Serverless computing lets businesses build agile applications that can easily adapt according to a company’s IT demand and needs. Providers of serverless computing offer pay-as-you-go services, and the platform is great for creating and hosting backend systems that handle mini-programs, web apps, containers, orchestration layers, Artificial Intelligence models, as well as various Application Programmer Interfaces (APIs). Serverless computing can act like Backend as a Service (BaaS) platform and serverless providers take care of all system infrastructure management, all operation and maintenance (O&M) needs while giving clients the freedom to build, develop, and deploy systems and applications without having to worry about hardware, software, networking, or data orchestration needs.

Is serverless computing right for your business? Well, that depends. As with everything in business, it’s best to look at the risk-reward ratio as well as the return on investment (ROI) when deciding whether or not to implement new technology. Since the serverless providers have made these platforms quick to set up, simple to scale, and easy to turn on and turn off, serverless is usually a cost-effective way to reduce IT expenses. Serverless computing can also cut down on capital expenditure because, whereas the purchase of new servers can be considered a capital expenditure or a CapEx expense, cloud costs can be treated as operating expenses or an OpEx. The latter is usually treated more favorably as a tax expense, therefore there might not be direct revenue generation but there could be simple bottom-line improvement with a serverless computing implementation when growing an IT estate.

Standard Extract, Transform, Load (ETL) tasks can also be simplified, while time and energy can be saved when an ETL job run encounters data issues, as they often do. Should particular files not be ready for extraction, the system can trigger an alert that informs any necessary department or individual that there are data issues. The ETL run could be put on hold or even shut down until all required data is ready to be imported. Event-based computing even allows developers to write code that updates compute and storage needs on a serverless system, thereby optimizing a workflow.

On the risk side of the ledger, going serverless means giving up a certain element of control over a company’s IT estate. Although, in general, cloud computing environments are highly secure, any company that falls victim to a cyberattack must coordinate all responses through the cloud provider who hosts the serverless environment. Since the actual servers and infrastructure are owned by the cloud provider, they will be the ones leading the cyberattack response and they will be the ones ultimately responsible for getting the attack under control. Also, serverless computing providers often rely on open-source libraries, but this software tends to be less secure than commercial software.

Today, companies as distinctive as Slack, HomeAway, GreenQ, and Coca-Cola are all successfully utilizing serverless computing platforms to handle such divergent things as chatbot applications, real-time traveler recommendation systems, Internet of Things (IoT) systems that collect key metrics from garbage trucks to improve waste management pickup and delivery, as well as payment processing systems to buy a coke.

Serverless computing can give companies more control over their infrastructure spending. It also can reduce operations and maintenance expenses, increase a system’s reliability, and allow instant scalability to ensure customers won’t be frustrated by a lack of access. Above all else, a technology that allows developers time to focus on the one thing they do best – coding – should be embraced and heralded.

There are various SaaS services that make our lives easier. There are SaaS from complex Cloud SCADA services to digital forms for data collection. Most services provide instant functionality, reports and graphs of collected data. This is all great and very convenient.

There is one problem with this approach: customers do not own their data! All data collected belongs to the SaaS service. Once the SaaS service collects enough data, they will analyze and sell it back to companies at a big premium. The service providers will build Machine Learning algorithms and sell them as a service.

We have been approach by companies that have heard of machine learning and they are ready to deploy a solution. They encounter one problem: they do not have any data yet. Without millions of records of data, it is impossible to develop and train any ML algorithms.

It is very important to start collecting and storing data in a digital format as soon as possible. The format does not matter much. It could be simple text, CSV, XML, JSON, PDF, Doc, Xls, image, … As long as there are many many records, eventually you will be able to analyze it and build ML/AI algorithms against it and take your business to a new level.

Currently, when setting up data lakes, almost any format of data could be stored for processing. The tools for processing and understanding data are getting better and better, but unless a company has troves of data, they will not be able to take advantage of the digital transformation and will rely on 3rd party services to tell what is best for them.

How LoadSys Solutions can help?

LoadSys can help you get setup up with Cloud Storage and provide an ability to collect data for any type of equipment. We can collect data from your machinery, equipment, environment and even provide digital inspection and mobile form solutions fully integrated into your business.

Please contact LoadSys Solutions for a free consultation on how to start collecting your data and get ready for digital transformation.

Ubuntu is an open source software operating system that runs on a wide range of devices. Ubuntu is a primary choice when developing a custom data collection and analytics solution. Ubuntu’s emphasis on security made it a primary choice for enterprise data collection applications. As all Linux based operating systems, Ubuntu is secure right out of the box. Ubuntu is also chosen for its container operations.There is no system that is 100% secure, but what matters most is the speed at which security vulnerabilities are resolved and made available and how easy it is to deploy them without interrupting operations.

Why Ubuntu Core?

Ubuntu Core provides a fast and reliable transactional OS for IoT solutions. It is a perfect choice for Edge-to-Cloud gateways. Edge-to-Cloud solutions collect data from sensors and equipments and the “edge” and send to the cloud for processing. Ubuntu is supported by various major IoT gateway manufacturers like Dell, Intel, Moxa, and others. For a faster and cheaper deployment of a custom solution, existing hardware could be chosen to meet the deployment’s physical environment and data processing. To protect the information on the OS, penetration testing service by Nettitude is a must, even for this operating system.

LoadSys uses Ubuntu with Raspberry PI for IoT prototyping solutions. Ubuntu also supports AWS IoT Greengrass. AWS Greengass allows to deploy applications remotely with AI/ML logic and sending data to the cloud.

What is AWS Greengrass?

AWS Greengrass provides tools to manage IoT infrastructure and securely collect and process data from remote data sources such as machinery or equipment. AWS Greengrass could be configured to collect data when internet connection is not present and even deploy ML/AI services directly to the edge. With AWS Greengrass, remote APIs and containerized applications could be deployed and managed to edge locations.

Please contact LoadSys for a free consultation on your next digital transformation/data collection project. We work with any size or stage projects, including startups. We will help you to bring your next IoT idea to life.

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