Top 8 Kubernetes Best Practices to Get the Most out of It

SAYANTANI BHATTACHARYA | June 23, 2021 | 215 views

With the growth of cloud technology, several enterprises are now aware of the benefits of adopting hybrid and multi-cloud models. However, when shifted between different cloud environments, they face a set of challenges to ensure the applications' reliable performance. Thus, the introduction of the concept of containers in cloud computing comes into action. Containerization is simply the clustering of an application and all its components into a single, portable suite. With containerization rapidly gaining popularity in cloud computing, leading providers, including Amazon Web Services (AWS), Azure, and Google, offer container services and orchestration tools to accomplish container creation and deployment. Based on Forrester's 2020 Container Adoption Survey, about 65% of entrepreneurs are already using or are planning to implement container orchestration platforms as part of their IT transformation approach. Kubernetes is one of the most known and future-ready, portable container orchestration platforms developed by Google. It is a scalable, reliable, robust, and secured platform, which can manage and accommodate high traffic for cloud applications and microservices. For optimal performance, implementing Kubernetes best practices and following a tailored configuration model is significant to ensure the optimal platform efficiency your enterprise requires.

This article will highlight the top eight best practices of Kubernetes that will help you orchestrate, scale, control, and automate your enterprise applications. But before we start, let us know the basic concept of Kubernetes. 

What is Kubernetes?

Kubernetes (a.k.a. k8s or "Kube") is Google's open-source container management platform spanning public, private, and hybrid clouds that automates numerous manual processes involved in scaling, deploying, and managing the containerized applications. Kubernetes is an ideal platform for hosting cloud-native applications that require quick scaling, like real-time data streaming through Apache Kafka. In simple words, you can cluster together groups of hosts running Linux containers, and Kubernetes supports you in managing those clusters quickly and efficiently. Gartner forecasts that worldwide container management revenue will grow sturdily from a small base of $465.8 million in 2020 to register $944 million by 2024. It seems that the popularity of Kubernetes across the enterprises will make the forecast achievable.

Using Kubernetes, outsourcing the data centers to public cloud service providers, or providing web hosting to optimize software development processes can become manageable. Moreover, website and mobile applications with intricate custom codes can deploy Kubernetes on their product hardware for a cost-effective solution. Moreover, it helps you completely implement and trust a container-based infrastructure in production environments, where you need to manage the containers that run the applications and ensure zero downtime. For example, if a container goes down and another container needs to start, Kubernetes handles the situation with its distributed system framework efficiently. 

Reasons Behind the Popularity of Kubernetes Strategy

Kubernetes is in the headlines, and we hear about it on social media or at user groups and conferences. So, what is the reason behind its popularity? According to the Kubernetes service providers, it has become the standard for container management platform as it offers several advantages:
  • Scalability: It offers easy scalability of the containers across many servers in a cluster through the auto-scaler service, thereby maximizing resource utilization with a simple command, with a UI, or automatically based on CPU utilization.
  • Flexibility: The flexibility of Kubernetes expands for applications to operate consistently and efficiently irrespective of the complexity of the requirement.
  • Storage Orchestration: The open-source attribute of Kubernetes gives you the liberty to take advantage of storage orchestration from different cloud environments and shift the workloads effortlessly to their destinations.
  • Automation: Using Kubernetes, you can automatically place containers as their resource requirements without any availability concerns. It helps to combine critical and best-effort workloads, to drive the utilization and save resources.
  • Health-Check and Self Heal: Kubernetes allows you to perform the health-check and self-heal your containers with auto-replacement, auto-restart, auto-replication, and auto-scaling properties. 
  • Reliability and Security: Kubernetes offers tolerance and clustering of significant errors, bringing stability and reliability to the project. Built-in data encryption, vulnerability scanning, etc., are some of the services of Kubernetes that enhance its security aspect.
  • Self-discovery: Kubernetes allows self-discovery by providing their IP address to the containers and providing a single DNS name to a group of containers.
  • Roll Out and Roll Back Automation: Kubernetes gradually rolls out changes to your application or its configuration while monitoring the application's health to ensure it does not kill all your instances at the same time. Kubernetes rolls back the changes in case of any discrepancy.

