What is Serverless?
Serverless is a new paradigm of computing that abstracts away the complexity associated
with managing servers for mobile and API backends, ETL, data processing jobs, databases, and more.
No upfront provisioning - Just provide your code and data, and Google dynamically
provisions resources as needed.
No management of servers - Get out of the repetitive and error-prone task of
managing or automating server management like scaling your cluster, OS security
Pay-for-what-you-use - Because of the dynamic provisioning and automatic scaling,
you only pay for what you use.
Applications with rapid time-to-market and unpredictable scale requirements benefit
the most from Serverless. Here are some benefits experienced by Google Cloud Customers:
Time-To-Market Improvement - Infrastructure management takes time, so eliminating
it means you can get new code to production faster.
Infrastructure Cost Reduction - Paying only for what you use means lower costs.
Ops Cost Reduction - Automating repetitive provisioning and management tasks means
you get to do higher-value devops tasks.
Serverless - Microservices Built Right
Properly designed microservices have a single responsibility and can independently
scale. With traditional applications being broken up into 100s of microservices,
traditional platform technologies can lead to significant increase in management
and infrastructure costs. Google Cloud Platform’s serverless products mitigates
these challenges and help you create cost-effective microservices.
Serverless by Google
Google Cloud has always believed in the vision of serverless, starting with
Google App Engine in 2008, Google's first fully serverless compute service. Since then,
Google has evolved more serverless offerings in both Application Development and Analytics.
Data center as a computer
As computation continues to move into the cloud, the computing platform of interest
no longer resembles a pizza box or a refrigerator, but a warehouse full of computers.
These new large data centers are quite different from traditional hosting facilities of
earlier times and cannot be viewed simply as a collection of co-located servers.
Large portions of the hardware and software resources in these facilities must work in
concert to efficiently deliver good levels of Internet service performance, something
that can only be achieved by a holistic approach to their design and deployment.
To learn more, please read: The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
Serverless Application Development
||Serverless application that completely abstracts away infrastructure so
you focus only on code
||Serverless environment to build and connect cloud services
||Highly-scalable NoSQL database with automatic sharding and replication
||Geo-redundant object storage for high QPS needs
||Geo-redundant real-time messaging for all message sizes and velocities
||Enterprise API management for multi-cloud environments
||API management apps built on Google Cloud
Serverless Analytics and Machine Learning
||Serverless stream and batch data processing service
||Serverless data warehousing services that help you to deploy advanced cloud
data warehousing solutions for your enterprise
|Cloud ML Engine
||Serverless machine learning services that automatically scales built on
custom Google hardware (Tensor Processing Units)
||Serverless with Google
||App Engine -> Datastore
||Cloud Functions -> Datastore
|IoT device messages
||Cloud Pub/Sub -> Dataflow
||Cloud Dataflow -> BigQuery
|Blob file storage
|Analytics warehouse (SQL)
||Cloud Machine Learning Engine