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The coronavirus pandemic has inspired many enterprises to accelerate the pace of their cloud migration and digital transformation. Thus, organizations and development teams are looking for ways to boost the productivity of their project development processes to launch cloud-native software in the market.<\/p>\n
And this productivity boost can be achieved through containers<\/strong>!<\/p>\n In this post I will show you the top containerization trends that will come handy in making the development process faster and more efficient for developers who are going to work with cloud-native applications in the future.<\/p>\n However, before checking those trends, it\u2019s important to acknowledge what containers are.<\/p>\n Containers are the packages of software that consist of all the required components to run in any environment. A container helps in virtualizing the operating system to run anywhere, from a public cloud to the private data center and developer\u2019s laptop. The apps we use regularly like YouTube or the search engines like Google and Microsoft Edge operate in containers.<\/p>\n Moreover, containerization enables developers<\/a> to move fast, deploy software, and operate at an incredible level. Technically, containers are lightweight packages of application code, along with their dependencies such as runtimes and libraries of the programming language needed to run the services in the software.<\/p>\n A container makes it easy to share the central processing unit (CPU), network resources, and storage at the operating system level to provide a sensible packaging device where the application can be abstracted from the environment they run on.<\/p>\n Gartner<\/a> predicted that by 2022, 75% of global organizations will be running containerized applications in making software for their business, compared to less than 30% today. So it would not be wrong to say that containers along with microservices are the driving force behind the digital transformation our industry is seeing.<\/p>\n Now, it\u2019s time to uncover the trends that you as a developer should know about.<\/p>\n Keeping updated with trends can be quite overwhelming. However, not knowing which development technology will be in trend can lead to having outdated skills, and whether you are a freelancer or a full-time employee, it can be a barrier in your career progress. So to avoid any consequences, let\u2019s take a look at the top containerization trends for this year.<\/p>\n Kubernetes<\/a> is an open-source, extensive, and portable platform that is used for containerized workloads and services. It facilitates automation for scaling, management, and deployment. According to the CNCF Survey Report 2020<\/a>, 83% of survey respondents (from the global cloud native community) use Kubernetes in production.<\/p>\n Kubernetes has been around for more than six years, but it has now gained more popularity than ever due to its offering container scaling across several servers in a cluster, high fault tolerance, built-in data encryption, and better portability of software across different platforms.<\/p>\n Besides, it offers self-healing, storage orchestration, load balancing, automatic bin packing, assigning states, and sensitive information and configuration management. The Kubernetes interface will additionally regulate the basic cloud and edge capabilities. It will also enhance and standardize the edge products to quicken container application implementation in 5G and Internet of Things (IoT).<\/p>\n For seamless service-to-service communication and network traffic management, service mesh works as an abstraction layer. It attaches itself to all the services in the microservices architecture without modifying the code. Over 27% of the global cloud-native community uses service mesh in production, leading it to take its place in the trends for containerization, according to the CNCF report.<\/p>\n You can integrate it with HTTP, REST, HTTP\/2, and other protocols. Mutual TLS automatically gets applied by the service mesh to secure and authenticate the communication between services residing in the containers. As it intercepts every outbound and inbound call of a microservice, it can provide unbeatable network visibility to gain deep insights.<\/p>\n AIOps is an artificial intelligence application that uses big data, machine learning, and analytics to enhance IT operations. Based on the reports<\/a>, AIOps Market was valued at $13.51 billion in 2020 and is estimated to reach $40.91 billion by 2026.<\/p>\n It provides deep visibility across the environments into the performance data and dependencies. With AIOps it becomes easier to analyze the data for slowdowns or outages. Other than that, it automatically alerts the team about the problem, its cause, and the solutions and therefore can be used with Kubernetes to acknowledge the issue and find its root cause.<\/p>\n The core reason behind AIOps trend in the containerization industry is its ability to handle a tidal wave of ever-increasing data with steady uptime and efficiency. Moreover, it offers intelligent clustering of data to identify patterns that may cause issues in the future.<\/p>\n With the development of IoT, 5G, or live broadcasts, more computing businesses and forces are sinking data sources to obtain good response time and less costs. Being an extension of cloud computing, edge computing will be widely used in hybrid cloud scenarios that will require infrastructure with autonomous edge facilities, edge cloud hosting and decentralization.<\/p>\n The cloud layer retains the cloud-native management and rich product capabilities and sinks them to the edge through the cloud management channel, resulting in the transformation of massive amounts of edge nodes into the cloud-native system\u2019s workload.<\/p>\n Building an automated cloud-native infrastructure for applications is one of the major factors to explore in 2021, as it can reduce the costs per handled container. It increases the consistency, reliability, security, and predictability of port operations. What\u2019s more, it will not only automate the application deployment or operation management but also automate the risk control and prevention while providing automated runtime of the operator.<\/p>\n Data has always been an essential part of every industry. Data transformation is the process of transforming the data from one format into another through extract load transform (ELT), offering better insights about the variables and improving interoperability.<\/p>\n Cloud-native technologies will also promote data-driven applications to back digitally intelligent IT transformation. Migrating high-performance computing applications and traditional big data to Kubernetes is a problem faced by cloud-native communities. The cloud-native AI that was developed by Docker and Kubernetes can offer some relief in the future.<\/p>\n The flexible framework of Kubernetes, the capacity scheduling, and batch scheduling are being implemented for resource scheduling during data transformation. Besides, the Kubernetes cluster uses a container and plugin-based scheduling strategy to support GPU resource sharing and scheduling.<\/p>\n Moreover, new scenarios of elastic data tasks and a unified cloud-native base for AI and big data will be used in containerization.<\/p>\nWhat Are Containers?<\/h2>\n
Top Trends in Containerization<\/h2>\n
Kubernetes<\/h3>\n
Service Mesh for Containers<\/h3>\n
Artificial Intelligence for IT Operations (AIOps)<\/h3>\n
Rapid Cloud Edge Integration<\/h3>\n
High Automation of Cloud-Native Apps<\/h3>\n
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Because of Kubernetes final state concept, cloud-native architecture now enables high automation. While developing cloud-native applications, the automation facility can be fully utilized to track the number of replicas, error retry, version consistency, and asynchronous event-driven.<\/p>\nData Transformation<\/h3>\n
IoT Proliferation Using Containers<\/h3>\n