By Bahubali Shetti, Senior Director of Observability Solutions at Elastic

Kubernetes is the fastest growing open-source project (apart from Linux) since its initial release in 2014. Its place in the essential toolkit for enterprise IT has been well-established - Kubernetes has been widely adopted across market verticals for both on-premises and cloud deployment models. But the success of container orchestration relies on the right observability.

Too often, observability observability and security security remain siloed

Historically, IT has thought about the monitoring and security of applications and infrastructure separately, each handled by separate tools managed by separate teams.

But this makes it difficult to understand the root cause of an operational issue. Is it a problem with the infrastructure? A defect in an application? Or a security breach? Far too often, IT is working on this in siloes doubling up on select observability data across multiple data platforms to understand the answers to these questions. This leads to massive inefficiencies, double or tripling the cost of data storage, support and training. And worse still, analysts are missing the holistic view they need across these domains in order to understand what's really going on.

Separating observability and security is counter-productive to the integrated service deployment that Kubernetes allows.

Automating observability's role in Kubernetes

A good observability companion ensures that you are getting the most from your Kubernetes and the data collected, allowing for full visualisation of exactly what is being captured. Businesses often collect and hoard unnecessary data, leading to poor allocation of computing resources, making it harder to tell the useful data from the useless, all while creating a greater risk in the event of a breach.

The good news is that observability can be automated too. Kubernetes can be set to push telemetry data (metrics, logs) to observability software which will process them with application telemetry (metrics, logs, and traces) providing an end-to-end picture of how the system is performing. This unified view can then not only be used to add value to the business, but also to further refine processes.

For example, observability software can help identify if Kubernetes telemetry is indicating which pods, with no business purpose, are usurping vital resources that would be better deployed elsewhere. This type of information can be used to revise operations by identifying these containers and disabling or reallocating resources for containers which do not meet the criteria.

Despite the lack of human involvement in Kubernetes there is also still room for error, most commonly as a result of issues in the supplied commands.

Three critical factors for successful observability on Kubernetes

There are three critical factors to success.

First, all observability and security data, inclusive of application, service, and infrastructure logs, traces, metrics and security events must be stored in a unified data platform in a manner which is optimized for both search (correlation and latency) and storage (cost).

Second, the unified data platform must also be capable of correlating data and presenting it in role-based fashion: for example, if an operations engineer (SRE/DevOps/IT) is trying to root cause an issue, the platform should guide them toward the likely issue, and allow them to seamlessly interact with the data without caring about its underlying form or source.

And finally, instrumenting applications and infrastructure should align with the Kubernetes mantra: repeatable, scalable deployments without bespoke configuration.

Regular observability reporting should ensure that these practices are upheld are deviations are caught in a timely manner, showing what vectors are underperforming and allowing for the identification and correction of errors.

With the right observability, comes new possibilities

There is still a lot of room for Kubernetes' continued growth and development as its use cases expand across new plugins and processes. Ultimately, that will rely on developers, operators, and security analysts alike having a unified end-to-end view of their system spanning across applications and infrastructure. Infrastructure deployment teams need a unified, Kubernetes-native deployment pattern to provide this visibility and secure their clusters.

Observability opens up the possibilities for increased efficiency, laying bare the current issues across a system and its container architectures. Companies that get this right will see an improvement not only in day-to-day operational processes but in the quality of the insight gleaned from the data collected and greater impact for the business as whole.

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To learn more about the transformative nature of cloud native applications and open source software, join us at KubeCon + CloudNativeCon Europe 2023, hosted by the Cloud Native Computing Foundation, which takes place from April 18-21.          

ABOUT THE AUTHOR

Bahubali Shetti Senior Director Observability Solutions, Elastic