DevSecOps plays a significant role as both a mindset and a practice. It goes beyond merely automating security measures and instead fosters a culture that yields valuable outcomes for businesses. Consequently, DevSecOps raises an important question: While DevOps prioritizes software delivery performance, what should security prioritize to effectively support this objective?
To gauge success, it is crucial to identify the key metrics to monitor. Here, we outline these metrics and provide guidance on how to leverage them.
The term “DevSecOps” has recently emerged in the realm of security to describe the integration of DevOps and security practices. As we delve into the topic further, we will understand why this hybrid approach holds significant merit.
Traditionally, DevSecOps has primarily focused on the narrow interpretation of DevOps, emphasizing the automation of the build and delivery pipeline. This conventional view of DevSecOps centers on the software development lifecycle, aiming to incorporate testing as early as possible in the design process to safeguard the integrity and performance of the entire system.
Determining the Relevance of Security Metrics
Prior to delving into our compilation, it is crucial to acknowledge that the majority of security metrics tend to favor specific vendors, particularly those endorsing DevSecOps-related metrics. Unfortunately, due to the nature of the security testing market, metrics originating from individual security products are predominant. Vendors refrain from promoting metrics that cannot be measured by their own products.
Nevertheless, it is essential to understand that your chosen metrics shape your overall security posture. This is why businesses must exercise caution when selecting metrics that align with their security objectives, regardless of whether they embrace DevOps principles or not. Opting for a narrowly focused goal will inevitably lead to a limited security program.
The Importance of DevSecOps Metrics
In a broad sense, metrics refer to measurements that assess the performance, behaviors, or properties of something. Typically, metrics involve aspects such as time, rate, or volume.
Common metrics focus on measuring the time required to complete a task or the frequency of achieving a certain rate. When carefully considered and implemented, metrics offer decision-makers an objective understanding of present or potential situations, enabling them to make informed choices. These choices may include:
- Determining the stability and predictability of a process or service, distinguishing between a reliable and repeatable operation versus an unpredictable or erratic one.
- Evaluating the success or failure of a process or service, identifying any errors or disruptions encountered.
- Assessing whether goals are being met and if the process or service is generating the intended business outcomes.
- Comparing processes, services, and products to identify areas of improvement.
- Deciding how and when to manage change effectively.
Metrics have assumed a central role in software development, contributing to the refinement of software quality and the associated processes. With the advent of modern development tools and agile development toolchains like DevOps and DevSecOps, substantial volumes of data can be generated concerning the creation and operation of software products.
Data-driven metrics assist workload owners and stakeholders in achieving optimal business outcomes by addressing key questions such as:
- Is the software secure, operating reliably, and devoid of vulnerabilities?
- Is the software or infrastructure vulnerable to attacks?
- Is the software delivering the expected value and meeting business objectives?
- Is the infrastructure adequately supporting the software in terms of performance and reliability?
- Can the software or infrastructure be adequately supported and scaled?
- How do costs and risks factor into new development initiatives?
IT organizations leverage metrics to report on the number of software defects and the average time required to address these flaws, including identified vulnerabilities that necessitate patching. The nature and quantity of these issues can provide insights into software quality concerns, team performance, and adherence to development guidelines. Meanwhile, time-to-fix metrics offer insights into the efficiency and effectiveness of the underlying processes.
10 Key Metrics for Effective DevSecOps Measurement
In the realm of DevSecOps, businesses have the flexibility to adopt metrics that align with their operational objectives and goals. While the choice of metrics may vary, there is a set of 10 common metrics well-suited for DevSecOps practices:
Application change time:
This metric measures the duration between code commit and deployment in production. It serves as an indicator of development pipeline velocity, encompassing activities like building, testing, and releasing updates. Shorter change times imply more efficient pipelines. However, it’s crucial to consider this metric in conjunction with others, such as failure or rework rates, to gain a comprehensive understanding of the DevSecOps process.
Application deployment frequency:
This metric denotes the number of deployments to production within a specific time period. It should not be evaluated in isolation, but rather interpreted alongside other metrics. For instance, a lower deployment frequency might be acceptable for a mature product, while a higher frequency is common during the early stages of a product’s lifecycle. Additionally, a low deployment frequency coupled with high issue volume or long patch times could indicate underlying issues with the team or workflow, warranting further investigation.
The availability metric assesses the uptime or downtime of an application over a given time frame. It can be expressed as either time values or percentages. Availability holds significance as it pertains to the application’s service-level agreements, which the business must uphold.
Change failure rate:
This metric represents the number or percentage of failed production deployments that resulted in an aborted deployment or reverting back to the previous working version. A high failure rate, typically within a few percent, may indicate skill gaps within the team, unclear operational goals, deployment process issues, or inadequate understanding and management of the existing deployment infrastructure.
