Operations | Monitoring | ITSM | DevOps | Cloud

One Line Developer Experience - Terraform, ArgoCD, Crossplane, and Shipa

As we kick off the new year and our release of Shipa 1.5.0, dabbling in the art of the possible, what if it was possible to provide your developers with a single line of configuration to get their ideas into production. Shipa is an application and policy abstraction layer which easily integrates with your DevOps toolchains. In this example, we will show what platform engineering or DevOps teams can create to allow for development teams to only have to make a change to a singular line of YAML to get their ideas into production.

4 Strategies for Modernizing your Business Applications

Today, organizations across sectors are driving relentless efforts in migrating to cloud platforms. But the presence of heavy, legacy enterprise systems makes the journey towards cloud extremely challenging. These complex systems are not only deprived of the security needed to operate in today’s business world, but the absence of integration capabilities also make them an extreme misfit in a cloud-friendly world.

Chaos & Order: Breaking and Fixing Things in K8s Environments With Komodor & Gremlin

You can’t build a CI/CD pipeline and support fast-paced development cycles without considering continuous reliability. On the one hand, this means being rehearsed and prepared for every scenario. On the other, this calls for a contingency plan for when (inevitably) something will go wrong. Join this live event and see how DevOps tools can help you plan for the best and prepare for the worst, as Julie from Gremlin injects chaos into the Bank of Anthos’ system and Rona from Komodor troubleshoots things back into order.

2021 Kubernetes on Big Data Report: Data Management | Pepperdata

Get the Pepperdata 2021 Kubernetes on Big Data report and start your journey of better understanding how your competitors are managing their data with Kubernetes. Cloud vendors have proliferated and promised users optimal performance and tight spend. Still, many of these vendors don't provide visibility into Kubernetes big data, resulting in performance issues, poor resource allocation, overspending, and ineffective tuning. To fully optimize your Kubernetes big data, maximize performance, and reduce spend, you need to step beyond the basic K8s measurements and look at app performance.