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• Antithesis – verify your system’s correctness without human review or traditional integration tests – and avoid bugs or outages.
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• Sentry – application monitoring software considered “not bad” by millions of developers
—
Kelsey Hightower went from a self-taught technician installing DSL modems to becoming one of Google’s elite Distinguished Engineers, whom the CEO of Microsoft personally tried to recruit. Hightower’s career achievements are rooted in hard work and self-directed learning, and today he’s one of the most influential voices in modern infrastructure, through his talks, open source work, and writing.
In this episode of The Pragmatic Engineer podcast, Kelsey and I cover his unconventional path into tech and the lessons he’s learned during three decades in the industry. We discuss his entrepreneurial years, building a reputation through open source, the rise of containers and Kubernetes, and his time at Google during one of the most consequential periods in cloud computing.
He recounts how a job offer from a big tech giant led to the biggest raise of his career, what prompted him to slow down after years of career acceleration, and we also discuss his perspective on AI. Throughout, Kelsey keeps a simple idea front of mind: that technology is ultimately about people. Whether it’s infrastructure, leadership, careers, or AI, he argues that the goal is not to build technology for its own sake; it’s to solve meaningful human problems.
—
Timestamps
00:00 Intro
03:34 Kelsey’s first job at McDonald’s
05:04 His non-traditional path into tech
11:45 Landing his first tech job with an A+ certification
15:33 His entrepreneurial years
19:45 Joining Google as a data center technician
27:48 Learning automation at a Rackspace spinoff
33:26 Moving into financial services
50:00 Building a reputation through open source
53:55 From configuration management to containers
1:08:20 The rise of Kubernetes
1:25:05 Why he almost joined NASA instead of Google
1:29:20 Defining DevRel at Google
1:38:20 Demonstrating impact at Google
1:41:20 Microsoft's offer
1:55:20 Learning how to slow down
2:06:39 Advising and investing
2:15:03 A people-first view of GenAI
2:24:27 Using AI with guardrails
2:28:26 Matching AI to the task
2:36:06 Staying relevant in the AI era
—
The Pragmatic Engineer deepdives relevant for this episode:
• Career paths for software engineers at large tech companies
• The past and future of modern backend practices
• How Kubernetes is built
• How Linux is built
• The Staff Engineer’s Path: You’re a role model now (sorry!)
—
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@pragmaticengineer.com.
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At Google Cloud Next 2026, Finout co-founder and CEO Roi Ravhon and Google Cloud FinOps lead Pathik Sharma discussed how FinOps is rapidly evolving for the AI era. Ravhon argued that while cloud FinOps had a decade to mature, AI economics are forcing the industry to adapt within a year. Unlike traditional cloud workloads, AI costs are unpredictable because token usage varies even for identical prompts, while advanced reasoning models consume significantly more tokens despite falling prices.
Both emphasized that effective AI FinOps requires intelligent orchestration, routing workloads to the cheapest capable models instead of defaulting to expensive frontier models. Sharma noted that AI costs extend beyond APIs to GPUs, storage, training, and organizational adoption. They also cautioned against relying solely on LLMs for operational automation. Deterministic systems, observability metrics, and human approvals remain essential guardrails. Ultimately, both stressed that FinOps is primarily an organizational and cultural discipline, recommending newcomers start with the FinOps Foundation before investing in tools.
Learn more from The New Stack around the latest in FinOps:
Why FinOps Isn’t About Saving Money
FinOps Foundation’s FOCUS 1.2 Expands to SaaS, PaaS
Join our community of newsletter subscribers to stay on top of the news and at the top of your game.
At KubeCon Europe, Google Cloud’s Jago Macleod and Abdel Sghiouar argued that adopting Arm for Kubernetes workloads has shifted from a complex migration to a practical, low-friction choice. After a year of production use, Google’s custom Arm-based Axion processors—powering C4A and N4A instances—are positioned as broadly viable for most containerized applications, offering strong gains in performance, cost efficiency, and energy usage compared to x86.
Rather than requiring a full overhaul, moving to Arm typically involves recompiling containers for a multi-architecture target and gradually rolling out via Kubernetes practices like canary deployments. While edge cases exist, they are relatively uncommon.
A key enabler is GKE’s compute classes, which allow workloads to express preferences across VM types, turning infrastructure decisions into automated scheduling choices rather than manual provisioning.
Ultimately, the conversation points to a larger constraint: energy. As AI workloads grow, efficiency—measured in “tokens per watt”—is emerging as the defining metric, with cost savings translating directly into greater compute capacity.
Learn more from The New Stack about the latest developments around Google’s work with Axion:
Arm: See a Demo About Migrating a x86-Based App to ARM64
Do All Your AI Workloads Actually Require Expensive GPUs?
Join our community of newsletter subscribers to stay on top of the news and at the top of your game.
Startup founders are being pushed to move faster than ever, using AI while facing tighter funding, rising infrastructure costs, and more pressure to show real traction early. Cloud credits, access to GPUs, and foundation models have made it easier to get started, but those early infrastructure choices can have unforeseen consequences once startups move beyond free credits and into real cloud bills.
On this episode of TechCrunch's Equity podcast, Rebecca Bellan caught up with Darren Mowry, Google Cloud’s vice president of global startups who is right at the center of those tradeoffs. Together, they discuss what Mowry’s seeing across the startup ecosystem, how Google Cloud is competing for AI startups, and what founders should be thinking about as they scale.
Listen to the full episode to hear about:
How Google positions against AWS and Microsoft in the AI startup race.
TPUs vs GPUs: How much does hardware choice matter for early-stage companies?
Which AI verticals are seeing real growth, and what’s standing out in biotech, climate tech, developer tools, and world models.
What red flags will signal that a startup isn’t going to make it.
Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod.
