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Things to Keep in Mind to Successfully Deploy Kubernetes in Production by@priya11
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Things to Keep in Mind to Successfully Deploy Kubernetes in Production

by Priya KumariAugust 21st, 2022
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According to Gartner's prediction, more than 75% of the global organizations will be running containerized applications in production and Kubernetes adoption curve, in general, is on a surge. While in general, Kubernetes adoption has amplified there are significant challenges in adoption that are preventing Kubernetes from becoming more prevalent.

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Introduction

Kubernetes is governing the cloud native world and its adoption is at an all-time high. Almost every major IT organization invests in a container strategy and consequently arises the need for Kubernetes as the most popular container orchestration tool. Kubernetes is by far the most used and most popular container orchestration technology. While there are many flavors of Kubernetes, managed solutions like AKS, EKS and GKE are by far the most popular.


Kubernetes is a very complex platform, but setting up a Kubernetes cluster is fairly easy as long as you choose a managed cloud solution. A self-managing Kubernetes cluster comes with its own share of hick-ups and is generally not advisable unless one has a very good reason to do so.


According to Gartner's prediction, more than 75% of the global organizations will be running containerized applications in production and Kubernetes adoption curve, in general, is on a surge. While in general, Kubernetes adoption has amplified there are significant challenges in adoption that are preventing Kubernetes from becoming more prevalent.


So, let’s try to figure out the key considerations that we should keep in mind to successfully run Kubernetes in a production environment.


If you're already familiar with Kubernetes, then you may want to consider running it in production. You'll need to pick a managed solution (AKS or GKE), which means you won't need to install any software on your own servers. If you want to run Kubernetes on your own hardware, that's also possible; however, it can be costly and time-consuming—and it's not recommended unless there's no other option available due to cost or complexity issues (for example, if your infrastructure isn't ready.

Best Practices: Planning & Preparation to Effectively Deploy Kubernetes in the Production Environment

Kubernetes is a powerful tool, but to make it work in production, you’ll have to carefully plan and prepare your cluster. Ensure that your Kubernetes cluster can withstand a load of your production workloads by following industry best practices including setting up multi-node clusters, using centralized logging for monitoring, and making sure each pod has access to needed resources. This starts with learning how Kubernetes works, the benefits of running a production-ready cluster, how you can use Kubernetes to provide secure access and improve application security, and how to configure the cluster.


Planning and preparation are necessary to set up production-ready Kubernetes. A good Kubernetes setup makes the life of developers a lot easier and gives them time to focus on delivering business value.


The Kubernetes ecosystem is growing and becoming more complex, so there is a demand for people who can understand the breadth of this technology and help businesses with day-to-day operations. A good Kubernetes setup makes the life of developers a lot easier, using automation or fewer operations it is easier to deploy applications from a stable environment.


(Key Components Governing Effective & Successful Kubernetes Deployment in Production)


So, without further ado let’s jump to critical components that you should keep in mind to setup Kubernetes in an efficient and smooth way:


  1. Use Infrastructure as Code (IaC) for Managing Cloud Infrastructure

Using Infrastructure as Code (IaC) for managing your cloud infrastructure means that you can easily test infrastructure changes in non-production environments. This will help prevent the manual deployment cycle, leading to improved quality and reliability of your infrastructure.

IaaS cloud providers tend to provide excellent support for IaC and the benefits are well-known: continuous deployment, zero human errors, and automated scaling. The general cloud best practice in terms of IaaS is Infrastructure as Code - IaC. It allows you to specify your infrastructure (changes) in non-production environments using a declarative approach, making it more reliable and repeatable. This gives organizations the ability to deploy their entire infrastructure wherever they want and enables them to test changes in non-production environments.


Migrating to Kubernetes is challenging, and managing your cloud infrastructure like a business-continuity management system (BCMS) is critical. Kubernetes Placing Layer (KPL) provides a set of tools that help administrators and developers automate many core Kubernetes features, including deployment, scaling, and health monitoring.


To manage infrastructure as code in a cloud environment, Terraform or Pulumi tools can be of great help for organizations. One can create his entire Kubernetes cluster with networking, load balancers, DNS configuration, and an integrated Container Registry into his Cloud of Choice. One can even configure this via a simple YAML configuration file called Terraform Aliases for software deployment and can do all the needed configuration changes via CLI commands.


