Welcome to episode 341 of The Cloud Pod, where the forecast is always cloudy! Matt & Ryan are picking up Justin’s slack this week while he’s traveling for work, but don’t worry, because they have plenty of news! We’re talking about those mass layoffs over at AWS, a major security breach over at Notepad++, and some new slight of hand over at Elon’s companies. There’s a lot to cover, so let’s get into it!

• Finally, a Chatbot That Actually Knows Where Your Data Lives **Anthropic
• Microsoft Adds Security Analyzer to MSSQL Extension: Because Bobby Tables Jokes Are Only Funny Until They Happen to You
• From Sequential Sadness to Parallel Paradise: GKE Node Pools Get Concurrent
• From Vibe Coding to Production: AWS MCP Server Gets SOPs
• One Prompt to Deploy Them All: AWS MCP Server Automates Infrastructure
• AWS Layoffs: Scaling Down Instead of Scaling Out
• Mutual TLS: Because CloudFront and Your Origin Need Couples Therapy
• Claude Team Plan: Now With More Seats and Less Bills
• From Snowflake to Snowball: Rolling Data and Dev Into One Platform
• From Notepad++ to Notepad Pwned: A Six-Month Hosting Horror Story
• EventBridge Payload Capacity Gets a 4x Upgrade: No More Event Splitting Headaches
• CloudFront Finally Learns to Check ID Before Knocking on Origin’s Door

01:30 SpaceX acquires xAI, plans to launch a massive satellite constellation to power it – Ars Technica

• SpaceX has acquired xAI to create a vertically integrated AI and space infrastructure company, with plans to deploy up to 1 million satellites as orbital data centers.
• This represents a significant bet that space-based compute infrastructure can be cost-competitive with traditional ground-based data centers for AI workloads.
• The merger combines SpaceX’s launch capabilities and satellite manufacturing expertise with xAI’s Grok chatbot and X social platform.
• The strategy assumes AI demand will continue to grow and that compute capacity, rather than other factors, is the primary bottleneck to AI adoption.
• The orbital data center concept raises questions about latency, power requirements, thermal management, and maintenance compared to terrestrial facilities.
• Traditional cloud providers have invested heavily in ground-based infrastructure optimized for these factors.
• This consolidation of Musk’s companies creates potential conflicts between SpaceX’s established government and commercial contracts and xAI’s more controversial products.
• The integration of a proven aerospace company with a newer AI venture introduces execution risk to SpaceX’s core business.
• The plan depends on several unproven assumptions, including sustained AI market growth, viable economics for space-based computing, and the ability to manufacture and launch satellites at unprecedented scale.
• Cloud providers and enterprises will need to evaluate whether orbital compute offers advantages over existing multi-region terrestrial deployments.

03:22 Ryan – “I feel like this is a shell game con; taxes are over here – no, now they’re over here!”

06:49

Welcome to episode 340 of The Cloud Pod, where the forecast is always cloudy! It’s a full house (eventually) with Justin, Jonathan, Ryan, and Matt all on board for today’s episode. We’ve got a lot of announcements, from Gemini for Gov (no more CamoGPT!) to Route 52 and Claude. Let’s get started!

• Claude’s Pricing Tiers: Free, Pro, and Maximum Overdrive
• GitHub Copilot Learns Database Schema: Finally an AI That Understands Your Joins
• SSMS Gets a Copilot: Your T-SQL Now Writes Itself While You Grab Coffee
• Too Many Cooks in the Cloud Kitchen: How 32 GPUs Outcooked the Big Tech Industrial Kitchens
• Uncle Sam Gets a Gemini Twin: Google’s AI Goes Federal
• Route 53 Gets Domain of Its Own: .ai Joins the Party
• Thai One On: Google Cloud Plants Its Flag in Bangkok
• NAT So Fast: Azure’s Gateway Gets a V2 Glow-Up
• Beware Azure’s SQL Assistant doesn’t smoke your joints.

30:10 Announcing BlackIce: A Containerized Red Teaming Toolkit for AI Security Testing | Databricks Blog

• Databricks released BlackIce, an open-source containerized toolkit that bundles 14 AI security testing tools into a single Docker image available on Docker Hub as databricksruntime/blackice:17.3-LTS.
• The toolkit addresses common red teaming challenges, including conflicting dependencies, complex setup requirements, and the fragmented landscape of AI security tools, by providing a unified command-line interface similar to how Kali Linux works for traditional penetration testing.
• The toolkit includes tools covering three main categories: Responsible AI, Security testing, and classical adversarial ML, with capabilities mapped to MITRE ATLAS and the Databricks AI Security Framework.
• Tools are organized as either static (simple CLI-based with minimal programming needed) or dynamic (Python-based with customization options), with static tools isolated in separate virtual environments and dynamic tools in a global environment with managed dependencies.
• BlackIce integrates directly with Databricks Model Serving endpoints through custom patches applied to several tools, allowing security teams to test for vulnerabilities like prompt injections, data leakage, hallucination detection, jailbreak attacks, and supply chain security issues.
• Users can deploy it via Databricks Container Services by specifying the Docker image URL when creating compute clusters.
• The release includes a demo notebook showing how to orchestrate multiple security tools in a single environment, with all build artifacts, tool documentation, and examples available in the GitHub repository.
• The CAMLIS Red Paper provides additional technical details on tool selection criteria and the Docker image architecture.

04:30 Ryan – “It’s very difficult to feel confident in your AI security practice or patterns. I feel like it’s just bleeding edge, and I’m learning so much all the time. And so I spend a lot of time reading papers and talking to others and seeing what they’re doing and meeting with vendors trying to figure out strategy, and it just feels like I’m drinking from a fire hose, and it’s really difficult to feel confident. So I like tools like t...

