After a whirlwind summer break (Georgia was in Australia, the US, Switzerland, France and back to the UK), your hosts return to talk fake spring in Melbourne, big AI news, and the latest progress in our Agentic AI Experiment. 🚀 AI News HighlightsGemini Nano Banana (2.5 Flash): Google’s new multimodal model nails hands (finally) and shines at storyboarding with JSON prompts. Kimi K2: A front-end coding powerhouse from China’s Moonshot AI — cheaper than Claude Sonnet 4, though backend isn’t its strong suit. GPT-5: Quietly flexing its ability to augment answers with real-time web searches. Regulation: Australia looks set to ditch bespoke AI laws — a move we (cautiously) support. Cloud & Infra: AWS NZ finally opens after a 4-year wait, while Oracle’s $300B OpenAI deal catapults Larry Ellison to the #1 richest spot. 🤖 The Agent Experiment: Content Co-Creator We update you on our experimental AI system designed to help creators generate social content ideas.The Vision: AI that uses your interests, calendar, and activities to suggest posts, captions, and even storyboards. The Hurdles: Social APIs = pricey + restrictiveScraping trending content = messy (lots of “weird” results)TikTok ≠ Instagram: their algorithms play by very different rulesCreator Insights: TikTok’s algorithm makes it easier to go viral from scratch — and creators earn more there than on Insta. ❤️ The MLP (Minimum Lovable Product)Instead of chasing APIs, we’re starting simpler:Web app that asks about passions & activities Optional calendar integrationAI-generated content ideas + Nano Banana-powered storyboardsReal-world testing on ourselves firstAnd with Instagram’s new “Edits” feature echoing this direction, the market clearly agrees. 🔮 What’s NextIterating the Content Co-Creator with real feedbackUpcoming episodes on renewables + data center powerInviting listeners to weigh in (feedback@cloud-dialogues.com) This episode blends AI news, social media realities, and product-building tradeoffs — with plenty of laughs along the way.

In the second instalment of our Agentic AI series, Georgia and Matt are joined by returning friend of the pod and AI product expert, Pete Sbarski, to put our AI-generated startup ideas under some very real scrutiny. But first… the news: ⚖️ Legal & Regulatory Shakeups A US court ruled that training AI on legally purchased books = OK, pirated books? Not so much. Germany's taking on DeepSeek, pressuring Apple and Google to block the app over privacy concerns. ⚡️ Infrastructure Watch Amazon's going big in Australia, announcing a massive $13B investment in data centers and solar by 2029. Cloudflare and Google Cloud had a rough week, with outages reminding us that even hyperscalers aren’t immune to single points of failure. 💡 Back to Business: Can AI Actually Build a Startup? Last episode, Claude and Gemini pitched six startup ideas. This week, we brought in Pete to roast them (constructively). Here’s what made the shortlist: 📝 AI RFP Assistant ✅ Compliance Monitor for SMEs 🔍 B2B Data Quality Tool ⚖️ AI Paralegal for Small Firms 💰 Grant Guru for Nonprofits ✍️ Content Copilot for Solo Creators 🧠 Key Takeaways from Pete “Just because you can, doesn’t mean you should” — some use cases (like legal AI) come with huge liability baggage. Data hygiene does not necessarily mean fancy tools — a lot of orgs want AI, but what they really need is cleaner, more structured data. AI isn’t the bottleneck — people are — from resistance to change to unclear ownership, it’s often human systems holding us back. ✅ What We’re Testing Next We’re moving ahead with two experiments: The Content Copilot – using AI to repurpose and summarise our own podcast archive. RFP / Grant Assistant – trialing real-world applications with a friend’s health tech startup. We’ll be back soon with some early results — and hopefully a winner. 👀 📩 Want early access and exclusive insights from our experiments? Subscribe to our newsletter for weekly executive takeaways from the edge of AI, cloud and innovation here: cloud-dialogues.com

