AWS Lambda vs. Watson IoT Platform

Lambda excels at event-driven, short-lived tasks, such as processing files or building simple APIs. However, it's less ideal for long-running, computationally intensive, or applications that rely on carrying the state between jobs. Cold starts and constant load can easily balloon the costs.

Incentivized

For large companies with large-scale manufacturing, electronics management, and infrastructures that require lots of maintenance, IBM Watson IoT is a must-have. It greatly increases performance, decreases downtime, and is an all-around great management dashboard. This is best for infrastructures that have a larger infrastructures of IoT devices in an enterprise/manufacturing setting, otherwise IBM Watson may not bring many benefits to your team.

Incentivized

• No provisioning required - we don't have to pay anything upfront
• Serverless deployment - it gets executed only when request comes and we pay only for the time the request is getting executed
• Integrates well with AWS CloudWatch triggers so it is easy to setup scheduled tasks like cron jobs

Incentivized

• The asset information is available in both static and dynamic format (from thermal images, to OEM data, to time series data). The ability to ingest all the information using a single platform has great value.
• Another benefit is a seamless integration with Maximo. This has been a challenge with other 3rd party systems available.
• The experience of IBM Maximo systems updates is positive.

Incentivized

• Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
• For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
• Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
• Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.

Incentivized

• Some of the tutorials could use a little more improvement - While there is a considerable amount of documentation, most of the good documentation for Watson IoT we found to be from third-parties.
• Administration and billing tools could use a bit more improvement - The UI is a bit clunky and poorly-designed here.
• Be prepared to work with IBM support to get this going - Their turn-around support for inquiries can be lengthy, and setup time may also be quite lengthy because of this.

Incentivized

I give it a seven is usability because it's AWS. Their UI's are always clunkier than the competition and their documentation is rather cumbersome. There's SO MUCH to dig through and it's a gamble if you actually end up finding the corresponding info if it will actually help. Like I said before, going to google with a specific problem is likely a better route because AWS is quite ubiquitous and chances are you're not the first to encounter the problem. That being said, using SAM (Serverless application model) and it's SAM Local environment makes running local instances of your Lambdas in dev environments painless and quite fun. Using Nodejs + Lambda + SAM Local + VS Code debugger = AWESOME.

Incentivized

Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.

Incentivized

AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for both front-end and back-end infrastructure, while AWS Lambda is only for small back-end functions

Incentivized

Predix has recently launched their Asset Performance management Unified system. I am keen to see how it stacks up against Watson.

Incentivized

• Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage.
• Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run.
• Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.

Incentivized

• Positive - This tool greatly increases most company's manufacturing and production efficiency, and the use-cases are extensive. It was a great way of decreasing down-time for us.
• Negative - Took lots of work and energy to get up and running, we had to rely on IBM support and tutorials many times during this process.
• Positive - Quite cheap, most of the tiers of pricing cost very little, and it's possible to use Watson IoT for a few months for free to see if it is beneficial for your company.

Incentivized