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Kubernetes automation: Use cases and tools to know
Kubernetes automation simplifies the configuration, deployment and management of prepackaged container components supporting business apps, but it's not recommended in all cases.
Kubernetes, also known as K8s, automates enterprise workloads at the container level. Kubernetes automation simplifies the configuration, deployment and management of prepackaged container components supporting enterprise applications. The open source system can also streamline the provisioning of data and AI infrastructure.
Kubernetes sits between traditional approaches for managing workloads at the level of physical hardware and VMs at one end and more abstract cloud PaaS approaches at the other end. As a result, Kubernetes has more fine-grained control compared to physical server and VM approaches. It also supports increased flexibility compared to PaaS and cloud-native approaches.
Container packages must be precompiled and tested to support Kubernetes deployment. As such, Kubernetes automation is commonly used alongside continuous integration and continuous deployment (CI/CD) tools to safely manage the transformation of raw code into packaged containers running apps. Kubernetes packages also tend to be better suited for longer-duration and stateful data management use cases than the more ephemeral approaches used in serverless PaaS approaches.
"Kubernetes automation is most beneficial when managing large-scale, multi-cloud and dynamic workloads, improving efficiency, security and cost management," said Mukesh Ranjan, vice president of cloud and infrastructure, at consultancy Everest Group. "However, it may not be necessary for small, manually intensive or short-lived environments where simplicity is preferred. Ensuring the right balance between automation and control is key to maximizing its benefits."
What functions to automate with Kubernetes
Kubernetes infrastructure is a good fit when using microservices to build complex enterprise applications from simple and reusable components packaged into containers. It can help scale the deployment of individual components at a more granular level than traditional approaches. It can also facilitate communication between components.
Functions that can be automated on top of basic Kubernetes infrastructure include the following:
- Automated cluster scaling. This function simplifies the provision of a collection of containers as part of a cluster.
- CI/CD integration. CI/CD transforms raw code into new container packages. Kubernetes automation provisions these packages into running microservices. Some Kubernetes tools natively support CI/CD capabilities.
- Automated testing and healing. Developers and quality assurance teams assess code quality during software development. Kubernetes automation can help test new container packages in conjunction with other container infrastructure and mitigate problems after deployment.
- Automated backups, rollouts and rollbacks. Kubernetes backups can take snapshots of various Kubernetes configurations, which can be rolled out into deployment and rolled back to a known good configuration when problems are discovered.
- Automated bin packing. This process optimizes the deployment of container packages into bins across multiple physical computers in a cluster to improve the utilization of storage, compute and network resources.
- Service mesh automation. The service mesh is the communication infrastructure between individual containers, which needs to be scaled to support communication requirements between microservices running in containers.
- Security policy enforcement. Teams can use policy enforcement to define appropriate security policies involving individual microservices and the communications between them.
- Continuous monitoring. This function creates an abstraction tier to transform log data into important events that can be assessed by the automation tool or surfaced to external quality or security tools.
- Configuration management. This type of management streamlines the process of defining configuration settings into code that can be versioned, tested, provisioned and rolled back when required.
- Resource quota management. Teams can specify resource consumption limits to mitigate unexpected costs when automated scaling spirals out of control.
Why Kubernetes automation is important
A Kubernetes environment is a complex system that consists of dynamically shifting container workloads, service mesh communication infrastructure, security policies, and configuration management and monitoring tooling.
"The primary reason Kubernetes automation is important is to mitigate human error and operational overhead," explained Ju Lim, senior manager of hybrid platforms product management at open source platform provider Red Hat. Manual management of Kubernetes clusters can be error-prone and time-consuming, especially as the scale and complexity of deployments increase. Kubernetes has many built-in automation features that focus on self-healing, automated rollouts, dynamic scaling, service discovery, load balancing, storage orchestration and batch execution.
Automated workflows ensure processes are executed consistently across teams, eliminating discrepancies that occur with individual manual tasks while increasing consistency, reliability, scalability and auditability in development, testing and production environments. Additionally, automation with complementary product integrations enables consistent end-to-end workflows for enterprise customers.
"Automation can also help coordinate off-cluster IT infrastructure and services with Kubernetes systems," Lim added. This capability includes automation for infrastructure, applications, networks, and security and management tools. Automation also can support end-to-end business continuity and disaster recovery of Kubernetes systems.
Another critical function is harmonizing data management across stateless microservices and stateful database services. Kubernetes, for example, can manage application infrastructure tasks and cover areas such as availability, but it doesn't directly support data backup, replication or synchronization.
"Understanding where Kubernetes will handle some of these steps and where it should be managed elsewhere is essential," said Kate Obiidykhata, senior product marketing manager at open source database software provider Percona. "[O]therwise, you could end up with automation workflows that actually conflict with each other, rather than complementing each other."
The dos and don'ts of Kubernetes automation
Kubernetes automation delivers the greatest value when it supports the middle ground between the simplicity of VM approaches and the flexibility of cloud-native approaches.
When to use Kubernetes
The best fit use cases for Kubernetes automation include the following, advised Pranav Sharma, a principal in the digital and analytics practice at consultancy Kearney, who also provided the following use case examples:
- Microservices. Automation enables independent scaling of services while maintaining a seamless user experience. It also facilitates complex interservice communication and management. Spotify uses Kubernetes automation to orchestrate numerous microservices.