8 Kubernetes Best Practices for Efficient Deployment

According to Red Hat's "The State of Enterprise Open-Source Report," 85% of the interviewees agree that Kubernetes is the key to cloud-native application strategies. Kubernetes has evolved from the code that Google used to manage its data centers at scale. Nowadays, organizations use Kubernetes for complete data center outsourcing, web/mobile applications, SaaS support, cloud web hosting, or high-performance computing. For any platform to operate and perform at its optimum capacity, there are certain best practices that you should consider. In this article, we will discuss a few of the best practices of Kubernetes that can improve the efficiency of your production environment.

Use The Latest Version and Enable RBAC

Kubernetes releases new features, bug fixes, and platform upgrades with its consistent version update. As a rule, you must always use the latest version to make sure that you have optimized your Kubernetes. By upgrading to the newest release, you will get technical support and a host of advanced security features to control the potential threats while fixing reported vulnerabilities.

Enabling RBAC (Role-Based Access Control) will help you control access and admittance to users and applications on the system or network. The introduction of RBAC in the Kubernetes 1.8 version helped to create authorization policies using rbac.authorization.k8s.io API group. It allows Kubernetes to permit access to the user, add/remove approvals, set up regulations, etc.

Organize With Kubernetes Namespaces

A namespace is a kind of virtual cluster that helps your Kubernetes environment organize, secure, and perform. Thus, it can be considered one of the Kubernetes best practices that enables you to create logical partitions and apply separation of your resources and restrict the scope of user permissions. Thus, you can use it in a multi-user environment spanning multiple teams or projects.

Namespaces cannot be nested inside one another, and each Kubernetes resource must be in its own unique namespace. However, it is not essential to use multiple namespaces to distinguish slightly unlike resources, such as different releases of the same software: use labels to separate resources within the identical namespace.

Consider Small Container Images

Using base images may include the unnecessary inclusion of additional packages and libraries. Hence it is significant to use smaller container images as it helps you to create a high-performing platform quickly. As one of the Kubernetes best practices, you can consider Alpine Linux Images, which are much smaller than the base images. Alpine Images have access to a package repository that has necessary add-ons. You can add essential packages and libraries for your application as required. Smaller container images are also less vulnerable to security threats as they have lesser attack surfaces.

Setting Up Health Checks

Managing extensive distributed systems can be complex, especially when things are not running perfectly. The primary reason for the complication in the distributed system is that multiple operations work together for the system to function. So, in case of any discrepancy, the system has to identify and fix it automatically. Kubernetes health checks are simple ways to ensure that application instances are working.

Health checks are the effective Kubernetes best practices to analyze whether your system is operational or not. If an instance is non-operational or failed, then other services should not access or communicate with it. As an alternative, the system can divert the requests to some other ready and operational instances. Moreover, the system should bring your app back to a healthy state. Kubernetes provides you two types of health checks, and it is significant to recognize their differences and utilities.

Readiness probes allow Kubernetes to identify whether the application is ready to serve the traffic before permitting the traffic to a pod (most miniature Kubernetes objects). It fundamentally shows the availability of the pod to accept the workload traffic and respond to requests. In case the readiness probe fails, Kubernetes halts the traffic towards the pod until it is successful. 

The liveliness probe allows Kubernetes to perform a health check to verify whether the application operates as desired. In case it fails, Kubernetes removes the pod and initiates its replacement.

Setting Kubernetes Resource Usage (Requests and Limits)

Kubernetes uses the process requests and limits to control resource usages such as CPU and memory. If a container requests a resource, Kubernetes will only map the schedule on a node to provide the requested resource. Whereas limits help to make sure a container never goes beyond a specific request value. The container will be automatically restricted if it goes beyond the limit. 

To get a total resource value of Kubernetes pods (usually available in a group) comprising one or multiple containers, you need to add the limits and requests for each container. While your Kubernetes cluster might be operational without setting the resource 'requests and limits', you will start getting stability issues as the workloads start scaling. Adding 'requests and limits' will help you to get the optimal benefit of Kubernetes.

Discovering External Services on Kubernetes

If you want to discover and access the services living outside your Kubernetes cluster, you can do it by using the external service endpoint or Config Maps directly in your code. Even if you are unwilling to identify those today, there can be a compulsion to do so tomorrow. Mapping your external services to the internal ones will enhance the flexibility to transmit these services into the cluster in the future while reducing recoding efforts. Additionally, it will help you to easily manage and understand the external services your organization is using.

