Kubernetes adoption in production settings has accelerated over the past few years. As Kubernetes usage grows, there is often demand to move applications presently deployed using other methods to Kubernetes. Effectively migrating these apps to Kubernetes may assist companies in adopting DevOps techniques and in unifying their operations around a particular set of cloud tools and expertise.
However, cloud services structures vary in several ways from conventional designs. As a result, migrating a system to a cloud-native environment is not as straightforward as simply rehosting. This article discusses the fundamental tools required when it comes to deployment, management, command-line interface (CLI), monitoring, security, and troubleshooting.
Defining the Purpose Behind Your Kubernetes Migration
Thorough knowledge of the migration's objectives is critical to success. First, decide whether:
• The application should be changed to accommodate the environment's behavior or;
• The environment should be adjusted to reflect the application's behavior.
Upgrading an application that is not yet cloud-native to take advantage of cloud-native design advantages may involve significant effort. However, it is often feasible to avoid this redesign initially and work around the issues with a non-cloud-aware design.
Therefore, before beginning the migration, you should ask the following questions:
• What is the purpose of the migration?
• Is it possible to modify the application's behavior?While an unchangeable program is often very simple to migrate, it might not significantly benefit from Kubernetes.
Your Kubernetes Needs: During and After Deployment
The personnel and expertise required to support your Kubernetes configuration
You should certainly bear in mind that your IT experts and developers may be required to upgrade their expertise in Kubernetes and other cloud-native architectural technologies. This is particularly true if you decide to go all-in and host and maintain your Kubernetes clusters on your own, but is less relevant if you choose a hosted-Kubernetes configuration.
Whether to use in-house clusters or managed services
Whether you run your Kubernetes cluster or utilize a managed Kubernetes service is determined by how you answer the following questions:
• Do you have sufficient internal knowledge of Kubernetes? Kubernetes is often said to be 'easily grasped but tough to master.’ Although it is simple to grasp the fundamentals of Kubernetes, implementing it in a complicated context is beyond the capabilities of a newcomer.
• Are you aware of the potential issues associated with a solo Kubernetes deployment and how a higher purpose Kubernetes provider may assist in resolving them?
• If you want to run your Kubernetes cluster, you must purchase your infrastructure.
Migration costs and ongoing assistance
Another consideration is cost. "What cost?" you may question. "Isn't this meant to be a non-factor when I build an open-source platform?" To be honest, yes and no. Yes, there are no licensing costs associated with the software. However, there are extra unforeseen expenses such as the expense of coaching your developers and DevOps staff in order to acquire the new skills necessary to support your new Kubernetes clusters.
Another rarely considered issue is the opportunity cost of on-the-job learning, in which members of your development team exchange productivity for learning time.
Kubernetes Enterprise Tools
For Deployment: Helm
Helm is a very popular Kubernetes package manager and the equivalent of yum or apt in K8s. Helm distributes charts, which may be thought of as bundled applications. It is a set of all your application's versioned, pre-configured resources that can be delivered as a single unit. After that, you may launch a new version of the chart with a modified configuration.
It is a client/server program that, until recently, was installed in your cluster through the helm server. This is deployed during the helm installation/initialization process on your client’s computer. The helm server simply accepts client requests and installs the requested package into your cluster. Helm is comparable to RPM or DEB packages on Linux. It enables developers to package and distribute applications to end users for installation.
Once Helm is installed and configured, you may use a single helm install command to install production-ready apps from software providers such as MongoDB, MySQL, and others into your Kubernetes cluster. Additionally, uninstalling apps from your cluster is as simple as installing them.
Helm contributes in three critical ways:
• Increases productivity
• Simplifies the process of microservices deployments
• Ensures that cloud-native apps can be adapted
For Management: JAAS
JAAS stands for Juju-as-a-Service. Juju is a program that manages your software. It enables you to exert complete control over your apps, infrastructure, and environments. You can utilize it to:
• Eliminate hours of script maintenance for your team
• Reduce expenses
• Ensure redundancy and resilience
• Monitor all activities across layers
• Optimize your hybrid cloud infrastructure
You'll make a transition from configuration management to application management and have a hybrid cloud that runs workloads from apps, databases, and monitoring on Kubernetes and virtual machines.
Juju makes use of Charmed Operators ("Charms") and a Charmed Operator Lifecycle Manager to centrally manage the deployment, update, integration, administration, and operation of those workloads throughout your hybrid cloud.
Charms are tiny programs that bundle basic maintenance tasks, transforming them into repeatable and dependable code for Day 0 to Day 2. It allows your operations staff to focus on application and scenario management rather than configuration management.
