Remove AWS Remove Engineering Remove Forecasting
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Payment and Checkout Scalability for D2C Gaming Partners

FastSpring

Our team partners with you to help forecast demand spikes and proactively prepare our infrastructure accordingly. With AWS elasticity and real-time observability, FastSpring can make adjustments and scale instantly, ensuring uninterrupted transactions no matter how many players are buying.

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The Complete Guide to SaaS Pricing Strategy

Tom Tunguz

AWS, Twilio, Heroku, etc. This keeps morale high and creates a very predictable revenue forecast. Makes capacity planning harder : With less visibility into maximum usage requirements, engineering teams may struggle to provision infrastructure appropriately. So does Expensify, which decreases the time to file expenses.

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What’s New At WorkOS and What It Takes To Be “Enterprise-Ready” in SaaS with WorkOS CEO and Founder Michael Grinich

SaaStr

If you go back 10-15 years, when people ask about build vs. buy for the long-term, people would consider building their own data center if they were spending $100k/month on AWS. Now, the goalposts are constantly moving, and it’s challenging to forecast when making this kind of decision. The takeaway? And 99.99% of the time, it won’t.

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Managing infrastructure costs as your company grows

Intercom, Inc.

For example, at Intercom, we primarily focus on return for effort; the estimated savings we will make per engineering hour required to execute the work. Instead of trying to democratize complex, per-product billing knowledge across your team, create a small team of engineers to navigate the world of cloud computing. Zero touch costs.

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How and why we spent $400K on AWS in 4 months

Baremetrics

From my experience, the three options are usually: I don’t want my engineers to even be able to pronounce Kubernetes I want my engineers to understand how to manipulate pipelines and automation I want my engineers to understand the whole stack and use DevOps as a way to deliver features.

AWS 115
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Scaling to $5B with Cockroach Labs’ CEO Spencer Kimball’s Formula for Sustained Growth and Resilience

SaaStr

They had open cores and created enterprise features around it to protect the business model until it got torpedoed by AWS early on. But eventually, it becomes engineering. You should have a good forecasting methodology for how each quarter will go and total visibility to slice and dice all segmentations across the customer set.

Scale 243
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Tabular: Turning Your Data Swamp into a Data Lakehouse with Apache Iceberg

Clouded Judgement

Typical data lake storage solutions include AWS S3, Azure Data Lake Storage (ADLS), Google Cloud Storage (GCS) or Hadoop Distributed File System (HDFS). Compute engine (query engine): Performs the actual data retrieval. The Hive engine gave us more efficient access patterns to data lake storage.

Data 130