Microservices architecture is getting adopted extensively in the world of distributed applications. There are various options and frameworks available to implement the Micro Services, e.g., Azure Service Fabric, Azure Kubernetes Services, Azure Functions, etc. The hottest trend these days seems to be serverless. The promise of consumption-based pricing, where you only pay for what you use and nothing more, is enticing.

System downtime is a part of the IT infrastructure. Very often, the system goes into a snag or downtime involving an unplanned stoppage of operations. More often than not, this is a direct result of a lack of appropriate maintenance. However, the smallest of downtimes can lead to heavy business and financial losses within the company. Hence, the idea is to conduct maintenance tasks and operate the IT infrastructure to reduce potential downtimes.

In keeping with our vision of offering a universal feature set across all the package formats we support, we are delighted to announce that we are now offering configurable upstream proxying and caching support for RedHat packages. As we touched upon when announcing the same for Debian and Maven packages, there are a lot of reasons why this is a really good thing, so instead of going over those again, let’s jump straight into how you can set this up in you Cloudsmith repository.

As the world collectively evaluates the return to work and shift to remote operations, digitally transformed enterprises are coming out faring better in this transition. This shift is aided by the work developers are putting in to create applications that better their organizations, and they need to continually adopt modern DevOps best practices to increase application delivery velocity and quality in order to stay nimble.

When we talk about the reliability of services, SRE encourages us to take a holistic view. Unreliability in service delivery can be due to anything, from hardware malfunctions to errors in code. One source of unreliability that is often overlooked is security. A security breach can damage customer trust far beyond the impact of the breach itself. Even smaller infractions, like failing a service audit, can make users wary.

In the previous article, we have created the Continuous Integration (CI) pipeline for a simple Java application. It is now time to start working on the Continuous Deployment (CD) pipeline that will take the Java application and deploy it to AWS. To build the CD pipeline, we will extend the existing AWS Jenkins pipeline. If you have missed the previous article on building a CI pipeline for a Java application using Jenkins, make sure you read that first before continuing.

Do you need to integrate a new company in with your existing employer and therefore in to your already provisioned Azure AD tenant. Or perhaps just need to share your tenancy and office 365 services with more than one company, then you could find yourself in a position where you need to sync users from another domain and have already configured AD Connect, well there is a way to add the second domain to your current Azure tenancy, so you can sync those users from the second domain.

If there’s no customer, there’s no job. In a competitive marketplace, every site element matters from the functionality of your service to your UI; your documentation to your marketing. Your SLA should mirror that structure. Building a strong customer experience is about consistency on every level. The key is visibility, offering all the verification your customers need with an intuitive click of the mouse.

There are many articles and videos about practicing Continuous Delivery (CD) with applications, but not nearly as many for infrastructure. The same can be said for GitOps applied to infrastructure. That is a bit strange given that applications and infrastructure are almost the same today. Both are defined as code, and everyone stores code in Git repositories. Hence, GitOps is just as good of a fit for infrastructure as for anything else.