10 best practices to achieve Kubernetes resilience for enterprises

Resilience has more than one meaning, but the one we typically think of is the capability to withstand a crisis when it strikes and be equipped to face higher challenges. Building and adopting resilient technological solutions is the need of today's modern businesses. An enterprise fortified with resilience is well-equipped to face any unforeseen disruptions, mitigate damages, recover quickly, and reduce incident management costs. In this blog, we'll explore why an enterprise needs resilience with a real-life example and the strategies that can be adopted to achieve resilience.

Why is enterprise resilience needed?

A study by Cisco states that by 2030, 500 billion devices will be connected to the internet, and 5.35 billion people in the world already use the internet. As demand for more advanced technological solutions that surpass their predecessors grows day by day, businesses have no other choice but to adapt to fast-paced advancements, particularly in IoT technology, and upgrade to provide better services and solutions.  

Every organization struggles to increase revenue and profits. In this race, they are likely to encounter technical mishaps and stagnancy at some point in time. No enterprise is devoid of such technological issues. 

The credibility and reliability of an organization solely depend upon the service and support it provides, which should also be consistent. Needs vary from customer to customer, and retaining a faithful base is challenging. We say "challenging" because ensuring uninterrupted services for customers, especially during peak times and sudden surges, can be tricky. Cost management and profit retention are also crucial. The solution is the adoption of resilient technology. 

As Kubernetes has greatly simplified microservices deployments and management, it is now the leading container orchestration platform widely used by enterprises. Sixty-one percent of organizations were already using Kubernetes in 2022. It is now the pioneer in steering the ship of containerized orchestration. And so, in this article, we are focusing on enterprises that employ Kubernetes for their application deployment. 

A crash that led to the journey towards resilience 
Here is a real-life scenario of a banking enterprise that understands the importance of resilience after experiencing an outage. 

A successful banking enterprise with more than 30 million users has been running its banking application in a Kubernetes environment. Everything was going well until there was a sudden spike in the number of transactions. The servers were running hot, and suddenly, the application crashed like never before. The IT team was working very hard to find out the root cause—with their applications running on more than 500 clusters, multiple nodes, and numerous pods, the issue wasn't fixed for some time, and this proved to be a heavy blow. 

The number of users and transactions decreased gradually. Regular customers expressed their discontent and were unsure about utilizing the applications for significant transactions. It took months to regain the trust and satisfaction of customers. That one day taught a life-changing lesson to the organization. 

All the IT admins, DevOps teams, and managers were looking for a preventive strategy that was reliable, easy to adopt, and could help identify the root cause of the issue through complete observability. Finally, they arrived at the ultimate solution: Kubernetes observability, which could track the metrics, traces, and logs of their clusters, nodes, and pods. The key requirements included tracking CPU, memory, and network utilization at the cluster, node, and pod levels as well as tracing and logging all events. They chose Site24x7's Kubernetes observability and monitoring tool to become resilient to potential outages and crashes. All their resources were added for monitoring, and they created custom dashboards based on their specific needs. 

From then on, the enterprise was able to avoid bottlenecks and downtime, and Site24x7 sent alerts when set thresholds were breached due to a sudden surge or when any anomaly was detected. The enterprise was also able to plan its load balance with capacity planning and assign workloads with the help of forecasting analysis. Thus, it was able to retain the trust and loyalty of its customers and continue to serve them with added agility and confidence in the IT setup.

This is just one example, but we have encountered many different IT monitoring requirements. At the end of the day, whatever industry is concerned, if it uses technology—for IT operations specifically—this is the clarion call: Build resilient technology that is resistant to disruption. 

Kubernetes resilience

Kubernetes resilience is more oriented towards maintaining the functionality and availability of the overall Kubernetes infrastructure, even when encountering various challenges or failures. It is crucial to have efficient monitoring and alerting systems in place to ensure the resilience of Kubernetes. By consistently monitoring the health of a cluster, the usage of resources, and the performance of applications, organizations can promptly identify problems and take proactive actions to avoid any downtime.

Below, we have listed a few strategies that will help you achieve Kubernetes resilience through efficient monitoring and prevent and overcome mishaps as soon as possible.