In this episode, Georgia and Matt serve up your weekly dose of AI and cloud news — plus the launch of something brand new (and a little wild): *The Agentic Series* — our hands-on experiment to see if AI agents can design, build, and run a business… with minimal human meddling. 📰 Headlines This Week: Amazon’s AI Workforce Shift: Andy Jassy’s latest shareholder letter teases a leaner, more AI-powered workforce. The hosts dig into what this could *really* mean (and how Amazon Fresh’s “AI stores” were actually powered by humans in a control center in India). BBC vs. Perplexity: The BBC’s getting legal over AI scraping — accusing Perplexity of publishing full articles without permission. Is AI crossing the fair use line? Big Tech Chessboard: Rumors swirl of Apple sniffing around Perplexity, while Elon’s XAI Grok cozies up to Microsoft *and* Oracle Cloud. Game on. 🤖 Launching The Agentic Series What happens when you put Claude Opus, Gemini 2.5 Pro, and ChatGPT 4.5 in a virtual war room and ask them to create a business? We're finding out. 🧪 The Challenge: Create a digital-only, serverless product business — researched, designed, and architected by AI agents. Each LLM acts as a specialist: Claude & Gemini: product strategist & market analysts ChatGPT: evaluator and judge They were tasked with:  Finding underserved problems Sizing the market  Proposing architecture + GTM strategy  Recommending pricing and monetization models 📊 The Outcome: Claude’s Top Picks: 1. AI-powered RFP response assistant 2. Continuous compliance monitoring for SMEs 3. Real-time B2B data enrichment Gemini’s (eventual) Suggestions: 1. AI-powered paralegal for law firms 2. “Grant Guru” for nonprofits 3. Content co-pilot for solo creators 🎯 Winner (according to GPT-4.5): The AI content co-pilot for creators, thanks to high relatability, market size, and strong demo potential. 🔜 What’s Next? We’re moving into solution design and technical architecture in the next episode — with expert guests joining the build. Expect practical use cases, ethical debates, cost guardrails, and a few surprises as we let the agents do their thing. 💡 Don’t want to miss what AI builds next? 👉 Subscribe to our newsletter for exclusive insights on executive strategy, AI architecture, and emerging tech trends - subscribe here cloud-dialogues.com

🎙️ Cloud Dialogues #34: Plugging AI Into the Real World — Why MCP Matters In this episode of Cloud Dialogues, Georgia and Matt go beyond the buzzwords and into the wiring of enterprise AI. From AI agents that write code to cloud strategies that make a lick of sense, we unpack the tools and protocols reshaping modern AI — starting with the week’s wild headlines. 🔥 News Highlights: Databricks acquires Neon, strengthening the serverless Postgres story OpenAI drops Codex, a multitasking software agent that’s raising a few eyebrows Google launches Gemini 2.5 and VO3, stepping further into multimodal territory Microsoft open-sources GitHub Copilot, plus introduces a new SRE agent Oracle bets big on AI, snapping up $40B in Nvidia chips for U.S. data centers We also call out the rise of “vibe coding” and the risks of AI-powered startups without adult supervision. Georgia thinks that credentials still matter.... 🧠 Deep Dive: What the Heck Is MCP? MCP (Model Context Protocol) is an answer to a growing problem that we are all hearing about: LLMs are powerful, but kind of clueless. Without fresh data, structured tools, and the ability to reason in real-time, they hallucinate. A lot. MCP fixes that — by letting AI agents safely plug into real systems (think APIs, dashboards, HR tools) with structure, permissions, and traceability. 💼 Why Execs Should Care: ✅ Inject real-time data into AI workflows without retraining models ✅ Reduce hallucinations and increase trust, auditability & reliablity ✅ Enable secure, role-based access to internal systems (HR, finance, ops) ✅ Build agents that do more than chat — they act 🛠️ Real-World Use Cases: Pulling support ticket history during a live customer call Executing a compliance check via a secure API Asking your AI assistant to summarize live KPIs across platforms 🎧 We wrap up with a challenge: what would it really take to let an AI agent run an entire startup? (Spoiler: we’re not there yet — but we’re closer than you think - eyes on this space 👀) 📩 Want weekly insights like this straight to your inbox?Subscribe to our newsletter for exec-focused takes on AI, cloud, and digital transformation — link in the comments. #CloudDialogues #MCP #GenAI #AgenticAI #Copilot #CloudStrategy #AIIntegration #Anthropic #Claude #APIs #ModelContextProtocol #TechLeadership #DigitalTransformation

