New devops tool industrializes Kubernetes deployments accross multiple clouds
Increased adoption of containers use in production and Kubernetes orchestration matches equally growing DevOps frustration, especially in multi cloud environments partly barred by cloud lock in. A new DevOps tool designed to abstract infrastructure stack lifecycle management shortcuts Kubernetes learning curves through accelerated adoption of Infrastructure-as-Code.
Increased Kubernetes adoption, from opportunity to frustration
With containers production usage on the rise, Kubernetes is becoming the first-choice orchestrator, even considered a Cloud OS by some (though definitely a framework), fueling a very lively ecosystem on the way. While delivering an invaluable service to DevOps teams, facilitating the deployment of microservices and containers at cluster scale to production environments, many agree on the fact that the learning curve to mastering Kubernetes is a very steep one, and turns into an even harsher experience in multi-cloud environments.
Prone to sharing their frustration on social media, developers even started creating "memes" to illustrate their difficulties on their journey to Kubernetes implementation, or compile fails to share their poor experience, like the infamous "Kubernetes Failure Stories"
Multi-cloud benefits limited by cloud lock-in
Cloud Vendors lock-in is a reality fueled by countless technical details on both data, applications and infrastructure, seriously impacting resources of teams trying to leverage multi-cloud opportunities. Indeed, Kubernetes deployments imply different implementations for each public cloud with renewed learning time, risks and difficulties for each.
With a whooping 63% of IaaS users now deploying to multiple clouds, multi-vendor public Cloud is a standard, often pushed by DevOps looking for the best solutions for their projects. But deploying Kubernetes clusters (even managed ones like EKS), on AWS does not make them automatically skilled enough to do the same on Microsoft Azure or GCP. Multiplying year-long learning curves to get the most of each Cloud specificity does not go together with immediate needs and project delivery deadlines.
CloudSkiff : A new tool, to cut learning curves across multiple Clouds
CloudSkiff builds upon the belief that developers and teams should be able to choose their cloud provider depending on their project needs and the added value delivered by the cloud provider on this specific need, and decided to tackle this issue with a new DevOps tool to help them launch production ready Infrastructure-as-Code, and deploy managed Kubernetes Clusters like EKS, AKS and GKE with Terraform.
Empowering DevOps, CloudSkiff helps them accelerate the Kubernetes learning curve and time to value via infrastructure automation. CloudSkiff industrializes Kubernetes deployment by managing the lifecycle of infrastructure stack with clean Infrastructure-as-Code, so that DevOps can focus on building and running their apps.
The SaaS platform is based on Terraform (Hashicorp) to deploy and configure managed Kubernetes clusters across AWS, Azure and GCP. It will also provide additional workflow and governance tools for teams. V1 launch is planned in December 2019.
CloudSkiff is being built by a team of seasoned entrepreneurs :
Stephane Jourdan: Strong Experience in infrastructure automation with 15+ years experience building/maintaining complex Infrastructures for blue chips and startups. Author of the Book "Infrastructure-as-code”
Eric Mahé: Repeat entrepreneur in Enterprise Software. Co-Founder of RunMyProcess (acquired by Fujitsu in 2013). CIO
of Netsize (acquired by Gemalto). Partner at Axeleo, Mentor at Wilco Startup accelerator.
Gerald Crescione : Repeat entrepreneur with a focus on Marketing and startup launch. Repeat entrepreneur. Co-Founder and COO
at Startup Maker (Startup Studio).
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