10 best practices for monitoring Kubernetes 

1. Automatic service discovery:

Modern cloud-native infrastructures like Kubernetes employ microservices that are used to create, deploy, run, and manage applications, which is a continual process. Various components collaborate and contribute to make the applications work and accomplish a job. Whenever a new service or workload is added to the infrastructure, it's tiring to add each service one by one for monitoring. Two services a day may be easy to add, provided you have a dedicated engineer assigned to do so. Plainly, this will directly affect your productivity. 

If you wish to install a tool, forget about it, and let the tool do the monitoring, add services for monitoring, and send an alert if there is an anomaly, you need a monitoring tool that has an automatic service discovery feature. Auto-service-discovery is a boon that will help reduce manual labor and save time and money. When services are auto-discovered, they will be automatically added for monitoring. This is one of the top-favored and essential practices to achieve Kubernetes resilience.

2. Full-stack Kubernetes observability:

The world, at large, is progressing steadily towards AIOps and automating everything. Crisis analysis and root cause detection are getting trickier with all these advancements. A Kubernetes monitoring tool that supports full-stack observability is all you need to achieve resilience and cater to the growing needs of complex infrastructure. By observability, we mean understanding the A to Z of your infrastructure, comprising all the smaller and larger components—an analysis of telemetry data for data-driven decision-making. Simply put, you need full knowledge of metrics, traces, and logs. Also ensure that the Kubernetes monitoring tool supports hybrid cloud environments and third-party integrations for unflinching collaboration.

3. Monitoring key performance metrics:

Metrics, metrics, metrics! Metrics are all you need to have a good grasp on what actually happens in your infrastructure. We have captured a list of metrics at the cluster, node, and pod levels that you should monitor to ensure resource availability and optimization. Some of them include cluster-level pod monitoring; CPU, memory, and disk utilization; resident set size memory; pods consuming high CPU and memory; the reason a container was terminated; deployments based on unavailable pods; DaemonSets based on misscheduled Daemon pods; and DaemonSets based on ready replicas. 

These metrics are the key performance indicators that help you identify, analyze, and fix issues. These indicators point out the health status of your entire infrastructure. Be informed that there are multiple-level metrics, beginning with clusters all the way through containers. The more insight you get, the more resilient your business becomes.

4. Tracking traces across applications:

If there is an issue in any of the applications you are running, it can be overwhelming to spot where it went wrong. Tracking the transaction traces will aid in spotting the source of the problem, aka, the root cause of the issue, and show you how a negligible error can lead to a chain reaction affecting other components. Tracing plays an integral role in observing and debugging applications running on Kubernetes. It is imperative for developers to trace performance, identify obstacles, and troubleshoot problems. To achieve effective tracing, it is necessary to utilize a distributed tracing tool. These tools provide a comprehensive view of the request flow and offer detailed information about components, services, and any encountered errors. 

5. Kubernetes alerting and logging:

Among all the other capabilities, having real-time alerting when something is about to get out of hand is critical for any business, be it small-scale or an enterprise. Kubernetes logs and effective log management have helped enterprises spot negligible errors, troubleshoot promptly, and avoid node-pod failures and downtime that will eventually affect the health of the cluster. Logs provide granular-level insight into applications. Collecting and managing the logs will help you record events, analyze issues, secure operations, and investigate deviations at all stages of an operation. This entails capturing and analyzing a spectrum of log types, including pod logs, audit logs, event logs, and application logs. Using different operators in query language aids in eliminating invalid values, and configuring log-based alerts will help notify you about critical events in advance.

6. A security-first approach:

Securing the data and the infrastructure is the foremost concern of every business. Choosing a reliable Kubernetes monitoring tool helps in predicting the health trend of a cluster and its components. Prevention is always better than a cure. Analyzing performance trends is far better than fixing a disaster. Forecasting reports and intelligent alerts help prevent crashes and bottlenecks. Keeping an eye on file integrity and node-level configuration checks helps avoid major calamities. Without adequate security measures, malicious actors could exploit vulnerabilities to gain unauthorized access to these resources, potentially compromising the entire cluster. So, it is essential to detect anomalous behavior or potential security breaches within Kubernetes clusters. 