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AI is good at seeing patterns, but it’s humans who figure out what to do next, says technologist Priyanka Vergadia. She shares three stories of human excellence sparked by AI insights and offers a pathway to identify and cultivate your irreplaceable qualities, turning the AI revolution from a threat into an opportunity.
Hosted on Acast. See acast.com/privacy for more information.
Ryan sits down with Dan Ciruli, VP and General Manager of Cloud Native at Nutanix, to talk about getting your virtual machines and Kubernetes to play nice in cloud-native environments, why VMs are still relevant in enterprise applications, and how AI can help modernize legacy systems.
Episode notes:
Nutanix combines compute, storage, virtualization, and networking so you can run applications and manage data across on-premises datacenters, public clouds, and edge locations all on one platform.
Connect with Dan on Linkedin and Bluesky.
Congrats to Necromancer badge winner David Ferenczy Rogožan! They won the badge on their answer to Where does adb shell mkdir create directories.
TRANSCRIPT
See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
GPUs dominate today’s AI landscape, but Google argues they are not necessary for every workload. As AI adoption has grown, customers have increasingly demanded compute options that deliver high performance with lower cost and power consumption. Drawing on its long history of custom silicon, Google introduced Axion CPUs in 2024 to meet needs for massive scale, flexibility, and general-purpose computing alongside AI workloads. The Axion-based C4A instance is generally available, while the newer N4A virtual machines promise up to 2x price performance.
In this episode, Andrei Gueletii, a technical solutions consultant for Google Cloud joined Gari Singh, a product manager for Google Kubernetes Engine (GKE), and Pranay Bakre, a principal solutions engineer at Arm for this episode, recorded at KubeCon + CloudNativeCon North America, in Atlanta. Built on Arm Neoverse V2 cores, Axion processors emphasize energy efficiency and customization, including flexible machine shapes that let users tailor memory and CPU resources. These features are particularly valuable for platform engineering teams, which must optimize centralized infrastructure for cost, FinOps goals, and price performance as they scale.
Importantly, many AI tasks—such as inference for smaller models or batch-oriented jobs—do not require GPUs. CPUs can be more efficient when GPU memory is underutilized or latency demands are low. By decoupling workloads and choosing the right compute for each task, organizations can significantly reduce AI compute costs.
Learn more from The New Stack about the Axion-based C4A:
Beyond Speed: Why Your Next App Must Be Multi-Architecture
Arm: See a Demo About Migrating a x86-Based App to ARM64
Join our community of newsletter subscribers to stay on top of the news and at the top of your game.
In this episode of The New Stack Podcast, hosts Alex Williams and Frederic Lardinois spoke with Keith Ballinger, Vice President and General Manager of Google Cloud Platform Developer Experience (GPC), about the evolution of agentic coding tools and the future of programming. Ballinger, a hands-on executive who still codes, discussed Gemini CLI, Google’s response to tools like Claude Code, and his broader philosophy on how developers should work with AI. He emphasized that these tools are in their “first inning” and that developers must “slow down to speed up” by writing clear guides, focusing on architecture, and documenting intent—treating AI as a collaborative coworker rather than a one-shot solution.
Ballinger reflected on his early AI experiences, from Copilot at GitHub to modern agentic systems that automate tool use. He also explored the resurgence of the command line as an AI interface and predicted that programming will increasingly shift from writing code to expressing intent. Ultimately, he envisions a future where great programmers are great writers, focusing on clarity, problem decomposition, and design rather than syntax.
Learn more from The New Stack about the latest in Google AI development:
Why PyTorch Gets All the Love
Lightning AI Brings a PyTorch Copilot to Its Development Environment
Ray Comes to the PyTorch Foundation
Join our community of newsletter subscribers to stay on top of the news and at the top of your game.
GKE turned 10 in 2025! In this episode, we talk with GKE PM Gari Singh about GKE's journey from early container orchestration to AI-driven ops. Discover Autopilot, IPPR, and a bold vision for the future of Kubernetes.
Do you have something cool to share? Some questions? Let us know:
web: kubernetespodcast.com
mail: kubernetespodcast@google.com
X: @kubernetespod
bluesky: @kubernetespodcast.com
News of the week
Cloud Native Computing Foundation Announces Knative's Graduation
llm-d 0.3: Wider Well-Lit Paths for Scalable Inference
vllm-project/semantic-router on github
Announcing the Certified Meshery Contributor (CMC)
Introducing Headlamp Plugin for Karpenter - Scaling and Visibility
Links from the interview
Kelsey Hightower's Kubernetes the Hard Way
MiniKube
Kind
Docker Compose
Docker Swarm
GKE Autopilot
Dynamic Resource Allocation (DRA)
Google Cloud TPUs
Node Auto Provisioning (GKE)
Jax (Machine Learning Framework)
Horizontal Pod Autoscaling (HPA)
Serverless on Google Cloud
Grafana
Prometheus
Kubectl-ai
Vertical Pod Autoscaler (VPA)
Kubernetes v1.33: In-Place Pod Resize Graduated to Beta
In-place Vertical Scaling of Pods - Resize CPU and Memory Resources assigned to Containers
GKE under the hood: Container-optimized compute delivers fast autoscaling for Autopilot
AI isn’t just changing software, it’s causing the biggest buildout of physical infrastructure in modern history.
In this episode, Raghu Raghuram (a16z) speaks with Amin Vahdat, VP and GM of AI and Infrastructure at Google, and Jeetu Patel, President and Chief Product Officer at Cisco, about the unprecedented scale of what’s being built — from chips to power grids to global data centers.
They discuss the new “AI industrial revolution,” where power, compute, and network are the new scarce resources; how geopolitical competition is shaping chip design and data center placement; and why the next generation of AI infrastructure will demand co-design across hardware, software, and networking.
The conversation also covers how enterprises will adapt, why we’re still in the earliest phase of this CapEx supercycle, and how AI inference, reinforcement learning, and multi-site computing will transform how systems are built and run.
