Operations | Monitoring | ITSM | DevOps | Cloud

We’ve all been in the situation before: it’s Friday at 5 PM and the only on-call engineer available to handle incidents is about to hit the slopes. Unfortunately, at that very moment, a customer reports to support that they are unable to access the company’s ecommerce website to complete a purchase. Internal monitoring systems seem quiet and services appear available on internal health dashboards.

As organizations are adopting more of the FinOps foundation practices and trying to optimize their cloud-computing costs, engineering plays an imperative role in that maturity. Traditional troubleshooting of applications nowadays relies heavily on static logs and legacy telemetry that developers added either when first writing their applications, or whenever they run a troubleshooting session where they lack telemetry and need to add more logs in an ad-hoc fashion.

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.