Software Stack Investing - Investing analysis of the software companies that power next generation digital businesses

Q4 2023 Hyperscaler Earnings Review

February 13, 2024 / poffringa

After over a year of headwinds from customer workload optimization, it appears the hyperscalers are finally reaching a point where future growth will be driven by a more normalized expansion cycle. All three hyperscalers delivered annual growth in Q4 that was either equal to or above the prior quarter. Sequential revenue growth rates for AWS and GCP even accelerated.

With cloud workload utilization returning to being driven by new applications and the expansion of existing ones, software and data infrastructure investors can breathe a small sigh of relief. The strong headwind of workload optimization is yielding to the renewed secular tailwind of cloud migration and digital transformation projects. Lest we get too excited, though, it still isn’t clear what the post-Covid, steady state revenue growth rate will be. It’s likely that the natural growth rate has moderated from the rush to the cloud in 2020, forced by work from home and interruption of physical channels.

Making the recovery picture more complicated, AI initiatives are introducing a new demand tailwind for cloud infrastructure. Just as the obfuscation from workload optimization abates, IT enterprise spend appears to be shifting towards capitalizing on new AI-driven capabilities. Enterprises are delivering tangible workforce efficiencies, productivity improvements and better customer experiences by applying foundational models to their own data troves and business processes.

Whether this AI investment represents incremental budget or is being pulled from existing digital transformation work remains to be seen. If there has been borrowing for AI, that funding may be reset in 2024 as updated annual budgets are rolled out. Additionally, as worker productivity prototypes transition into full scale deployment across the employee base, realized cost savings can be shifted back into budgets for further investment.

The recent earnings results from the hyperscalers provide some hints. The market is certainly interpreting the re-acceleration of revenue growth as a positive signal for software and data infrastructure companies across the board. Stocks for these companies were up significantly the day after Amazon’s earnings (in spite of a strong Jobs report). In the time since I started this post, we have received better than expected earnings reports from CFLT and NET, resulting in outsized jumps in those stocks.

Overall, I think the hyperscaler results portend well for the basket of software and data infrastructure companies going forward. The big hindrance over the past year has been pressure from cost cutting and delayed expansion of utilization. Further, the reset phase for digital natives that spent big during Covid has likely reached its end, with investment picking up again going forward. Additionally, start-up investment (outside of AI) may re-emerge later this year or into 2025, which will bring another tailwind of infrastructure spend to the cloud providers.

In this post, I review the Q4 earnings reports from Microsoft, Google and Amazon with particular focus on their cloud divisions. I also digest commentary on their AI initiatives and speculate what this might mean for budget allocations. As we have already seen, the activity on the hyperscalers has implications for supporting software and data infrastructure providers.

Data Infrastructure Opportunities in 2024

January 23, 2024 / poffringa

After languishing for most of 2023, software and security infrastructure stocks finished the year with an impressive run. This inflection started with Q3 results as the hyperscalers telegraphed a moderation of the optimization headwinds that had been plaguing the sector since 2022. After spending the prior 12 months wringing out savings from their cloud workloads, enterprise IT teams began reaching the end of their optimization exercises. These were largely catch-up efforts from delayed post-launch tuning during the Covid spending surge, as well as right-sizing of workload resources that had been over-provisioned in expectation of maximum growth.

This curtailing of optimization removes a negative headwind to revenue growth for the hyperscalers and the downstream software infrastructure companies. Revenue growth can return to being predominantly driven by positive influences, like the creation of new cloud workloads and expansion of usage for existing ones. Drafting off the hyperscaler trends, software infrastructure companies generally reported better than expected Q3 results, sharing similar commentary as the hyperscalers around less pronounced optimization and recovery towards normal spending patterns. They were quick to point out that they still feel macro pressure – it just isn’t getting worse.

This narrative helped several of the independent software infrastructure providers revisit their 52 week highs in stock price coming into 2024. Beneficiaries included SNOW, DDOG, NET, ESTC and MDB, among others. Cybersecurity companies fared even better with CRWD, PANW and ZS surpassing 100% gains for 2023.

Quick Update and a Look Forward

December 31, 2023 / poffringa

I want to thank everyone for your inquiries over the past couple of months. I took a break from regular blog posts, in order to focus on a few side projects. These included new research areas, doubling down on angel investing and another guest lecture for the London Business School. A common thread within these pursuits was exploration of current trends associated with AI. Without stating the obvious, AI is touching every industry and will have huge ramifications for software infrastructure going forward. This trend is too large to treat as an extension of the existing growth vector for software, which has largely projected through the rise of the Internet and mobile device proliferation.