Resources:
Follow Raghu on X: https://x.com/RaghuRaghuram
Follow Jeetu on X: https://x.com/jpatel41
Follow Amin on LinkedIn: https://www.linkedin.com/in/vahdat/
Stay Updated:
If you enjoyed this episode, be sure to like, subscribe, and share with your friends!
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Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
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Nicole Forsgren created the most widely used frameworks for measuring developer productivity—DORA and SPACE. She wrote the foundational book Accelerate and is about to release her newest book, Frictionless, a practical guide for helping teams move faster in the AI era. She’s currently Senior Director of Developer Intelligence at Google.
We discuss:
1. Why most productivity metrics are a lie
2. Signs that your engineering team could be moving much faster
3. Why AI accelerates coding but developers aren’t speeding up as much as you think
4. AI’s impact on engineers getting into “flow”
5. Her framework for building and scaling a developer experience team
6. The three components of developer experience: flow state, cognitive load, and feedback loops
—
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—
Where to find Nicole Forsgren:
• Twitter: https://twitter.com/nicolefv
• LinkedIn: https://www.linkedin.com/in/nicolefv/
• Website: https://nicolefv.com/
—
Where to find Lenny:
• Newsletter: https://www.lennysnewsletter.com
• X: https://twitter.com/lennysan
• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/
—
In this episode, we cover:
(00:00) Introduction to Nicole Forsgren
(05:09) The concept of developer experience (DevEx)
(08:33) Flow state and cognitive load in the age of AI
(12:02) Challenges in measuring productivity with AI
(21:19) The importance of developer experience for business value
(22:20) Common issues and solutions in developer experience
(26:49) Signs your eng team is moving too slow
(29:52) How AI is improving productivity
(33:32) Real examples of productivity improvements
(36:35) Introducing her new book, Frictionless
(43:40) How to get started building a DevEx team
(45:15) The impact of forming developer experience teams
(46:15) How to measure the impact of DevEx teams
(48:53) Measuring the impact of AI tools on productivity
(55:16) Survey design for developer experience
(57:59) Popular AI tools for developers
(59:08) Bringing a product mindset to DevEx improvements
(01:00:40) AI corner
(01:02:33) Lightning round and final thoughts
—
Referenced:
• How to measure and improve developer productivity | Nicole Forsgren (Microsoft Research, GitHub, Google): https://www.lennysnewsletter.com/p/how-to-measure-and-improve-developer
• DORA: https://dora.dev/
• The SPACE framework: A comprehensive guide to developer productivity: https://getdx.com/blog/space-metrics/
• Measuring developer productivity with the DX Core 4: https://getdx.com/research/measuring-developer-productivity-with-the-dx-core-4/
• Gloria Mark’s website: https://gloriamark.com/
• Taking Flight with Copilot: https://dl.acm.org/doi/10.1145/3589996
• DevEx in Action: https://spawn-queue.acm.org/doi/10.1145/3639443
• CodeX: https://openai.com/codex/
• Devin: https://devin.ai/
• Abi Noda on LinkedIn: https://www.linkedin.com/in/abinoda/
• DX is joining Atlassian: https://getdx.com/blog/dx-is-joining-atlassian/
• GitHub Copilot: https://github.com/features/copilot
• Cursor: https://cursor.com/
• The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/the-rise-of-cursor-michael-truell
• Gemini Code Assist: https://codeassist.google/
• Claude Code: https://www.claude.com/product/claude-code
• The AI-native startup: 5 products, 7-figure revenue, 100% AI-written code | Dan Shipper (co-founder/CEO of Every): https://www.lennysnewsletter.com/p/inside-every-dan-shipper
• Love Is Blind on Netflix: https://www.netflix.com/title/80996601
• Shrinking on AppleTV+: https://tv.apple.com/us/show/shrinking/umc.cmc.apzybj6eqf6pzccd97kev7bs
• Ninja Creami: https://www.amazon.com/Ninja-NC301-CREAMi-Containers-Bundle/dp/B0BLGR5JPV/
• Jura coffee maker: https://www.amazon.com/Jura-Nordic-Automatic-Coffee-Machine/dp/B0CF65BFZ1/
—
Recommended books:
• Frictionless: https://developerexperiencebook.com/
• DevEx Workbook: https://developerexperiencebook.com/#workbook
• Outlive: The Science and Art of Longevity: https://www.amazon.com/Outlive-Longevity-Peter-Attia-MD/dp/0593236599
• Back Mechanic: https://www.amazon.com/Back-Mechanic-Stuart-McGill-2015-09-30/dp/B01FKSGJYC
• How Big Things Get Done: The Surprising Factors That Determine the Fate of Every Project, from Home Renovations to Space Exploration and Everything in Between: https://www.amazon.com/How-Big-Things-Get-Done/dp/0593239512/
• The Undoing Project: A Friendship That Changed Our Minds: https://www.amazon.com/dp/B01KBM82M4/
—
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.
Lenny may be an investor in the companies discussed.
To hear more, visit www.lennysnewsletter.com
Aja Hammerly, director of developer relations at Google, sees AI as the always-available coding partner developers have long wished for—especially in those late-night bursts of inspiration. In a conversation with Alex Williams at Google Cloud Next, she described AI-assisted coding as akin to having a virtual pair programmer who can fill in gaps and offer real-time support.
Hammerly urges developers to start their AI journey with tools that assist in code writing and explanation before moving into more complex AI agents. She distinguishes two types of DevEx AI: using AI to build apps and using it to eliminate developer toil. For Hammerly, this includes letting AI handle frontend work while she focuses on backend logic. The newly launched Firebase Studio exemplifies this dual approach, offering an AI-enhanced IDE with flexible tools like prototyping, code completion, and automation. Her advice? Developers should explore how AI fits into their unique workflow—because development, at its core, is deeply personal and individual.
