to the customer.

Evaluate the MVP – This step involves measuring and analyzing the results of the MVP against the leading indicators and the hypothesis.

Implement additional Features – This step involves developing and delivering additional features or capabilities that enhance the value proposition of the initiative, based on the learning from the MVP.

WSJF determines work can stop – This step involves using the Weighted Shortest Job First (WSJF) prioritization method to determine whether the initiative has delivered enough value to the customer and the enterprise, or whether it needs more investment or termination 3

According to the SAFe DevOps Practitioner 6.0 study guide 1 , 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.

According to the SAFe DevOps Practitioner 6.0 study guide and handbook, working in isolation on long-lived code branches can have negative consequences for the Continuous Delivery Pipeline. This includes making the trunk/main branch less stable and more prone to conflicts and errors.  The handbook states that " Working in isolation on long-lived code branches can make the trunk/main branch less stable and more prone to conflicts and errors. " 1  Therefore, it is recommended to use short-lived feature branches and merge them frequently into the trunk/main branch.

Two areas that should be monitored in the Release on Demand aspect to support DevOps and Continuous Delivery are the build status and the deployment cycle time. The build status is the measure of whether the code and components can be successfully compiled, linked, packaged, and verified into deployable binaries. The build status indicates the quality and consistency of the code and the readiness for deployment. Monitoring the build status helps to support the Release on Demand aspect in SAFe by providing valuable information for the following purposes:

To identify and fix any errors or defects that may prevent the code from being deployed or released

To ensure that the code meets the quality standards and security checks, such as static code analysis, code coverage, and code review

To verify that the code and components are integrated and merged correctly into the trunk

To track the progress and status of the features and capabilities that are being developed and delivered

The deployment cycle time is the measure of how long it takes to deploy the code and components from the source control system to the production environment. The deployment cycle time indicates the efficiency and reliability of the deployment process and the speed of delivery. Monitoring the deployment cycle time helps to support the Release on Demand aspect in SAFe by providing valuable information for the following purposes:

To optimize the deployment process and reduce the lead time and variability

To automate the deployment process and eliminate manual steps and errors

To align the deployment process with the market demand and release strategy

To evaluate the impact and value of the deployed features and capabilities  7

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

Value stream mapping metrics include calculations of three metrics: total process time, rolled % complete and accurate, and activity ratio. 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 metrics are used to measure the efficiency and effectiveness of a production process, and to identify areas for improvement. Some of the common value stream mapping metrics are:

Total process time: the sum of the process times for all the activities in the value stream. It measures how long it takes to complete a unit of work from start to finish.

Rolled % complete and accurate: the percentage of units that are completed and accurate at each step of the value stream, multiplied across all the steps. It measures the quality and reliability of the process output.

Activity ratio: the ratio of value-adding time to total lead time.  It measures the proportion of time spent on activities that create value for the customer, versus activities that do not

One aspect of the Continuous Delivery Pipeline is Continuous Integration. Continuous Integration (CI) is the practice of merging all development versions of a code base several times a day and verifying them with automated tests. CI helps to improve the quality and consistency of the code, and to accelerate the delivery and deployment of new functionality. 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: develop, build, test end-to-end, and stage 1 2

According to the SAFe DevOps Practitioner 6.0 study guide and handbook, the statement that illustrates the biggest bottleneck is B. WT = 10 days, AT = 0.5 day, %C & A = 100%. This means that the value stream has the longest lead time (WT), the shortest actual time (AT), and the highest relative economic value (C & A). These are the three metrics that are used to measure and optimize the value stream performance.  The handbook states that " The three metrics used to measure and optimize value stream performance are WT, AT, and %C & A. " 1  Therefore, a bigger bottleneck indicates a lower value stream efficiency and a higher waste or inefficiency.

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

According to the SAFe DevOps Practitioner 6.0 study guide and handbook, Weighted Shortest Job First (WSJF) is applied to backlogs to identify relative economic value. This means that the WSJF algorithm uses factors such as user and business value, time criticality, risk reduction and/or opportunity enablement, and job size to rank the jobs in the backlog based on their economic benefit.  The handbook states that " WSJF is estimated as the relative cost of delay divided by the relative job duration. " 1  Therefore, WSJF helps teams prioritize their backlog items for continuous delivery.

