With enterprises and ISVs adopting containers and Kubernetes (k8s) to increase the agility and scalability of their applications, they would want more applications to be deployed on k8s. Applications can be a mix of stateful and stateless. Until recently, only stateless applications were supported by k8s. However, with the advent of persistent storage on k8s, stateful applications will be supported. In the pet Vs cattle analogy of service, you would want to treat the storage as cattle.

As we all know, the on-demand capacity mode of DynamoDB is great but can be cost-prohibitive in some cases (up to seven times more expensive than the Provisioned Capacity mode). The Provisioned mode, on the other hand, shifts to the development team the burden of predicting what level of capacity will be required by the application. And it’s not quite as straightforward to achieve the same level of scalability in the Provisioned mode as we enjoy in the On-demand one.

Amazon Web Services Elastic Load Balancer (AWS ELB) enables websites and web services to serve more requests from users by adding more servers based on need. Unhealthy ELB can cause your website to go offline or slow down dramatically. Elastic Load Balancing automatically distributes incoming application traffic across multiple Amazon EC2 instances.

As a cloud project owner, you want your environment to run smoothly and efficiently. At Google Cloud, one of the ways we help you do that is through a family of tools we call Recommenders, which leverage analytics and machine learning to automatically detect issues and present you with optimizations that you can act on.

One of the most popular cloud disaster recovery models in the industry today is the “pilot light” model where critical applications and data are in already place so that it can be quickly retrieved if needed. A simple question one must ask before adopting this model is what thought has been given to whether the AWS/GCP/Azure APIs will work and if the requisite capacity will be available in the alternate region.

The traditional method of planning server, network, and storage capacity is to look at the usage peaks and then add a safety margin. Most cloud hosting is planned this way. The idea that you only pay for what you use is not based on actual usage, rather on the capacities you initially specify. Most cloud migrations involve a ‘lift and shift’ approach of moving an application to a different host with minimal maintenance.

Google Cloud Platform (GCP), a suite of cloud computing services offered by Google, launched in 2008. It is a powerful cloud platform that offers Infrastructure as a Service (IaaS), Platform as a Service, and serverless computing environments. Many companies are now using GCP to build, modernize, and scale their businesses. GCP monitoring with Applications Manager Monitoring GCP service instances can be pretty challenging.

This post was originally published in JAXenter.com. Serverless is a relatively novel concept and cloud architectural model but has been advancing very quickly over the past 5 years. In this article, we’ve compiled a list of recent changes that are likely to shape how development teams use Serverless in practice. In this article, we’ll be heavily focussing on AWS serverless services. The cloud provider has been investing heavily in the advancement of Serverless.

At STRABAG, we are using Elastic Cloud Enterprise (ECE) for two main use cases within our on-premises web applications. One to power different kinds of search and a second for operations where we ship more than 25,000 log entries per minute to Elastic from our load balancers. The ECE platform runs in an air-gapped environment, and we would still like to be able to use our corporate logins for the ECE platform.

JFrog is pleased to announce that our comprehensive Cloud Enterprise+ plan is now available on Amazon Web Services (AWS) Marketplace through Private Offers. JFrog Cloud Enterprise+ on AWS is a universal, highly-available SaaS offering of the JFrog Platform for demanding DevSecOps at global scale.