What is driving the growth of open source container orchestrator Kubernetes? A study from Pepperdata shows how companies are using K8s and the challenges they face in getting a grip on cloud costs.
With the rush to cloud enterprises comes the increasing use of Kubernetes to get applications up and running on the web. A recent study by Pepperdata, a big data monitoring company, looked at both the growth of Kubernetes adoption and how companies are addressing it from the cost and revenue fronts.
Pepper dates The state of Kubernetes 2023 The report shows that organizations deploy an average of three to ten Kubernetes clusters. It also revealed that the use of the open-source container orchestration system is expanding into data ingestion, cleaning and analytics, databases, and artificial intelligence and machine learning.
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Pepperdata, in its survey of 800 C-level execs and DevOps professionals working in financial services, healthcare, technology and advertising, asked:
- How many K8s cluster organizations run.
- What workload types do they deploy on K8s containers.
- Challenges enterprises face when using Kubernetes.
- How enterprises measure the ROI of their K8s implementations.
- Where companies are in their FinOps journey.
Kubernetes: Deployment outside of microservices leads to wider use
As Kubernetes matures and becomes an industry standard for container orchestration, its use is expanding beyond its core application as a microservices mothership. The study found that:
- 30% of executives reported three to five K8 implementations.
- 38% reported six to ten clusters.
- Nearly 15% said they had between 11 and 25 clusters.
- 4% reported having deployed more than 25 clusters.
In terms of how enterprises deploy Kubernetes for specific workloads, Pepperdata found:
- 61% of companies surveyed use Kubernetes to implement data ingestion, cleaning, and analytics through software such as Apache Spark.
- 59% use Kubernetes to deploy databases or data cache through platforms such as PostgreSQL, MongoDB, and Redis.
- 58% reported using Kubernetes on web servers such as NGINX.
- 54% said they deploy AI/ML software such as Python, TensorFlow, and PyTorch on Kubernetes.
- 48% said they use Kubernetes for programming languages like Node.js and Java.
- 42% reported using Kubernetes for logging and monitoring through tools like Elastic and Splunk.
- 35% said they deploy application servers with Kubernetes.
Microservices are still a good proxy for Kubernetes deployment
Pepperdata’s research suggests that organizations will adopt Kubernetes in greater numbers given their plans to deploy microservices such as NGINX. Forty-four percent of respondents said they plan to do so this year, while 36% said they have already deployed microservices and only 20% said they had no plans to do so.
Also, the majority of those surveyed said Kubernetes provides them with a strong core microservices architecture, accelerates application deployment, and supports platform consistency across development, testing, staging, and production clusters.
Looking at Kubernetes for ROI
Pepperdata found that among those surveyed, implementation cost was the top metric for measuring Kubernetes ROI, with findings indicating that nearly 44% of organizations are looking for ways to reduce cloud costs.
After costs, revenue growth (54%), resource utilization (49%), followed by deployment frequency (48%), developer productivity (46%), infrastructure utilization (35%), and IT staff productivity savings (25%) were the top ROI metrics . Companies reported that they expect Kubernetes to increase ROI by reducing administrative and operational burdens, speeding up deployment times, and making resource management more efficient.
Cost surprises are a major challenge for K8s
When Pepperdata surveyed IT leaders about the challenges they faced in adopting Kubernetes:
- 57% reported significant or unexpected expenditures on computing power, storage network infrastructures, and cloud-based IaaS.
- 56% cited the learning curve for employees to upskill for operations and security in Kubernetes environments.
- 52% pointed to limited support for stateful apps (such as applications that store customer data).
- 50% said lack of visibility into Kubernetes spending.
Organizations are moving towards cloud cost reduction
In his FinOps performance study, the FinOps Foundation defines levels of familiarity with FinOps from crawling to walking to running, among other things. In Pepperdata’s survey, most respondents self-identified in the walking phase.
According to the survey, nearly all respondents were familiar with cloud cost optimization, with 32% describing themselves as “crawling”. The majority (43%) said they are “walking,” meaning they have the ability to implement cloud cost reduction recommendations today. Seventeen percent themselves reported being “running,” meaning they are actively working to reduce costs through autonomous procedures. Six percent say they have not yet started.
Interestingly, more than 98% of respondents said they are comfortable with FinOps and see themselves somewhere on the continuum of implementing cloud cost recovery best practices. In addition, more than 17% of respondents identified in the run phase, with the ability to autonomously recover cloud costs.