There are three major reasons why startups and innovative companies choose cloud-first models.
First, scaling applications without the headache of an infrastructure and beneficial pricing models. This is the most obvious and biggest use case for going to the cloud. The major reason Snapchat signed a $2B deal with the Google Cloud team is for Google App Engine which allows them to scale without worrying about the underlying infrastructure. It’s also why companies like Uber use AWS to make sure the service survives Halloween and New Year’s Eve, the two busiest nights of the year.
Second, with the creation of Data Pipelines, Data Lakes, and many other data-focused services native to the cloud, data is treated as a first-class citizen. You now have the ability to ingest any type of structured and unstructured data across your organization and create insights from disparate data sources, all performed in real-time. This is important as it becomes critical for organizations to make business and operational decisions based on large amounts of unstructured data. Peloton, founded in 2012 and already raised nearly $1B, places a huge focus on data. They rely on AWS to power its on-demand, live and customizable leaderboard.
Lastly, the big three cloud providers are using a data-first mentality to provide functional APIs that allow you to utilize Machine Learning and Artificial Intelligence computing in a single API call. This puts unbelievable computing power in the hands of any company, big or small. Coinbase, the leader in digital cryptocurrency exchanges, uses Artificial Intelligence in the cloud to prevent fraud. And ZocDoc, a company that connects patients with doctors, uses Google’s TensorFlow in the cloud to reduce the wait time for appointments. Without data being treated as a first-class citizen, you cannot feed the machines the information it needs.
In the not so distant future, AWS envisions a new generation of developers that won’t think about instances, servers, and clusters. Developers will focus on writing software, or possibly purchasing Lambda functions, and it will automatically be available and connected across every imaginable service in the infrastructure. “We are expecting a totally different programming model.” says Jassy, CEO of AWS.
The good news is that when it comes to data, the cloud has a little something for every occasion. Each one of these tools serves its purpose to make sure you can process, store, and analyze data natively in the cloud.
Let’s talk about our data-first solution architecture in the cloud. Here are our main components of a data-first organization
- Cloud Operations (Infrastructure Automation)
- Modern Data Platform Architecture (Data Lakes)
- Next Generation Applications
- Predictive Analytics using Machine Learning and AI
If you want to learn more about how companies are building cloud-native data platforms, make sure to read our whitepaper on how billion dollar startups are building data platforms in the cloud.
Set up a conversation with one of our data architects to unearth the low-hanging fruit in your organization and get on the fast track to ringing-up your first cloud win.
- Cloud Native
- Data Engineering