Learn more from The New Stack about the latest AI insights with Google Cloud:
Google AI Coding Tool Now Free, With 90x Copilot’s Output
Gemini 2.5 Pro: Google’s Coding Genius Gets an Upgrade
Q&A: How Google Itself Uses Its Gemini Large Language Model
Join our community of newsletter subscribers to stay on top of the news and at the top of your game.
In this episode of AI Basics, Jason sits down with Amin Vahdat, VP of ML at Google Cloud, to unpack the mind-blowing infrastructure behind modern AI. They dive into how Google’s TPUs power massive queries, why 2025 is the “Year of Inference,” and how startups can now build what once felt impossible. From real-time agents to exponential speed gains, this is a look inside the AI engine that’s rewriting the future.
*
Timestamps:
(0:00) Jason introduces today’s guest Amin Vahdat
(3:18) Data movement implications for founders and historical bandwidth perspective
(5:29) The shift to inference and AI infrastructure trends in startups and enterprises
(8:40) Evolution of productivity and potential of low-code/no-code development
(11:20) AI infrastructure pricing, cost efficiency, and historical innovation
(17:53) Google's TPU technology and infrastructure scale
(23:21) Building AI agents for startup evaluation and supervised associate agents
(26:08) Documenting decisions for AI learning and early AI agent development
*
Uncover more valuable insights from AI leaders in Google Cloud's 'Future of AI: Perspectives for Startups' report. Discover what 23 AI industry leaders think about the future of AI—and how it impacts your business. Read their perspectives here: https://goo.gle/futureofai
*
Check out all of the Startup Basics episodes here: https://thisweekinstartups.com/basics
Check out Google Cloud: https://cloud.google.com/
*
Follow Amin:
LinkedIn: https://www.linkedin.com/in/vahdat/?trk=public_post_feed-actor-name
*
Follow Jason:
X: https://twitter.com/Jason
LinkedIn: https://www.linkedin.com/in/jasoncalacanis
*
Follow TWiST:
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Instagram: https://www.instagram.com/thisweekinstartups
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Substack: https://twistartups.substack.com
In a candid episode of The New Stack Makers, Kubernetes pioneer Kelsey Hightower and AWS’s Eswar Bala explored the evolving relationship between enterprise cloud providers and open source software at KubeCon+CloudNativeCon London. Hightower highlighted open source's origins as a grassroots movement challenging big vendors, and shared how it gave people—especially those without traditional tech credentials—a way into the industry. Recalling his own journey, Hightower emphasized that open source empowered individuals through contribution over credentials.
Bala traced the early development of Kubernetes and his own transition from building container orchestration systems to launching AWS’s Elastic Kubernetes Service (EKS), driven by growing customer demand. The discussion, recorded at KubeCon + CloudNativeCon Europe, touched on how open source is now central to enterprise cloud strategies, with AWS not only contributing but creating projects like Karpenter, Cedar, and Kro.
Both speakers agreed that open source's collaborative model—where companies build in public and customers drive innovation—has reshaped the cloud ecosystem, turning former tensions into partnerships built on community-driven progress.
Learn more from The New Stack about the relationship between enterprise cloud providers and open source software:
The Metamorphosis of Open Source: An Industry in Transition
The Complex Relationship Between Cloud Providers and Open Source
How Open Source Has Turned the Tables on Enterprise Software
Join our community of newsletter subscribers to stay on top of the news and at the top of your game.
This episode is sponsored by Thuma.
Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details.
To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai
What happens when AI agents start negotiating, automating workflows, and rewriting how the enterprise world operates?
In this episode of the Eye on AI podcast, Will Grannis, CTO of Google Cloud, reveals how Google is leading the charge into the next frontier of artificial intelligence: agentic AI. From multi-agent systems that can file your expenses to futuristic R2-D2-style assistants in real-time race strategy, this episode dives deep into how AI is no longer just about models—it's about autonomous action.
In this episode, we explore:
How AgentSpace is transforming how enterprises build AI agents
The evolution from rule-based workflows to intelligent orchestration
Real-world use cases: expense automation, content creation, code generation
Trust, sovereignty, and securing agentic systems at scale
The future of multi-agent ecosystems and AI-driven scientific discovery
How large enterprises can match startup agility using their data advantage
Whether you're a founder, engineer, or enterprise leader—this episode will shift how you think about deploying AI in the real world.
Subscribe for more deep dives with tech leaders and AI visionaries.
Drop a comment with your thoughts on where agentic AI is headed!
(00:00) Preview and Intro
(02:34) Will Grannis' Role at Google Cloud
(05:14) Origins of Agentic Workflows at Google
(09:10) How Generative AI Changed the Agent Game
(12:29) Agents, Tool Access & Trust Infrastructure
(14:01) What is Agent Space?
(16:30) Creative & Marketing Agents in Action
(23:29) Core Components of Building Agents
(25:29) Introducing the Agent Garden
(28:06) The "Cloud of Connected Agents" Concept
(33:53) Solving Agent Quality & Self-Evaluation
(37:19) The Future of Autonomous Finance Agents
(40:55) How Enterprises Choose Cloud Partners for Agents
(43:50) Google Cloud's Principles in Practice
(46:27) Gemini's Context Power in Cybersecurity
(49:50) Robotics and R2D2-Inspired AI Projects
(52:39) How to Try Agent Space Yourself
Thomas Kurian is the CEO of Google Cloud Platform. He joins Big Technology Podcast to discuss how AI is changing the competitive balance in cloud services and why he believes Google has a chance to win. We also discuss the various use cases Google customers are finding for GenAI in the technology's early days, and whether the agent buzz is real. Finally, towards the end of the conversation we touch on tariffs and their impact on the cloud services business. Tune in for a wide ranging conversation with Google's top guy on cloud computing.
