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It’s worth pointing out that Azure is a bit above the long term trendline, while AWS is still below (but accelerating up). It’s worth pointing out that Azure is a bit above the long term trendline, while AWS is still below (but accelerating up). So what are these consensus estimates and who creates them?
Subscribe now Cloud Giants Report Q3 ‘23 Not a great signal for software this week from the Cloud Giants (AWS, Azure and Google Cloud)…After Q2 (3 months ago), the tone from the Cloud Giants around optimizations was largely: optimizations have started to ease, and net new workloads have picked up. which feels unlikely.
It looks at the YoY dollar change in quarterly revenue from the hyperscalers (just looking at Azure / AWS because the data goes back further) going back a few years. If we break this down and look at Azure and AWS independently (graphs below), you’ll see how the AWS “swings” were a lot more volatile.
Cloud Downgrades This week UBS came out with a couple research reports citing concerns in AWS / Azure growth. This brings me back to AWS / Azure downgrades. This was the worst tone that we’ve heard in years from large AWS/Azure partners, a group that usually expresses different shades of optimism about AWS/Azure growth.”
AI = Data + Compute I’ll continue beating this drum, but we got two great quotes from Azure and AWS this week. Powell said the Fed staff no longer is forecasting a recession. This week we had two of the hypserscalers report (Microsoft / Azure and Google / GCP), and everyone was eager to see their results.
Azure / Confluent / Datadog reported a few weeks back (they all had March quarter ends), and their commentary suggested the worst was behind us. There’s a lot more volatility baked into these models, and they’re quite hard to forecast. This means we got commentary for the first time on May trends.
On the Microsoft earnings call they said (related to Azure): “But at some point, workloads just can't be optimized much further. Every public company has a number of equity research analysts covering them who build their own forecasted models, which combine guidance from the company and their own research / sentiment analysis.
With our new destinations, you can send your clean and tidy revenue data to be combined with other data points in: Amazon S3, Google Cloud, Microsoft Azure , Snowflake, Amazon Redshift, or Google BigQuery. Many of our customers use MRR movements from ChartMogul to predict churn or generate financial forecasts. That’s a wrap on 2022.
building data hug out, which was in the predictive forecasting, you know, pipeline management space. It really does need to be broken down into parse and process the invoice, then check the ERP, then do these things. cloud infrastructure and you know, many thousands, hundreds of thousands of startups, you know, built on top of Azure.
5⃣ Focus on Recurring Revenue (Subscriptions or Lifetime Deals) Predictable revenue = stable business. Subscription model (SaaS) = Customers pay monthly or yearly (best for long-term growth). Some Micro-SaaS founders start with a lifetime deal to get early traction, then shift to subscriptions for long-term stability.
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