🎙️ Cloud Dialogues: Vegas, AI, and What’s Next with Google This week on Cloud Dialogues, Georgia and Matt are joined by Anupam Phoghat, fresh off the tarmac from Google Next 2025 in Las Vegas, to break down the biggest announcements, hottest trends, and a few surprises from the cloud world’s glitziest event. But first… the news roundup was 🔥: 🚨 In the News: AWS’s Big Growth Energy: 19% year-over-year growth and strong focus on making AI cheaper and faster—thanks to Tranan 2 chips. Data Center Power Drain: By 2030, data centers could be drawing more power than Japan. Edge computing, you’re up. OpenAI Eyes Windsurf: Rumored $3B acquisition of a VS Code fork to boost its dev game—and catch up to Claude Code. Nvidia’s $5.5B Problem: U.S. export restrictions to China are biting hard. Kubernetes is Back (Again): KubeCon London showed signs of a Kubernetes renaissance—maybe AI on the edge is to thank. MCP Becomes the Standard: Google jumps on Anthropic’s Model Connection Protocol bandwagon. AI models are finally learning to play nice with data.   🎰 Straight from the Vegas Strip: Google Next 2025 Highlights Anu gives us the inside scoop from the Strip, where 35,000+ attendees spread across 10 hotels saw Google go all-in on AI everything. ✨ Big Announcements: The AI Hyper Computer: Custom hardware to supercharge inference at scale GKE Upgrades: Now with inference gateway and full VM support Cloud Run & Cloud WAN: Big leaps in serverless and networking Vertex AI’s Model Garden: A smorgasbord of foundation models, including Claude and Llama Agent Development Kit: Tooling to build your own AI agents (think RAG meets agents IRL) Open-source + Interop Love: More cross-platform support, less vendor lock-in We also dug into: ⚾️ MLB’s use of AI agents to manage network ops🧠 Why your AI is only as smart as your training data🚩 Twitter/X as a case study in what not to feed your model Anu wrapped by sharing the mission behind Nebulla Action—his new venture building practical, industry-focused AI tools for healthcare, finance, and retail.   🎧 Ready to decode Google’s big bets and what they mean for your business? Tune in now wherever you get your podcasts—or hit the link in our bio.   #CloudDialogues #GoogleNext2025 #AI #CloudComputing #VertexAI #DevOps #OpenSource #CloudStrategy #GKE #AIInfrastructure #Podcast

In this episode of Cloud Dialogues, Georgia and Matt are joined by Amit from OpenOps for a deep (and refreshingly honest) dive into the state of cloud automation today—and where it's heading next. We kick things off with a look at the latest industry news: Huawei gears up to produce its own AI chips in response to ongoing tariff challenges Microsoft and Amazon hit pause on data center expansion due to power constraints And yes… humanoid robots just ran a half-marathon in China (because why not?) Then we shift gears into automation. Amit brings a wealth of experience—from Microsoft to cybersecurity to autonomous vehicles—and shares sharp, real-world insights on what it actually takes to build a sustainable automation strategy in the cloud. 🔍 Topics We Cover: The journey from visibility → orchestration → automation Why “human-in-the-loop” automation is often the safest bet How risk appetite should drive your automation roadmap Why not automating can cost you more than you think—especially in cloud security and efficiency The growing role of AI in automation (and why it still needs a chaperone) 💡 Amit reminds us that while the dream of fully autonomous cloud ops is on the horizon, we’re not quite there yet—and human oversight remains as crucial as ever. Whether you're early in your automation journey or deep in fine-tuning, there’s something in this episode for every cloud leader. 🎧 Listen now wherever you get your podcasts—and check out OpenOps on GitHub for some powerful tools to get started. Fine OpenOps on GitHub https://github.com/openops-cloud  #CloudAutomation #CloudOps #AI #DevOps #CloudStrategy #CloudDialogues #OpenOps

In this lively crossover episode, Mark, Michael, Georgia, and Matt bring their unique podcasting perspectives together for a deep (and occasionally hilarious) dive into the world of cloud, AI, and developer experience. Here's what went down: 👋 Meet the HostsThe episode kicks off with introductions:- Georgia & Matt host a show aimed at execs exploring cloud and AI strategy, launched in 2023.- Mark & Michael bring a laid-back, pub-style tech chat that started back in November. Think of it as business meets banter. 💥 Breaking Prod: A Dev ConfessionMatt shares a "whoops-that-could’ve-been-bad" moment—he accidentally wiped critical files from a pre-prod app server right before a major CRM migration. The silver lining? A stealthy recovery from backups saved the day, and no one was the wiser (until now). ☁️ Cloud & AI News RoundupThe crew unpacks the latest in cloud and AI, including:- Model Context Protocol (MCP): An open standard for LLMs to interface with APIs—recently adopted by OpenAI.- Big Money, Big Roles: A jaw-dropping $255–450K job posting at Anthropic focused on MCP.- AI Art & IP Issues: The debate over AI-generated images and artist rights heats up.- AI + Security = Headache: From vulnerabilities to weaponization, AI’s security implications are growing.- Oracle Data Breaches: Recent incidents affecting Oracle Cloud and Oracle Health (formerly Cerner) spark a discussion on health data privacy. 🛠️ Deep Dive: Developer Experience (DevX)This is where things get real. The team unpacks what’s working—and what’s painfully broken—when it comes to how developers work inside big organizations. What is DevX, Anyway?- It’s the day-to-day reality of building software: tools, processes, workflows.- Google’s monorepo + DevX team gets a gold star, but most companies? Not quite there yet. Common DevX Pain Points:- Security rules that block the tools devs actually *want* to use.- Glacial laptops and outdated hardware.- Missing, buried, or just plain wrong documentation.- Slow, bureaucratic approval chains.- No proper API tooling in place (hello, Postman and Backstage!). Why It Matters:- Bad DevX = unhappy developers = high turnover.- Wasted time for high-salary engineers isn’t just annoying—it’s expensive.- Cloud migration without DevX in mind? Recipe for inefficiency and surprise costs. Fixing DevX (Yes, It’s Possible):- Build "paved paths"—secure, approved, and actually usable.- Strike a balance between security and speed.- Track where time is wasted (slow builds, anyone?).- Treat developers like customers. Ask what they need. Then deliver it. 📚 Recommended ReadsThe team wraps with book recs for anyone looking to level up:- Platform Engineering (Michael)- Unlearn by Barry O’Reilly (Matt)- Working Backwards (Georgia)- Amped Up by Frank Sluman - Plus: [DX.com/research/overview](https://DX.com/research/overview) for even more DevX insights Bottom Line: Whether you’re leading cloud adoption or building internal platforms, don’t overlook DevX. Great tools and experiences aren’t a nice-to-have—they’re your competitive edge.

