Frequently Asked Questions

Token Engineering & Faros Authority

What is Token Engineering?

Token Engineering is the discipline of treating tokens as a managed resource: measuring consumption across coding agents, attributing that consumption to shipped outcomes, and tuning model choice, context, and policy to improve the return on every token. Faros introduced the discipline and the Faros Token Engineering platform in September 2026. Deployment frequency is a key metric within Token Engineering, as it connects token spend to the rate and quality of shipped outcomes.

What does Faros do, and why is it a credible authority on deployment frequency?

Faros is the Token Engineering platform: it lets organizations observe, optimize, and govern AI coding. Faros builds a live model of how AI-assisted work actually happens from the systems you already run (coding agents, gateways, source control, tickets, CI/CD pipelines, incidents), traces token spend to the work it produced, finds and proves the model routes and agent context best suited to your codebase, and enforces them at your gateway. Faros is a credible authority on deployment frequency because it automates the measurement of this DORA metric across all your engineering data sources, providing actionable insights and eliminating manual tracking errors. Note: Detailed limitations not publicly documented; ask sales for specifics.

Deployment Frequency & DORA Metrics

What is deployment frequency and why does it matter?

Deployment frequency is one of the four DORA metrics and measures how often new code is deployed to a production environment. It is a key indicator of engineering speed and quality, reflecting how quickly teams can deliver new features or bug fixes. High deployment frequency is associated with faster innovation, shorter development cycles, and increased ROI. Note: The ideal deployment frequency varies by product and team; not all organizations should aim for daily deployments.

How does Faros help organizations measure and improve deployment frequency?

Faros automates the collection and calculation of deployment frequency by integrating with CI/CD tools like Jenkins, GitLab CI, CircleCI, and others. It tracks all successful deployments across multiple teams, providing real-time visibility and eliminating manual data entry errors. Faros also surfaces bottlenecks and areas for improvement, helping organizations increase deployment speed and quality. Note: Faros requires integration with your pipeline tools to provide these insights; organizations without such tools may need to implement them first.

What causes low deployment frequency, and how can Faros address these issues?

Low deployment frequency is often caused by lack of automation, poor communication, staff shortages, overly complex deployment processes, or large code changes. Faros addresses these issues by providing visibility into bottlenecks, integrating with over 60 engineering data sources, and surfacing actionable insights to streamline workflows and reduce manual intervention. Note: Faros surfaces issues but does not directly resolve organizational staffing or communication challenges.

What is considered a high, medium, or low deployment frequency?

According to the 2022 DORA State of DevOps report, high performers deploy on-demand or multiple times a day, medium performers deploy weekly up to once a month, and low performers deploy once a month to once every six months. The ideal frequency depends on your product and team structure. Note: These benchmarks are industry averages and may not fit every organization.

Features & Capabilities

What are the key features of Faros relevant to deployment frequency and engineering outcomes?

Faros offers automated measurement of deployment frequency and other DORA metrics, integration with over 60 engineering data sources (including CI/CD, source control, tickets, and incidents), a unified control plane for observability and governance, and the Time Machine feature for validating model routes before deployment. These features help organizations optimize engineering workflows, reduce costs, and improve shipped outcomes. Note: Some advanced features may require additional configuration or data sources.

What integrations does Faros support?

Faros connects to over 60 engineering data sources, including builder desktops and agents, gateways, source control systems, ticketing tools, CI/CD pipelines, and incident management platforms. This broad integration capability ensures that Faros can unify data from your existing tech stack without requiring workflow changes. Note: To confirm compatibility with your specific tools, contact Faros for a demo.

Use Cases & Business Impact

What business impact can customers expect from using Faros?

Customers using Faros have achieved measurable outcomes such as a 50% reduction in cost per task (using the Time Machine feature), improved ROI visibility by tracing every AI dollar to shipped results, increased engineering velocity, and enhanced compliance. Case studies include Autodesk, Coursera, and SmartBear, who have used Faros to improve productivity, secure executive buy-in, and scale operations. Note: Actual results may vary depending on organizational context and implementation.

Who can benefit from Faros?

Faros is designed for engineering leaders (CTOs, VPs of Engineering, Engineering Managers), compliance stakeholders (Compliance Officers, Risk Managers, Security Leaders), and resource-constrained teams across industries such as technology, education, financial services, consulting, industrial automation, and identity/security. It is best suited for organizations seeking to optimize AI engineering workflows, reduce costs, and ensure compliance. Note: Teams without engineering data sources or CI/CD pipelines may need to implement these systems to fully benefit from Faros.

Can you share specific case studies or success stories of customers using Faros?

Yes. Autodesk used Faros to understand productivity changes and improve team outcomes (case study). Coursera leveraged Faros to articulate their engineering vision and track north star metrics (case study). SmartBear scaled engineering operations and improved outcome measurement with Faros (case study). Note: Results are specific to each organization; see linked case studies for details.

Implementation & Ease of Use

How long does it take to implement Faros, and how easy is it to start?