- High-traffic environments. Horizontal Pod Autoscaler and Cluster Autoscaler tools handle demand spikes, providing cost-effective resource utilization during varying load conditions. E-commerce platforms, such as eBay, use Kubernetes automation for traffic management.
- Hybrid and multi-cloud deployments. Automation ensures consistent deployment across distributed environments and streamlines configuration management across multiple platforms. Airbnb uses Spinnaker to manage its multi-cloud environment.
- CI/CD. Enterprises can streamline the provisioning of new packages to accelerate deployment cycles while maintaining reliability, reducing operational overhead through automated monitoring and management. Intuit uses Argo CD to automate CI/CD integration.
When not to use Kubernetes
Sharma pointed to the following simple, small-scale and legacy scenarios to demonstrate when it's more appropriate to deploy alternatives to Kubernetes:
- Simple applications. Single-container applications rarely justify the complexity of Kubernetes automation. The cost of Kubernetes implementation can outweigh the benefits. Personal blogs and basic websites can operate effectively with simpler container management.
- Small-scale operations. Applications with predictable, steady workloads have a limited need for dynamic scaling capabilities. A cost-benefit analysis might favor simpler orchestration approaches.
- Legacy systems. Businesses that heavily invested in traditional infrastructure have many systems that don't easily support containerization. Refactoring these workloads to a Kubernetes architecture can be particularly challenging for government agencies and financial institutions whose requirements are specialized.
Which Kubernetes automation approach is best for me?
When choosing a Kubernetes automation approach, Ranjan suggested that teams focus on scalability, automation reliability and cost efficiency. It's also important to ensure Kubernetes automation integrates well with the company's existing ecosystem and offers flexibility in resource management. "Futureproofing with multi-cloud compatibility and ongoing enhancements is key to long-term success," Ranjan advised.
Also, start your Kubernetes automation journey with the tools you know best. "If you're familiar with a specific Kubernetes solution," Lim explained, "you can start by automating with it and can assess complexity, scale and integrations with other tools. As your solution matures and more coordination and orchestration are needed between IT systems and your Kubernetes solution, then an enterprise-grade automation solution will likely be required."
Some of the more popular Kubernetes automation platforms include the following:
- BuildPiper streamlines CI/CD processes for Kubernetes infrastructure.
- K9s takes a terminal-based UI approach to Kubernetes infrastructure through a command-line interface that supports infrastructure-as-code approaches.
- Open source tool set kOps combines Kubernetes and cloud infrastructure automation.
- Kubespray open source orchestration framework enables teams to manage Kubernetes infrastructure using Ansible IT automation tools and skills.
- Lens is a Kubernetes-specific integrated development environment that helps developers manage and troubleshoot workloads through a context-aware UI.
- Rancher open source Kubernetes management platform simplifies container management, centralizes authentication, supports access control and facilitates observability.
- ScaleOps real-time Kubernetes resource optimization platform helps enterprises improve reliability and reduce costs.
When selecting Kubernetes automation tools, Lim suggested the following factors should be considered:
- The tool's compatibility with existing infrastructure and workflows to ensure seamless integration and minimize operational disruptions.
- Security features, including role-based access control and vulnerability scanning, to protect the environment from potential threats.
- Scalability to grow with business needs while ensuring the tool's automation capabilities for auto scaling, load balancing and self-healing, which can greatly reduce manual intervention and improve efficiency.
- Integration with the existing environment of applications, platforms, tooling and workflows.
Future of Kubernetes automation
There are several new developments in Kubernetes automation to look out for, according to Haritha Gorthi, digital and analytics management consultant at Kearney.
Serverless Kubernetes. Cloud provider-managed Kubernetes clusters could eliminate the need to manage the underlying infrastructure. Some current tools can reduce infrastructure management overhead by more than 50%.
AI/ML workloads. Kubernetes automation is increasingly helping businesses spin up new data science and AI applications, improving the scalability and rollout of new AI and machine learning services.
Enhanced security measures. Security spending on Kubernetes is expected to grow significantly, with a focus on adopting zero-trust security architectures to harden the Kubernetes attack surface against emerging and unknown threats.
Multi-cloud and hybrid deployments. Enterprises will increasingly use Kubernetes automation to manage deployment across distributed clouds and on-premises infrastructure to save costs and ensure resilience.
To prepare for advancements in Kubernetes automation tools and their deployment, businesses should increase their workforce's Kubernetes knowledge and skills companywide. "IT decision-makers will have to perform a cost-benefit analysis of training costs vs. market skill demand," Gorthi explained. When creating a Kubernetes automation roadmap, she recommended starting small with two to three clusters for noncritical workloads, measuring success and scaling gradually to expand on validated metrics. Also, perform workload assessments to identify practical Kubernetes automation use cases in light of application complexity, expected resource utilization and scaling requirements.
George Lawton is a journalist based in London. Over the last 30 years, he has written more than 3,000 stories about computers, communications, knowledge management, business, health and other areas that interest him.
