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Jean Dwit (Chief Business Officer at Stripe) and Lindsay Scrace (COO at Checker) have done it multiple times at companies like Google Cloud, Stripe, and Checker. But watch out – this is a major undertaking that touches product, engineering, sales, and finance. Thinking enterprise is just a go-to-market play. It’s not.
He had the idea that the Cloud, not called the Cloud back then, would enable two entities to see the same transaction from their perspective. With a trillion in payment volume coming through BILL in the last five years, managing the payment and compliance engine has required an ongoing effort of a sizable team.
And what you can see is there is really almost no liquidity for startups and scale-ups in SaaS and Cloud at the moment. Now, to some extent, the issues here have been masked by several factors: The VC engine continues, more or less, and has been re-energized by AI. Epic times. See above from Thomasz. Deals are fast and furious.
So some Cloud and SaaS stocks are on fire, even now. Why is Palantir the highest valued public SaaS and Cloud stock? Artificial Intelligence Platform (AIP) is a Year Old But Fueling $159m in Q2 Bookings Alone To some Cloud and SaaS leaders, AI is a table-stakes addition. And a true engine of growth. #9. Billion ARR.
My laptop is faster than your cloud. Instead of requiring a scale-out database in the sky, most analyses are faster with an optimized database on your computer that can leverage the cloud when needed. For the last ten years, the data ecosystem has focused on big data - the bigger the data set, the more exciting.
Raising Guidance and Growth Rate for Cloud Revenue To +24% a Year That’s pretty darn impressive growth at almost $5B in ARR, and just as importantly, they’re raising their prediction here. #2. The Atlassian engine just keeps on running. Wall Street is happy. Let’s dig in. 5 Interesting Learnings: #1.
No different in the real world - whether you’re buying a car or hiring an engineer, there are “budget” options and there are premium options. So, I don’t think that trajectory changes, but I do think the smaller, domain-specific models will play an increasing role.
So Cloud and SaaS have had a bit of a rollercoaster the past 4 years, from the boom times of 2020-2021, to the tougher times overall of 2023, to the AI boom of 2024+. 221,000 Total Paying Customers, But 65% of Revenue From 3,200 Large Customers This is what you should see when a “long tail” engine is just working at scale.
But at end of the day, in Cloud, the question is if CIO and related spend will slow down. So follow AWS, Azure and Google Cloud. So there’s much angst and even panic with so many SaaS and Cloud public stocks down 50% or more from their peaks. They are the Cloud. That’s the engine we’re all building on.
So yes, while it’s true that challenges are real for those in the right-hand column above – overall cloud spend is still up 20%. Google Cloud , Azure, and GitLab, all tied directly or indirectly to AI, are seeing massive acceleration. But Google Cloud, Azure, and GitLab are all benefiting and on fire.
“And as engineers,” Sanjit explains, “we just like building things. And while we were tinkering, we were building little sensor systems, cause we knew how to make hardware and we knew how to cloud connect it.” So they stepped away and decided to start tinkering again. It’s the world behind the curtain.
But the clouds are rolling in for open source companies (pun intended). Today, open source software faces an identity crisis: what does it mean to be an open source company in the cloud? On the other hand, the future is in cloud. But what does it mean to be open source in the cloud? It’s enterprise-first selling.
Every week I’ll provide updates on the latest trends in cloud software companies. Imagine if a lack of cargo, passengers, rails, etc stopped companies from investing in steam engine technology in the 1760s. Subscribe now Share Clouded Judgement Leave a comment Follow along to stay up to date!
Cloud Data Lakes are a trend we’ve been excited about for a long time at Redpoint. A cloud data lake is a repository of data in the cloud, with the tools and infrastructure to analyze it securely. The cloud data lake architecture enables companies to achieve scale, flexibility, and accessibility.