While today’s AI is the outcome of years of steady, but familiar, efforts in machine learning, it has become significantly more accelerated, broad-reaching and impactful. We are entering an exciting period where software is inflecting from helping humans retrieve information more quickly (traditional Internet) to actually performing tasks on our behalf (generative AI, co-pilots and ultimately autonomy). This shift dramatically alters the value proposition and economic benefit, particularly as AI-driven systems start to perform work that has traditionally been addressed by salaried humans.

The ramifications will be far-reaching for society and naturally create a number of investment opportunities. I am considering these within the context and through the lens of software infrastructure. At the simplest level, AI training and operations will drive a step-change in the consumption of compute and data. The same technology functions that benefitted from the growth of mobile devices will see increased demand driven from enablement of new AI services, except that the magnitude will likely be 10x the influence of mobile.

As it relates to this blog, I plan to continue the same scope of coverage, but will account for the impact of AI on software development and infrastructure. Look for upcoming posts on the business implications for the companies that provide data infrastructure, application delivery, security, observability and core hosting. It is an exciting time to be in the software space – even surpassing the acceleration we experienced during Covid.

Cloudflare (NET) Q2 2023 Earnings Review

September 18, 2023 / poffringa

Following a disappointing Q1 earnings report highlighted by challenges in the go-to-market effort, Cloudflare demonstrated renewed momentum in Q2. The sales reorganization is progressing well. Large enterprises expanded spend, adding to multi-product subscriptions across several categories. In parallel, profitability measures continue to improve with growing operating margin and cash flow.

With a mission statement to help make a better Internet, Cloudflare’s product strategy is grounded in disruption. By owning and operating a network of data centers in 300+ cities worldwide, Cloudflare enters product categories with the assumption that they can deliver better service than incumbents through lower cost, improved performance and greater customization.

This messaging appears to be resonating with new enterprise customers. In Q2, Cloudflare landed their largest Zero Trust deal to date, pushing paid seats in a single customer deployment past 25,000. A critical requirement to land new enterprise Zero Trust deals is to have existing ones as reference customers. Several major Zero Trust customer wins in Q2 may provide the tipping point for future large enterprise adoption.

The developer platform (Act 3), is starting from a smaller base, but is experiencing rapid growth. The number of Worker applications reached 10M in Q2, quadrupling since Q3 of 2022. R2 usage accelerated to 85% sequential growth in Q2, up from an impressive 25% q/q rate in Q1. These products are showing up in new customer wins, contributing to near record additions of $100k, $500k and even $1M ACV customers.

As part of Investor Day, the leadership team showed how Cloudflare’s largest customers are also those adopting multiple product subscriptions. Similar to peers in software infrastructure that report on customers paying for 4+, 6+ and even 8+ products, Cloudflare is demonstrating that an expanding product offering can drive incremental revenue. Over the last four years, the attach rates for customers with 8+, 9+ and 10+ product subscriptions have more than doubled. These customers now contribute the majority of Cloudflare’s annual revenue.

For fast-growing start-ups establishing a software and security stack from scratch, Cloudflare’s platform appears particularly appealing. This is evidenced by the rapid uptake from many of the leading AI companies. As developer-led organizations, Cloudflare’s bottoms-up sales motion naturally resonates. A new CRO with enterprise sales experience will help Cloudflare win business where a top-down approach is needed as well.

Confluent (CFLT) Q2 2023 Earnings Review

August 21, 2023 / poffringa

After delivering favorable results in Q1, Confluent continued on largely the same trajectory in Q2. Sequential growth rates even imply stabilization around 30% annually, after almost 2 years of deceleration from Covid highs. This growth is being led by rapid adoption of Confluent Cloud, with the licensed Confluent Platform offering for on-premise deployments demonstrating surprising resiliency as well.

The other factor providing support is a sharp improvement in profitability measures, with Non-GAAP operating margin increasing by 25 points year over year from -34% to -9%. The company expects operating margin to reach break-even by Q4. Free cash flow is following a similar path. Profitability was helped by an 8% headcount reduction in January, which notably doesn’t appear to have impacted growth.

Confluent’s recent revenue outperformance has been driven by customers exceeding their commitments for Cloud service usage. While customers may be limiting the size of future contractual obligations (reflected in RPO), engineering teams are choosing to allocate more spend to Confluent as the quarter proceeds. To me, this signals the value customers are extracting from the Confluent Cloud product, as they willingly spend more than they had budgeted.