You can also connect them in "models" to manage scalability, administration, and cross-service dependencies. Your application model specifies which apps offer service and how those applications communicate with one another. These Models, cross-modal relationships, and model-driven operations empower you to manage deployments and processes at scalability, across hybrid clouds, through the CLI, or via a visual interface such as the Juju GUI or JAAS.
For Kubernetes Troubleshooting: Komodor
Komodor is a troubleshooting tool that has been gaining popularity in the Kubernetes dev community. What Komodor offers is the ability to gain a full view of all changes across the entire k8s stack - and their ripple effects - to streamline the usually laborious task of understanding what went wrong, when something goes wrong.
By installing its own agent, Komodor acts as a single source of truth for all changes, pulling data from cloud providers, source controls, underlying infrastructure, DBs, CI/CD tools, monitoring tools, and incident response platforms. When an issue occurs, it notifies about it via Slack, and also provides a suggestion for how it can be fixed.
Installing Komodor requires adding its agent as a Helm chart on your cluster, which sends data with the cloud UI. There is no need to enable any ports or change your firewall's whitelist to include particular port ranges. Other integrations can be initiated directly from Komodor’s application itself.
After successful installation, your dashboard will be quickly populated with data from most recent activities.
Komodor supports Deployments, DaemonSets, and StatefulSets and integrates with many Kubernetes tools, like Sentry, LaunchDarkly, GitLab and Grafana from which it can pull data for its insights.
For Monitoring: DataDog
DataDog is a go-to enterprise monitoring platform. DataDog offers a real-time view of all activities and application configurations across Kubernetes services. One of its best features is the ability to present the data it collects in elegant and customizable charts and configure alerting criteria without managing any data or monitoring infrastructure.
With Datadog, clients can utilize integrations to pull together the infrastructure's statistics and records and can get visibility into the centralized database as a whole. Moreover, you can view individual components and the effect of individual components on the whole:
It is ideal to begin gathering metrics on your projects as soon as possible in the development process, but you may begin at any point.
• Datadog offers three different integration categories:
Agent-based integrations are deployed with the Datadog Agent and specify the metrics to gather via a Python class function called check.
• In Datadog, integrations based on authentication (crawlers) are configured, in which you give credentials for collecting metrics through the API. Among them are well-known integrations such as Slack, AWS, Azure, and PagerDuty.
• Library integrations use the Datadog API to enable you to monitor apps regardless of their programming language, such as Node.js or Python.
For Security: Aqua Security
Aqua is a great solution that approaches Kubernetes security systemically. The Aqua security toolkit comprises three main solutions, the combination of which enables Kubernetes users to guarantee the highest level of security.
The first feature is Aqua Security's threat assessment tool, called Kube-bench. This is a CIS compliance tool that analyses your Kubernetes infrastructure in depth. To do so, Kube-bench combines over 100 tests and security metrics, providing a comprehensive view of the environment's security at the end of the procedure.
The second feature is a control for image deployment, that ensures that no harmful code or spyware has been introduced into the environment. With this feature enabled, only authorized images are permitted for deployment, and the permission procedure is strictly controlled.
The third and final feature is application-level security, responsible for safeguarding the nodes and processes that operate within your Kubernetes clusters. The component is sufficiently mature to handle robust cybersecurity duties such as user access profiling, infiltration, and pattern recognition.
These components are integrated as a complete lifecycle security solution, which further enhances the security of Aqua Security's solution.
For CLI: Kubectl
You can execute commands against Kubernetes clusters using the Kubernetes command-line tool, kubectl. kubectl enables the deployment of applications, the inspection and management of cluster resources, and the viewing of logs.
Kubectl is the user interface for controlling Kubernetes. It enables you to execute any Kubernetes action.
Kubectl is a user of the Kubernetes API from a technical standpoint. This API corresponds to the authentic Kubernetes user interface and provides complete control over Kubernetes. This implies that each Kubernetes activity is accessible as an API endpoint that can be invoked through an HTTP request.
As a result, kubectl's primary responsibility is to make HTTP calls to the Kubernetes API: Kubernetes is an entirely resource-centric system that keeps an internal state of services, and all Kubernetes processes are CRUD actions on these resources. By managing these resources, you have complete control over Kubernetes. The reference to the Kubernetes API is structured as a set of resource categories and their related actions. Kubernetes comprises a collection of self-contained components that operate as distinct processes on the cluster's nodes. Specific components operate on master nodes, while others run on worker nodes, and each part performs a unique role.
Final Remarks
The use of Kubernetes in production environments has increased in recent years. As its use increases, there is often a need to migrate applications currently deployed using other techniques.
We examined several types of Kubernetes tools to ensure a smooth start. While this is just a small list of tools available for Kubernetes, each of them may help you handle containers more efficiently and with less stress.
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