  1. Employ Monitoring Solutions & Centralized Logging

Kubernetes has restorative and self-healing properties and is ordinarily a very stable platform. However, problems in production may arise nevertheless and that's where monitoring becomes important. Things such as certificate authentication to allow users to log in and memory overcommit are some normal chaotic scenarios in a production environment. By using monitoring tools such as Prometheus and Grafana, one can manage and monitor their Kubernetes platform in production as well as the applications running on top of it.


To cope with downtimes, failures, or loss of data within the Kubernetes cluster using Alertmanager for alerting seems to be a good option.


If you are using a centralized logging platform like ElasticSearch for collecting monitoring and error logs, it is important to use centralized components like Fluentd or Filebeat which can send logs to this system. A centralized logging platform provides key advantages for applications. Logs can be searched and analyzed in real-time, reducing the number of manual work developers must do to debug problems. Centralized logging also makes it possible for applications to use one system for collecting logs and monitoring metrics from all components, rather than having each component log individually.


  1. A Central Ingress Controller such as SSL Certificate Management

In a Kubernetes cluster, there is a central single point of control for managing ingress configurations. An Ingress Controller manages all traffic flow from external sources on the Internet to your application. When an Ingress Controller is linked to a public Cloud LoadBalancer, all traffic is automatically load-balanced among Nodes and sent only to the right pods' IP addresses. It provides an efficient solution to easily control and monitor traffic in a cluster of Kubernetes.


Owing to centralization, an Ingress Controller may offer innumerable benefits alongside taking care of HTTPS and SSL certifications. An integrated component known as cert-manager is a centrally deployed application in Kubernetes that takes care of HTTPS certificates. Cert-manager also takes care of wildcard certificates or even a private Certification Authority for internal certificates that can be trusted by the company. All the incoming traffic is automatically encrypted using the HTTPS certificates and is forwarded to the Kubernetes pods that are functional at the current times. This sets the developers free and they don't need to worry about many things in one go.


  1. Role-Based Access Control (RBAC)

Role-Based Access Control (RBAC) is a way of managing permissions in a system where each user has different levels of access to different objects and resources. RBAC provides a flexible way of controlling who has what level of access to different objects and resources in your system. This allows you to create an environment that maintains security while allowing users with different levels of access to perform specific tasks or tasks within certain contexts.


Role-Based Access Control (RBAC) is a security model that allows us to control access to Kubernetes resources by applying roles and groups to users. This means that not everyone should be able to perform all possible actions.


We should always apply the principle of least privilege when it comes to Kubernetes access. This means that we should only give users access to the resources they need in order to do their job, and not more. For example, we might give a user who manages infrastructure an increased level of privileges than a user who just needs to run analytics on data.


When we integrate Kubernetes with an IAM solution like Keycloak, Azure AD, or AWS Cognito, we can centrally manage authentication and authorization using OAuth2 / OIDC for both platform tools and applications. Roles and groups can be defined to give users access to the resources they need to access based on their team or role.


  1. GitOps Deployments

People who work with Kubernetes use kubectl one way or the other. Maybe you're a developer who has been using Kubernetes for years and loves it. Maybe you're new to this world of containerized applications, and you've been struggling to get started. Maybe you just want to know how to get your code into production as quickly as possible.


Whatever your reason, we have a solution for you: GitOps deployment platforms. These are tools that let developers take their code from one place—their local machine or a staging environment—and push it up into production as quickly as possible (without having to manually apply changes). With GitOps, everything is traceable and automated, so there's no need for any manual intervention. You can even manage environments, teams, projects, roles, policies; hell yeah pretty much everything!


Some of the most popular GitOps platforms out there today include ArgoCD and Flux. When you're working with Kubernetes, you need to know that the code you push to the cluster is exactly what will get deployed. That's when the role of ArgoCD and Flux becomes crucial; these two tools make it easy to deploy your code to Kubernetes.


We love these platforms because they're so powerful. Additionally, they also make sure that your changes are traceable and manageable—no more manual work! With GitOps, all changes are automatically rolled back if a change is made outside of Git. And this is just one way to get started: there are many other ways to use GitOps.


GitOps is a deployment platform that makes it easy to use Git as the single source of truth for your Kubernetes state. With ArgoCD and Flux, you can deploy your applications to Kubernetes by simply pushing your code. No need to worry about setting up an environment or rolling out configuration changes manually—your desired state will be rolled out automatically. With GitOps, every change you make will be traceable, easily automated, and manageable.