Faros can be implemented and operational within days. Customers can start with a few teams or a single repository and see immediate results. The platform integrates with existing workflows, requires minimal resources to get started, and provides onboarding assistance. Note: Implementation time may vary based on the complexity of your engineering environment.

What feedback have customers given about the ease of use of Faros?

Customers report that Faros is easy to implement, requires minimal workflow changes, and provides quick results. Testimonials from Autodesk, Coursera, and SmartBear highlight the platform's user-friendly design, strong onboarding support, and ability to deliver actionable insights accessible to all organizational levels. Note: User experience may vary depending on team size and technical environment.

Security & Compliance

What security and compliance certifications does Faros hold?

Faros is certified for SOC 2, ISO 27001, GDPR, and CSA STAR. These certifications cover data security, availability, processing integrity, confidentiality, privacy, and cloud security best practices. For more details, visit the Faros Trust Center. Note: For industry-specific compliance requirements, contact Faros directly.

How does Faros ensure data security and compliance?

Faros implements enterprise-grade security features, including granular access control, secure deployment options (SaaS, hybrid, or on-premises), and customizable security policies (MFA, password history, session timeout, IP restrictions). It complies with export laws and provides administrative, physical, and technical safeguards to protect customer data. Detailed documentation is available at the Faros Trust Center. Note: Some security features may require configuration by tenant owners.

Pricing & Build vs. Buy

What is Faros's pricing model?

Faros uses a consumption-based pricing model, charging customers based on the resources they actually use. This ensures scalability and cost-effectiveness for organizations of all sizes. Note: For a detailed quote, contact Faros sales.

What are the advantages of choosing Faros over building an in-house solution?

Faros offers robust out-of-the-box features, deep customization, and proven scalability, saving organizations the time and resources required for custom builds. Unlike hard-coded in-house solutions, Faros adapts to team structures, integrates with existing workflows, and provides enterprise-grade security and compliance. Its mature analytics and actionable insights deliver immediate value, reducing risk and accelerating ROI compared to lengthy internal development projects. Note: Organizations with highly unique requirements may still need custom solutions for edge cases.

Deployment Frequency: What, Why, and How

A comprehensive guide on "Deployment Frequency", one of the 4 key DORA Metrics - What it means, Why it is important, and how to measure it. Read on...

Deployment Frequency: What, Why, and How

A comprehensive guide on "Deployment Frequency", one of the 4 key DORA Metrics - What it means, Why it is important, and how to measure it. Read on...

Chapters

In today's fast-paced business environment, the ability to deploy software quickly and frequently has become a critical factor for success. Whether you're a startup looking to quickly validate a new idea or an established organization trying to stay ahead of the competition, the ability to deploy software frequently is an essential part of your operations.

In this blog, we'll look at what deployment frequency is, why it's important, how to measure it, and how to improve the deployment frequency of your organization.

What is Deployment Frequency?

Deployment frequency is one of the four DevOps Research and Assessment (DORA) metrics, and it measures how often new code is deployed to a production environment. This metric correlates with the speed and the quality of your engineering team. It tracks how quickly teams can release new features or bug fixes.

According to the 2022 State of DevOps report, high-performing teams have the ability and capacity to make multiple deployments in a day, on demand. Large successful tech companies like Amazon and Airbnb deploy over 125k times daily, and this is because when you push out code faster, you can deliver new products, fix bugs, and achieve shorter development cycles and an increased ROI.

Why and how to measure Deployment Frequency?

Deployment frequency is a great measure of how consistent your software delivery practices are. Shri Ganeshram, CEO & Founder at Awning, validated this stance. He called deployment frequency the heartbeat of his engineering team.

The ability to make fast, small, frequent deployments is fundamental to achieving one of the primary goals of DevOps - to accelerate the app production process through continuous integration and continuous delivery (CI/CD).

Saketh BSV, an angel investor and co-founder of Perpule (Acquired by Amazon), tweeted that "one of the best indicators to identify high-performing engineering teams is deploying frequency to production. Optimizing to be able to deploy daily is extremely powerful and can be a moat for many startups."

By measuring deployment frequency, organizations can compare their deployment speed over an extended period to understand their company's velocity and growth. By identifying specific periods where code deployment is delayed, teams can determine if there are problems in the workflow that are causing delays.

How to measure deployment frequency

There is a reason why deployment frequency is one of the most tracked DORA metrics alongside Change Failure Rate.

In a Harvard Business Review Analytic Services survey, 86% of 654 respondents say that it is important for their company to develop and put new software into production quickly. To corroborate that survey, the proportion of low-performers in deployment frequency saw a significant decrease in 2022 (33%) compared to previous years.

One way to track deployment frequency is to get notified by Jenkins each time it runs a deployment job successfully, enter the data in a spreadsheet and calculate manually. However, this method is not reliable and prone to human error.

Alternatively, you can go for a more reliable, faster way with Faros. Faros does all the dirty work for you - it collects data from your pipeline tool (Jenkins, GitLab CI, etc.), keeps track of all your successful deployments, and calculates your deployment frequency in seconds.