Every week I’ll provide updates on the latest trends in cloud software companies. Let’s say you’re an engineer coming out of college - in a tight labor market companies don’t have tons of options to hire folks (because everyone is already employed). Subscribe now Share Clouded Judgement Leave a comment
There needs to be a layer between them to make all that data accessible to these users - a data lake engine. If you keep data in cloud data lake stores, and need a system to make that data accessible to analysis tools at interactive speed - without moving it - you’re looking for Dremio. That’s Dremio.
The Art of Doing Science and Engineering is a curious book. Richard Hamming, the author, was a professor of science and engineering at the Naval Postgraduate School and researcher at Bell Labs. He knew quite a bit about science and engineering. Others approach the field with a beginner’s mind.
Our product engineers are empowered to build great features, fast. You can watch a video of that talk below, or read on to learn how we built our Elasticsearch cloud on AWS. In Intercom, we believe that shipping is our company’s heartbeat. A large part of making this belief a reality is the idea of running less software.
Today, SaaS and Cloud is back. This might get you more revenue today but doesnt fuel the word-of-mouth engine. So the 2021 GTM Playbook is Dead. Almost all of us agree about that. That playbook was fueled by a desire to load up on 100s of new SaaS apps to fuel a pandemic-inspired buying spree. Our app count is staying flat.
Yesterday, Dremio hosted the Subsurface Conference , the first conference on cloud data lakes. If one had doubts that cloud data lakes are a strategic area for many in the data ecosystem, those figures should quash them. There is a mega-trend underpinning the changes in data design philosophy and tooling: the rise of the data engineer.
Software engineering teams have been early adopters of AI coding assistants precisely because they provide an immediate, measurable lift. The current state of AI adoption resembles the early days of cloud: great infrastructure exists, but there’s a lack of applications to use it effectively.
“State of the Cloud with Bessemer Venture Partners” The most recent update on where the Cloud is — and is going. #2. “Hyperscaling At Scale with PagerDuty’s CEO, Jennifer Tejada” A terrific session with PagerDuty’s and Sendgrid’s CEOs on how to keep a growth engine … growing. #3.
The patois of data teams has become a dialect of modern engineering teams because the commonalities in the stack. Data teams receive tickets from their internal customers & develop data products that serve both internal & external users, much like a classic product management & engineering team.
Unparalleled Networking Opportunities SaaStr Annual brings together thousands of SaaS, Cloud and AI executives, founders, VCs, and industry leaders under one roof across our 40+ acre campus, May 13-15 in SF Bay! VIP Networking app for B2B founders and execs attending (no service providers, sorry!) And the VCs that want to fund them!
Alert fatigue is a common problem among engineering teams that handle operations and maintain infrastructure. The result is lots of semi-meaningful alerts, noise, context-switching, and multitasking for the on-call engineer. Are the steps clear enough to be followed by any engineer on the team? Is the alert still relevant?
Cloud Data Lakes are the future of large scale data analysis , and the more than 5000 registrants to the first conference substantiate this massive wave. Also, Tableau’s Chief Product Officer François Ajenstat will discuss the Tableau’s role in the cloud data lake. Data engines query the data rapidly, inexpensively.
For the very first time, we’re releasing Engineer Chats , an internal podcast here at Intercom about all things engineering. Previously hosted by Jamie Osler , a Senior Product Engineer at Intercom for over seven years, it’s now up to Principal Systems Engineer Brian Scanlan to pick up the baton and keep the chats going.
Many businesses are moving their infrastructure and software to the cloud to adopt Kubernetes and microservices. Chaos engineering or resiliency engineering is the dominant way to mitigate the intricacies of modern cloud stacks. Just how effective is chaos engineering? Teams that perform chaos have more uptime.
As the co-founder and CEO of Intellimize (acquired by Webflow), Guy brings a unique perspective from his journey through iconic companies like Microsoft, Yahoo, and Twitter, as well as his background in aerospace engineering. Trusted by GTM leaders at the likes of Snowflake Five9 and Google Cloud to improve GTM efficiency.