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SaaStr 796: The Secrets Inside Google Cloud's Growth with Sarah Kennedy, Vice President Google Cloud Marketing
In our latest episode of the SaaStr What's New series, SaaStr CEO and founder Jason Lemkin spoke with Sarah Kennedy, VP of Google Cloud Marketing. The conversation explores the explosive growth of Google Cloud and what's driving this momentum. Kennedy highlights the critical role AI plays in their success, from Google's world-class infrastructure to the cutting-edge AI models like Vertex AI and Gemini. We dive into the specifics of why startups and enterprises are increasingly choosing Google Cloud, the importance of customer-centric strategies, and the shift towards developer-led decisions. We also explore Google Cloud's major partnership with Salesforce and how AI and security are transforming business strategies. Tune in for insights on how Google Cloud is shaping the future of AI and stay ahead of the curve with expert tips on leveraging these technologies for your business.
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Alright everybody in SaaS, this is it.
The biggest, best, most action-packed SaaS + AI event of the year—SaaStr Annual 2025—is coming this May. Three full days. 10,000+ SaaS and AI leaders and more tactical, no-fluff content than you'll find anywhere else.
If you want to scale faster—$10M, $50M, $100M ARR and beyond—you need the right playbooks, the right connections and the right people in your corner. And SaaStr Annual is where it all happens.
We'll have 100's of Legendary speakers from companies like Snowflake, HubSpot, OpenAI, Canva, and more.
More networking than you can handle—meet your next investor, co-founder, or biggest deal.
A New AI Demo & Pitch Stage— with your chance to win up to $5M in funding!
So don't wait—grab your tickets now at SaaStrAnnual.com with my code jason100 to save $100 on tickets before prices go up. That's jason 100 at saastrannual.com
See you in May!
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Maya Kaczorowski noticed that AI identity and AI agent identity concerns were emerging from outside the security industry, rather than from CISOs and security leaders. She concluded that OAuth, the open standard for authentication, already serves the purpose of granting access without exposing passwords.
Kaczorowski, a respected technologist and founder of Oblique, a startup focused on self-serve access controls, recently wrote about OAuth and AI agents and shared her insights on this episode of The New Stack Makers. She noted that developers see AI agents as extensions of themselves, granting them limited access to data and capabilities—precisely what OAuth is designed to handle.
The challenges with AI agent identity are vast, involving different approaches to authentication, such as those explored by companies like AuthZed. While existing authorization models like RBAC or ABAC may still apply, the real challenge lies in scale. The exponential growth of AI-related entities—from users to LLMs—could mean even small organizations manage hundreds of thousands of agents. Future solutions must accommodate this massive scale efficiently.
For the full discussion, check out The New Stack Makers interview with Kaczorowski.
Learn more from The New Stack about OAuth requirements for AI Agents:
OAuth 2.0: A Standard in Name Only?
AI Agents Are Redefining the Future of Identity and Access Management
Join our community of newsletter subscribers to stay on top of the news and at the top of your game.
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How do you architect a live streaming system to deal with more load than it’s ever been done before? Today, we hear from an architect of such a system: Ashutosh Agrawal, formerly Chief Architect of JioCinema (and currently Staff Software Engineer at Google DeepMind.)
We take a deep dive into video streaming architecture, tackling the complexities of live streaming at scale (at tens of millions of parallel streams) and the challenges engineers face in delivering seamless experiences. We talk about the following topics:
• How large-scale live streaming architectures are designed
• Tradeoffs in optimizing performance
• Early warning signs of streaming failures and how to detect them
• Why capacity planning for streaming is SO difficult
• The technical hurdles of streaming in APAC regions
• Why Ashutosh hates APMs (Application Performance Management systems)
• Ashutosh’s advice for those looking to improve their systems design expertise
• And much more!
—
Timestamps
(00:00) Intro
(01:28) The world record-breaking live stream and how support works with live events
(05:57) An overview of streaming architecture
(21:48) The differences between internet streaming and traditional television.l
(22:26) How adaptive bitrate streaming works
(25:30) How throttling works on the mobile tower side
(27:46) Leading indicators of streaming problems and the data visualization needed
(31:03) How metrics are set
(33:38) Best practices for capacity planning
(35:50) Which resources are planned for in capacity planning
(37:10) How streaming services plan for future live events with vendors
(41:01) APAC specific challenges
(44:48) Horizontal scaling vs. vertical scaling
(46:10) Why auto-scaling doesn’t work
(47:30) Concurrency: the golden metric to scale against
(48:17) User journeys that cause problems
(49:59) Recommendations for learning more about video streaming
(51:11) How Ashutosh learned on the job
(55:21) Advice for engineers who would like to get better at systems
(1:00:10) Rapid fire round
—
The Pragmatic Engineer deepdives relevant for this episode:
• Software architect archetypes https://newsletter.pragmaticengineer.com/p/software-architect-archetypes
• Engineering leadership skill set overlaps https://newsletter.pragmaticengineer.com/p/engineering-leadership-skillset-overlaps
• Software architecture with Grady Booch https://newsletter.pragmaticengineer.com/p/software-architecture-with-grady-booch
—
See the transcript and other references from the episode at https://newsletter.pragmaticengineer.com/podcast
—
Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@pragmaticengineer.com.
Get full access to The Pragmatic Engineer at newsletter.pragmaticengineer.com/subscribe
This episode of the Eye on AI podcast is sponsored by JLL.
JLL's AI solutions are transforming the real estate landscape, accelerating growth, streamlining operations and unlocking hidden value in properties and portfolios. From predictive analytics to intelligent automation, JLL is creating smarter buildings, more efficient workplaces and sustainable cities.
To learn more about JLL and AI, visit: jll.com/AI
In this episode of the *Eye on AI* podcast, we explore the world of AI at Google Cloud with Nenshad Bardoliwalla, Director of Product Management for Vertex AI.
