Real-World Problems Being Solved By Open Source
Real-World Problems Being Solved By Open Source
Learn about the real-world problems open source is tackling - pretty much everything, since 90 to 95% of all apps are built with open source software.
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To gather insights on the current and future state of open source software (OSS), we talked to 31 executives. This is nearly double the number we speak to for a research guide and believe this reiterates the popularity of, acceptance of, and demand for OSS.
We began by asking, "What are real-world problems being solved by Open Source software today?" Here's what they told us:
- Enabling “fail fast” as it is now so easy to try software before making commercial commitments. As an example, previously if I wanted to try Oracle RAC, I would need to engage consultants, develop POC’s etc, now I can spin up a Docker version of Oracle RAC in seconds.
- With Project Flogo, customers are embedding Flogo within their IoT devices to do predictive maintenance and predictive analytics. We also have customers writing their microservices leveraging Project Flogo and deploying functions to AWS Lambda. Apart from Project Flogo, if you consider the open source ecosystem more broadly, open messaging such as Kafka, MQTT, etc have slowly become the standard in messaging. No topic on open source would be complete without mentioning Linux, as there are a massive number of services running Linux in a production sense. Put another way, open source technologies are solving problems that proprietary software had been previously solving -- messaging, databases, microservice frameworks, etc.
- Open Source software is providing a wide array of solutions to today’s real-world problems. The software is allowing for innovative solutions to be brought to problems relating to cybersecurity, private access, scaling database, scaling cloud infrastructure and software management and provisioning, among others.
- Our AI product improves the productivity of application testing automatically generating test cases that look for patterns of bugs in applications. An application may have 50 billion user journeys – we use AI to test these journeys and improve the user experience (UX) using TensorFlow 9 that makes it easy to get into AI. We integrate with open source to use any assets to get benefits (e.g., Selenium assets with added AI learning elements).
- 1) LinkedIn contributor to and user of Couchbase with security needs. Challenge they bring as scale environments. 2) Availability of software on the mobile side, innovation building new apps.
- The projects powering machine learning/AI are solving real-world problems at scale today. In the past couple of years, machine learning has moved from mainly theoretical to something even a well-trained novice can take advantage of. The impact of automation via machine learning is going to have a major effect on jobs, interactions with businesses, privacy and the law in the next decade in ways we can just barely understand today.
- Open source software is solving a range of real-world problems ranging from IoT implementations to artificial intelligence applications. Increasingly, a great number of users are using IoT home automation applications like Home Assistant and OpenHab. In the field of Artificial Intelligence, many deep learning tools and libraries have been developed and open sourced, gaining a widespread adoption in the commercial and academic worlds. Besides the cutting-edge implementations of IoT and AI, open source tools since decades have been used in any conceivable web applications. With the wide adoption of programming languages like Java and Python, the ecosystem of open source software around these two languages has evolved tremendously and a lot of repeated functionality has been factored out as reusable open source tools. For example, XML and JSON became standard transmission formats and a lot of open source tools evolved to parse these protocols and are currently being used in all applications that consume XML or JSON.
- Many different problems and solutions with our clients. We help automotive clients with their entertainment systems. We help medical device manufacturers with their heart rate monitors. We help clients combine OSS with their own apps to bring the entire stack together.
- Our life science practice is helping with genome sequence visualizations and tools by publishing open source code. Our GitHub repository has 15 projects in life science alone being used by universities to solve real problems. Personalized medicine research to provide genetically tailored medicine.
- Open source software is behind virtually everything today. A large chunk of machines, web servers, databases and application are built on open source software. For Apache Flink specifically, we see companies adopting it so they can transition from a slow-moving, batch world to a real-time streaming world. Stream processing makes it possible for companies to understand and respond to data the moment that it’s created. 1) For example, ING, a Global 500 banking company, uses Flink to power its real-time fraud detection system, protecting its customers from theft. 2) Alibaba, one of the largest ecommerce companies in the world, uses Flink to update its search ranking models in real-time, ensuring that it provides users with the most relevant possible results at a given point in time. 3) Uber has built an internal stream processing platform for its engineers and business analysts, allowing them to answer ad hoc questions about the business and receive answers immediately--significantly speeding up the decision-making cycle. Those are just a few specific examples, but the overarching pattern is consistent: to best serve their customers, businesses need to be able to operate in the present and to respond to changing realities immediately. Stream processing is a technology that enables this change.