  1. Secret Management

Secret Management is key to any security-focused company. Using Role-Based Access Control (RBAC) with secrets can help you protect your employees and apps from secret leakage, as well as prevent misalignment or accidental leaks in your pipelines.


Secrets used in Kubernetes are managed through manifests which can be injected either into environment variables or file mappings. Using role-based access control is a security best practice, and secrets can also be managed through a central vault like Azure Key Vault or AWS Secrets Manager. This way, secret references can be stored in GIT, pointing to an entry in an external secrets Vault.


  1. Other Production Considerations

Production Kubernetes environments typically have more requirements than any personal development, learning, or test environment, and most of the time they're pretty complex. They require secure access by many users, consistent availability, and the resources to adjust to changing demands.


How do you choose where your production Kubernetes environment will live and what level of management will be required? You must also determine how much of a learning curve you want to take on. Will you learn by relying on support staff, or develop your own procedures for managing your cluster?


Your Kubernetes production environment may either be managed and maintained by a team of people or a large organization. You can choose to outsource management to ensure that you have a stable environment with minimal effort and risk. The requirements of a Kubernetes cluster are influenced by the following issues:


a) Availability: Single-machine Kubernetes learning environments have a single point of failure because there is a single server where all the workloads run. Creating highly available Kubernetes clusters is important in order to support rapidly changing workloads, as well as having enough workers available.


Availability is a measure of how reliable your Kubernetes cluster’s endpoints are. You can test the overall availability of a single-machine Kubernetes learning environment by waiting for console output for failure. A highly available cluster has the following characteristics:

  • The control plane and the worker nodes are separate
  • The control plane components can be replicated across multiple nodes
  • The traffic can be load balanced across the cluster’s API server
  • A number of enough worker nodes must be available or should quickly be made available as changing workloads may warrant


b) Scalability: In order to adequately manage your Kubernetes environment, you need to consider how the platform will respond to change. For example, if your production environment sees a high rate of growth in production or special events, you need to plan how to scale up or down depending on the situation. You can set limits for resources and request volumes, for instance, or use capacity management solutions such as horizontal scaling.


When you're running an application in a cloud Kubernetes cluster or with services deployed with a Service Fabric connection, you're almost always going to need some way of scaling based on workload. If you’re not ready to scale and manage the resources your Kubernetes environment needs, you may find that the process is more difficult.


c) Security and access management: Kubernetes, a popular open-source system for managing applications, also provides a number of different options you can use to manage security. You have full admin privileges on your own Kubernetes learning cluster. But it’s important that users have access to resources only when they need them. You can manage this by using role-based access control (RBAC), filtering traffic across different applications and operating system boundaries, as well as logging and auditing.


Kubernetes is flexible and open source, so each user can make the most of it for their own needs. However, there are things you want to manage and secure. You can use RBAC capabilities to determine which users and workloads can call certain APIs.

Also, before setting up a production-grade Kubernetes environment on their own organizations can consider taking some help for additional jobs from Kubernetes Partners such as Turnkey Cloud Solutions. A few options are as follows:


  • Going Serverless: Serverless technology is a developer experience that allows you to run workloads on third-party equipment. It allows you to pay only for what your application consumes, such as CPU usage, memory, and disk requests.
  • Managing control plane: The managed control plane allows you to take advantage of scale and availability benefits provided by the provider. A managed solution is built around the infrastructures, tools, and technologies that your organization uses to manage your infrastructure. Managed control plane allows you to scale up and down as needed without having to worry about hardware scaling or hardware maintenance.
  • Managing worker nodes: You can set up managed worker nodes to run in a pool. This feature allows you to configure how many nodes are running, then the provider automatically monitors those nodes and makes sure they are available, and ready to implement upgrades when needed.
  • Integration: This refers to the services that integrate Kubernetes with other parts of your infrastructure. It can allow you to utilize a self-built solution or work with an existing one, such as Kubernetes integration with cloud providers like Google Cloud and Azure. Kubernetes allows you to take advantage of a lot of different software projects by allowing them to be shared with other tools and services in one easy-to-use container.


In addition to the Kubernetes service, there are other products and services provided by Google that enable you to integrate Kubernetes with different third-party systems. These integrations with Google Cloud Platforms offer flexibility for your applications, in terms of how you architect your infrastructure.


  1. Evaluating Your Cluster Requirements

You can begin to evaluate your cluster's control plane, worker nodes, user access, and workload resources before setting up your Kubernetes production-grade clusters.