This may reflect the larger overall theme that enterprises are scrambling to improve their data processing infrastructure in anticipation of leveraging AI to create new offerings for their customers, employees and partners. While the expected benefits from AI are still unfolding and enterprises are largely in proof of concept mode, it is generally understood that effective AI requires good data.

Quality data as an input for AI and ML processing isn’t new, but the priority has been increased. This translates into more focus on consolidation, filtering, cleansing and categorization of silo’ed data stores. Data recency is also recognized as an advantage, which is creating a greater push towards real-time data distribution. It is this focus on reaching more data and delivering it in near real-time that is served by Confluent.

As other software infrastructure companies are experiencing rapid drops in NRR, Confluent appears to be holding up well. While they don’t share the actual values, management reported that overall NRR is still over 130% and for Cloud it exceeds 140%. These are pretty remarkable numbers in this IT environment for a product that is approaching an $800M annual run rate.

Q2 2023 Hyperscaler Earnings Review

August 6, 2023 / poffringa

Headwinds from workload optimization may have peaked in Q2. After nearly a year of negative drag on revenue growth for the hyperscalers, it appears that cloud infrastructure customers are shifting their focus away from workload optimization and back towards the deployment of new ones. At least that is what Amazon’s CEO told us in the opening statement of their earnings release. While the hyperscalers delivered revenue growth rates that decelerated from the prior year, they are now showing an uptick sequentially from Q1.

This circumstance makes sense. After rapidly spinning up new cloud workloads during Covid, established enterprises and start-ups alike postponed the normal post-launch clean-up cycles that address right-sizing server instances, tuning queries and rationalizing data retention. In an environment of flush IT budgets and pressure to ship fast, it’s easy for engineering teams to postpone this technical debt.

As budgets contracted and digital transformation project pace slowed down in 2022, engineering teams were encouraged to shift cycles back to paying down their technical debt. With pressure to generate cost savings, a lot of that work focused on optimizing existing application workloads. Engineering teams were able to review cloud resource utilization, reset capacity allocations, tune database queries, clean up prolific logging and refactor code to run more efficiently. All normal engineering best practices.

Except that they happened all at once. As this optimization work digested the oversized backlog of Covid technical debt, it created an unusually large reduction in resource consumption over a shorter period. This translated into less revenue for the hyperscalers and software infrastructure vendors that are consumption based. A normal application workload tuning exercise can reduce resource utilization by 20-30% or more. Excessively over-provisioned capacity might even be cut by 50%, simply by downsizing server instances. The hyperscalers rightfully make this easy to execute as a consequence of elasticity, but lower resource consumption means less revenue.

While this tuning is standard practice, in the post Covid catch-up period, it created a larger than normal reduction in spend. Enterprises were increasing consumption in some areas by launching new cloud workloads and digital transformation projects (although probably at a slower rate), but the immediate drop in cost for existing workloads created a large negative headwind to revenue growth. This caused the prior cadence of sequential quarterly increases in hyperscaler spending to slow down rapidly and even go negative briefly.

The optimization catch-up cycle can only last a finite amount of time. Eventually, technical debt is worked off and Covid workloads are tuned and right-sized. The effort to capture savings has diminishing returns, or as Microsoft’s CFO said in April, that workloads can’t be optimized forever. With the latest earnings commentary from the hyperscalers, it appears the catch-up period is wrapping up. Hyperscaler spend by enterprises will be increasingly driven by new activity, with the negative drag created by post-launch optimization returning to its pre-Covid levels.

Where the steady state growth rate lands remains an open question. Data points during Covid were clearly inflated, as both large enterprises and rapidly growing start-ups threw money at their cloud migration and digital transformation projects. We can assume that this rate of new investment has slowed down from the peak, but is still robust. Over the past 12 months, negative consumption trends from optimization have obfuscated the post-Covid steady state. When optimization stabilizes, investors will get a clear idea of what the steady state growth rate will be.

Unfortunately, that growth rate won’t be easily comparable to the pre-Covid period as another force has injected a new variable, which is investment in AI. As enterprises consider their AI strategy, they are spinning up IT projects to harness their data to create digital services powered by new AI models. These efforts are generating demand for AI specific services from the hyperscalers. There would be some spillover into demand for generalized software infrastructure services as well.

