Taikun blogs, guides and articles

Kubernetes has emerged as the de facto container orchestration platform. Its ability to seamlessly manage and scale containerized applications has revolutionized how software is developed, deployed, and managed. According to CNCF’s Annual Survey 2021, 96% of organizations have either implemented or are currently assessing Kubernetes as their container orchestration platform, the highest record since 2016.
The demand for DevOps is on the rise, and with good reason. This hybrid development model has allowed highly competitive businesses to work at lightning speed.But with more incredible speed comes more significant security risks, especially regarding compliance issues, which can cost hundreds of thousands of dollars if they need to be addressed quickly.
Almost 81% of enterprises rely on the cloud. Additionally, the global health crisis has considerably increased the rate of cloud use. A recent Flexera poll found that 27% of leaders indicated that Covid-19 has significantly increased cloud spending. To help businesses mitigate cloud adoption risk, architects now have another option – Managed private cloud solutions.
Kubernetes has emerged as the de facto standard for coordinating containerized applications as businesses seek more efficiency in the ever-changing software development and deployment world. However, when manually configuring a Kubernetes cluster, the task can become quite daunting. This article will dive deep into this issue and provide actionable advice for streamlining your Kubernetes administration!
without the proper tools and infrastructure in place, maximizing DevOps efficiency can be difficult. Services for managing data in the cloud are necessary in this case. This article will discuss benefits, best practices, and concrete examples of how cloud management services can improve DevOps productivity.
Infrastructure as Code (IaC) is necessary for any modern software company or cloud service. Machine-readable definition files replace time-consuming manual procedures for managing and provisioning infrastructure resources by developers and operations teams. IaC increases flexibility, scalability, and repeatability but poses new security risks. 
According to the study by Emergent Research, the infrastructure as code market size was USD 0.64 Billion in 2021 and is projected to exhibit a CAGR of 24.0% over the forecast time frame.  The need for improved efficiency of corporate processes is a key element propelling revenue development in the infrastructure as a code industry. As software systems get more complicated and sophisticated, new technical methods are necessary.
Now more than ever, businesses of all sizes are seeing the benefits of IaC’s ability to automate infrastructure deployment, including decreased operational expenses and increased dependability. However, to put IaC into practice effectively, one must thoroughly comprehend its fundamental concepts and be willing to adhere to best practices.
Within the context of the modern digital world, the performance of apps is an essential factor in providing a fluid user experience. As organizations grow more dependent on software programs to run their operation, it is crucial to monitor the performance of applications and detect any possible bottlenecks or concerns. However, picking the appropriate solution can be challenging because of such a wide variety of monitoring software on the market. This article offers a complete examination of elements to consider when choosing monitoring tools for application performance, as well as an explanation of how Taikun can aid you in making an educated selection.
86% of respondents name technological obstacles as a barrier to observability adoption. These technological issues include poor legacy tools, a lack of platform alternatives, worries about open-source tools, and tool fragmentation. However, as these settings get more complex, the insights gained from conventional monitoring system performance and troubleshooting methods become insufficient. Here, the concept of observability becomes important!  This blog will explore observability, why it matters, and how it can transform today’s IT infrastructure. 
The use of digital technology across all facets of a company results in a fundamental shift in how the company functions and provides value to its consumers. This shift is referred to as digital transformation! Cloud Computing is an essential enabling technology for digital transformation because it allows organizations to swiftly grow and adapt in response to shifting market conditions. This blog post will look into real-world instances of successful digital transformations made possible by cloud computing.
Developing a thorough cloud adoption plan is the first step toward a smooth transition to the cloud. This plan must detail how the company intends to migrate its data and apps to the cloud. In addition to listing the advantages to a company, it should detail any dangers or difficulties associated with moving to the cloud.
The provision of on-demand access to computer resources, storage, and apps has fundamentally altered how organizations function. However, when it comes to embracing cloud computing technology, many companies face certain obstacles despite the many advantages that come with doing so. According to the 2022 Cybersecurity Insiders Survey, the most surprising barriers to cloud adoption were the lack of visibility (49%), high costs (43%), lack of control (42%), lack of staff resources or knowledge (39%), and lack of security (22%).  
The introduction of cloud computing ushered in a technological revolution that altered the way organizations functioned online. It has helped organizations broaden their customer base, enhance their teamwork, and reduce waste. In this article, we will discuss how cloud computing can aid organizations in their digital transformation efforts.