We’re back with another powerful conversation — this time with the incredible Julia Arnott-Neenee, Cofounder of Fibre Fale, tech leader and advocate for digital equity. 🚀 But first, we break down this week’s biggest Cloud & AI news: 🔹 Google’s eye-watering $32B acquisition of Wiz – what does it mean for cybersecurity? 🔹 Oracle’s $5B investment in UK Cloud – big moves in Europe! 🔹 Tencent’s new AI reasoning model & Apple’s clean energy fund in China (Georgia covers off on 'what are reasoning models?' 🌱 🔹 Microsoft’s Malaysia data center expansion 🔹 The growing data center power consumption problem ⚡ 🔹 EU’s push to dominate the AI chip industry Then, we dive into a must-listen conversation with Julia Arnott-Neenee, tackling: 🌍 The digital & AI divide—who’s being left behind? 💡 Empowering Pacific communities through tech 🔄 Why technology needs to shift power to those most impacted 👀 The big question: Who isn’t in the room when decisions are made? Julia’s journey is inspiring—leaving a global career to serve her community and co-founding a Pacific social enterprise that’s already making waves (her co-founder just won Young New Zealander of the Year! 🏆). 🚀 Key Takeaways: ✅ AI & tech reflect existing biases—how do we fix this? ✅ Marginalized communities must be seen as creators, not just consumers ✅ Moving from tech for profit → to tech for people ✅ The need for community-led solutions in digital transformation   🔊 Listen now for a thought-provoking discussion on why digital inclusion matters more than ever. 👉 And if you want more insights like this straight to your inbox, subscribe to our newsletter for the latest in Cloud, AI & tech leadership! cloud-dialogues.com Find Julia's Fibre Fale here: https://www.fibrefale.com #CloudTransformation #DigitalInclusion #AI #TechLeadership #PacificInnovation

In this latest episode of Cloud Dialogues, we dive into the evolving world of AI, data governance, and cloud transformation. Packed with insights for tech leaders, here's what you can expect:   AI Industry Insights - CoreWeave's $12B OpenAI Contract: A reminder that infrastructure shortages could be on the horizon as AI scales. - China's AI Ambitions: Baidu's Ernie models and Honor's $10B AI investment signal big moves in the East. - Copyright Controversy: OpenAI wants easier access to copyrighted material—raising big questions for creators. - Regulation Rundown: The EU’s early AI regulation contrasts with the US's more relaxed approach. - Data Center Growth: Thailand's $3B investment and AWS’s new region create fresh opportunities for startups. - Security Spotlight: Apple’s stand against UK encryption laws sparks debate. - Productivity Buzz: JP Morgan claims AI coding tools improved productivity by 10-20%, and our hosts would lose to analyse this data. AI Innovations and Tools - OpenAI’s New Agent Tools: Potentially big competition for Anthropic’s MCP. - Robotics Advances: DeepMind’s Gemini Robotics pushes "embodied reasoning" in AI-driven robots. - Sustainability Challenges: AI’s energy demands rise, with Amazon and Google pledging nuclear energy support.   Cloud Transformation for CIOs — The New Rules of Innovation with Steve Tzortzidis from V2 Digital Steve brings a wealth of insights on building AI-ready data foundations: - Data Readiness: To harness AI’s potential, data must be accessible, trusted, and well-governed. - Federated Data Models: Balancing centralized governance with domain-driven autonomy to improve speed and accountability. - "Start Small" Approach: Focus on specific use cases rather than boiling the ocean. - DBT's Role: DBT’s testing, validation, and documentation features simplify data transformation. - AI’s Future: Expect 2025 to focus heavily on AI agents, multimodal models, and real-world operationalization. Key Takeaway for Tech Leaders Success with AI isn’t just about the tools—it’s about strong data foundations, smart governance, and embracing iterative change. If you’re steering your organization through data and AI transformation, this episode is packed with actionable insights. 🎯 Stay Ahead of the Curve: For weekly insights on AI, data, and digital transformation, subscribe to Cloud Dialogues weekly executive insights at cloud-dialogues.com

