Latest / Bull Market Conversations with Fexingo: Rallies, Momentum, and Riding Market Strength / Why Cloud Stocks Are Defying the Market Rally
Transcript
- Lucas: Look at the tape this week. The S&P five hundred is grinding sideways, barely holding onto those seven thousand six hundred levels, but look at what’s actually moving. CrowdStrike is up more than ten percent in just five days. NetApp is nearly nine. Datadog is up four and a half. While the broad market is taking a breath, these specific cloud and security names are breaking out with serious momentum. Luna: It feels less like a speculative run and more like a panic buy of operational stability. When you see that kind of volume in cybersecurity during a general market pullback, it usually means something fundamental has shifted in how CTOs allocate budget. Lucas: Exactly. And here is the thing most people miss: they think AI is all about building new models. But for the average enterprise, the immediate pain point isn’t building the model; it’s securing the pipeline and monitoring where the money is going. We are seeing a shift from experimental AI spend to defensive infrastructure spend. It’s boring, it’s unsexy, and it is currently the only part of the tech stack that investors are willing to pay a premium for right now. Luna: So you’re saying the narrative has flipped from innovation to insurance? Because if an AI agent makes a mistake, the liability falls on the company, not the developer. Lucas: Precisely. Think about the recent headlines coming out of Goldman Sachs and JPMorgan. They aren’t just buying generic tech ETFs anymore; they are picking winners in security and observability. Why? Because when interest rates stay sticky around three point eight percent, companies don’t have the slack to absorb massive breaches or compliance failures. Security becomes a non-discretionary expense. It’s not optional anymore; it’s the tollbooth for doing business digitally. Luna: That explains why names like CrowdStrike and Datadog are decoupling from the broader Nasdaq weakness. Their revenue streams are tied to uptime and safety, which don’t shrink when GDP growth slows. Lucas: Right. Let’s look at the numbers for a second. Real GDP growth is down to two point two percent year-over-year. In a typical slowdown, software spending gets cut first. But cloud security? That stays flat or grows slightly. It’s counter-cyclical. If anything, fear drives adoption. When the market gets jittery, IT directors double down on monitoring tools because they need visibility into every transaction. That’s why Datadog is sitting near two hundred seventy dollars despite the macro headwinds. Luna: But isn’t there a risk that eventually, the cost of all this infrastructure becomes too heavy? We’ve seen companies burn cash trying to integrate AI without clear ROI. Does that pressure ever hit the providers? Lucas: That is the legitimate concern. If enterprises start realizing that their AI agents are costing them more in compute and security than they are saving in labor, they will pull back. But we are not there yet. Right now, October twenty twenty-six, the dominant story is still capability. Companies are terrified of being left behind by competitors who have successfully deployed autonomous workflows. So they keep buying the shovels, even if they aren’t sure exactly where the gold is yet. Luna: So it’s a gold rush mentality, but focused on the gear shop rather than the mine itself. You buy the helmet and the pickaxe because you know someone is digging somewhere. Lucas: I love that analogy. And it highlights another layer: the stickiness of these platforms. Once you embed a tool like CrowdStrike’s Falcon platform or Datadog’s APM solution into your core operations, switching costs are astronomical. You can’t just rip and replace them on a whim. That creates a recurring revenue moat that investors love, especially when growth elsewhere is stagnant. It turns volatile tech stocks into bond-like proxies with equity upside. Luna: Which brings us to valuation. These stocks are trading at multiples that would have been unthinkable eighteen months ago. Is the market pricing in perpetual growth, or is there a realistic expectation of deceleration baked in? Lucas: Good question. Most of these names are priced for high single-digit to low double-digit growth, assuming margins expand as they scale. The risk isn’t that growth stops; it’s that it flattens. If we see a hard landing, even security budgets can get trimmed, albeit slowly. But for now, the consensus view is that these companies have enough backlog and contract renewals to guide through any mild recession. That confidence is what keeps the bid under the stock prices steady. Luna: And what about the smaller players? We’re seeing a lot of focus on the big caps here. Are there mid-cap opportunities in this same resilience theme? Lucas: There are, but it’s harder to find them cleanly. The market tends to lump everything into either 'AI hardware' or 'AI software.' The middle ground—companies providing the data governance or API management layers—is often overlooked. But honestly, for most listeners, sticking to the leaders in security and observability is the safer play. You get the exposure to the trend without betting on a niche startup that might get acquired or fail to scale. Luna: Makes sense. Diversification across the whole tech sector is risky right now. Concentration in the defensive sub-sectors feels smarter. Lucas: Absolutely. Now, before we dig deeper into the specific mechanics of how these contracts are structured, I want to take a quick beat. This show is independent, ad-free, and produced entirely by our team. If our money conversations have helped you think about a decision differently, we’d be grateful for your support. Honestly, if today was worth a coffee to you, that's the link — buy me a coffee dot com slash