In any Kubernetes cluster setup that has been in use for a while, many teams will create their own Kubernetes resources. With an array of required and optional parameters, each team will create and configure them as per their specific needs. At some point, there is bound to be a need for standardisation. Besides, every organisation will have their own governance and legal policies to be enforced. With that in mind, an open-source, general-purpose policy engine was created. Open Policy Agent (OPA, pronounced “oh-pa”) helps IT administrators unify policy enforcement across the stack. 
According to Cisco 2022 Global Hybrid Cloud Trends Report, “82% of survey respondents indicated having adopted a hybrid cloud”. A hybrid cloud approach allows organizations to combine the benefits of public and private cloud environments, resulting in greater agility, scalability, and cost efficiency. As we move into 2023, we expect to see a continued increase in hybrid cloud adoption and the emergence of new trends and technologies that will shape the future of this approach.
Cloud computing is becoming increasingly popular due to the quick rate of technological innovation and the growing desire for digital transformation. The cloud has rapidly emerged as an integral component of many companies’ ongoing digital transformation efforts, and this trend is anticipated only to accelerate. In this article, we will investigate the future trends in cloud adoption and digital transformation, as well as the influence that these trends will have on your business.
In the era of digital transformation, where companies of all sizes swiftly adopt technological innovation to keep up with the demands of a dynamic and unpredictable marketplace, cloud adoption has become vital to their success. It allows them to quickly and easily gain access to massive amounts of data, expand their operations globally, and work together effectively regardless of physical location.
In today’s increasingly digital environment, data is essential to running any enterprise. Therefore, businesses must ensure their data is secure and readily accessible. Cloud computing has enabled companies to keep their data in a central location and access it from any device at any time. However, stateful apps in the cloud present unique management challenges due to their reliance on persistent storage.
Kubernetes has quickly gained traction as a platform for managing microservices architectures due to its capacity to help businesses with containerised applications’ deployment, management, and scalability. Cloud Native Survey indicated that 96% of firms are either actively utilizing or investigating Kubernetes, representing a significant increase from previous surveys.
This piece will go into Kubernetes’s strengths and how they can be applied to data science and machine learning projects. We will discuss its fundamental principles and building blocks to help you successfully install and manage machine learning workloads on Kubernetes. More over, this article will give essential insights and practical direction on making the most of this powerful platform, whether you’re just starting with Kubernetes or trying to enhance your machine learning and data science operations.
Kubernetes Federation is an invaluable solution that unifies multiple Kubernetes clusters into one entity, making it simpler to deploy applications across diverse environments. With Federation, users can create a global namespace that spans across all clusters in the Federation, allowing for seamless deployment and management of resources.
Kubernetes is quickly becoming the most popular platform to manage the massive scale of containerized workloads and with the right reasons. It’s versatile, flexible and comes with a broad selection of tools and features to manage containerized applications. However, managing applications that run on the top of Kubernetes can be a challenge particularly when it comes to deployment as well as scaling up workloads. This is the reason Helm Charts can help They simplify the process of deployment and let users effectively manage their apps.
Kubernetes has emerged as one of the most popular container orchestration platforms, powering a vast majority of modern cloud-native applications. According to Gartner: 90% of the world’s organizations will have containerized applications in production by 2026, that is up from 40 percent in 2021.
In recent years, microservices have emerged as a popular approach to building modern software applications. This approach breaks down applications into smaller, independent components, each responsible for a specific task or function. However, managing the communication between these components can be challenging, especially as the number of services grows.
In today’s digital world, websites and applications are expected to handle a high traffic volume, especially during peak hours or promotional campaigns. When server resources become overwhelmed, it can lead to slower response times, decreased performance, and even complete service disruptions.
In a nutshell: The article explores the similarities and In a nutshell: The article explores the similarities and difference between private and public clouds and will help you decide which is best for your organization. Businesses have a choice between private and public clouds, and each has its own unique set of benefits and challenges. While both have advantages and drawbacks, the right choice depends on your business needs, goals, and budget. 
Since businesses increasingly rely on data and digital technology, cloud computing has become an integral part of their strategy for IT. While the public cloud has long been a go-to option for many companies, the hybrid cloud has emerged as an appealing alternative that provides the advantages of both public and private clouds – according to Flexera’s study, 87% of enterprises have adopted a hybrid cloud strategy, with 50% of workloads currently located within this environment. Furthermore, 84% have implemented multi-cloud strategies, showing the widespread appeal of using multiple cloud providers.
