Remove AWS Remove Azure Remove Engineering Remove GCP(Google Cloud Platform)
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Snow Angels Come Early to Data : Snowflake's Strength Spells Success for Startups

Tom Tunguz

” Unstructured data is the growth engine : 17x growth y/y suggests a small number last year, but phenomenal interest. “Yes, we actually saw quite a bit of energy coming from the Azure platform this quarter. And as a result, our salespeople are really not inclined to do much in GCP.”

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The Critical Question Facing Web3 Infrastructure Startups

Tom Tunguz

That’s much more work than the automatic credit card payment with AWS. Can you imagine a site reliability engineer managing 15 to 20 tokens, coordinating with finance teams to ensure proper treasury management, while ensuring high uptime? Third, software engineers decentralize only a subset of the app.

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The 4 Questions Startups Should Ask Themselves about Building with Generative AI

Tom Tunguz

Layer : application, platform, or infrastructure? In the cloud, AWS, Azure, & GCP have created about as much market cap as all the top 100 B2B & B2C publics built on cloud (Netflix, ServiceNow, AirBnb, etc). The PC increased GDP by 0.006%, according to NBER That alone should turn heads.

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Thanks to Demandwell, DuploCloud, Prismatic, SafeBase, and WorkOS for Sponsoring SaaStr Annual 2023!

SaaStr

DuploCloud offers an end-to-end DevOps software platform for dev teams that don’t have dedicated DevOps engineers and augments those that do. The platform automates the provisioning of your application to the cloud (AWS, GCP, Azure), integrating cloud ops, DevOps, and security/compliance with 24×7 monitoring and support.

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5 Security Changes Your Company Needs to Make to Land Enterprise Deals from Secureframe

SaaStr

You’re now pulling engineers to answer security questionnaires, and you’ve just learned that getting a SOC 2 report will take 6-8 months to prepare for the audit, plus another 6-12 months to complete the audit itself. That is, until you’ve got a major enterprise deal close to the finish line.

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Moving ChartMogul to AWS and Kubernetes

Chart Mogul

A few months ago, we retired our last pieces of infrastructure on DigitalOcean, marking our migration to AWS as complete. Our journey was not your regular AWS migration as it involved moving our infrastructure from classic VMs to containers orchestrated by Kubernetes. Ultimately, we decided to go with AWS. Team expertise.

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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.

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