For part 2 of our 2025 IWD series We chatted to Natalie Badawy from Circuit Recruitment about how to attract, retain, and empower more women in tech! 🎯 From Neurophysiology to Tech Recruitment: Natalie shares her inspiring career switch and how her background in human sciences shaped her approach to helping people break into tech. 🤝 Creating Inclusive Cloud Cultures: We explore practical strategies for supporting women in tech, from running internal bias workshops to ensuring interview panels reflect diverse backgrounds. 👩‍💻 Her Tech Circle: Learn how this fantastic DE&I organization is empowering women in tech careers. 🌍 The Business Case for Diversity: We discuss how token efforts can backfire, while meaningful change improves retention, innovation, and business outcomes. 💬 Male Allies in Tech: How men can better support women in the workplace — even if they don’t always know where to start. 📈 Flexibility & Return to Office (RTO): The episode dives into how workplace flexibility is vital for creating inclusive environments, particularly for caregivers. We discuss how rigid RTO mandates can disproportionately impact diverse employees and why trust-based flexibility leads to better outcomes for everyone. It’s an episode full of practical advice, real-world insights, and thought-provoking discussion. Don’t miss it!📲 Join the conversation about creating meaningful change in tech. Subscribe to our newsletter for Weekly Cloud Roundup: Top cloud news + exclusive podcast insights! https://www.cloud-dialogues.com/

To kick off our 2025 International Women’s Day series, Georgia and Matt sat down with Yasmin Benjamin, Head of Cloud and Finance, for an incredible conversation about navigating leadership, staying technical, and thriving as a woman in cloud. 🚀 Cloud & AI News Highlights We covered some of the week’s biggest cloud and tech stories, including: 🔬 Quantum Race Heats Up – Google, Microsoft & AWS all making quantum moves (but don’t expect breakthroughs just yet). 📞 Skype & Amazon Chime Say Goodbye – Both platforms heading for retirement. Georgia reminisces about Chime. 🚀 Satellite Showdown– China’s “Space Sale” takes on Starlink, while Australia's National Broadband Network picks Amazon over Musk. 📱 iPhone Encryption Shakeup – UK pressures Apple to soften its backup encryption. 💬 Signal Stands Its Ground – May leave Sweden to protect message security. 💡 In the Spotlight: Yasmin Benjamin Yasmin’s career is a masterclass in blending deep technical expertise with bold leadership. With a background spanning systems engineering, AI & robotics, and even a current PhD in quantum computing (!), she’s proof you don’t have to choose between tech and leadership — you can own both. Key Themes We Covered: 👩‍💻 From Engineer to Leader – How Yasmin stayed hands-on even as she moved up the ranks. 👶 Balancing Motherhood & Career – Keeping technical skills sharp during career breaks. 👩‍🚀 The Power of Community – Building networks to avoid feeling isolated as a senior woman in tech. ✨ Authentic Leadership – Why being yourself beats fitting the mould every time. 💰 The Reality of Cloud in Financial Services - If you thought banking was all cutting-edge tech — think again. Yasmin gave us a behind-the-scenes look at where financial services really are: 🎶 Legacy Lives On – Yep, some banks are still running on systems from the disco era. ☁️ Hybrid Cloud is the Default – Most are juggling on-prem with Azure & AWS. 🤖 AI in Banking – Right now, it’s all about smarter chatbots & faster data processing (with RAG models ensuring accuracy). 📊 Data is (Still) Hard – Especially when compliance, structured & unstructured data all collide. 💬 Yasmin’s Advice for Women in Tech 🔧 Stay Technical – Don’t lose your hands-on skills, even in leadership roles. 🤝 Find Your People – Mentors, sponsors & allies make all the difference. 👨‍💼 Bring the Guys Along – Male allyship is critical to driving real change. 🌱 Pace Yourself – Careers are marathons, not sprints — focus on learning, not rushing to the top. Bonus gem: Yasmin wrapped up by sharing her creative side — she wrote an e-book called "How The Two Worlds Collide”, blending her love of Star Trek & Star Wars. Tech leaders who write sci-fi? We’re here for it. You can find it here: https://tayloryasmin.gumroad.com/l/eyqci