By monitoring audit logs, network traffic, and other security-related metrics, you can identify suspicious activity and respond quickly to mitigate potential threats. Configuration-level monitoring, security policy insights, event analysis through logs, and tracking the certificates of applications are also not to be overlooked. By prioritizing security in monitoring practices, organizations can maintain the integrity, confidentiality, and availability of their Kubernetes environments.

7. Integration compatibility:

Every organization has its own preference for third-party collaboration tools. Communication is crucial for software development, testing, deployment, servicing, support, management, and every other workflow. An ideal observability tool should be compatible with multiple third-party integrations so that the business collaboration thrives and its continuity stays untainted. Whichever tools your organization uses, the monitoring tool should integrate with all other major tools for communication, collaboration, and analytics, ensuring your organization's workflows are uninterrupted and it is easy for your teams to collaborate and receive alerts. Ensure that your monitoring tool supports other popularly used ones, such as Jira, Slack, Zapier, Microsoft Teams, Amazon EventBridge, ManageEngine ServiceDesk Plus, and Zendesk.

8. Support for hybrid ecosystems:

Compatibility with the different deployment environments is another fundamental feature to look for. Ensure that the tool you choose supports Kubernetes monitoring in diverse ecosystems, including in Amazon, Azure, Google, and on-premises environments. Extended monitoring support for in-demand environments like Azure Kubernetes Engine, AWS Elastic Kubernetes Service, AWS Fargate, Google Kubernetes Engine, RedHat Openshift, and others including Kind, MicroK8s, K3s, and self-managed clusters is an added advantage.

9. Scalability:

A scalable and expandable Kubernetes monitoring tool can withstand the test of time and over-expanding needs. This is an added advantage of using cloud-based tools. A scalable monitoring tool ensures optimal resource utilization by efficiently allocating monitoring resources based on workload requirements. It should be equipped to adapt to changes in the Kubernetes cluster's size and configuration, ensuring that resources are neither underutilized nor overprovisioned. The tool should empower organizations to thrive by helping them foresee and maintain consistent performance levels even during peak usage periods or when the Kubernetes cluster experiences sudden spikes in workload. 

Insightful dashboards with real-time data and comprehensive reports with historical insights into system performance, trends, and patterns over extended periods can help you comprehend any impactful scenario. Thus, businesses can guarantee 24/7 availability and effective utilization of pods, individual containers, and namespaces. We stress this because a dynamic, arbitrary, and scalable Kubernetes environment can only be tracked by a scalable monitoring solution provider that provides end-to-end visibility, beginning with cluster-level insights to pod-level insights.

10. Chaos engineering:

Inevitable failures, even in robust platforms, necessitate a visionary approach to production outages. Chaos engineering is the approach of designing and executing controlled disruptions to pinpoint weaknesses and improve resilience proactively. Implementing chaos engineering in a Kubernetes environment helps simulate real-world failure scenarios and assess the overall response. It facilitates a plunging understanding of system and application vulnerabilities, leading to more resilient configurations. 

In the case of Kubernetes, chaos engineering builds confidence in a Kubernetes environment's resilience by conducting controlled experiments to simulate various failure scenarios, like cluster failure, pod evictions, too much resource utilization, too much memory and network consumption, or cluster instability. This is done by executing experiments in the Kubernetes cluster according to predefined scenarios and monitoring the system's behavior during the chaos injection phase to observe any disruptions, performance degradation, or unexpected outcomes. By testing these chaotic experiments, organizations can validate assumptions, identify weaknesses, and refine their resilience strategies.
To wrap up

Regardless of the complexities, you can foster resilience in your enterprise by choosing the right observability tool. By incorporating these practices, and with the assistance of an observability and monitoring solution like Site24x7, you can guarantee resilience at every point. 

Site24x7 provides an all-in-one observability platform with end-to-end visibility into all your clusters, nodes, pods, and workloads. The solution tracks metrics, traces, and logs, depicted through insightful dashboards and in-depth reports, automates remedial actions before something gets out of hand, aids in capacity planning, performs AI-driven forecasting and alerting, hosts multiple third-party integrations, and has cost management capabilities, along with everything else you need. And the best part is you can shrink your observability costs by 50% with this all-in-one solution. 

We hope you found these tips and suggestions useful—kudos to you for implementing resilient practices and building a fortified enterprise!

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