Agile Teams are responsible for ensuring quality is built into the code in SAFe. SAFe is a framework for scaling agile practices across the enterprise, based on the principles of Lean, Agile, and DevOps. SAFe organizes the enterprise into Agile Release Trains (ARTs), which are teams of Agile Teams that deliver value in a regular cadence. Agile Teams are the fundamental building blocks of SAFe, and they are cross-functional, self-organizing, and self-managing teams that deliver value in short iterations. Agile Teams are responsible for ensuring quality is built into the code in SAFe, by applying the following practices:

Test-first – Test-first is a practice that involves writing tests before writing code, to ensure that the code meets the requirements and standards, and does not introduce any defects or vulnerabilities. Test-first helps to improve the design and maintainability of the code, and to accelerate the feedback and validation process. Test-first can be implemented using various techniques, such as Test-Driven Development (TDD), Behavior-Driven Development (BDD), or Acceptance Test-Driven Development (ATDD).

Built-in quality – Built-in quality is a practice that involves applying quality standards and checks throughout the solution lifecycle, rather than inspecting quality after the fact. Built-in quality helps to prevent defects from escaping to downstream stages or customers, and to reduce the cost and risk of rework and waste. Built-in quality can be achieved using various methods, such as code quality and security analysis, code review, pair programming, refactoring, and continuous testing.

Continuous testing – Continuous testing is a practice that involves automating and executing tests at every stage of the Continuous Delivery Pipeline, to verify that the solution meets the functional and nonfunctional requirements and standards, and to detect and resolve any issues or defects as early as possible. Continuous testing helps to ensure the reliability and performance of the solution, and to support the delivery and deployment of value to the customer.  Continuous testing can be performed using various tools and frameworks, such as unit testing, integration testing, system testing, acceptance testing, performance testing, and security testing

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 guide 1 , 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.

One of the recommended ways to architect for operations is to implement feature toggles, which are mechanisms that allow developers to turn features on or off without redeploying the code. Feature toggles enable faster and safer deployments, as well as experimentation and testing in production. They also allow the operations team to control when and how new features are released to the end users, based on business needs and market demand.  Feature toggles can also be used to mitigate risks and roll back changes in case of errors or failures

According to the SAFe DevOps Practitioner 6.0 study guide 1 , one of the top advantages of mapping the current state of the delivery pipeline is to achieve a collective understanding and consensus around problems. Mapping the current state of the delivery pipeline is a technique that helps teams visualize and analyze their current processes, practices, and performance. Mapping the current state of the delivery pipeline enables teams to identify pain points, inefficiencies, and opportunities for improvement. Mapping the current state of the delivery pipeline also fosters collaboration, communication, and alignment among team members and stakeholders. By mapping the current state of the delivery pipeline, teams can gain a shared vision of their current situation, challenges, and goals. This can help them to reach a collective understanding and consensus around problems that need to be solved or opportunities that need to be pursued. Therefore, mapping the current state of the delivery pipeline is an advantage that can improve team cohesion and decision making.

According to the SAFe DevOps Practitioner 6.0 study guide 1 , one of the organizational anti-patterns that DevOps helps to address is teams that are isolated and working within functional areas (e.g., business, operations, and technology). This anti-pattern creates silos, conflicts, and inefficiencies that hinder the collaboration and integration needed for continuous delivery. For example, some teams may prioritize speed over quality, while others may prioritize security over innovation. Some teams may resist change and adopt outdated practices, while others may embrace new technologies and methodologies. These differences can lead to misalignment, duplication, and waste of resources that slow down the delivery pipeline and reduce the value to customers. Therefore, DevOps helps to break down the functional silos and enable cross-functional teams that work together to deliver value to customers faster and more reliably.

According to the SAFe DevOps Practitioner 6.0 study guide 1 , one of the main challenges of a DevOps transformation is when various groups in the organization have different directions and goals. This can create silos, conflicts, and inefficiencies that hinder the collaboration and integration needed for continuous delivery. For example, some groups may prioritize speed over quality, while others may prioritize security over innovation. Some groups may resist change and adopt outdated practices, while others may embrace new technologies and methodologies. These differences can lead to misalignment, duplication, and waste of resources that slow down the delivery pipeline and reduce the value to customers. Therefore, having a common vision, culture, and set of technical practices that support the SAFe CALMR approach to DevOps is essential for overcoming this challenge.