fexingo. That's F. E. X. I. N. G. O. Luna: Yeah, it really helps keep the research deep and the commentary honest. Thanks for keeping us going. Lucas: Anyway, let’s talk about the contract structures themselves. Enterprise deals for these tools are rarely one-off purchases. They are multi-year agreements with annual escalators. When you lock in a customer for three years, you essentially pre-sell your growth. That’s why these companies can give such confident guidance even when the macro environment is cloudy. They already know what the revenue looks like for the next twelve to eighteen months. Luna: So the volatility comes from new logo acquisition, not churn? Because if retention is high, the base revenue is protected. Lucas: Exactly. Churn is minimal in this sector. If you are running your entire security posture on a platform, you are not leaving unless there is a catastrophic failure. So the risk is purely top-line expansion. Can they sell more seats? Can they upsell additional modules? That’s where the margin expansion happens. As customers add more features to their existing contracts, the marginal cost of serving them drops, and profitability improves. Luna: That sounds like a classic land and expand model. It’s elegant, but does it create dependency issues? What if a competitor offers a cheaper alternative for a specific module? Lucas: Price sensitivity is real, but context matters. For a small business, maybe. For a global bank or a healthcare provider, the cost of a breach outweighs the savings of a cheaper tool by orders of magnitude. They pay for reliability and brand trust. That’s why CrowdStrike and Palo Alto Networks dominate. They are expensive, but they are also the safest bet in a crisis. Investors know that pricing power exists here, which supports the current valuations. Luna: It’s interesting how much this mirrors the early days of cloud computing. AWS started as infrastructure, but the value became the ecosystem. Here, the ecosystem is security and observability. Lucas: Spot on. And just like AWS, the companies that win are the ones that make it easiest for developers to build securely. If you reduce friction for the engineer, you win the wallet. That’s the key metric these companies track: developer adoption. Not just C-suite sign-off, but actual usage by the teams writing the code. If developers love the tool, they champion it internally. That bottom-up adoption is incredibly hard to stop. Luna: So the sales motion is changing. It’s less about convincing the CFO and more about empowering the engineering lead. Lucas: Completely. The buyer persona has shifted. Ten years ago, you sold to the CIO. Today, you sell to the Chief Information Security Officer, the VP of Engineering, and sometimes directly to the developer community. This decentralization of buying power actually accelerates sales cycles. Deals close faster when the end-users are advocating for the product. Luna: That must make forecasting much more dynamic. You can’t just rely on traditional pipeline metrics anymore. Lucas: No, you have to look at engagement metrics. How many active users? How many integrations installed? Those leading indicators tell you more about future revenue than the number of proposals sent out. And right now, those engagement numbers are sky-high. People are building more stuff, which means they need more monitoring and protection. Luna: Which circles back to the AI angle. More automation means more complex systems, which means more potential points of failure. Lucas: Yes. Complexity is the enemy of security. As your architecture becomes more distributed and automated, your attack surface expands exponentially. You can’t secure what you can’t see. That’s why observability tools are becoming just as critical as the security tools themselves. You need to detect anomalies in real-time across thousands of microservices. It’s a technical arms race, and it’s funding these companies’ growth for years to come. Luna: It feels like we are entering a mature phase for enterprise tech. The hype cycle is over, and now it’s just about execution and efficiency. Lucas: I think that’s the best way to describe it. The speculation about whether AI will work is gone. Now it’s about how well it works and how safely it runs. The market rewards competence, not promises. And in that regard, these cloud and security stocks are delivering exactly what they promised: stability in an unstable world. Luna: So for the listener holding these positions, the thesis remains intact as long as complexity continues to grow? Lucas: As long as digital transformation continues, yes. And given that nominal GDP is still expanding, albeit slowly, businesses are still investing in their digital cores. The direction of travel is clear. The question is just timing. And right now, the momentum suggests we are still early in this particular cycle of defensive tech adoption. Luna: Interesting. Do you think we’ll see a rotation out of these names once the broader market stabilizes, or is this structural change permanent? Lucas: Permanent in the sense that security and observability will always be needed. But the premium valuation might compress if the broader market rallies hard and capital flows back into consumer discretionary or cyclicals. It’s not that these companies will fail; it’s that their relative attractiveness might fade compared to higher-beta plays. But for now, they are the anchor. Luna: Anchors hold you steady in a storm. That’s a comforting thought when the VIX is twitching. Lucas: Exactly. In a volatile market, stability is the most valuable commodity. And it seems like the tech sector has finally found its version of gold. Luna: Well said. Let’s see if this trend holds through earnings season, because that’s when the rubber meets the road. Lucas: Agreed. Until then, keep an eye on the usage metrics. They tell the real story.