As growth rates for the hyperscalers potentially level out and even inflect back upwards, investors can expect a similar pattern to follow for various software infrastructure providers. Logically, if enterprises are consuming more compute and storage resources on the hyperscalers to support their new AI-driven applications, then a similar increase in demand should materialize for adjacent software services, like databases, monitoring, delivery, orchestration and application security. Serving content at scale to users worldwide over the Internet still requires these things.

Insights from a Pair of Data Summits

July 23, 2023 / poffringa

AI has crashed onto the investing stage in 2023, driving significant stock price gains for several companies. Some, like Nvidia and Microsoft have already projected a direct revenue benefit as part of recent earnings reports. Others have indicated they expect AI to drive demand tailwinds going forward as part of management commentary.

Eventually, most software service and infrastructure providers should benefit from increased demand, as AI services proliferate and contribute to all areas of the economy. Because many AI services are delivered through Internet-based applications, the same guardrails of security, delivery, monitoring and operational data storage will be needed. This is in addition to the increased consumption of data services to collect, prep, distribute and process the inputs for various AI models.

AI-driven expert systems and co-pilots will raise the productivity of information workers. Enterprises will need fewer of them to accomplish the same amount of work. This will free up budget to increase spend on AI software services, similar to the efficiencies gained from the proliferation of SaaS tools over the last decade that helped internal business teams automate most aspects of their operations.

Software development teams, in particular, will experience a significant boost in output per employee. Enterprises will be able to clear their application backlogs more quickly, increasing the demand for hosting infrastructure and services. At steady state, fewer developers will be needed, supporting a shift of IT budget from salaries to software.

As data is the largest ingredient to these enterprise AI development efforts, software vendors providing data processing and infrastructure services stand to benefit. AI has further elevated the value of data, incentivizing enterprise IT leadership to review and accelerate efforts to improve their data collection, processing and storage infrastructure. Every silo’ed data store is now viewed as a valuable input for fine-tuning an even more sophisticated AI model.

In the realm of big data processing, enterprises need a place to consolidate, clean and secure all of their corporate data. Given that more data makes better AI, enterprise data teams need to ensure that every source is tapped. They are scrambling to combine a modernized data stack with an AI toolkit, so that they can rapidly, efficiently and securely harness AI capabilities to launch new application services for their customers, partners and employees.

At the center of these efforts are the big data solution providers. These include legacy on-premise data warehouses, cloud-based data platforms and of course, the hyperscalers. Among these, Snowflake and Databricks are well-positioned, representing the fastest growing modern data platforms that can operate across all three of the hyperscalers. While the hyperscalers will win their share of business, enterprise data team leadership often expresses a preference for an independent data platform where feasible.

Fortunately for investors, Snowflake and Databricks held their annual user conferences recently. Perhaps it was intentional that they fell within the same week – at least they staggered the events between the first and second half. Both companies made major product and partnership announcements, leading to many comparisons between the two and speculation about changes in relative product positioning.

The market for the combination of big data and AI processing will be enormous, with some projections reaching the hundreds of billions of dollars in annual spend. While the Snowflake and Databricks platforms are clearly converging in feature set scope, they still retain different approaches based on their historical user types. Such a large market will likely support multiple winners.

MongoDB (MDB) Q1 FY2024 Earnings Review

July 2, 2023 / poffringa

After guiding for a sequential 4% drop in revenue for Q1, MongoDB delivered a strong beat. More importantly, their preliminary estimate for Q2 revenue would achieve a reacceleration of annual growth if they outperform at the same level as Q1. The revenue projection for Q2 even leapfrogged past the analyst consensus for Q3. While the market expected some conservatism, this level of outperformance caught investors by surprise, with the stock surging 28% the next day.

Equally impressive were improvements in profitability. In the past, MongoDB has been discounted for poor operating leverage. The transition to 2023 has brought record levels of operating income and FCF, closing the gap with peers in the software infrastructure space. This also led to a significant beat and raise on EPS, which we don’t often see with high growth SaaS companies.

Even customer activity notched records. Both total customer additions and those with spend over $100k in ARR represented all-time quarterly highs. Of new customers, over 200 companies are categorized in the burgeoning AI industry, providing another catalyst as these start-ups are landing new capital at levels on par with the Covid beneficiaries of 2020-2021.

MongoDB has emerged as a hot stock once again, with its valuation multiple now pressing up against the top of its peer group. The stock has more than doubled in 2023 and reached its 52-week high recently. MongoDB is well-positioned to capitalize on tailwinds from AI, as enterprises revamp their data infrastructure to deliver new insights and services from their proprietary data sets. With new product announcements at MongoDB.local in June, MongoDB is further supporting the case for consolidation of application workloads onto its developer data platform.