Welcome to episode 337 of The Cloud Pod, where the forecast is always cloudy! Justin, Matt, and Ryan have hit the recording studio to bring you all the latest in cloud and AI news, from acquisitions and price hikes to new tools that Ryan somehow loves but also hates? We don’t understand either… but let’s get started!

• Prompt Engineering Our Way Into Trouble
• The Demo Worked Yesterday, We Swear
• It Scales Horizontally, Trust Us
• Responsible AI But Terrible Copy (Marketing Edition)

00:58 Watch ‘The Thinking Game’ documentary for free on YouTube

• Google DeepMind is releasing the “The Thinking Game” documentary for free on YouTube starting November 25, marking the fifth anniversary of AlphaFold.
• The feature-length film provides behind-the-scenes access to the AI lab and documents the team’s work toward artificial general intelligence over five years.
• The documentary captures the moment when the AlphaFold team learned they had solved the 50-year protein folding problem in biology, a scientific achievement that recently earned Demis Hassabis and John Jumper the Nobel Prize in Chemistry.
• This represents one of the most significant practical applications of deep learning to fundamental scientific research.
• The film was produced by the same award-winning team that created the AlphaGo documentary, which chronicled DeepMind’s earlier achievement in mastering the game of Go. For cloud and AI practitioners, this offers insight into how Google DeepMind approaches complex AI research problems and the development process behind their models.
• While this is primarily a documentary release rather than a technical product announcement, it provides context for understanding Google’s broader AI strategy and the research foundation underlying its cloud AI services. The AlphaFold model itself is available through Google Cloud for protein structure prediction workloads.

01:54 Justin – “If you’re not into technology, don’t care about any of that, and don’t care about AI and how they built all the AI models that are now powering the world of LLMs we have, you will not like this documentary.”

04:22 ServiceNow to buy Armis in $7.7 billion security deal • The Register

• ServiceNow is acquiring Armis for $7.75 billion to integrate real-time security intelligence with its Configuration Management Database, allowing customers to identify vulnerabilities across IT, OT, and medical devices and remediate them through automated workflows.
• The deal is expected to close in the second half of 2026 and aims to triple ServiceNow’s current $1 billion annual security revenue.
• The acquisition represents a strategic data play when combined with ServiceNow’s recent purchase of Data.World, giving the company both massive volumes of se...

Welcome to episode 335 of The Cloud Pod, where the forecast is always cloudy! This pre-Christmas week, Ryan and Justin have hit the studio to bring you the final show of 2025. We’ve got lots of AI images, EKS Network Policies, Gemini 3, and even some Disney drama.

Let’s get into it!

• From Roomba to Tomb-ba: How the Robot Vacuum Pioneer Got Cleaned Out **OpenAI
• From Napkin Sketch to Production: Google’s App Design Center Goes GA
• Terraform Gets a Canvas: Google Paints Infrastructure Design with AI
• Mickey Mouse Takes Off the Gloves: Disney vs Google AI Showdown
• From Data Silos to Data Solos: Google Conducts the Integration Orchestra
• No More Thread Dread: AWS Brings AI to JVM Performance Troubleshooting
• MCP: More Corporate Plumbing Than You Think
• GPT-5.2 Beats Humans at Work Tasks, Still Can’t Get You Out of Monday Meetings
• Kerberos More Like Kerbero-Less: Microsoft Axes Ancient Encryption Standard
• OpenAI Teaches GPT-5.2 to PowerPoint: Death by Bullet Points Now AI-Generated
• MCP: Like USB-C, But Everyone’s Keeping Theirs in the Drawer
• Flash Gordon: Google’s Gemini 3 Gets a Speed Boost Without the Sacrifice
• Tag, You’re It: AWS Finally Knows Who to Bill
• Snowflake Gets a GPT-5.2 Upgrade: Now With More Intelligence Per Query
• OpenAI and Snowflake: Making Data Warehouses Smarter Than Your Average Analyst
• GPT-5.2 Moves Into the Snowflake: No Melting Required

01:06 Meta’s multibillion-dollar AI strategy overhaul creates culture clash:

• Meta is developing Avocado, a new frontier AI model codenamed to succeed Llama, now expected to launch in Q1 2026 after internal delays related to training performance testing.
• The model may be proprietary rather than open source, marking a significant shift from Meta’s previous strategy of freely distributing Llama’s weights and architecture to developers. We feel like this is an interesting choice for Meta, but what do we know?
• Meta spent 14.3 billion dollars in June 2025 to hire Scale AI founder Alexandr Wang as Chief AI Officer and acquire a stake in Scale, while raising 2026 capital expenditure guidance to 70-72 billion dollars.
  • Wang now leads the elite TBD Lab developing Avocado, operating separately from traditional Meta teams and not using the company’s internal workplace network.
• The company has restructured its AI leadership following the poor reception of Llama 4 in April, with Chief Product Officer Chris Cox no longer overseeing the GenAI unit.
• Meta cut 600 jobs in Meta Superintelligence Labs in October, contributing to the departure of Chief AI Scientist Yann LeCun to launch a startup, while implementing 70-hour workweeks across AI organizations.
• Meta’s new AI leadership under Wang and former GitHub CEO Nat Friedman has introduced a “demo, don’t memo” development approach, replacing traditional multi-step approval processes with rapid prototyping using AI agents and newer tools.
• The company is also leveraging third-party cloud services from CoreWeave and Oracle while buil...