Compute Services

What the stats say about container development

Share this post:

59% improved application quality and reduced defects. 57% reduced application downtime and costs. All adopted container development.


In 2017, IBM conducted an in-depth research study on the state of container adoption across all industries, startups to enterprises. The study reveals the most important solutions driving usage and highlights the key challenges that must be addressed by cloud providers. Lastly, it dives deep into the benefits experienced, from both a business and application quality perspective.  

It’s important to note the capabilities and solutions that influence decision makers to invest in containers are highly linked in positive relationships. It’s not a matter of which benefit is more needed, but rather, how accomplishing one greatly increases experiencing the other. 

Solutions driving container development adoption

Enterprise-grade security is of utmost importance when considering or adopting commercial container solutions.  The implementation of DevTest tools and microservices development in an organization requires full confidence in the integrity of the platform, because they are seen as the bridge between DevOps and a microservices-based application architecture.  While tools equip DevOps teams to begin operating in a new way, additional support is needed by those looking to leverage innovative technologies like AI within containerized apps (i.e. consulting services, non-x86 architecture support).

container development

Though respondents perceive importance of the drivers consistently, there is a discrepancy in their perceived availability. Enterprise-grade security garners the highest interest, however only a quarter of respondents consider it widely available today. Easy-to-use IDEs, integrated operational tools, preferred platformsolutions, and supporting containers securely across multiple cloud environments are also seen as important but not easily accessible. Important and widely available offerings include DevTest and automation tools, public cloud on-premises support, the ability to design a compute environment, and commercial container solutions. Lastly, consulting services and industry use cases are not considered essential needs, though readily availableOnly companies seeking to leverage AI indicate the need for consulting services.

The benefits of container development by role

container developmentIn terms of business value, business executives focus most on practical benefits. They highly value (61%) the potential of containers to reduce costs of production downtime, improve application quality (56%) and employee productivity (53%). While wary of unproven efficiency (55%), they nevertheless see the potential advantages for the DevOps pipeline (77%) as the single most valuable potential benefit.
IT executives also focus on practical benefits. They see improved software quality (61%) as the highest business value of containers, and enhancing security (72%) as the greatest technical opportunity. In contrast, IT executives see the skepticism of top business executives as the biggest challenge (65%).
container developmentDevelopers focus most on innovation(66%), valuing the quick responses to market changes (64%). For them, the potential for high security (84%) is the most important thing about containers and their environments. Lack of adequate expertise within their organization is the biggest concern (62%).

The state of container development 

For a deeper look into the factors driving adoption, download the study
More Compute Services stories

Improving App Availability with Multizone Clusters

Downtime costs money and results in unhappy customers.  Whether you have developed a new cloud-native application or repackaged an existing app to run as a container, now you need to ensure your app and the infrastructure running it are highly available.  IBM is excited to announce the availability of multizone clusters, targeted for June 2018.  Now […]

Continue reading

Process large data sets at massive scale with PyWren over IBM Cloud Functions

(Ed.–Josep Sampé–Universitat Rovira i Virgili–co-authored this post.) Let’s say you write a function in Python to process and analyze some data. You successfully test the function using a small amount of data and now you want to run the function as a serverless action at massive scale, with parallelism, against terabytes of data. What options do you have? Obviously, […]

Continue reading

Combine organizational transformation and IBM Cloud infrastructure for a successful AI journey

With our recent cloud infrastructure and Deep-Learning-as-a-Service (DLaaS) announcements, IBM Cloud is a key contributor to the push towards AI. We’ve delivered a comprehensive suite of AI tools, high performance bare metal servers, and NVIDIA® GPUs that enables companies of all sizes to analyze complex unstructured data faster, more thoroughly and accurately, and at a far less cost than ever before.

Continue reading