In this episode, we go beyond the tech and dive into what really makes cloud transformation work: people, culture, and leadership. It’s not just about moving workloads—it’s about shifting mindsets! 🔥 Here’s what we unpacked: 💧 AI & Industry Trends – From the impact of AI data centers on the UK’s water supply to shifting DEI commitments and ongoing tech layoffs, we break down what’s shaping the industry. 👥 Culture is the Real Challenge – Cloud isn’t just a tech upgrade, it’s a people-first transformation. Upskilling your current teams, fostering innovation, and finding internal champions is the real game-changer. 💰 Cloud Costs & FinOps – Spoiler: Estimating cloud costs upfront is tricky! We talk about bridging the IT-finance gap, avoiding hidden licensing costs, and why FinOps is a team sport. 🔄 Managing Change (Without the Drama!) – Pilot projects, gradual adoption, and bringing people along rather than pushing them away—we cover strategies for making change stick. 🧠 Talent Trends in 2025 – The on-prem vs. cloud skills gap is growing, and companies need flexible work policies and smart upskilling to stay ahead. 🤖 AI in the Cloud – AI is powerful, but do you really need to build your own models? We discuss data management, AI biases, and why human oversight still matters. 🚀 Bottom line: Successful cloud transformation isn’t just about technology—it’s about creating a culture that embraces learning, adaptability, and collaboration. 🎧 Listen now and tell us: What’s been your biggest challenge with cloud culture? Drop it in the comments! 👇 #CloudDialogues #CloudTransformation #CloudCulture #Leadership #CloudStrategy #FinOps #AI #CloudOps

Episode Overview Kicking off 2025 with a 3 part series focussed on helping the executives and the C suite make impactful business decisions with technology.  For episode 1, we sit down with Jez Back, Cloud Economist & Finops Professional at Capgemini, to tackle one of the biggest boardroom conversations—cloud economics and strategy. With cloud costs rising, CFOs stepping into tech decisions, and efficiency becoming a top priority, we break down what really matters in 2025: cutting waste, maximizing value, and making smarter cloud investments. What’s Inside? 💡 Cloud Headlines You Need to Know The Chinese AI model, DeepSeek, that’s making waves with lower training costs Oracle’s big multicloud play—what it means for vendor lock-in Meta’s renewable energy push for data centers and what it means for sustainability 💰 Cloud Economics & CFOs: What’s Changing? Cost vs. Value: Why slashing budgets isn’t always the smartest move CapEx vs. OpEx: The accounting shift that’s reshaping IT spending SaaS Spend Gone Wild: 49% of licenses go unused, and 70% of contracts are managed outside IT—what’s going wrong? 🌱 Cloud & Sustainability—Are We Actually Going Green? GreenOps vs. FinOps: Where efficiency meets ESG goals The hidden environmental costs of cloud—water use, energy, and ‘net zero’ debates Balancing sustainability with business realities Key Takeaways ✔️ Tech decisions need transparency and predictability, not just cost-cutting✔️ The best cloud strategies are measured by business value, not just technical KPIs✔️ Sustainability matters, but cost efficiency still drives decisions✔️ Cloud repatriation? Hype vs. reality—here’s what’s really happening 💭 Final Thought:Cloud economics isn’t just about cutting costs—it’s about making the right investments, proving value, and staying ahead of the curve. 🎧 Tune in to Cloud Dialogues Episode 1 of 2025 and get the insights you need to lead cloud transformation this year! 🚀