Database Running- Whether to consider or not?

Running a database on Kubernetes can get you some benefits regarding the automation Kubernetes provides to keep the database application active. However, it would help if you analyze them before you start. There can be failure incidents because the pods (database app containers) are susceptible to letdowns compared to a traditionally hosted or fully managed database. Databases with concepts like sharing, failover elections, and replication built into its DNA will be easier to run on Kubernetes. 

Thus, simple questions like the following will help to draw a Kubernetes strategy to consider whether to run a database or not.
  • Are the features of the database Kubernetes-friendly?
  • Are the workloads of the database compatible with the Kubernetes environment?
  • What is the limit of the Ops workload acceptable in the Kubernetes environment?
If the answers to all the questions are affirmative, your external database is ready to run on the Kubernetes environment. Otherwise, you should consider other platforms such as managed DB or VM. 

Termination Practices

Addressing failures is inevitable in distributed systems. Kubernetes helps in handling failures by using controllers that can keep an eye on the state of your system and restart the halted services. However, Kubernetes can also often compulsorily terminate your application as part of the regular operation of the system. It can terminate Kubernetes objects for various reasons because enabling your application to handle these terminations efficiently is essential to create a steady plan and provide a great user experience.

Winding Up

The CNCF survey report 2020 highlights the progressive inclination towards adapting the Kubernetes platform. The survey received 1324 responses inferred in 2020, where 91% of respondents report using Kubernetes, 83% of them are in production, showing a steady upsurge of 78% from last year and 58% in 2018. Adhering to the Kubernetes best practices will provide you an opportunity to take your production environment to the next level and meet the business requirements. In addition, it will have a positive impact on the Kubernetes market size.

Several top marketers and service providers are doing their best to ensure their customers get the desired benefits for Kubernetes deployment in production. Moreover, they also pitch for services on Kubernetes and allow businesses to gain the most out of it. In the latest interview with Media 7, Red Hat's Director of Product Marketing, Irshaad Raihan says, "We look to inspire great ideas and help our customers reach for the impossible. Once we have buy-in into the "why," we arm customers with the most relevant data points to help them make a purchase decision around product and vendor."

FAQ’s

What exactly is Kubernetes?

Kubernetes is an open-source, portable, and scalable platform for container orchestration, automating several manual tasks for managing the containerized workloads. Kubernetes allows clustering running Linux containers and supports managing those clusters quickly and efficiently.

Why is Kubernetes so popular?

Kubernetes has become one of the efficient container management systems as it offers several advantages, such as easy scaling of the containers across many servers in a cluster. It helps in the easy movement of workloads between different types of environments. It also offers high error tolerance, which contributes to the stability and reliability of the workload and has built-in security tools that provide enhanced safety to the platform.

What is an example of Kubernetes?

One of the most popular Kubernetes use cases is the popular game Pokemon Go. Niantic Inc. was the developer and witnessed more than 500 million downloads with 20 million active users every day. Pokemon Go's parent company was not expecting this kind of traffic. As an advanced solution, they opted for Google Container Engine powered by Kubernetes.

Where is Kubernetes used?

You can use Kubernetes to manage microserver architecture. Kubernetes simplifies various facets of running a service-oriented application infrastructure. For instance, it can control the allocation of resources and drive traffic for cloud applications and microservices.

Spotlight

Flexxible IT

Flexxible IT offers the only industrialized solution for virtual workspaces with proprietary technology and Citrix in a hyper-converged infrastructure. For 8 years now, Flexxible IT has been researching and implementing VDI technology for virtual desktops in the cloud and on-site. Our proprietary technology means we can offer a product that can be deployed instantly and managed independently by IT teams.

OTHER ARTICLES
CLOUD SECURITY

What Is Cloud-Native and Why Does it Matter for CI

Article | July 11, 2022

Continuous intelligence (CI) relies on the real-time analysis of streaming data to produce actionable insights in milliseconds to seconds. Such capabilities have applications throughout a business. In today’s dynamic marketplace, new CI applications that use data from various sources at any given time might be needed on very short notice.The challenge is how to have the flexibility to rapidly develop and deploy new CI applications to meet fast-changing business requirements. A common approach employed today is to use a dynamic architecture that delivers access to data, processing power, and analytics capabilities on demand. In the future, solutions also will likely incorporate artificial intelligence applications to complement the benefits of traditional analytics. Increasingly, cloud-native is the architecture of choice to build and deploy AI-embedded CI applications. A cloud-native approach offers benefits to both the business and developers. Cloud-native applications or services are loosely coupled with explicitly described dependencies.

