SUSE Previews Observability Platform Integrated With Rancher Management Framework
SUSE at the KubeCon + CloudNativeCon 2024 conference today announced it is providing early access to an observability platform designed specifically for Kubernetes clusters that are being managed by its Rancher platform.
SUSE Cloud Observability is a software-as-a-service (SaaS) platform that provides visibility across multiple cloud computing environments, including Amazon Web Services (AWS), Google Cloud and Microsoft Azure to enable IT teams to detect issues using data collected in real-time from OpenTelemetry agent software and instances of extended Berkely Packet Filtering (eBPF) technologies. It includes more than 40 pre-configured dashboards to provide a complete view of the Kubernetes environment.
Andreas Prins, vice president of observability at SUSE, said those capabilities are critical because Kubernetes telemetry data needs to be shaped in a way that surfaces actual actionable insights.
Additionally, IT teams will be able to also run historical analyses of those environments using graph technologies that SUSE is embedding in the platform.
The goal is to make it simpler for IT teams to collect the telemetry data needed to optimize Kubernetes environments, said Prins.
In general, IT organizations are investing more in observability as cloud-native applications make IT environments more challenging to manage. A Techstrong Research survey finds that 63% work for organizations that will be making additional investments in observability over the next two years, with 21% describing those investments as significant. Nearly half (48%) work for organizations that already practice observability regularly. At the same time, roughly 60% work for organizations that are making significant investments in container and orchestration technologies over the next two years. Well over half of respondents work for organizations that have already deployed cloud-native applications in a production environment, with another 22% now evaluating whether to follow suit, the survey finds.
While observability has always been a core tenet of any set of best DevOps practices, software engineering teams are moving beyond simply tracking a set of pre-defined metrics. Modern observability platforms make it possible to analyze the logs, metrics and traces created by an application environment in a way that enables DevOps to launch queries to help identify the root cause of an application performance issue. That’s especially critical in cloud-native application environments where the microservices that make up an application often have multiple hidden dependencies.
The challenge, as always, is finding the funding for observability initiatives and then convincing software engineers to rely less on existing monitoring tools that track a pre-defined set of metrics. Reducing the need for those tools is often critical to help justify the investment in a modern observability platform.
Hopefully, IT environments with the rise of AI will soon be less challenging to manage. However, in the absence of a rich set of telemetry data to train an AI model, IT teams will find the overall effectiveness of any given AI platform to be limited. In effect, observability platforms are essentially a pre-requisite for employing AI, to not just manage applications at scale, but also reduce the total cost of IT.