Nenshad unpacks the three core layers of Vertex AI: the Model Garden, where users can access and evaluate a diverse range of models; the Model Builder, which supports model fine-tuning and prompt optimization; and the Agent Builder, designed to develop AI agents that can perform complex, goal-oriented tasks.
He shares insights into model evaluation strategies, the role of Google's Tensor Processing Units (TPUs) in scaling AI infrastructure, and how enterprises can choose the right models based on performance, cost, and regulatory requirements.
Nenshad also delves into the challenges and opportunities of AI prompt optimization, highlighting Google's approach to ensuring consistent outputs across different models. He discusses the ethical considerations in AI design, emphasizing the need for human oversight and clear guardrails to maintain safety.
Whether you're in AI, tech, or curious about AI's potential impact, this episode is packed with insights on next-gen AI deployment.
Don't forget to like, subscribe, and turn on notifications for more episodes!
Stay Updated:
Craig Smith Twitter: https://twitter.com/craigss
Eye on A.I. Twitter: https://twitter.com/EyeOn_AI
(00:00) Introduction to Nenshad Bardoliwalla & Vertex AI
(01:52) Overview of Vertex AI's Three Core Layers
(05:35) Nenshad's Journey to Google Cloud
(06:36) Choosing the Right AI Model
(08:00) Google's AI Infrastructure & Tensor Processing Units (TPUs)
(10:15) Model Builder: Fine-Tuning & Prompt Optimization
(12:11) Agent Builder: Building AI Agents with Tools & Planning
(17:57) Model Evaluation & Prompt Management
(21:23) Generative AI for Business Analysts
(23:24) AI Model Modality & Use Case Selection
(25:23) Popularity Distribution of AI Models
(28:18) Prompt Optimization Tools
(34:20) Building AI Agents: Real-World Use Cases & Ethical Safeguards
(40:13) The Capabilities & Limitations of AI Agents
(45:48) TPU vs. GPU
(50:33) Future of AI at Google Cloud
On this Screaming in the Cloud Replay, we revisit our chat with Forrest Brazeal. When this episode first aired, Forrest was the Head of Content at Google Cloud, but today, he helps run Freeman & Forrest, an influencer marketing service focused on enterprise tech. In this trip down memory lane, Forrest goes into detail on how he is working to give back to the cloud community. Forrest discusses his time at A Cloud Guru, his time as an AWS Serverless Hero, and the technical excellence he brings to his vast-ranging and prolific content. Forrest is also a successful author of a newsletter and multiple books, including a children's book about the cloud! Needless to say, Forrest is an incredibly varied personality in the cloud community, tune in for a chance to get to know him better!
Show Highlights
(00:00) Intro
(1:10) Backblaze sponsor read
(1:36) Starting a new job as the Head of Content for Google Cloud
(2:32) Forrest’s background as a cloud consultant
(3:57) Writing endeavors and The Cloud Resume Challenge
(6:30) Being authentic and helpful in the cloud
(11:43) Forrest’s experiences with Google Cloud
(13:18) Being a thought leader in the cloud community
(16:44) The interview process for Google Cloud
(20:24) Creating online cloud content
(25:51) Having creative freedom at Google
(29:07) The viability of Google Cloud
(31:52) Where you can find more from Forrest
About Forrest Brazeal
Forrest is a cloud educator, cartoonist, author, and Pwnie Award-winning songwriter. He’s also led some of the world's most innovative developer content and community teams at companies like Google and A Cloud Guru.
Links
The Cloud Bard Speaks: https://www.lastweekinaws.com/podcast/screaming-in-the-cloud/the-cloud-bard-speaks-with-forrest-brazeal/
The Read Aloud Cloud: https://www.amazon.com/Read-Aloud-Cloud-Innocents-Inside/dp/1119677629
The Cloud Resume Challenge Book: https://forrestbrazeal.gumroad.com/l/cloud-resume-challenge-book/launch-deal
The Cloud Resume Challenge: https://cloudresumechallenge.dev
Twitter: https://twitter.com/forrestbrazeal
Original Episode
https://www.lastweekinaws.com/podcast/screaming-in-the-cloud/creatively-giving-back-to-the-cloud-community-with-forrest-brazeal/
Sponsor
Backblaze: https://www.backblaze.com/
On this Screaming in the Cloud Replay, we’re revisiting our conversation with Stephanie Wong. When she first sat down with Corey, she was the Head of Developer Engagement at Google, but today, she serves as the company’s Head of Technical Storytelling. While Stephanie is certainly a key player at such a massive company, her passion lies in her own advocacy for women in tech as well as making tech more approachable to larger audiences. Stephanie is not one to put her job title first. Her bio covers the spread from dancer, to hip-hop medalist, to podcast host. Stephanie gives us the birds eye view on her own non-traditional and interdisciplinary path that led to her work both in and outside of Google. Stephanie’s focus on producing content that reaches across a wide spectrum of participants is crucial to how she has broken the mold on what tech can do, and her lessons are ones we can all learn from.
Show Highlights:
(0:00) Intro
(1:06) Backblaze sponsor read
(1:32) Explaining the Head of Developer Engagement
(2:13) Stephanie’s background and authenticity in tech
(7:11) Approaching developer relations from a non-”traditional” tech background
(11:04) Building a personal and company online presence
(14:41) Corey’s perceived contradictions with Google Cloud
(22:29) Through engaging your audience through media and storytelling
(27:23) Helping find the next generation of tech talent
(29:23) The cloud and the inflection of tech
(38:51) Where you can find more from Stephanie
About Stephanie Wong:
Stephanie Wong is an award-winning speaker, engineer, pageant queen, and hip hop medalist. She is a leader at Google with a mission to blend storytelling and technology to create remarkable developer content. At Google, she's created 100s of videos, blogs, courses, and podcasts that have helped developers globally. Stephanie is active in her community, fiercely supporting women in tech and mentoring students.