- More data is being generated than ever before, and much of it is location-based. In order to fuel important business processes, we need to be able to access and make sense of this data quickly and with minimal hassle. Geospatial data can be put to use in a wide variety of situations, and open source enhances these benefits. For example, food shortage is a serious global issue. Precision agriculture is an approach to farming designed to find smarter, better ways to produce more food using fewer resources. Precision agriculture relies on GPS data to help farmers boost their efficiency and incomes by making better-informed decisions on everything from seed choice and crop location to when and how much to water and fertilize. With an open-source approach to precision agriculture, farms can choose the best geospatial tools for their jobs, change or update those tools at will, and integrate their GIS with other technology tools. Open source GIS lets farmers scale their technology as needed and to integrate location-based data into their existing farm IT environment. When not locked into a single GIS vendor, the farm staff can gain flexibility and attain well-rounded expertise by becoming proficient in more than one type of software. The farm can swap out technology as needed for newer, more cost-effective, or more full-featured systems—and the staff can migrate to the new technology without extensive retraining. Another real-world issue being solved by open source software is transportation logistics. Moving people and things from point A to point B presents enormous logistical challenges. Consider a municipal government that wants to establish optimal bus and light rail routes, a hospital that wants to provide its patients with the best and fastest route to their facilities at a particular moment, an oil company that wants to plan its pipeline locations, or a manufacturer that wants to ship its products as efficiently and cost-effectively as possible. In each case, analyzing complex location-based information is crucial. With proprietary geospatial software, subscriptions determine not only how many data sources can be considered, but also how much it will cost to determine optimal routing. In contrast, open source geospatial software allows enterprises, state and local governments, and transportation and healthcare organizations to leverage location-based data without incurring per-user, per-login, or per-CPU cycle costs. They are not penalized for increasing their number of users or doing as much analytics as they require to determine the ideal routing.
- Open source has become pervasive and an integral part of the enterprise IT stack. We are at the initial stage of the migration of IT stacks from proprietary-only software to open source; notably supported by the cloud. In the past year, open source has moved away from data-at-rest to focus on a broad range of use cases. Leading technologies in open source include machine learning, artificial intelligence, and data analytics. The ecosystem has evolved into its next phase where open source is transforming businesses to be data-driven by achieving real-world business outcomes. Verticals include Financial Services, IoT, Healthcare, Telcos, Manufacturing, e-commerce, AdTech, Entertainment, Transportation, Utilities, Military, Mobile and more. Some notable real-world problems include using AI to reduce the error rate in diagnosing medical X-ray images, and the digitization of all financial transactions. Open source is commoditizing software as the world transforms to be data-driven, just as mobile transformed communication. Data is the new oil, and open source is the main ingredient required to harvest data. In the near future, we expect open source-led products to be as pervasive as LAMP was for the web. The presence of open source in an IT stack will be ubiquitous and commoditized.
- A better question would be: What are the real-world problems not being solved by open source software today?
- If you need an artificial pancreas in order to live, then OpenAPS seems pretty "real-world" if you want to stay in the world. If you're missing part of your leg, you can now 3d-print a prosthetic because of open source software and hardware. Those are exciting examples. However, open source is all around us. You're on the Internet going through several servers that run Open Source software. Your TV probably has open source software. Our use of open source is all about connecting people to their data, so they can make better decisions.
