The latest News and Information on Containers, Kubernetes, Docker and related technologies.
Nowadays, it is rather common to see companies adopt several monitoring solutions based on Prometheus, but this is not exempt from pain. A huge number of systems, applications, and third-party software are not instrumented to expose Prometheus metrics natively. Here is where Prometheus exporters come into play.
You'll notice that monitoring and logging don't appear on the list of core Kubernetes features. However, this is not due to the fact that Kubernetes does not offer any sort of logging or monitoring functionality at all. It does, but it’s complicated. Kubernetes’ kubectl tells us all about the status of the different objects in a cluster and creates logs for certain types of files. But ideally speaking, you won't find a native logging solution embedded in Kubernetes.
Content The Sysdig 2023 Cloud-Native Security and Container Usage Report has shed some light on how organizations are managing their cloud environments. Based on real-world customers, the report is a snapshot of the state of cloud-native in 2023, aggregating data from billions of containers.
As the world’s leading local delivery platform, Delivery Hero brings groceries and household goods to customers in more than 70 countries. Their technology stack comprises over 200 services across 20 Kubernetes clusters running on Amazon EKS. This cloud-based, containerized infrastructure enabled them to scale their operation to support increasing demand as the volume of orders placed on their platform doubled during the pandemic.
By kickstarting a monitoring project with Prometheus, you might realize that you get an initial set of out-of-the-box metrics with just Node Exporter and Kube State Metrics. But, this will only get you so far since you will just be performing black box monitoring. How can you go to the next level and observe what’s beyond? They are an essential part of the day-to-day monitoring of cloud-native systems, as they provide an additional dimension to the business and app level.
Since the very first version, Epinio has made use of an internal S3 endpoint to store the user’s projects in the form of aggregated tarballs. Those objects are then downloaded and staged by the internal engine’s pipeline and, finally, they are deployed into the Kubernetes cluster as consumable applications. Epinio makes use of S3 as an internal private service. In this scenario, S3 can be thought of as an internal ephemeral cache with the purpose of storing temporary objects.