Links:
Personal Website: https://stephrwong.com
Twitter: https://twitter.com/stephr_wong
Original Episode
https://www.lastweekinaws.com/podcast/screaming-in-the-cloud/breaking-the-tech-mold-with-stephanie-wong/
Sponsor
Backblaze: https://www.backblaze.com/
In this Screaming in the Cloud Replay, we revisit a spirited debated between Corey and the VP of Product and Industry Marketing at Google Cloud, Brian Hall. The topic — How much time should one spend in a job? But thankfully, their conversation doesn’t limit itself to just that! Corey and Brian chat about how social media’s failure to capture nuance and context can lead to some unfortunate misinterpretations. Brian offers some insight on his significant amount of time spent at Microsoft under various roles. He gives his perspective on how one should optimize their career path for where they want to go, and not just follow the money. Tune in to see how Corey and Brian let the dust settle, and develop what was a disagreement into a well-rounded conversation.
Show Highlights:
(0:00) Intro
(1:02) Chronosphere sponsor read
(1:36) Job hopping vs. job loyalty
(6:14) Being in the right place at the right time
(9:57) Investing in the job vs. the job investing in you
(13:31) Weighing the cost of job hopping
(20:14) Chronosphere sponsor read
(20:47) Changing jobs to get a raise
(24:02) How to attract people as a cloud employer
(26:31) Changing paths into the industry
(30:14) What's ahead for Brian
(32:33) Where you can find more from Brian
About Brian Hall
Brian Hall leads the Google Cloud Product and Industry Marketing team - focused on accelerating the growth of Google Cloud. Before joining Google, he spent more than 25 years in different forms of product marketing or engineering.
Brian is the father of three children who are all named after trees in different ways. He met his wife Edie at the beginning of their first year at Yale University, where he studied math, econ, and philosophy and was the captain of the Swim and Dive team my senior year. Edie has a PhD in forestry and runs a sustainability and forestry consulting firm she started, that is aptly named “Three Trees Consulting”. They love the outdoors, tennis, running, and adventures in Brian's 1986 Volkswagen Van, which is his first and only car, that he can’t bring myself to get rid of.
Links:
Twitter: https://twitter.com/IsForAt
LinkedIn: https://www.linkedin.com/in/brhall/
Episode 10: https://www.lastweekinaws.com/podcast/screaming-in-the-cloud/episode-10-education-is-not-ready-for-teacherless/
Original Episode:
https://www.lastweekinaws.com/podcast/screaming-in-the-cloud/letting-the-dust-settle-on-job-hopping-with-brian-hall/
Sponsor
https://chronosphere.io/?utm_source=duckbill-group&utm_medium=podcast
On this Screaming in the Cloud Summer Replay, we revisit our conversation with Aparna Sinha, the Head of AI Product at Capital One. As a former Director of Product Management at Google Cloud, Aparan joins Corey to talk about GCP and how Corey was surprised to find that, in some ways, it was “its own universe.” She offers up why folks can expect a developer user-friendly experience when using GCP, and how it differentiates them from the litany of cloud providers out there. From focusing on developing, to a vast array of customers, GCP is bringing their best forward. Check out their conversation on how GCP is keeping its focus on the user!
Show Highlights:
(0:00) Intro
(0:48) Duckbill Group sponsor read
(1:21) Role of a Director of Outbound Product Management
(2:43) Developer experiences on Google Cloud
(8:47) The philosophy of courting developers
(11:38) The shift to serverless
(17:17) Cloud Run observations
(22:59) Duckbill Group sponsor read
(23:43) Customer involvement with Google Cloud
(28:55) Cloud Build vs. Cloud Deploy
(32:50) Google and cloud security
(38:45) Where you can find Aparna
About Aparna
Aparna Sinha is Senior Vice President and Head of Enterprise AI/ML products at Capital One. She is also a startup investor / advisor at PearVC. Aparna has a track record of successful P&L ownership, creating new revenue streams and building $B+ businesses through technical and go-to-market innovation.
She was Sr. Director of Developer Products at Google Cloud leading a 100+ member PM, UX, and DevRel Engineering team responsible for >40 cloud services and open source tools. She was an early contributor to Kubernetes, built the team and grew Google Kubernetes Engine 100x into a Top 3 revenue generator for Cloud. Prior to Cloud Aparna worked on Android, ChromeOS and Play. Previously at McKinsey & Company she was a leader in the business technology office, working with CIOs on server virtualization strategy, pricing, and SaaS.
Aparna holds a PhD in Electrical Engineering from Stanford, and a patent from Google. She served as Chair of the Governing Board of the Cloud Native Computing Foundation (CNCF).
Links:
DevOps Research Report: https://www.devops-research.com/research.html
Twitter: https://x.com/aparnabsinha
Original Episode:
https://www.lastweekinaws.com/podcast/screaming-in-the-cloud/building-a-user-friendly-product-with-aparna-sinha/
Sponsor:
The Duckbill Group: https://www.duckbillgroup.com/
Kelsey Hightower is back to share more of his wisdom. This time it’s one year after his retirement from Google. But guess what? He might be “retired,” but he’s not tired. In this episode Kelsey shares what drives him, what he fears, and how he thinks through his life choices and parenting. This is a good one.
Join the discussion
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Sponsors:
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Featuring:
Kelsey Hightower – GitHub, X
Adam Stacoviak – Website, GitHub, LinkedIn, Mastodon, X
Jerod Santo – Website, GitHub, LinkedIn, Mastodon, X
Show Notes:
“I’m retired, not tired.”
Changelog & Friends #6: Even the best rides come to an end
Run:ai
Brondell Bidet
From Sleeping in His Car to Distinguished Engineer at Google (Kelsey Hightower)
Something missing or broken? PRs welcome!
