Due to the accelerated adoption of cloud-native technologies in the last years, organizations have boosted their ability to scale applications at high speed and deliver breakthrough innovations, organizations have exploded in their ability to scale applications at high speed and deliver breakthrough innovations. This shift has also dramatically increased the complexity of their application topology, with thousands of microservices and containers deployed, leaving IT teams with visibility gaps across the entire technology landscape. This new, highly complex environment has brought on challenges in managing availability and performance.
This explains why organizations today are prioritizing full-stack observability to achieve traceability into these dynamic and distributed cloud native technology environments. In fact, an AppDynamics report, The Journey to Observability, reveals that more than half of businesses (54 per cent) have now started the transition to full-stack observability.
To understand the performance of their applications, technologists recognize they need visibility into the entire application tier, into the supporting digital services (such as Kubernetes) and into the underlying Infrastructure-as-Code (IaC) services (ie compute, servers, databases, networking) they use from their cloud providers.
The distributed and dynamic nature of cloud-native applications makes it extremely difficult for technologists to identify the root cause of problems. Cloud native technologies, such as Kubernetes, dynamically create and terminate thousands of containerized microservices and generate a massive volume of metrics, logs and traces (MLT) telemetry every second. Many monitoring solutions do not collect the necessary detailed telemetry data, making it virtually impossible to understand and troubleshoot problems.
Importance of advanced Kubernetes observability
By leveraging the portability, isolation, and immutability provided by containers and Kubernetes, development teams can ship more features faster by simplifying application packaging and deployment—all while keeping the application highly available without downtime. And Kubernetes’ self-healing properties not only enables operations teams to ensure application reliability and hyper-scalability but also boost efficiency through increased resource utilization.
As organizations are leveraging Kubernetes technology, the footprint can expand exponentially and traditional monitoring solutions struggle to deal with this dynamic scaling. Therefore, technologists require a new generation solution that can monitor and serve these dynamic ecosystems at scale and provide real-time insights into how these elements of their virtual infrastructure are actually operating and affecting one another.
Technologists should look to achieve full-stack observability for managed Kubernetes workloads and containerized applications, with telemetry data from cloud providers for the infrastructure such as load balancer, storage and compute, additional data from the managed Kubernetes layer, grouped and analyzed with application level telemetry from OpenTelemetry.
When troubleshooting, technologists need to have the ability to quickly alert and identify the problem domain and root cause(s). To accomplish this, they need a solution that can navigate Kubernetes constructs such as clusters, hosts, namespaces, workloads and pods and their impact on the supported containerized applications running on top of them. Making sure they can get a unified view of all MLT data, be it Kubernetes events, pod status or host metrics, infrastructure data, application data or data from other supporting services.
Cloud native observability solutions are essential for organizations preparing for the next decade
Understanding the need for technologists to gain greater visibility into Kubernetes environments, technology vendors have rushed to market with proposals that promise monitoring or observability in the cloud.
Conventional approaches to availability and performance were often based on long-lived physical and virtualized infrastructures. Ten years ago, IT departments operated with a fixed number of servers and network cables: they faced fixed constants and dashboards for each layer of the IT stack. The arrival of cloud computing added a new level of complexity, and organizations continually scaled their IT usage up and down, depending on real-time business needs.
While modern monitoring solutions have adapted to accommodate growing cloud deployments alongside traditional on-premise environments, they were not designed to efficiently manage today’s dynamic and highly volatile cloud native environments.
It is important for technologists to remember that traditional and future applications are built in completely different ways and managed by different IT teams. To be efficient, they need a completely different type of technology to monitor and analyze availability and performance data.
They should look to implement a next-generation, cloud-native observability solution that is truly tailored to the needs of future applications and can scale functionality at high speed. This will allow them to eliminate complexity and provide observability in cloud-native applications and technology stacks. They need a solution that can deliver the capabilities they will need over the next 10 years that will enable them to drive the best digital experiences that will positively affect their growth.