Typically, the data resides in the customer’s cloud account. This cloud account has many names but no real moniker yet. Some call it a VPC for virtual private cloud. Others call it cloud prem, a contraction of cloud and on-prem(ises). Today, many of those data centers are in the cloud, hence cloud prem.
Every week I’ll provide updates on the latest trends in cloud software companies. Subscribe now Foundation Models Are to AI what S3 was to the Public Cloud Many people look at 2006 as the birth of the public cloud - the year Amazon launched AWS. Follow along to stay up to date! However, a couple things happened.
Focus on scaling what works best, but don’t over-engineer and waste valuable time. After helping customers succeed with your first product, figure out what other problems you can solve for them – and as you progress, you’ll uncover new use cases and add more products and features to the cloud. Test, measure, and iterate.
From Asana to Zoominfo: this year’s Europa lineup is bringing the best Cloud speakers from around the globe together for two days of incredible learning and insights. There will be over 2,500+ SaaS and Cloud professionals joining us there in person. Get your ticket now and get a front-row seat when the Cloud comes to Barcelona.
From premature optimization to over-engineering solutions for your product, it’s easy to get caught up in making technology decisions that slow you down instead of speeding you up. Multi-cloud architectures. Look, there are situations where a multi-cloud strategy will be of benefit to you. But for the rest of us?
A key question for the Cloud infrastructure leaders (Amazon, MSFT, and Google) is how deep do they want to go on the application layer. So to keep the engine going, the leaders have to be asking themselves if they can leverage the SaaS / application layer to win overall in Cloud. Who is #1 in the SaaS layer of Cloud?
They’re at almost $500m in ARR, with 1,850 customers, now growing a modest but steady 19% and they have gotten pretty efficient, like most other public SaaS and Cloud leaders. 1M+ Customers Are Key to the Growth Engine With 73 $1m+ customers. Engineering also took a small hiy as well. A year ago, growth was at 48%.
Amplitude is a quiet Cloud leader that you might not have heard of — unless you are building software. Some leaders like Slack have seen the same, but most Cloud leaders at scale with high NRR end up getting more and more of their revenue from their existing base, not new customers. 5 Interesting Learnings: #1. This is rare.
By breaking down large codebases into smaller pieces, microservices empower engineers to ship code faster. Engineers developing microservices work with the ground shifting underneath them all the time. Engineers developing microservices work with the ground shifting underneath them all the time.
Pomel focused his session on: Making your SaaS startup customer-centric: Hw event marketing has helped him integrate his engineering and sales teams. How many of you guys’ product rely on the highly functioning engineering team? Helping the engineering teams run smoothly and being super productive thanks to mentoring.
UiPath is one of the most amazing not-really-an-overnight success stories in Cloud, SaaS and software. It was founded way back in 2005 as an outsourcing company, then developed Windows software to automate scripts and more, and turned this into a powerhouse for automating complex functions integrating Cloud and on-prem.
First, it’s a Cloud and SaaS leader we all look up to and know. 1m+ Customers Growing the Fastest (48%), With 98% Logo Retention This isn’t unique to Atlassian, but a reminder of how much the biggest customers are the fuel for growth for many SaaS and Cloud leaders today. A pretty stunning cash engine at scale.
The Rise of 1000 Unicorns and 100 Decacorns, combined with the overnight changes to fundraising processes from Covid, have radically changed venture capital: Tiger alone is deploying $100 billion , mostly into Cloud startups, and very quickly. Funding “engines” / machines at Tiger, Insight, etc. With many more coming.
I thought it would be cloud-prem and customers driving SaaS products to use a single database. Here’s a schematic (click to enlarge) that describes how data flows with a cloud datawarehouse (CDW) fed SaaS app. I was wrong about the catalyst for this hub-and-spoke model. This may be the next shift.
For most software companies, COGs encompasses cloud hosting costs and some fraction of customer success and professional services salaries. For startups, there tend to be two significant drivers of gross margin: cloud computing costs and professional services. Assume the company grows 5% per month. The company burns $1.9M
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