To ensure that your Kubernetes cluster meets your needs, you should ask yourself these questions: Is the project going to run any workloads? Can you deploy and manage a Kubernetes cluster? Do you want the control plane to be highly available and redundant? How will users interact with the Kubernetes cluster? What access controls are needed for network admission control or security groups? How will workload resources be provisioned in a production cluster, and how will they be scaled up or down when required (e.g., resources like CPU/memory, storage)?


Kubernetes Adoption Curve: The Current State

With increased availability and ability to scale up rapidly with usage patterns and demand for these platforms from enterprises around the world today, it is no surprise that Kubernetes is seeing rapid growth at an unprecedented pace when compared with previous generations of infrastructure automation technologies such as virtualization and software-defined networking (SDN).


Kubernetes is an open-source container orchestration system developed at Google and now maintained by the Cloud Native Computing Foundation (CNCF). It has seen rapid adoption since its inception and is now used by many of Fortune 500 companies.


Kubernetes has enjoyed broader adoption, with many of its offerings now available from all of the major cloud vendors (AWS, Microsoft, Google, etc.), in addition to most enterprise platform providers (HP, IBM, Cisco, VMware, etc.). Kubernetes is now available from all of the major cloud vendors and enterprise platform providers, including AWS, Microsoft, Google, and many more.

The Kubernetes adoption curve looks on the surge and the future of the technology looks bright. Here’re a few points that back the fact up:


  1. Kubernetes Is Rolling the Cycle of Innovation

Kubernetes has been on the rise for years, but it's still not quite the ubiquitous solution that some would like. Kubernetes is in its "rolling the cycle of innovation" phase and still has a lot of work ahead of it.


To better visualize the status of Kubernetes, consider the Hype Cycle by Gartner and criticality of Kubernetes in nurturing the cloud-native ecosystem. The cycle represents Gartner’s graphical depiction of technological growth and outlines a common pattern for new technologies, from the highs of the initial hype and the lows of disillusionment to enlightenment and productivity. This model provides an excellent framework for assessing the state of Kubernetes in present, and what challenges might cease the technology from being the phenomenal success that it’s headed towards.


As the cycle depicts, Kubernetes has experienced a peak phase of hype. The effort of deploying containerized workloads at scale has also completed its descent into the "trough of disillusionment," as organizations continue to struggle with selecting the right container management offerings to support developer agility, modernization, and operational efficiencies.


When it comes to managing your Kubernetes cluster, you've got a lot on your plate. You want to be sure that all of your services are running smoothly, and you need to keep an eye on workloads as they scale and shrink. But there's another challenge that you may not have considered: staying up-to-date with the latest innovations in Kubernetes.


Gartner has affirmed this, stating that Kubernetes is now poised for the most exciting shift in the cycle — the steady climb out of the troublesome trough and into the light of maturity and wider adoption. An organization’s ability to conquer this ascent, however, relies squarely on operationalizing the technology amidst certain challenges.


  1. The Key Challenges That Might Hamper Kubernetes Adoption

Going from the idea of containers and microservices to production is a daunting task for any organization. Kubernetes provides a solution for this challenge, but several hurdles might be in your way to reaching deployment readiness. The learning curve related to running Kubernetes into production is a steep curve that organizations should take into consideration and avoid falling back into disillusionment. Ascent to the pinnacle of adoption still remains a key challenge for organizations primarily because of technological skill gaps being prevalent in organizations and the lack of in-house technical experts.


Most enterprises face significant challenges ranging from managing clusters to provisioning the right infrastructure with minimal downtime.


  1. Understand About the Plugins and Integrations & Put Them Into Practice to Deploy Kubernetes Seamlessly in Production

Deploying Kubernetes in production might seem a complex affair for many organizations as the technology is fairly new. So, it's quite obvious that the majority of organizations feel crippled when it comes to deploying the Kubernetes platform in production. Fortunately, an array of tools now integrate with Kubernetes that ensure that organizations can rapidly deploy Kubernetes clusters in production in a hassle-free manner. It’s up to businesses to utilize them.


With plugins and integrations, organizations can extend core functionality to Kubernetes seamlessly in production. This allows PaaS providers to offer their services as part of a complete enterprise Kubernetes stack, in a manner that is production-ready. As they extend the overall functionality of the application or add-on, they can be used for things like logging and monitoring or scaling out applications automatically.


