Tag Archives: AWS Lambda

Cloud Serverless Computing: Why? and With Whom?

What is Cloud Serverless Computing?

Based on your application Use Case(s), Cloud Serverless Computing architecture may reduce ongoing costs for application usage, and provide scalability on demand without the Cloud Server Instance management overhead, i.e. costs and effort.
Note: Cloud Serverless Computing is used interchangeability with Functions as a service (FaaS) which makes sense from a developer’s standpoint as they are coding Functions (or Methods), and that’s the level of abstraction.

Microsoft Flow

 

Microsoft Flow Pricing

As listed below, there are three tiers, which includes a free tier for personal use or exploring the platform for your business.  The pay Flow plans seem ridiculously inexpensive based on what business workflow designers receive for the 5 USD or 15 USD per month.  Microsoft Flow has abstracted building workflows so almost anyone can build application workflows or automate business manual workflows leveraging almost any of the popular applications on the market.

It doesn’t seem like 3rd party [data] Connectors and Template creators receive any direct monetary value from the Microsoft Flow platform.  Although workflow designers and business owners may be swayed to purchase 3rd party product licenses for the use of their core technology.

Microsoft Flow Pricing
Microsoft Flow Pricing

Microsoft Azure Functions

Process events with a serverless code architecture.  An event-based serverless compute experience to accelerate development. Scale based on demand and pay only for the resources you consume.

Google Cloud  Serverless

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.

Google Serverless Application Development
Google Serverless Application Development

 

Google Serverless Analytics and Machine Learning
Google Serverless Analytics and Machine Learning

 

Google Serverless Use Cases
Google Serverless Use Cases

 

Amazon AWS  Lambda

AWS provides a set of fully managed services that you can use to build and run serverless applications. You use these services to build serverless applications that don’t require provisioning, maintaining, and administering servers for backend components such as compute, databases, storage, stream processing, message queueing, and more. You also no longer need to worry about ensuring application fault tolerance and availability. Instead, AWS handles all of these capabilities for you, allowing you to focus on product innovation and get faster time-to-market. It’s important to note that Amazon was the first contender in this space with a 2014 product launch.

IBM Bluemix OpenWhisk

Execute code on demand in a highly scalable serverless environment.  Create and run event-driven apps that scale on demand.

  • Focus on essential event-driven logic, not on maintaining servers
  • Integrate with a catalog of services
  • Pay for actual usage rather than projected peaks

The OpenWhisk serverless architecture accelerates development as a set of small, distinct, and independent actions. By abstracting away infrastructure, OpenWhisk frees members of small teams to rapidly work on different pieces of code simultaneously, keeping the overall focus on creating user experiences customers want.

What’s Next?

Serverless Computing is a decision that needs to be made based on the usage profile of your application.  For the right use case, serverless computing is an excellent choice that is ready for prime time and can provide significant cost savings.

There’s an excellent article, recently published July 16th, 2017 by  Moshe Kranc called, “Serverless Computing: Ready for Prime Time” which at a high level can help you determine if your application is a candidate for Serverless Computing.


See Also:
  1. “Serverless computing architecture, microservices boost cloud outlook” by Mike Pfeiffer
  2. “What is serverless computing? A primer from the DevOps point of view” by J Steven Perry

Uncommon Opportunity? R&D Conversational AI Engineer

I had to share this opportunity.  The Conversational AI Engineer role will continue to be in demand for some time.


Title: R&D Conversational AI Engineer
Location: Englewood Cliffs, NJ
Duration: 6+ months Contract(with Possible extension)

Responsibilities:

  • Create Alexa Skills, Google Home Actions, and chatbots for various direct Client’s brands and initiatives.
  • Work with the Digital Enterprises group to create production-ready conversational agents to help Client emerge in the connected life space.
  • Create additional add-ons to the conversational agents
  • Work with new technologies not be fully documented yet
  • Work with startups and their technology emerging in the connected life space.

Quals–
Client is looking for a developer in conversational AI and bot development.

What is Media Labs?   Media Labs is dedicated to driving a collaborative culture of innovation across all of Clients . We serve as an internal incubator and accelerator for emerging technology and are leading the way with fresh ideas to ignite the future of media and storytelling. We are committed to partnering with another telecom giant, startups, research and academic groups, content creators and brands to further innovation at client. One of our main themes is connected life and we are looking for an engineer to lead this development.

Requirements for R&D Engineer: –

  • Bachelor in Computer Science, Engineering, or other related field
  • Experience working with new technologies that may not be fully documented yet
  • Experience communicating technology to non-technical people
  • Experience with AWS (Lambda, CloudWatch, S3, API Gateway, etc)
  • Experience with JavaScript, Node.js
  • Some experience creating Alexa Skills, Google Home Actions, or chatbots

Optional Requirements:

  • Experience creating iOS or Android applications (native or non-native)
  •  Experience with API.AI or another NLP engine (Lex, Watson Conversation)