The 5 Open Source Trends for 2021
Isabella Ferreira
Published at 01/12/2021
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Open source has become popular over the last two decades. Today, over 40M developers contribute to platforms such as GitHub, and it is expected that the open source industry will reach approximately $33B by 2022 according to the CB Insights’ Market Sizing tool [4]. As an example of the open source growth, the Linux maintained version by Red Hat has reached a 33% share of worldwide server operating environments in 2017, a lot more than predicted [2].

All this growth means that we still have a lot more to learn about open source and to contribute to it. To Heather Kirksey, vice president of community and ecosystem development at The Linux Foundation, "today’s open source trends vary by industry but include projects such as blockchain, which companies in finance and banking are eyeing, as well as containers and Kubernetes, which are continuing to evolve and grow in use by enterprise IT" [1]. Based on this, what are the open source trends for 2021? Here are our four predictions for 2021.

Cloud & Containers

There is an increased adoption of cloud-based tools especially now during COVID-19 times and remote work [4]. Companies have been adopting open source cloud-based technologies to develop their own innovations, such as RedHat's Codeready Workspaces [4]. As a consequence, open source cloud-based tools are advancing many domains such as mainframe development and workspace management. Furthermore, "legacy" domains, such as COBOL and other programming languages, might benefit from the cloud adoption. That is, the development of open source cloud applications might extend the life of infrastructures running older architectures.

The biggest boom in the open source cloud applications was projects such as Docker and Kubernetes. Over 3.5 million applications have been placed in containers that use Docker technology, and over 37 billion containerized applications have been downloaded, according to Docker [2].

Kubernetes, on the other hand, is part of edge computing. Edge computing refers to an area of cloud computing where the infrastructure for computing, storage and other requirements need to be placed in the field closer to users or their use cases. Thus, cloud computing helps to centralize and create large data centers that benefit from scale, and most interactions with users move to the edge. Based on this, there is an increase in the number of distributions or plugins to the Kubernetes ecosystem to support new use cases. Projects like KubeEdge and K3s bring the Kubernetes API and extensibility to more devices, even those on the edge.

Microservices & Service Mesh

Organizations are changing their architectures to microservices in order to rapidly adapt to customer requests and demands by building new customer experiences. According to Gartner, 91% of organizations are using or plan to use microservices [5]. The microservices adoption is increasing across industries. As you can see in the image below, many industries have already started to migrate their applications to microservices.

Microservices adoption. Source: 451 Research

According to Gartner [5], companies deploying microservices to production will require some form of service mesh capabilities to scale. Since the primary goal of service mesh is to make service-to-service communications secure, fast, and reliable, service mesh can help applications to migrate to microservices in a more reliable way.

As an example of a microservices open source project, we have TARS. TARS, a microservices open source project, has been around for 12 years. Despite providing service governance, development with multiple programming languages, and a bunch of functionalities that facilitate microservices development, the TARS team has already mentioned that service mesh is in the roadmap of TARS in order to address the industry's needs [6].


The COVID-19 pandemic accelerated digital transformation in many areas, and one of them is blockchain. Blockchains are distributed databases with no central authority or points of trust [1]. Blockchain is a trend for open source because it is expected that its market size will exponentially grow. That is, the blockchain global market size is expected to expand from USD 3.0 billion in 2020 to USD 39.7 billion by 2025, at an effective Compound Annual Growth Rate (CAGR) of 67.3% during 2020–2025 [7].

However, experts predict that 90% of blockchain projects will require replacement within a year [7], this is because most of these projects ignore key features such as tokenization, smart contracts, and decentralised consensus. Furthermore, according to Gartner, more than 40% of the surveyed companies have at least one blockchain pilot project. It is predicted that 30% of these projects will go into production in 2021 on a private enterprise blockchain platform.

If we look into the countries leading the blockchain market, we see that China is ahead when it is about blockchain games. China's state-backed Blockchain-based Service Network (BSN) is aimed to make blockchain an integral part of the country's digital infrastructure [8].

As an example of a blockchain open source project, the Hyperledger blockchain project, which The Linux Foundation sponsors, helps solving challenges such as security and authentication for a wide range of industries [1]. Emerging trends that use blockchain and Hyperledger are enabling transitions, supply chain verifications, and identity validations.

AI & Big Data

With the huge amount of data that exists nowadays, it is essential to integrate data from many sources and to make use of this data. For that, large structure and unstructured datasets and big data analytics will become an important tool for software engineers. Not only this requires software to automatically learn from a model, but also capabilities for data mining, predictive analysis, and forecasting [9]. This is where Artificial Intelligence (AI) plays an important role!

According to a survey conducted by O'Reilly [11], more than half of the respondents said that AI (most specifically, deep learning) will be part of their future projects and products. With artificial intelligence, companies can predict which additional products a customer is likely to buy, and which types of customers pose the greatest risk for insurance companies, for example. Although AI can be applied to a variety of industries, computer vision and text mining are the ones that draw the most attention (see image below).

Type of application of AI. Extracted from [11].

Developers might use a variety of tools to build AI (more specifically, deep learning) applications. The most common ones are Tensorflow and Keras open source projects.

AI Tools. Extracted from [11].

Edge Computing

According to Rosa Guntrip [12], a senior principal marketing manager of cloud platforms at RedHat, “Edge computing refers to the concept of bringing computing services closer to service consumers or data sources. Fueled by emerging use cases like IoT, AR/VR, robotics, machine learning, and telco network functions that require service provisioning closer to users, edge computing helps solve the key challenges of bandwidth, latency, resiliency, and data sovereignty...”
We believe that edge computing will be a trend for 2021 for three reasons. First, hybrid cloud is becoming very common, and this concept will be applied to edge computing architectures. Second, cloud providers such as AWS and Azure are delivering their own edge solutions. Hence, in 2021 they might continue this trend in order to speed up innovation [14]. Finally, the maturity of cloud models will help edge use cases such as AI, IoT, 5G and enhanced communications.
According to the IDC, the edge computing market worldwide will grow to $250.6 billion by 2024 [13]. With this new technology, companies will need to think about how to build the edge capacity with all the infrastructure and services required. Furthermore, companies will start to incorporate edge computing capabilities into the software deployment pipeline and use this infrastructure to support personalized content and streaming services [13]. The goal is that edge computing extends the cloud ecosystem by standardizing computes, storage, and networking product offerings alongside mature business models [15].

About the author:
Isabella Ferreira is Advocate at TARS Foundation, a cloud-native open-source microservice foundation under the Linux Foundation.