Snowflake (SNOW) Q1 FY2024 Earnings Review

June 19, 2023 / poffringa

Snowflake’s consumption business continues to feel pressure as large enterprise customers look for ways to optimize usage. While it seemed that management had a handle on forecasting the impact of this effect when they lowered guidance back in Q4, they still underestimated the trend. With the Q1 report, they once again brought down the full year revenue target.

This had the expected effect of torpedoing the stock the day after earnings, with a post-earnings drop of 16.5%. After that, a strange thing happened. The stock began appreciating again and surpassed its pre-earnings price two weeks later. As with other software infrastructure companies, the market’s perception that demand for AI services will drive incremental usage is propping up the stock. Snowflake management added to this momentum with a few key announcements, including a preview of their upcoming Snowflake Summit conference, which will include a fireside chat with Nvidia’s CEO. This all implies that Snowflake is positioning themselves to benefit from increased AI workload demand.

In the near term, Snowflake is being directly impacted by their consumption model, which magnifies changes in customer behavior as they identify ways to reduce costs. Looking forward, the market is anticipating the moderation of these optimization headwinds, as enterprises work through the low hanging fruit of cost savings. At that point, Snowflake’s growth should return to its prior cadence driven by new cloud migration workloads and the expansion of existing ones.

Given that enterprise benefit from AI hinges on access to a consolidated, clean and secure data set, Snowflake is well-positioned to serve as a primary data source. Their positioning is further solidified as the same environment could be leveraged to run jobs that enhance the AI models. This applies to LLMs and other foundation models, as well as more traditional types of machine learning output like recommenders. Snowpark, Steamlit and other extensions that make the environment more programmable started this process. New acquisitions are bolstering the platform’s capabilities as well. Investors are looking towards announcements at the upcoming Summit user conference for more insight into Snowflake’s planned AI capabilities.

Datadog (DDOG) Q1 2023 Earnings Review

June 4, 2023 / poffringa

Datadog stock surged 45% over the month of May, following their earnings report on May 4th. The results aligned with the common theme of “better than expected”, shared with several other software companies reporting results recently. This outperformance appears to have set a baseline across the software sector, with upward momentum building as more companies report results. A new tailwind has been excitement around the potential for AI to drive an incremental demand cycle for software and security infrastructure.

While AI holds promise, it will require several quarters or even years to play out. In the meantime, enterprise IT spend moderation, workload optimization and deal scrutiny have blunted the continuing secular trends of digital transformation and cloud migration. The market is eagerly trying to anticipate when optimization headwinds might abate, which could drive a re-acceleration of growth. AI’s impact on software infrastructure, if it materializes, would be through more consumption of supporting services as additional applications and digital experiences are brought online.

Datadog is navigating these same trade-offs. Over the last few quarters, their results have been impacted by the slowdown in cloud migration, workload optimization and even spend reduction in products with variable consumption like log retention. To account for these factors, management set 2023 revenue guidance conservatively, projecting just 24% annual growth this year, down from 63% in 2022.

While this represents a huge deceleration in growth, the market is looking for signs that revenue growth in the 20% range may represent the bottom. That explains why a slight beat to earnings estimates is generating an outsized reaction. Datadog stock jumped over 14% the day after the earnings report. One side effect of the revenue growth slowdown has been an increase in profitability. Datadog, and other software companies, began moderating staffing and other operational costs in anticipation of a slowdown. These reductions, compounded by revenue outperformance, are driving higher operating margins.

In at least one positive sign around the demand environment, software companies are still reporting “record customer pipelines”, with new customer additions roughly tracking with prior quarters, albeit on the lower end. The challenge has been in extracting larger contracts from those existing customers in the near term.

In Datadog’s case, their most important business metric, in my opinion, has been resilient. That metric is the growth in customers adopting multiple Datadog products. As the Datadog team keeps expanding the platform offering into new areas like security and developer experience, it’s critical that customers continue to add these product subscriptions to their contracts. If they weren’t, then Datadog’s outsized growth potential would be significantly limited. For Q1 at least, growth in customers subscribing to 2 or more, 4 or more and 6 or more products progressed almost linearly. Further, management shared anecdotes of customer contract renewals with subscriptions of 10 or more products, topping out at 14 for a large FinTech company in a 7-figure upsell.

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