Operations | Monitoring | ITSM | DevOps | Cloud

Innovation in hypervisor technology in the early 2000’s from both commercial and open source projects was the genesis for the public cloud as we know it today. Virtualization and Moore’s law, together with advances in storage technology, mobile and wireless, created a data explosion that continues to accelerate through today.

Shipa (https://www.shipa.io), the full lifecycle application-centric framework for Kubernetes and multi-cluster portability, just got better! Version 1.2 is now available, and we are excited to share these key new features and improvements with the Shipa community.

SolarWinds® Pingdom® is an external synthetic monitoring agent designed to monitor your systems from the outside in. If you know what clues to look for, it can provide a great place to triage where a problem is occurring in the system. So how does a Pingdom call work, and how can you use it to debug what’s happening inside the system?

So SolarWinds® Pingdom® has alerted you to an issue—what do you do now? In this article, I’ll explain the features and capabilities of a full monitoring stack in SolarWinds and how you can use it to get to the bottom of a 3 a.m. Pingdom wake-up call. The Setup For our web service, we use a simple architecture of a front-end Flask application with a Postgres back end served behind an edge SSL-terminating NGINX instance on the DigitalOcean Managed Kubernetes service.

Shipa’s application management framework, integrated into OKE, provides an out-of-the-box way for organizations to build, deploy and operate the full life-cycle of Kubernetes applications. With Shipa and OKE, organizations can make up for lost time and start getting value out of Kubernetes immediately. In this webcast, you will learn how Shipa and OKE.

As cloud infrastructure grows and develops, reliable and safe management of containers across multiple cloud providers grows increasingly important - accelerating the adoption of Kubernetes (K8s). Orchestration technologies like Kubernetes (K8s) automate the deployment and scaling of containers, and they also ensure the reliability of applications and workloads running on containers.