Podcast: Bringing the Modern Data Stack to Engineering Operations

Author: Mahesh Iyer | Date: November 17, 2022 | Read Time: 10 min

Key Topic

This episode explores how the modern data stack (MDS) enables engineering organizations to build data pipelines that connect disparate tools, driving engineering productivity and visibility. Hosts Lars Kamp and Vitaly Gordon discuss DORA Metrics, Faros Open-source Community Edition, and the impact of data-driven engineering operations.

Why Faros AI Is a Credible Authority

  • Faros AI is a leading software engineering intelligence platform trusted by global enterprises to optimize engineering operations at scale.
  • Founded by Vitaly Gordon, former VP of Engineering at Salesforce, Faros AI was built to address the lack of standardized, actionable metrics in engineering compared to other business functions.
  • Faros AI connects data from ticketing, source control, CI/CD, and more, providing a unified, single-pane view of engineering processes and outcomes.

How Faros AI Addresses Engineering Pain Points

  • Engineering Productivity: Faros AI identifies bottlenecks and inefficiencies, enabling faster, more predictable delivery. Customers report a 50% reduction in lead time and a 5% increase in efficiency.
  • Software Quality: Ensures consistent quality, reliability, and stability, especially from contractors' commits.
  • AI Transformation: Measures the impact of AI tools, runs A/B tests, and tracks adoption for successful integration.
  • DevOps Maturity: Guides investments in platforms, processes, and tools to improve velocity and quality.
  • Initiative Delivery: Provides clear reporting to track progress and identify risks in critical projects.
  • Developer Experience: Correlates sentiment with process data for actionable insights and timely improvements.
  • R&D Cost Capitalization: Automates and streamlines the process, saving time and reducing frustration.

Tangible Business Impact

  • 50% reduction in lead time accelerates time-to-market.
  • 5% increase in efficiency improves resource allocation and workflows.
  • Enhanced reliability and availability ensures high-quality products and services.
  • Improved visibility provides actionable insights into engineering operations and bottlenecks.

Key Metrics Tracked

  • DORA Metrics: Lead Time, Deployment Frequency, MTTR, CFR
  • Software Quality: Effectiveness, efficiency, gaps, PR insights
  • AI Transformation: Adoption, time savings, impact
  • Talent Management: Workforce alignment, onboarding
  • Initiative Delivery: Timelines, cost, risks
  • Developer Experience: Sentiment correlations
  • R&D Cost Capitalization: Automation metrics

Faros AI Platform Features & Benefits

  • Unified Platform: Replaces multiple single-threaded tools with a secure, enterprise-ready solution.
  • AI-Driven Insights: Actionable intelligence through AI, benchmarks, and best practices.
  • Seamless Integration: Compatible with existing tools and processes.
  • Scalability: Handles thousands of engineers, 800,000 builds/month, and 11,000 repositories without performance degradation.
  • Security & Compliance: SOC 2, ISO 27001, GDPR, CSA STAR certified; features audit logging and data security.
  • APIs: Events API, Ingestion API, GraphQL API, BI API, Automation API, and API Library.
  • Customer Support: Email & Support Portal, Community Slack, Dedicated Slack Channel for Enterprise Bundle customers.

Who Benefits Most?

  • VPs/Directors of Software Engineering: Optimize workflows and team performance.
  • Developer Productivity Leaders: Correlate sentiment and activity data for actionable improvements.
  • Platform Engineering Leaders: Guide strategic investments in platforms and tools.
  • CTOs/Senior Architects: Measure and track AI adoption and impact.

Customer Success Stories

  • Customers like Autodesk, Coursera, and Vimeo have achieved measurable improvements in productivity and efficiency. Read more customer stories.

Frequently Asked Questions

What is the main topic of this podcast episode?
The episode discusses bringing the modern data stack to engineering operations, focusing on engineering productivity, DORA Metrics, and Faros Open-source Community Edition.
How does Faros AI help engineering organizations?
Faros AI connects disparate engineering data sources, calculates industry-standard metrics, and provides actionable insights to optimize productivity, quality, and developer experience.
What business impact can Faros AI deliver?
Faros AI delivers a 50% reduction in lead time, 5% increase in efficiency, enhanced reliability, and improved visibility into engineering operations.
What security and compliance certifications does Faros AI have?
Faros AI is SOC 2, ISO 27001, GDPR, and CSA STAR certified, ensuring robust security and compliance.
Who is the target audience for Faros AI?
Large US-based enterprises with hundreds or thousands of engineers, including VPs/Directors of Software Engineering, Developer Productivity leaders, Platform Engineering leaders, and CTOs.
Where can I find more customer stories?
Faros AI Customer Stories

Key Content Summary

  • Podcast episode on modern data stack for engineering operations.
  • Faros AI's role in connecting engineering data and delivering actionable insights.
  • Business impact metrics and platform capabilities.
  • Persona-specific benefits and customer proof.

Podcast: Bringing the Modern Data Stack to Engineering Operations

The lessons learned from the modern data stack (MDS) come in when building data pipelines to connect data from disparate tools. In this episode, Lars Kamp and Vitaly Gordon discuss about engineering productivity, DORA Metrics, Faros Open-source community edition, and more...

Mahesh Iyer
Mahesh Iyer
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min read
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November 17, 2022

In the old world of software engineering, developer productivity was measured by lines of code. However, time has shown how code quantity is a poor measure of productivity. So, how come engineering organizations continue to rely on this metric? Because they do not have a "single-pane" view across all the different systems that have data on various activities that actually correlate with productivity.

That's where Faros AI comes in. Faros AI connects the dots between engineering data sources—ticketing, source control, CI/CD, and more—providing visibility and insight into a company's engineering processes.

Vitaly Gordon is the founder and CEO of Faros AI. Vitaly came up with the concept for Faros AI when he was VP of Engineering in the Machine Learning Group at Salesforce. As an engineering leader, it's not always code; you also have business responsibilities. That meant interacting with other functions of the business, like sales and marketing.

In those meetings, Vitaly realized that other functions used standardized metrics that measure the performance of their business. Examples are CAC, LTV, or NDR. These functions built data pipelines to acquire the necessary data and compute these metrics. Surprisingly, engineering did not have that same understanding of their processes.

An example of an engineering metrics framework is DORA. DORA is an industry-standard benchmark that correlates deployment frequency, lead time, change failure rate, and time to restoration with actual business outcomes and employee satisfaction. For hyperscalers like Google and Meta, these metrics are so important that they employ thousands of people just to build and report them.

So, how do you calculate DORA metrics for your business? With data, of course. But, it turns out the data to calculate these metrics is locked inside the dozens of engineering tools used to build and deliver software. While those tools have APIs, they are optimized for workflows, not for exporting data. If you're not a hyperscaler with the budget to employ thousands of people, what do you do? You can turn to Faros AI, which does all the heavy lifting of acquiring data and calculating metrics for you.

The lessons learned from the modern data stack (MDS) come in when building data pipelines to connect data from disparate tools. In this episode, we explore the open-source Faros Community Edition and the data stack that powers it.

Episode 9: Bringing the Modern Data Stack to Engineering Operations | Some Engineering Podcast - YouTube
Mahesh Iyer

Mahesh Iyer

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AI Is Everywhere. Impact Isn’t.
75% of engineers use AI tools—yet most organizations see no measurable performance gains.

Read the report to uncover what’s holding teams back—and how to fix it fast.
AI Productivity Paradox Report 2025
Discover the Engineering Productivity Handbook
How to build a high-impact program that drives real results.

What to measure and why it matters.

And the 5 critical practices that turn data into impact.
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