In this episode of Cloud Dialogues, Matt & Georgia dive into the big reveals and emerging trends from AWS re:Invent 2024. With over 72,000 attendees and an action-packed week in Las Vegas, this year's conference showcased a mix of cutting-edge announcements, practical innovations, and a few surprises. If you missed the event—or just want the TL;DR—this episode has you covered! What’s New at re:Invent? Conference Highlights - A record-breaking 72,000 registrations, with a strong in-person turnout in Las Vegas. - Expanded session formats, including breakout sessions, chalk talks, hands-on workshops, and a fresh addition: PeerTalk meetups for networking and knowledge sharing. Big AWS Announcements 1. Apple + AWS: A Powerful Partnership - Apple revealed it relies on AWS Compute for machine learning and AI applications (dubbed Apple Intelligence). - By leveraging AWS Graviton processors, Apple achieved a 40% efficiency boost. - Apple now operates across 10 AWS regions using Graviton-powered instances. 2. Smarter AI - Practical AI was the name of the game this year: - Bedrock Guardrails: Automated reasoning checks to reduce AI hallucinations. - Intelligent Prompt Routing: Dynamically directs prompts to the best AI model in the same family for the task. 3. Enterprise Enhancements - Declarative Policies: Simplified policy management across AWS environments. - Elastic VMware Service: Streamlines migrations from traditional VMware setups. - Amazon Q Developer: Packed with enterprise-friendly features like: - Automatic COBOL-to-modern-language code conversion. - Automated testing for smoother development. - Tools for investigating operational issues. 4. Data and Database Innovations - SageMaker Lakehouse: A unified hub for centralizing and managing data. - Aurora DSQL: A groundbreaking serverless, multi-region, Postgres-compatible database. Key Observations The hosts highlighted a noticeable shift from last year’s “AI everything” approach to more practical, value-driven AI solutions. The focus now is on delivering tools that make a tangible difference, and the hosts predict 2025 will bring realistic AI deployments as companies fine-tune their data and AI strategies. Looking Ahead The episode wraps with a teaser for the next recording in London, January 2025, and a call for listener input: who should be the next guest on Cloud Dialogues? Tell us in the comments!

In this exciting episode of Cloud Dialogues, Matt & Georgia sit down with Boris Tane—formerly of Baselime and now with Cloudflare — to dive deep into the latest in observability for cloud computing. Boris shares insights from his unique journey and discusses the challenges, requirements, and innovations shaping observability today. Boris combines technical expertise with a fresh perspective on observability. With a Master’s in Aerospace Dynamics and a background in predicting drone behavior, he’s tackled the complexities of data processing for unpredictable scenarios. His passion for analytics led him to a career in observability, where he now helps organizations unlock the potential of real-time data. What we Covered From Monitoring to Modern Observability - Traditional Monitoring: Built around dashboards that forecast issues or document past events. - Modern Observability: Emphasizes understanding application behavior live, without code changes, and goes beyond the classic "three pillars" (logs, metrics, traces) to focus on high-quality data and efficient query engines. Core Requirements for Effective Observability 1. High Cardinality: The ability to handle limitless unique values per field. 2. High Dimensionality: The capacity to track hundreds of attributes per event—like user ID, location, headers, and more. Tackling Common Obstacles - Over-reliance on Dashboards: Many teams are caught up in dashboards instead of implementing true observability. - Transition Hurdles: Moving from traditional logging to advanced observability can be tough. - Developer Experience: A seamless experience is crucial for adoption and successful implementation. Memorable Quotes “Observability without action is just storage. If you’re not actively using logs, metrics, and traces, you’re simply paying for storage.” “The quality of your observability is only as good as the quality of data your application produces.” Key Takeaways 1. Observability goes beyond debugging—it's about empowering teams to create better products. 2. Cloud providers are starting to integrate observability as a core platform feature. 3. Effective observability requires strong team ownership and a culture that values data-driven decisions. 4. A gradual, user-friendly transition to modern observability is essential—no need for complete application overhauls. Industry Trends - Cloud Maturity Levels: Different cloud providers vary widely in their observability capabilities. - Built-In Observability: Newer platforms like Cloudflare are incorporating high cardinality and high dimensionality into their infrastructure. - OpenTelemetry Standards: OpenTelemetry is emerging as a standard, but it still needs to be complemented with application-specific insights. Business Impact - Faster Problem Resolution: Enhanced observability enables teams to solve issues more efficiently. - Product Insights for Managers: Observability data can help track feature usage and user experience. - Informed Decision-Making: Teams with comprehensive data access make smarter choices. Final Thoughts This episode highlights that while the right tools are critical, the heart of effective observability lies in producing high-quality data and empowering teams to act on it. Organizations that foster a culture of observability and improve data quality over time will see a true business impact from their observability practices.

Liz Fong-Jones, Field CTO at Honeycomb talking Site Reliability Engineering (SRE)—a game-changer for scaling and automating large systems.

Matt & Georgia dive deep into the world of data strategy with Allison Howells, a seasoned expert with over 20 years of experience across industries like financial services, insurance, and consulting.

