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Tackle Application Infrastructure Sprawl with Cribl Edge: Kubernetes Data Collection Made Easy

September 10, 2024
Written by
Judith Silverberg-Rajna's Image

Judith spearheads product marketing for Cribl Edge and our partners. With extensive exper... Read Moreience in data platforms and artificial intelligence, she is passionate about addressing the challenges of big data, utilizing Cribl products to solve the most complex issues. A proud alumna of UC Berkeley, Judith holds a degree in economics and carries the ‘Go Bears’ spirit in all her work! Read Less

Categories: Cribl Edge, Learn

As more and more applications are delivered daily, it’s becoming increasingly difficult for teams to onboard and manage them manually. To keep up with this demand, many teams are embracing automation in application delivery and management, with Kubernetes being a popular tool of choice. While Kubernetes’ scalability helps manage application infrastructure sprawl, there is still a need to collect data from the applications directly and from Kubernetes to monitor the growing beast itself!

Collecting data from Kubernetes is critical for many reasons. First and foremost, it’s essential for application monitoring to identify performance issues and manage resource usage. The data can also be used for capacity planning by monitoring resource utilization. And, of course, there’s security—the star of the show! This data helps detect unusual activity and log patterns, which is crucial for maintaining a secure environment. Finally, we can’t overlook Kubernetes events, often undervalued yet vital for troubleshooting and detecting issues within your Kubernetes environment.

However, capturing data in Kubernetes environments is challenging. Kubernetes deployments can scale to thousands of containers, making monitoring at scale time-consuming. Many solutions are not designed for sprawling environments; they lack scalability and centralized management tools for efficient deployment and upgrades. Moreover, tracking and troubleshooting infrastructure performance is difficult due to the dynamic nature of Kubernetes. Most agents lack the ease of use and flexibility needed to adapt to these changes. Additionally, the lack of standard formatting, combined with the expertise required to configure other tools, makes integrating data into analytics platforms cumbersome. Teams need a solution that can effectively handle the volume, variety, and ephemeral nature of Kubernetes environments.

This is where Cribl Edge comes in! Cribl Edge is a vendor-neutral, intelligent agent designed specifically for the variety and scale of today’s modern architectures, including being purpose-built for Kubernetes. With its flexible edge-based data collection system, you can efficiently gather endpoint data in real-time from your Windows, Linux, or Kubernetes environments and deliver it wherever it needs to go—whether to Cribl Stream for further processing or directly to your chosen destination. Cribl Edge allows you to explore data at its egress point and quickly troubleshoot nodes using a rich interactive UI and autodiscovery. Offering centralized management for quick deployment, easy configurations, and time-saving upgrades, Cribl Edge enables you to save significant time and resources, allowing your team to focus on strategic priorities.

Get Started Quickly With a Painless Deployment

Managing the complexities of deploying and configuring agents to monitor your expansive Kubernetes environment can be a daunting and time-consuming task. However, with Cribl Edge, you can eliminate these challenges by achieving streamlined and simplified visibility in record time. Cribl Edge offers a powerful yet easy deployment solution using pre-packaged Helm charts, providing a fast, repeatable, and consistent way of deploying and upgrading the Cribl Edge environment. These Helm charts contain the minimum configuration required for installation and have been tested across multiple Kubernetes platforms on several cloud service providers. You can bootstrap a new Edge Node in your Kubernetes Fleet using the Helm chart script found in Cribl UI. This efficient deployment method accelerates your initial setup and ensures that scaling your monitoring capabilities as your environment grows is seamless, addressing the ever-expanding demands of modern application infrastructures.

Reduce Overhead Through Centralized Management

Cribl Edge revolutionizes the agent user experience with its modern, centralized management and monitoring console, featuring an intuitive interface that simplifies the entire process. With real-time change validation and visual configuration authoring, you can easily design and deploy configurations confidently. One of the standout features of Cribl Edge is its Fleet Management capability, which allows you to logically group Edge nodes into fleets, enabling you to configure and manage them as a single unit. This means you can say goodbye to the tedious task of manually updating hosts individually. Instead, you can now update hundreds of thousands of nodes at once with just a few clicks, dramatically improving efficiency and reducing the margin for error.

Gain Access Like Never Before and Leave No Data Behind

With Cribl Edge’s innovative Kubelet API approach, you can instantly find and retrieve Kubernetes logs without needing access first, significantly reducing time-to-value. This streamlined process allows you to access logs directly from containers effortlessly, eliminating the hassle of dealing with varying data formats. By removing these barriers, Cribl Edge ensures that your team can quickly gain the insights needed to optimize.

Explore and Process With Out-of-the-box Integrations

Effectively managing large volumes of Kubernetes data can be a complex challenge, but Cribl Edge simplifies the process by allowing you to interrogate and shape data at the edge using powerful functions and pipelines before forwarding it to Cribl Stream or your preferred tool. This approach enables you to optimize and refine your data where it’s generated, ensuring only the most relevant information is sent downstream. With Cribl Edge, you can use pre-built integrations to effortlessly capture Pod logs, generate Kube State Metrics (KSM), retrieve and enrich Kubernetes events, and scrape data from Prometheus endpoints. Additionally, you can easily visualize these insights using pre-built Grafana dashboards, providing you with a comprehensive and streamlined solution for managing and understanding your Kubernetes environment.

In today’s fast-paced digital landscape, where Kubernetes environments are growing more complex and expansive by the day, a robust, scalable, and efficient data collection and monitoring solution is no longer a luxury—it’s a necessity. Cribl Edge emerges as a game-changer, purpose-built to tackle the unique challenges posed by today’s Kubernetes deployments. By offering seamless deployment, centralized management, unparalleled access to logs, and powerful integrations, Cribl Edge empowers teams to manage their Kubernetes environments more easily and efficiently than ever before. With Cribl Edge, you’re not just keeping up with the demands of your infrastructure—you’re staying ahead, ensuring that your monitoring and data collection tools are as flexible and scalable as your Kubernetes environment.

Ready to experience Cribl Edge? Get your hands dirty in our Kubernetes with Cribl Edge Sandbox, or take our free Cribl University Edge Admin course to learn more.

 


 

Cribl, the Data Engine for IT and Security, empowers organizations to transform their data strategy. Customers use Cribl’s suite of products to collect, process, route, and analyze all IT and security data, delivering the flexibility, choice, and control required to adapt to their ever-changing needs.

We offer free training, certifications, and a free tier across our products. Our community Slack features Cribl engineers, partners, and customers who can answer your questions as you get started and continue to build and evolve. We also offer a variety of hands-on Sandboxes for those interested in how companies globally leverage our products for their data challenges.

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