A new report from SDxCentral found that containers can be beneficial for organizations, but many are still running into numerous deployment challenges, and they need to make sure the cost and risk of container adoption are worth the reward.
The report, Container Infrastructure – What You Need to Know in 2018, highlights the current container ecosystem, including the different components and players in the space. This includes a big emphasis on the Kubernetes container orchestration platform that has become the standard for most new offerings.
This maturing container ecosystem has allowed organizations to glean greater efficiencies from their cloud deployments. The use of containers allows for a reduction in compute resource overhead; greater scalability by using Kubernetes to automatically manage workloads; greater agility coming from the lower compute overhead and orchestration; facilitating the integration of developers and IT operations into DevOps organizations that can accelerate application testing and delivery; and enabling rapid deployment of new applications.
“Containers have exploded in popularity because enterprise developers, IT, and even business leaders have learned something the cloud builders like Google discovered long ago: containers can significantly improve infrastructure and application efficiency, agility, and reliability,” the report states.
Chief Barriers to Container Adoption
While the benefits are compelling, the report notes the continued challenges facing broader adoption of containers. Citing surveys of container users, the report found that the continued chief barrier to adoption is provisioning of persistent storage. This is linked to the broader challenge of integrating containers into existing IT environments and limitations of the core Kubernetes code.
Kubernetes is designed for stateless applications. This means that it was not created to handle data storage. This is not a problem for cloud native web services — like a web server or a front-end web user interface — that do not depend on the local container storage for the workload.
However, stateful applications are services that save data to storage and use that data to run the application. These include databases and complex applications like big data and AI use cases that involve large-scale data processing, data science, and machine learning (ML). Basically these are workloads that currently use platforms like Spark, Kafka, Hadoop, Cassandra, and TensorFlow.
This has led to a robust business of storage vendors developing stateful appendages that can plug into a Kubernetes-managed container deployment to handle storage needs.
Despite the challenges, the report notes that the momentum behind containers remains robust and that every organization should “perform some evaluation and testing of containers, which cloud services greatly simplify.” That testing should take into account an organization’s existing assets, strategies, and goals.
“Like any technology, containers aren’t the solution to every infrastructure problem, and using them correctly requires understanding the benefits, challenges, risks, and costs,” the report concluded.