In this exciting episode of "Cloud Dialogues," Georgia and Matt return from their well-deserved breaks, ready to dive deep into the world of cloud operating models. They unpack the challenges organisations face when transitioning to cloud environments and share insights on how to navigate this complex landscape. Here's what you can expect: 1. Tackling Operating Model Challenges: Dive into the common pitfalls of cloud transformation, emphasizing how misaligned operating model changes often lead to trouble. 2. DevOps and Product-Centric Thinking: The shift from traditional IT operations to a DevOps and product-focused approach, stressing the need for a cultural shift within organisations. 3. Platform Engineering Essentials: The importance of customising cloud platforms to meet the unique needs of DevOps teams, all while creating an exceptional developer experience. 4. The Role of Cloud Centers of Excellence (COE): Discover how COEs bridge the gap between platform teams and developers, ensuring smooth and efficient cloud usage. 5. Evolution of Change Management: Learn how change management is transforming in cloud environments, moving from rigid approval processes to more flexible, enabling approaches. 6. FinOps and Accountability: The critical role of product owners in balancing cloud costs and value, making accountability a key focus. 7. Navigating Data Management: Challenges of managing data across organisations, proposing a federated model with a central data catalog. 8. AI and Platform Teams: Should organisations build their own AI capabilities or rely on existing SaaS solutions? The hosts offer their take on this hot topic. 9. Mastering Containerisation: They shed light on the complexities of managing containerised environments like Kubernetes, with practical insights. 10. Strengthening Security Operations: The importance of well-resourced security teams in understanding and mitigating risks within intricate cloud setups. 11. Transforming Operating Models: Finally, the hosts advocate for small, incremental changes over sweeping transformations, ensuring smoother transitions. To wrap things up, Georgia and Matt hint at an upcoming discussion on Site Reliability Engineering (SRE)—stay tuned!

In this exciting episode of the Cloud Dialogues Podcast, we dive into the world of DevOps with none other than Patrick Dubois, the man who coined the term "DevOps" back in 2009. Here’s a breakdown of the key points we covered: 1. The Birth of DevOps: - Patrick takes us back to the origin story of DevOps, which he accidentally coined during the planning of DevOps Days in 2009. - DevOps isn't just about automation; it’s a holistic approach involving collaboration, feedback loops, and business strategies. 2. AI Meets DevOps: - Discover how AI is revolutionizing the software development lifecycle, from brainstorming ideas to deploying and maintaining applications. - Highlights include tools like GitHub Copilot for coding, AI-driven UX/UI designs, and AI-assisted testing and monitoring. 3. Navigating Challenges: - Organizations face the challenge of balancing innovative AI solutions with practical implementation. - The expertise of seasoned engineers is crucial to evaluate AI-generated code and solutions. - With AI integration, security and risk management are more important than ever. 4. The Future of Testing and Quality Assurance: - AI can lead to larger codebases and longer review times, emphasizing the need for automated testing with human oversight. - New concepts like "evals" (evaluations) are emerging to assess AI-driven applications. 5. Impact on Organizations: - Addressing concerns about job displacement due to AI automation. - A shift from coding roles to managing systems and reviewing outputs. - Faster onboarding processes and increased productivity could be on the horizon. 6. Strategies for AI Implementation: - Start with pilot teams, often involving data science experts, before scaling up. - Eventually, move to platform teams while ensuring strong governance, licensing, and data management. 7. Looking Ahead: - Organizations need comprehensive strategies for AI integration in their development pipelines. - AI promises better situational awareness and faster decision-making for executives. The episode wraps up with Patrick offering a strategic roadmap for executives on implementing AI in DevOps, emphasizing the dynamic nature of best practices in this rapidly evolving field.

In this exciting episode, Matt & Georgia dive into how organizations can harness the power of design thinking to unlock the full potential of cloud. Many organizations either struggle to reap the benefits of cloud migrations or are unsure how to leverage the cloud strategically. Our hosts coin a design thinking approach: starting with mission-critical processes and gaining a deep understanding of user journeys and interactions. They introduce a dynamic framework to guide executives through this transformation:  a. Empathize with users and pinpoint core problems and opportunities b. Define current value streams and map out user journeys c. Ideate and reimagine processes without existing constraints d. Develop comprehensive architectural frameworks and designs that deliver these reimagined journeys e. Validate solutions with stakeholders and users f. Continuously iterate and refine the process Georgia emphasises the need for involving a diverse group of stakeholders, balancing customer needs with the organization’s realities, and maintaining continuous feedback and communication with users and customers throughout the journey. A key takeaway for leaders is to support and celebrate the lessons learned from failures during these transformation efforts. Not all systems need a complete overhaul; some might be better suited for SaaS solutions. Additionally, the importance of allocating dedicated resources specifically for transformation projects, separate from the usual business operations. Please share your questions and experiences in the comments!