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If you're leading a team and considering implementing Kubernetes into your workflows, you rightly have plenty of questions about the process. How will it change my workflows? What kind of benefits will it bring? Where do I even start?
While these questions are all important, there's also one more worth asking: How can I avoid making mistakes during implementation that will set me back even further than where I began?
After countless implementations in this space, we've identified six major pitfalls you should look out for when setting up their Kubernetes environment - read on to find out what they are and strategies to avoid them.
Not Getting the Teams on the Same Page
Without being fully skilled in the exact nature of Kubernetes, the technology used for cloud-native systems is rendered useless. The lack of knowledgeable experts leaves some who install and maintain Kubernetes unaware of its potential, resulting in manual operations that are unable to meet the company's needs or take advantage of clustering opportunities.
It’s essential to have administrators knowledgeable in deployment proficiency and possess a deep understanding of what it takes to operate Kubernetes successfully; from familiarizing oneself with its components, monitoring it for effective performance, and understanding principles for installation and adjustment. Additionally, being well-versed in best practices for software delivery helps organizations leverage the full benefits of Kubernetes.
Also, yes, you want skilled professionals, but it is equally important to have the right processes in place in order to streamline operations. When introducing Kubernetes to a dev team, it's important discuss chances in DevOps procedures and processes that are needed to make a smooth transition. It can be tempting to keep using old operational methods while implementing new technology like Kubernetes, but both roles and responsibilities must shift if this is going to work effectively. Developers buy-in in process change is critical. Without embracing the commitment needed for effective DevOps strategies, all tools – including Kubernetes – will only become an afterthought in terms of success.
Making a Swift and Full Jump into Kubernetes
Companies are increasingly turning to Kubernetes as a unified container orchestration platform for managing their microservices. This can be an appealing and convenient approach, but it is also important to understand the potential drawbacks before making such a transition.
For example, while migrating databases over may sound like an attractive proposition on paper, there could be issues with network-attached storage delay times that make this process more complicated than expected - and even unnecessary in some cases! It's imperative to take all these things into account when thinking about using Kubernetes mobility for producing applications or managing large data sets. Those who choose to do so should ensure that their DBMS set up includes automatic Master/Slave switching and consider the effect of using network-attached storage instead of local storage - this could have implications for latency and other performance issues.
To deploy complex applications that require data storage, Persistent Volumes (PV) can be used with Kubernetes. The process requires creating a Data Storage System and appropriately configuring several things in relation to Kubernetes before use. Ultimately though, splitting an app into smaller independent components is key for transitioning from one large 'monolithic' system to its distributed alternative; freeing developers up from being weighed down by heaps of interdependency issues.
Not Managing Security Settings Upfront
When organizations move applications to Kubernetes, many mistakenly believe that simply leaving default settings unchanged will be enough to protect their cluster, apps, and data. Unfortunately, this is not the case. Far too often, teams have no knowledge of Kubernetes and fail to treat it as a legitimate infrastructure component, while administrators prioritize convenience over safety and the information security department simply presumes that an antivirus will be enough.
The good news is that there are effective ways for businesses to protect their Kubernetes-backed operations. By introducing DevOps mechanisms and switching all relevant departments to universal task-solving tools like DevSecOps pipelines, organizations can introduce automated security checks and ensure a more thorough implementation of data security tools into their existing systems.
Skipping Over Important Features
Kubernetes is an advanced application with a lifecycle that has its own unique challenges, such as adjustments and updates. Whilst it offers greater capabilities than traditional operating systems at independent servers, it still requires a deep understanding of the platform features along with a wide variety of solutions that make up the Kubernetes supporting ecosystem. Planning a roadmap of what features and third-party services you would like to leverage, and when would be the right time to implement them can be critical to your success.
For example, Kubernetes supports autoscaling, which enables the cluster to automatically adjust its resources in reaction to the increasing load. Horizontal Pod Autoscaler (HPA) and Cluster Autoscaler are critical components of orchestrating complex services and optimizing resource utilization while maintaining performance. However, you need to properly plan when you want to start using auto scaling, on what workloads, how you would like it to ideally work, and how you will measure autoscaling performance so you can continuously improve results over time.
Additionally, out-of-the-box Kubernetes requires a toolkit of third-party solutions to establish and manage a stable and productive application infrastructure successfully. You simply need to visit the Cloud Native Computing Foundation landscape to see an ecosystem of hundreds of different open-source projects and vendors that are here to help you do just that. From establishing your CI/CD pipeline, to effectively setting up application storage and networking, to monitoring system performance with observability. Below is a list of some tools to consider:
Keep in mind, third-party and open sources tools can help ensure consistent performance but they may not always guarantee issues-free operation. Implementing new solutions or upgrading versions can sometimes cause unforeseen issues once they have been introduced into your environment. This is especially true for open-source solutions (Kubernetes included). A general rule of thumb is to never implement the latest version, and let the early adopters find the bugs. However, an essential best practice is creating a test environment to get an understanding of how a new version will impact your production environments. This allows you to make any adjustments necessary for a successful push to production. So do the proper planning and take caution when first implementing any new tools or version updates to your production environments.
Expecting too much from the Managed Kubernetes
Managed Kubernetes service providers (such as AWS, GCP, and Azure) only provide a reliable orchestration layer, like master nodes, etcd, Kubernetes API etc. But to achieve the best availability customers should consider taking advantage of load balancing and replication for their workloads across multiple availability zones.
Providers are only responsible for the maintenance of their portion of the infrastructure - such as regular equipment operation and virtualization platform - while other IaaS and PaaS components are entrusted to you, the customer. It is important that users regularly assess workloads, traffic flow, and performance in order to adjust queries on time, plan capacity utilization efficiently, and enable auto-scaling when necessary.
Not starting a cost-conscious culture
As you look to benefit from the speed and agility of Kubernetes in your production environment, it’s critical that your systems are continually available to meet the load of your customers' demands. To achieve this, many simply over-provision the resource requirements they need for a given workload or service.
At first, this may seem okay, however, as your environment grows, and you add auto-scaling features, like HPA and Cluster Autoscaler, the over-provisioning leads large amounts of wasted resources, equating to extremely large cloud bills that seem to grow each and every month.
Building a culture of cost consciousness is all about driving accountability across development and DevOps teams. First, you need to understand who is spending what AND whether are they spending it wisely–a team may be within their budget limits, but still wasting a good chunk of resources. Second, you need to create a feedback loop that will help teams understand how they can improve and optmize the resources they are requesting for their Kubernetes services moving forward. Many times developers do not have a baseline for how many resources their individual services need, so they simply guess, and if nothing breaks, then why try to fix it?
Reducing cloud costs is not simply a problem that companies need to address, it is part of an ongoing journey of continuously optimizing their environment to maintain peak performance and availability of your systems at the lowest possible cost.
The benefits provided by Kubernetes make the move one of the most important technology decisions your organization will make. As teams move to adopt Kubernetes for their container orchestration tool of choice, it’s important you do the proper due diligence to mitigate and “gotcha” moments in the future. You may still hit a few bumps in the road, but if you follow this advice, your transition to Kubernetes will hopefully be a smooth one. PerfectScale can start you on that journey by providing you a free evaluation of the efficiency of your Kubernetes environment, along with recommendations to optimize your resources.
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