This metric quantifies the number of new features or functions deployed within a specific timeframe. It serves as a general indicator of development velocity. A higher change volume over time suggests a robust development effort. However, it must be considered in context. A high change volume alongside a low failure rate and low issue volume indicates successful development momentum. Conversely, a high change volume coupled with a high failure rate or significant issue volume may suggest challenges faced by the development team.
Issue resolution time:
This metric measures the average time required to resolve reported issues, encompassing the identification and resolution of software defects or configuration problems. The scope of this metric varies across businesses. For example, it can span from the creation of the initial help ticket to the deployment of the patch. Alternatively, it may focus on issues related to the deployment environment, such as the time needed to identify and rectify a server security configuration.
As the name suggests, issue volume reflects the number of issues reported by customers within a specific time period, such as the rate of help desk ticket creation. It is common to observe spikes in issue volumes during software updates or patches. However, a sustained high issue volume could indicate customer dissatisfaction or broader development problems that the team is struggling to address.
Mean time to recovery (MTTR):
This metric represents the duration between a failed deployment and the subsequent full restoration of production operations. Short MTTR figures suggest a capable DevSecOps team with strong control over the deployment environment, while longer MTTR figures indicate challenges in deployment preparation, workflows, and operational knowledge. Prolonged MTTRs can have negative implications for the business and often trigger significant responses from business leaders.
Time to patch:
This metric measures the time interval between identifying a vulnerability in the application and successfully deploying a patch in the production environment. While similar to issue resolution time, this metric provides more granular insight into the DevSecOps team’s ability to identify and rectify software defects promptly.
Time to value:
This metric captures the time span between receiving a feature or function request and realizing the associated business value, such as enhanced software capabilities, increased competitiveness, or revenue generation. Time to value is a subjective metric that needs to be tailored to specific business goals. However, every business strives for shorter timeframes in order to maximize value realization.
By monitoring and analyzing these 10 key metrics, businesses can gain valuable insights into their DevSecOps processes, identify areas for improvement, and optimize their operations accordingly.
Tools for Collecting and Analyzing DevSecOps Metrics
Organizations rely on a variety of tools to collect and analyze DevSecOps metrics. These metrics are derived from different stages of the development pipeline. Below are examples of suitable tools used in the process:
- Build and Release Tools:
- Azure DevOps
- Octopus Deploy
- Configuration Management Tools:
- Test Automation Tools:
- Deployment and Monitoring Tools:
- SolarWinds AppOptics
By leveraging these tools, organizations can gather comprehensive metrics. However, it’s important to note that not all metrics of interest may be natively supported by the existing DevSecOps toolset. Therefore, organizations need to review their current tools, assess the native metrics supported by each tool, and determine if and how they can configure custom metrics specific to their business needs. In some cases, additional customization or the adoption of new tools may be necessary to support unique or business-specific metrics, such as time to value.
DevSecOps Metrics FAQs
DevSecOps refers to the integration of DevOps and security practices. It emphasizes the automation of the build and delivery pipeline while promoting a culture of security. It is important because it helps organizations ensure the integrity and performance of their systems by incorporating testing early in the design process and prioritizing security alongside software delivery.
Security should prioritize key metrics that monitor the performance and effectiveness of DevSecOps practices. By measuring metrics such as application change time, application deployment frequency, availability, change failure rate, change volume, issue resolution time, issue volume, mean time to recovery (MTTR), time to patch, and time to value, security teams can assess the efficiency, reliability, and value generation of the DevSecOps process.
Businesses should exercise caution when selecting security metrics and avoid relying solely on metrics promoted by specific vendors. Metrics should align with their security objectives and provide a comprehensive view of their security posture. Narrowly focused goals can limit the effectiveness of the security program. It is important to choose metrics that support the organization’s overall security goals, regardless of whether they follow DevOps principles or not.
Metrics provide objective measurements of performance, behaviours, or properties of software and processes. They offer decision-makers insights into the stability, predictability, success or failure, goal achievement, and areas of improvement within the software development and DevSecOps processes. Metrics help organizations make informed choices, manage change effectively, enhance software quality, address vulnerabilities, and align software with business objectives.
The 10 key metrics for effective DevSecOps measurement are:
Application change time
Application deployment frequency
Change failure rate
Issue resolution time
Mean time to recovery (MTTR)
Time to patch
Time to Value
Organizations can use various tools to collect and analyze DevSecOps metrics. Examples include build and release tools like Git, Azure DevOps, Octopus Deploy, and Jenkins; configuration management tools like Ansible, Puppet, and Chef; test automation tools like Selenium, Worksoft, and Kobiton; and deployment and monitoring tools like Nagios, Splunk, and SolarWinds AppOptics.