Operations | Monitoring | ITSM | DevOps | Cloud

With over 58K stars on GitHub and over 2,200 contributors across the globe, Kubernetes is the de facto standard for container orchestration. While solving some of the key challenges involved in running distributed microservices, it has also introduced some new ones. Not surprisingly, when asked, engineers list monitoring as one of the main obstacles for adopting Kubernetes. After all, monitoring distributed environments has never been easy and Kubernetes adds additional complexity.

We’ve all experienced it – executives with unrealistic expectations who vastly underestimate the amount of time our work can take. Most of us assume that to be the exception and not the norm. But when it comes to monitoring and troubleshooting, that seems to be the all too commonplace.

ELK and Kubernetes are used in the same sentence usually in the context of describing a monitoring stack. ELK integrates natively with Kubernetes and is a popular open-source solution for collecting, storing and analyzing Kubernetes telemetry data. However, ELK and Kubernetes are increasingly being used in another context — that of a method for deploying and managing the former.

Kubernetes is THE buzzword these days. Almost every IT organization is currently using it or is in the process of implementing it as part of their infrastructure. The transition to Kubernetes is complicated, whether a company is using an on-premises, cloud, hybrid, or managed solution, and it usually involves other changes in the codebase, such as shifting to a microservices architecture. While the implementation phase is led by the DevOps team, it requires the participation of the whole R&D group.

Kubernetes is one of the most advanced orchestration tools that currently exists in the software world. It provides out-of-the-box automation for environment maintenance and simplifies deployment and upgrade processes. It has different implementation types (on-premise, cloud-managed, hybrid, and more), multiple open-source supporting tools, and supports a wide range of configuration options.

Monitoring systems gather and log a wide range of performance data on a diverse range of targets—from applications to user experience, networks, servers, and more. Usually, monitoring is conducted under runtime conditions, but synthetic monitoring can also be used to simulate loads and test the resilience of web services, for example.

Complex problems can often be solved with simple, practical solutions. That’s what our team at Kenshoo discovered when we realized that we needed a way to easily and proactively track specific log messages which indicate mission-critical events.