What are the Different Roles in the Cloud? Cloud computing has become an increasingly popular way for businesses to store and process data. According to a report by Gartner, The worldwide public cloud services market will grow 17.5% in 2019 to reach $214.3 billion, up from the 2018 total of $182.4 billion.” As more businesses move their operations into the cloud, demand for experienced professionals who can manage these systems has also grown significantly. Cloud computing includes a range of roles, each with their own set of responsibilities and necessary skill set, mostly requiring expertise in areas such as infrastructure management, security protocols, and software development. Let’s go thrught the job description of each position, so you can find the right professional for your needs.
Implementing a hybrid cloud environment has now become a major gateway to modernize your business. According to 82% of firms are now utilizing or planning to employ a hybrid cloud solution within the next 12 months, demonstrating the widespread adoption of this strategy. Most companies prefer to opt for a hybrid cloud strategy due to its various benefits, like data security, flexibility, cost-effectivity, and scalability. Despite these benefits, the path of adopting a hybrid cloud model is a bit complex due to certain challenges like security and governance.
As digital transformation continues to expand, businesses face the overwhelming challenge of managing and processing all the data produced daily. According to Statista, Global data production is forecasted to rise from 64.2 zettabytes in 2020 to 180 zettabytes by 2025 – emphasizing the need for effective data management.
Cloud computing’s popularity has increased as more businesses are aware of its benefits. According to Flexera 2020 State of the Cloud Report, around 80 percent of enterprises have a hybrid cloud strategy. They are adopting hybrid clouds for cost savings, greater agility, resiliency, availability, performance and scalability.
The hybrid cloud infrastructure remains the future for many companies as the cloud continues to evolve. According to Statista, “the global hybrid cloud market is expected to reach $262 billion in 2027.” But why and how do companies determine if they’re one of them? Let’s explore in this article below.
Let’s explore the differences between multi-cloud and hybrid cloud based on different characteristics, including architecture, intercloud workloads, vendor lock-in, availability, and cost. Cloud computing has revolutionized how businesses used to run in the past. Currently, there are many models of cloud computing. Cloud technologies have matured, expanded, and improved to support business purposes. According to Statista, “the global cloud applications market is expected to reach $168.6 billion by 2025.” As a result of the proliferation of cloud technologies, businesses, particularly those new to the cloud, sometimes need clarification on multi-cloud and hybrid clouds. While they both refer to types of cloud deployment integrating multiple clouds, there are significant differences between them. The article explores the key similarities and differences between multi-cloud and hybrid cloud environments.
A hybrid cloud refers to a single, unified, and flexible distributed computing environment that integrates public cloud services and on-premise infrastructure or private cloud and provides management and orchestration across them. It allows organizations to keep their sensitive data on-premises while taking advantage of the scalability and cost-effectiveness of public cloud services.
In our series on Kubernetes so far, we have covered an entire gamut of topics. We started with a comprehensive guide to help you get started on Kubernetes. From there, we got into the details of Kubernetes architecture and why Kubernetes remains a pivotal tool in any cloud infrastructure setup. We also covered other concepts in Kubernetes that are useful to know, namely, namespaces, workloads, and deployment. We also discussed a popular Kubernetes command, kubectl, in detail. We also covered how Kubernetes differs from another popular container orchestration tool, Docker Swarm. In this blog, we will consolidate all our learnings and discuss how to run applications on Kubernetes. Although we covered this topic in bits, we feel this topic deserves a blog of its own.
In this blog, we will discuss Kubernetes deployments in detail. We will cover everything you need to know to run a containerized workload on a cluster. The smallest unit of a Kubernetes deployment is a pod. A pod is a collection of one or more containers. So the smallest deployment in Kubernetes would be a single pod with one container in it. As you would know that Kubernetes is a declarative system where you describe the system you want and let Kubernetes take action to create the desired system. 
In the last few blogs we covered have covered Kubernetes in great detail. We started with an overview of Kubernetes and why it is one of the most important technologies in cloud computing today. We also spoke about what Kubernetes architecture looks like and how you can use Kubernetes using a simple kubectl tool. In this blog, we will cover everything you need to know about Kubernetes Namespaces. 