Read More
CLOUD SECURITY

Why Microsoft Should Spinoff Its Cloud Business

Article | July 8, 2022

Microsoft currently features old-school solutions that are growing relatively slowly (Office and Windows) and new cloud solutions that are growing tremendously (Dynamics 365 and Azure). If the company stays in its current form, Microsoft stock will keep steadily advancing. But because the company’s total top and bottom lines are never going to increase much more than 30% or 35% per year, the shares are never going to deliver truly huge returns. But that would change if the company was to spin off its rapidly growing cloud businesses. In such a scenario, the current owners of Microsoft stock would receive shares in a cutting edge cloud services company (let’s call it Azure), and shares in a company focused on providing old, mostly PC-based software to businesses and consumers.

Read More
CLOUD SECURITY

Intelligence Giant Upgrading its Cloud Technology

Article | July 13, 2022

With the huge amounts of data in all fields, a future in the cloud is imperative to help deal with this explosion of data, especially in the field of intelligence technology. This is the reason why the US Central Intelligence Agency is updating its cloud technology. The agency has recently released a draft request for proposal for its Commercial Cloud Enterprise contract.The C2E tens of billions contract will be a multi-award commercial cloud computing contract with a five-year base period and two five-year options for a period of performance of up to 15 years, according to nextgov.com.In a March 2019 presentation by the Directorate of Digital Innovation, a division of the CIA, the department outlined its vision for C2E. It would be broad and include infrastructure, platform and software cloud services supporting a broad range of users, with a variety of security clearances and a worldwide presence, as reported by techcrunch.com. The principal C2E Program objective is to acquire cloud computing services directly from commercial cloud service providers with established records for innovation and operational excellence in cloud service delivery for a large customer base,the department stated in the presentation.Apparently, the agency prefers to avoid all the attention that the Pentagon’s JEDI cloud procurement process got, and quietly go about its business.

Read More

AWS tags US$235 million to expand its cloud infrastructure in Latin America

Article | February 10, 2020

Amazon Web Services (AWS) is raising its stake on cloud computing infrastructure in Latin America. Proof of this is that the IT company will use R$1 billion (around US$235 million) to expand its data center in Sao Paulo. These millions will be used for its Data Processing Center located in that part of Brazil. In addition, a portion of these US$235 million will also be used to increase the services it offers to both public and private parties.The move gives reason to suggest that AWS is upping the ante in the future of startups and tech in the region that rely on cloud services to develop their own products.It launched its cloud center in Brazil in 2011 but it’ll be getting some beefing up thanks to these funds. Moreover, AWS has two Edge networks in São Paulo and two in Rio de Janeiro. As well as one in each of the following cities: Bogotá (Colombia), Buenos Aires (Argentina), and Santiago (Chile).The objective of all of this is to be the region’s prime provider of cloud infrastructure and beat out its competition AKA, Google Cloud Platform and Microsoft’s Azure.

Read More

Spotlight

Flexxible IT

Flexxible IT offers the only industrialized solution for virtual workspaces with proprietary technology and Citrix in a hyper-converged infrastructure. For 8 years now, Flexxible IT has been researching and implementing VDI technology for virtual desktops in the cloud and on-site. Our proprietary technology means we can offer a product that can be deployed instantly and managed independently by IT teams.