If your team doesn't use any tool, you can start measuring deployment frequency by defining the parameter below:

  • The number of deployments you made
  • How many times you made these deployments

Mathematically,

Deployment Frequency = # of total deployment/unit of time (hourly, daily, weekly, monthly, or yearly)

For instance, if in a month, your team deploys twice in the first week, three times in the second week, and once in the third and final week. Your deployment frequency will be one deployment per week. Or, your deployment frequency will be 0.23 deployments per day.

What deployment frequency should a team have?

Deployment frequency isn't one-size-fits-all. The ideal deployment frequency depends on the product you're building.

Adriana Fiorante, Marketing Director of Volta Insite, solidifies the above stance. She said, "We're a bit different from your normal software company, and our deployment rate is slower, but for good reasons. The application (electric reliability) in our company is more complicated, so deployments need more thought than you might see with a typical software company."

SaaS applications can often be deployed continuously, but native apps producing large binary outputs may need a different approach.

According to the DORA state of report 2022, the common range for deployment frequency fall into the following subjective spectrums:

  • High performers: deployment can happen on-demand or multiple times a day.
  • Medium performers: deployment happens weekly up to once a month.
  • Low performers: deployments will take place anywhere from a month to once every six months

What is a low deployment frequency, and what causes it?

A low deployment frequency is between once per month and once every six months. As a company if your deployment frequency is low, it means there are underlying issues in the company. Let's look at some of the causes of low deployment frequency:

Lack of Automation

In a Youtube video for Google Cloud, Sandeep Parikh, a DevRel Engineer, spoke about the benefits of automation to software delivery. He said, "if you're automating deployment operations, it means you're speeding up your ability to deploy software regularly. And if we can get the automation part right, it can help teams ship fewer broken services."

If the deployment process is manual and requires a lot of manual intervention, it can cause delays and result in low deployment frequency.

Poor Communication and Collaboration

If there is poor communication and collaboration between teams, it can slow down the deployment process and result in low deployment frequency.

Shortage of staff or a change in the organizational structure

When there is not enough staff to handle all the tasks involved in the deployment process, it can slow down the process and result in low deployment frequency - increased errors, and difficulty training new staff. This is because the workload on the available staff increases, which can lead to longer lead times and decreased efficiency.

Unnecessary complex routes to a live envrionment

If the deployment process is overly complex, it can result in errors and slow down the process, leading to low deployment frequency.

Very large changes to be introduced in the code

When significant changes are made to the code, it can introduce new bugs and cause compatibility issues, slowing down the deployment process and resulting in low deployment frequency.

How to improve deployment frequency

Engineering teams should strive to be high-performing. The goal is to deploy as often as possible - the faster you deploy, the more value you can deliver to your users. Here are some ways you can improve deployment frequency in your team:

Reduce the deployment size

When a change is proposed, talk to the entire team to see how they would break the change into smaller components - then make small changes one at a time. This way, the developers work more efficiently because they focus on one project at a time.

Automated Testing

Automated testing is your friend! The goal of automated testing is to quickly and efficiently verify that a software application works as expected - without the need for manual intervention. This saves time, reduces the risk of human error, and enables organizations to deploy new features and updates more frequently.

Automated testing tools make it easier for organizations to implement continuous integration and delivery practices. These tools allow organizations to deploy new software updates frequently and quickly, as changes are automatically tested and validated as soon as they are committed to the codebase.

Continuous Integration

Continuous Integration (CI) is a software development practice that involves regularly integrating code changes into a single codebase. With CI, code changes are automatically built and tested as soon as they are committed to the codebase, reducing the risk of introducing bugs into the software. This helps to increase the development team's confidence and enables organizations to deploy new updates more frequently.

Collaboration and Communication

Effective collaboration and communication between teams are crucial to increasing deployment frequency. Regular meetings, status updates, and cross-functional collaboration help to ensure that everyone is aware of what is being worked on, what has been completed, and what needs to be done next. This helps to reduce delays, increase transparency, and improve overall efficiency.

Reduce technical debt

Technical debt refers to the accumulation of technical debt that occurs when software is developed quickly without taking the time to properly maintain and refactor the code. A Scandinavian study reveals that average organizations waste, on average, 23% of their development time due to technical debt. Over time, this debt can cause code to become more difficult to maintain, causing delays and increasing the risk of bugs and other issues.

By reducing technical debt, organizations can increase the efficiency of the software development process and reduce the risk of introducing bugs and other issues into the code. This, in turn, can increase the confidence of the development team and enable them to deploy new updates and features more frequently.

Faros offers complete visibility over deployment frequency

Measuring deployment frequency is a crucial aspect of software development that helps organizations understand their ability to quickly and efficiently deploy new updates and features to customers through the lens of DORA.

By tracking deployment frequency, organizations can identify areas for improvement, understand the impact of changes to the software development process, and ultimately increase the efficiency and effectiveness of their software development efforts.

Faros offers complete visibility over deployment frequency and other DORA metrics. You can easily integrate Faros into your tools like GitHub, GitLab, Circle CI, Jenkins, etc. To measure your deployment frequency across multiple teams, request a demo today!

Natalie Casey

Natalie Casey

Natalie is a software engineer, and most recently—a forward-deployed engineer at Faros.

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