  1. Understand that Security Is Pivotal

Security is a top concern when cloud providers take on automated container orchestration. Because Kubernetes is still young, developers and operators of microservices are still discovering how to properly secure it. There are some basic security practices that can be put into place at deployment time, but following them isn't enough. Kubernetes needs more security work done on an ongoing basis. These include monitoring infrastructure devices and applications in production using tools like Prometheus and alerting teams when there are issues.


It is important to understand that security is a pivotal issue while Kubernetes deployment and a breach of confidentiality could have significant ramifications on the organization. Often security as a critical part of deployment, development, and operationalization of Kubernetes clusters might be overlooked and that’s where the problem arises.


Focus on configuring your Kubernetes production environment properly (e.g., ingress and egress controls, encryption and secrets management, role-based access controls, etc.). to secure the workloads effectively. Promote security best practices for Kubernetes clusters by ensuring ingress and egress controls are in place, encryption, and the secrets management mechanisms to protect sensitive data. This will ensure you have the agility and speed required to deploy workloads successfully while maintaining robust security practices.


The right tools can evolve the team’s security posture and help DevOps teams establish solid operating practices for keeping applications secure in production. By developing a formalized set of roles, processes, and responsibilities for different roles in the DevOps cycle, teams can create consistent patterns of thinking around Kubernetes security. When these patterns are built into automation, they become more efficient and faster to use than manual procedures. Fostering trust and alignment should be a priority for management, as well as ensuring that teams have a clear understanding of the Kubernetes technology. Once these steps are followed they help create an effective ownership model.


  1. Embrace Best Practices to Lay a Strong Kubernetes Foundation

Without proper governance and guardrails, organizations lose both security and currency. Learn how to become production-ready at scale by deploying Kubernetes correctly, with proper security and monitoring in place. Take control of your clusters, including a strategy for scaling up or down as needed. It doesn’t matter if your organization has just started to explore the Kubernetes platform or you have been using it for a long time, it is important to understand the process of becoming production-ready at scale. There is an entire community of experts that can help make you more productive and efficient with Kubernetes.


A strong Kubernetes foundation requires a consistent, accessible, and repeatable set of policies that can be enforced across the data center. The correct policy enforcement can ensure the consistency and efficiency of your infrastructure, reduce operational risks and accelerate time to market for new cloud services. Best practices should be followed across the board, from determining how to package resources for Kubernetes deployments and consolidating workloads into clusters, to understanding best practices for deploying images and services. With such secure enforcements deployed in the CI/CD pipeline, businesses meet the requisite security and compliance standards without compromising on speed.


  1. Devise a Powerful Container Management

A powerful and effective container management solution is a must for the continuous adoption of Kubernetes. Your container management solution needs to be powerful, reliable, and secure. If you want to run Kubernetes on your infrastructure, it needs to provide the right services in a way that leverages the strengths of cloud-native containers while also providing a high level of ease of use.


According to Forbes, the container management market is estimated at approximately $300 million and is expected to cross $1 billion by 2025, and that itself tells the entire story.


Containers are becoming a standard tool in the CI/CD pipeline. Container management solutions provide developers and operation teams with the security visibility, orchestration, and resource management they need to continuously deliver their applications.


With such technologies, the management of containers is uplifted to the level of excellence. Container management technologies can help us deploy and manage different virtual machines, provide security visibility into our containers, orchestrate and automate deployment and configuration (via PaaS or IaaS), and provide various other benefits.


Some of the most powerful solutions allow you to automatically retrieve, isolate and monitor containers in an all-in-one, automated way.


By focusing on a seamless and better deployment and delivery organizations can unleash the complete potential of Kubernetes and can reach the zenith of success with this technology.


In Conclusion

The best solution for managing your Kubernetes cluster is to use the best tooling, open source or proprietary.


It's important to have a good infrastructure solution, proper monitoring, and a good RBAC and Deployment mechanism. These will help you save time, failures, and headaches in the long run. Also, there are other factors like Service Mesh, Security scanning/compliance, and end-to-end traceability that are immensely important.


Properly setting up your production cluster includes properly planning the control plane and the worker nodes alongside managing the production-grade cluster with proper deployment tools and managing the users with the help of certifications to provide them with the proper authentication & authorization (for example by using client certificates, broker tokens, an authenticating proxy or HTTP basic auth. as well as by choosing RBAC and ABAC authorizations).


Using standardized open-source tooling instead of DIY tools will save you a ton of headaches in the long run. It also helps you provide more support and security to your infrastructure.