Related News

CLOUD STORAGE

Databricks and Google Cloud Announces New Partnership

Google Cloud, Databricks | February 19, 2021

Databricks and Google Cloud today declared another association that will bring to Databricks clients a profound combination with Google's BigQuery stage and Google Kubernetes Engine. This will permit Databricks' clients to bring their data lakes and the service’s analytics capabilities to Google Cloud. Databricks as of now include profound incorporation with Microsoft Azure — one that works out in a good way past this new organization with Google Cloud — and the organization is likewise an AWS accomplice. By adding Google Cloud to this rundown, the organization would now be able to profess to be the "solitary brought together information stage accessible across every one of the three clouds (Google, AWS and Azure)." It’s worth stressing, though, that Databricks’ Azure integration is a bit of a different deal from this new partnership with Google Cloud. “Azure Databricks is a first-party Microsoft Azure service that is sold and supported directly by Microsoft. The first-party service is unique to our Microsoft partnership. Customers on Google Cloud will purchase directly from Databricks through the Google Cloud Marketplace,” a company spokesperson told me. That makes it a bit more of a run-of-the-mill partnership compared to the Microsoft deal, but that doesn’t mean the two companies aren’t just as excited about it. “We’re delighted to deliver Databricks’ lakehouse for AI and ML-driven analytics on Google Cloud,” said Google Cloud CEO Thomas Kurian (or, more likely, one of the company’s many PR specialists who likely wrote and re-wrote this for him a few times before it got approved). “By combining Databricks’ capabilities in data engineering and analytics with Google Cloud’s global, secure network—and our expertise in analytics and delivering containerized applications—we can help companies transform their businesses through the power of data.” About Databricks As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

Read More

VMware eases container deployment on premise and in the cloud

December 08, 2014

Virtualisation heavyweight VMware announced it has bolstered technology integrations with Docker, Kubernetes, and Mesosphere in a bid to open up its platform to a range of containerisation technologies. The move comes as Linux containers start to pick up traction in the enterprise.

Read More

Google joins OpenStack to build bridges between public and private clouds

Google | July 16, 2015

Google has officially signed up to sponsor the OpenStack Foundation, the first of the big three – Google, Microsoft and AWS – to formally throw its weight behind the open source cloud orchestration software. Analysts believe the move will improve support for Linux containers across public and private cloud environments.Google has already set to work integrating Kubernetes with OpenStack with pure-play OpenStack software vendor Mirantis, a move the company said would help bolster its hybrid cloud capabilities.

Read More

CLOUD STORAGE

Databricks and Google Cloud Announces New Partnership

Google Cloud, Databricks | February 19, 2021

Databricks and Google Cloud today declared another association that will bring to Databricks clients a profound combination with Google's BigQuery stage and Google Kubernetes Engine. This will permit Databricks' clients to bring their data lakes and the service’s analytics capabilities to Google Cloud. Databricks as of now include profound incorporation with Microsoft Azure — one that works out in a good way past this new organization with Google Cloud — and the organization is likewise an AWS accomplice. By adding Google Cloud to this rundown, the organization would now be able to profess to be the "solitary brought together information stage accessible across every one of the three clouds (Google, AWS and Azure)." It’s worth stressing, though, that Databricks’ Azure integration is a bit of a different deal from this new partnership with Google Cloud. “Azure Databricks is a first-party Microsoft Azure service that is sold and supported directly by Microsoft. The first-party service is unique to our Microsoft partnership. Customers on Google Cloud will purchase directly from Databricks through the Google Cloud Marketplace,” a company spokesperson told me. That makes it a bit more of a run-of-the-mill partnership compared to the Microsoft deal, but that doesn’t mean the two companies aren’t just as excited about it. “We’re delighted to deliver Databricks’ lakehouse for AI and ML-driven analytics on Google Cloud,” said Google Cloud CEO Thomas Kurian (or, more likely, one of the company’s many PR specialists who likely wrote and re-wrote this for him a few times before it got approved). “By combining Databricks’ capabilities in data engineering and analytics with Google Cloud’s global, secure network—and our expertise in analytics and delivering containerized applications—we can help companies transform their businesses through the power of data.” About Databricks As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

Read More

VMware eases container deployment on premise and in the cloud

December 08, 2014

Virtualisation heavyweight VMware announced it has bolstered technology integrations with Docker, Kubernetes, and Mesosphere in a bid to open up its platform to a range of containerisation technologies. The move comes as Linux containers start to pick up traction in the enterprise.

Read More

Google joins OpenStack to build bridges between public and private clouds

Google | July 16, 2015

Google has officially signed up to sponsor the OpenStack Foundation, the first of the big three – Google, Microsoft and AWS – to formally throw its weight behind the open source cloud orchestration software. Analysts believe the move will improve support for Linux containers across public and private cloud environments.Google has already set to work integrating Kubernetes with OpenStack with pure-play OpenStack software vendor Mirantis, a move the company said would help bolster its hybrid cloud capabilities.

Read More

Events