Welcome to the second episode of the 4 part special series for the Kubernetes 10 year anniversary. In this episode we spoke to two very influential people in Kubernetes' history. Tim Hockin and Kelsey Hightower Both have been involved with the project since its inception and both had, and continue to have, impact on the project and the community.
Do you have something cool to share? Some questions? Let us know:
- web: kubernetespodcast.com
- mail: kubernetespodcast@google.com
- twitter: @kubernetespod
Chatter of the week KuberTenes Regional Events
Kubernetes Twitter Account
News of the week Kubernetes introduces hydrophone
AKS Automatic
CKS Changes after Sept 12, 2024
KubeCon and CloudNativeCon CFP Closes June 9th
KubeCon Co-Located events CFP Closes June 14, 2024
Links from the interview Google Borg
Google Omega
Let Me Contain That For You
Kubernetes Sidecars
Why Service Is the Worst API in Kubernetes
Kubernetes Maintainers Read Mean Comments
Kubernetes The Hard Way
Kelsey retirement announcement
Redpanda
Crossplane
Llama 3
Open-core model
Lets Encrypt
Google's infrastructure for everyone else
Kubernetes: Up and Running
CNI
Kubernetes Networking
Kubernetes Resource Model (KRM)
Maya Kaczorowski, Chief Product Officer at Tailscale, joins Corey on Screaming in the Cloud to discuss what sets the Tailscale product approach apart, for users of their free tier all the way to enterprise. Maya shares insight on how she evaluates feature requests, and how Tailscale’s unique architecture sets them apart from competitors. Maya and Corey discuss the importance of transparency when building trust in security, as well as Tailscale’s approach to new feature roll-outs and change management.
About Maya
Maya is the Chief Product Officer at Tailscale, providing secure networking for the long tail. She was mostly recently at GitHub in software supply chain security, and previously at Google working on container security, encryption at rest and encryption key management. Prior to Google, she was an Engagement Manager at McKinsey & Company, working in IT security for large enterprises.
Maya completed her Master's in mathematics focusing on cryptography and game theory. She is bilingual in English and French.
Outside of work, Maya is passionate about ice cream, puzzling, running, and reading nonfiction.
Links Referenced:
Tailscale: https://tailscale.com/
Tailscale features:VS Code extension: https://marketplace.visualstudio.com/items?itemName=tailscale.vscode-tailscale
Tailscale SSH: https://tailscale.com/kb/1193/tailscale-ssh
Tailnet lock: https://tailscale.com/kb/1226/tailnet-lock
Auto updates: https://tailscale.com/kb/1067/update#auto-updates
ACL tests: https://tailscale.com/kb/1018/acls#tests
Kubernetes operator: https://tailscale.com/kb/1236/kubernetes-operator
Log streaming: https://tailscale.com/kb/1255/log-streaming
Tailscale Security Bulletins: https://tailscale.com/security-bulletins
Blog post “How Our Free Plan Stays Free:” https://tailscale.com/blog/free-plan
Tailscale on AWS Marketplace: https://aws.amazon.com/marketplace/pp/prodview-nd5zazsgvu6e6
As the Lead for Generative AI in the Office of the CTO for Google Cloud, Kawal Gandhi has a unique vantage point on enterprise AI rollout. Sarah Guo and Elad Gil sit down with Gandhi this week to discuss his insights on how enterprises can effectively invest in AI development, the importance of TPUs, and Google’s internal AI applications. Plus, when will email get more intelligent?
Kawal Gandhi has worked at Google for nearly a decade in search and ad roles before focusing on the development and marketing of AI tools.
Show Links:
Kawal Gandhi | LinkedIn
Google Cloud
Sign up for new podcasts every week. Email feedback to show@no-priors.com
Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @geeztweets
Show Notes:
(00:00) - Generative AI in Google Cloud
(09:05) - AI Adoption in the Enterprise
(13:31) - Multi-Modal AI Models
(16:19) - AI Adoption, return-on-investment, anti-patterns
(24:43) - Google's TPU and NVIDIA GPU shortage
(31:00) - Data Marketplace and Model Training
Kelsey Hightower joins Corey on Screaming in the Cloud to discuss his reflections on how the tech industry is progressing. Kelsey describes what he’s been getting out of retirement so far, and reflects on what he learned throughout his high-profile career - including why feature sprawl is such a driving force behind the complexity of the cloud environment and the tactics he used to create demos that are engaging for the audience. Corey and Kelsey also discuss the importance of remaining authentic throughout your career, and what it means to truly have an authentic voice in tech.
About Kelsey
Kelsey Hightower is a former Distinguished Engineer at Google Cloud, the co-chair of KubeCon, the world’s premier Kubernetes conference, and an open source enthusiast. He’s also the co-author of Kubernetes Up & Running: Dive into the Future of Infrastructure. Recently, Kelsey announced his retirement after a 25-year career in tech.
Links Referenced:
Twitter: https://twitter.com/kelseyhightower
Forrest Brazeal, Head of Developer Media at Google Cloud, joins Corey on Screaming in the Cloud to discuss how AI, current job markets, and more are impacting software engineers. Forrest and Corey explore whether AI helps or hurts developers, and what impact it has on the role of a junior developer and the rest of the development team. Forrest also shares his viewpoints on how he feels AI affects people in creative roles. Corey and Forrest discuss the pitfalls of a long career as a software developer, and how people can break into a career in cloud as well as the necessary pivots you may need to make along the way. Forrest then describes why he feels workers are currently staying put where they work, and how he predicts a major shift will happen when the markets shift.
About Forrest
Forrest is a cloud educator, cartoonist, author, and Pwnie Award-winning songwriter. He currently leads the content marketing team at Google Cloud. You can buy his book, The Read Aloud Cloud, from Wiley Publishing or attend his talks at public and private events around the world.
Links Referenced:
Personal Website: https://goodtechthings.com
Newsletter signup: https://cloud.google.com/innovators