One of the recommended command-line methods to manage your Kubernetes setup is to use kubectl. With the kubectl command, you can interact with Kubernetes API servers to manage workloads in the Kubernetes infrastructure. In this blog, we will cover all aspects of the kubectl command that you would need to get started on managing Kubernetes with it. If you wish to get an overview of Kubernetes, you can read our series of blogs on it starting here.Let’s start with understanding what kubectl is and how it works with Kubernetes. 
In the last few blogs, we discussed how Kubernetes has become a gamechanger in the adoption of cloud computing and how you can get up to speed with it. We also discussed how Kubernetes differs from other orchestration tools like Docker Swarm and how you can make the right choice for your use case.
Kubernetes has been a game-changer in the growth of cloud adoption in the last decade. As more containerized applications take frontstage, Kubernetes has become the go-to container orchestration tool.  In this blog, we will go into the depths of Kubernetes and study its architecture. We will also see a simple workflow on how you can set up Kubernetes and deploy it on the cloud.  If you wish to read more about Kubernetes, you can start with our series on it from here. Let’s get started.
Kubernetes and Docker Swarm are both very popular container orchestration tools in the industry. Every major cloud-native application uses a container orchestration tool of some sort. Kubernetes was developed by Google in the early 2010s from an internal project which managed billions of containers in the Google cloud infrastructure. You can read more about it in our blog here. In this blog, we will go through the details of how Kubernetes and Docker Swarm differ from each other and how to choose the right tool for you.
As more and more applications became cloud-native, containers became the ubiquitous way to bring flexibility and scalability to the system. As applications gained more and more functionality, it became essential to have an automated system for container management.  A system that creates, manages, and destroys containers as the traffic requirements change. This is called Container Orchestration. Kubernetes is the leading container orchestration tool in the cloud infrastructure today. It gives a level of abstraction over containers on a cloud infrastructure and groups them into logical units for easier management and discovery.
According to a 2021 CNCF survey, 96% of all companies surveyed are either using or evaluating Kubernetes in their infrastructure. As you get comfortable using containers for your software deployment (read more about containers in our ultimate guide), you will soon require a tool to manage container deployments and configuration dynamically. This is where Kubernetes comes into the picture. Kubernetes is one of the most popular container orchestration tools. As the CTO for CNCF says, Kubernetes has now become utterly…
Software development in the last decade has largely moved from a monolithic architecture to a microservices-based architecture. The adoption of cloud platforms accelerated that transition to microservices architecture. But what does it really mean? Why did that happen, and which architecture is best for your development project? How does microservices architecture tie in with containers and cloud setups?
Storage is one of the most important aspects to take care of while dealing with containers in any architecture. By default, the data within the container is destroyed with the container. This makes it difficult for other containers to access the data and carry the process forward. In architectures of scale, container orchestration is internalized by tools like Kubernetes and Docker. This means that multiple containers are created, managed, and destroyed within the same workflow.
Most containerized applications need some form of communication with other network devices and applications. This is where container networking concepts play an important role. In this blog, we will tell you everything you need to know about container networking and how to get started on it.
Docker desktop gives you a straightforward way to use any Docker image and run a container.  You can choose to use any image. To start with, we advise you to take an image from Docker Hub. As discussed in the previous blog, Docker Hub is a public repository of Docker images that are verified by
In 2013, Docker revolutionized the virtualization space with Docker Engine. Containerization became more mainstream, and Docker became ubiquitous to containers. With Docker, developers could standardize the environments for their applications to work in. These standardizations made way for smoother deployments and faster time to market. In this blog, we tell you everything you need to get started with Docker. This is part of our extensive series of blogs on Containers. 
The virtualization world has seen a sea change in the last 10 years. For a long time, Virtual Machines ruled the virtualization world. But ever since Docker Engine was launched in 2013, containers have become the go-to virtualization method for developers. Over time, the software development process has now shifted from a blame game of “it-works-on-my-machine” to smooth deployment of software systems performed 1000s of times every day. 
Containers are self-sufficient software packages that can run the service being agnostic to the underlying environment. It would contain everything from binaries to dependent libraries to configuration files. This makes containers easy to port. Since containers do not have operating system images, they are lightweight compared to Virtual Machines. 
Containers have become near ubiquitous in today’s IT infrastructure. A 2020 survey showed 89% of companies agreeing that Containers will play a strategic role for them in the near future. This pace has only increased with the Covid-19 pandemic. By 2022, many more companies have adopted cloud technologies and containerization as their key strategic play.