- Basically, any software innovation that has happened in the past years is to a large extent based on open source. The value-added chain in software is much deeper than many people would think. For example, in our case: We consume libraries that partially consume libraries from others, and so on. Our own product is not an out-of-the-box app either but often embedded by our clients in their own products. The actual use cases are incredibly broad and can be found in basically any industry. We are focused on creating open source-based software that addresses the growing challenge of complex, long-running business transactions on a massive scale. We call this the “big workflow” problem, and more and more organizations struggle with the problem since their business is being digitized, thus the amount of business transactions (aka business processes) that are executed on IT is growing exponentially.
- Frankly, all of them. However, one of the newer problems being addressed by open source is wrangling large data sets, for which we’re applying compiler tooling in non-intuitive ways, dealing with data in languages. It’s such a rich ecosystem. You can find an OSS project for almost any problem you may have.
I think a big force behind the adoption of open source technology is that for many companies today, the information technology stacks are the business – not something supporting the business (like CRM or ERP). When IT is your business, you just can’t afford to be reliant on outside vendors who own key IP that you are relying on (and who are essentially free to decide what tax they want to put on your business every time license renewals come around). Open source gives you the choice of relying on outside vendors for management and support or doing it yourself. In the extreme case, if the open source tech you are using evolves in a way that doesn’t suit your business, you can make a fork and keep using it the way you want to.
- 1) Open Source provides flexibility to customize things to meet varying user needs. It’s similar to building a house – you have a solution as a foundation, but with open source, you have the flexibility to build a custom sink or bedroom if you want. Without commercial, off-the-shelf, proprietary software, customers get a ‘cookie cutter’, track housing, model home and it would cost a lot to personalize or extend its footprint. 2) Open Source is based on a ‘freemium’ model, which allows everyone to access, download and start using the tools—without charge. As a result, the total cost of ownership is a lot less than working with traditional software solutions. Open Source also comes with a vast community of people to help you innovate along the way. There are many resources so it’s easy to learn, you don’t need as many services, and you can fix it yourself or ask someone for help. 3) Because the vast community that supports Open source technology is constantly innovating, OSS allows users to respond faster to change, which enables IT to do a lot more and allows businesses to be more responsive and data-driven.
Here’s who shared their insights with us:
- Anthony Calamito, Chief Geospatial Officer, Boundless
- Jakob Freund, CEO, Camunda
- Pete Chestna, Director of Developer Engagement, CA Veracode
- Julian Dunn, Director of Product Marketing, Chef
- Matt Ingenthron, Senior Director of SDK Engineering, Couchbase
- Stephan Ewen, co-founder and CTO, data Artisans
- Amol Kekre, Co-founder and Field CTO, DataTorrent
- OJ Ngo, Co-founder and CTO, DH2i
- Stefano Maffulli, Director of Community, DreamHost
- Kelly Stirman, CMO and VP Strategy, Dremio
- Konstantin Boudnik, CTO Big Data and Open Source Fellow, EPAM
- Tyler McMullen, CTO, Fastly
- Jeff Luszsz, VP of Product Management, Flexera
- Angel Diaz, V.P. Developer Technology and Advocacy, IBM
- Ben Slater, Chief Product Officer, Instaclustr
- Grant Ingersoll, CTO, Lucidworks
- C J Silverio, CTO, npm
- Mark Gamble, Senior Director of Product Marketing, Analytics, OpenText
- Francis Dhina, CEO, OpenVPN
- Sirish Raghuram, CEO and Co-founder, Platform9
- Neil Cresswell, Co-Founder, Portainer.io
- Lars Knoll, CTO, Qt
- Brad Adelberg, Vice President of Engineering, Sauce Labs
- Giorgio Regni, CTO, Scality
- Dor Laor, CEO, ScyllaDB
- Harsh Upreti, Product Marketing Manager, API Products, SmartBear
- Jean-Baptiste Onofre, Technical Fellow and Software Architect, Talend
- Antony Edwards, CTO, Testplant
- Matt Ellis, Architect, TIBCO Software
- Karthik Ranganathan, Co-founder and CTO, YugaByte
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