GigaOm has once again placed VMware Tanzu Service Mesh within the leader ring of its Radar Report on Service Mesh. This year Tanzu Service Mesh has been upgraded to the Outperformer label, moving closer to the center and marking its heightened recognition as an industry leader. This is not only a testament to our robust enterprise capabilities and broad support for various application platforms, public clouds, and runtime environments, but also a validation of our strategic approach.

RabbitMQ is a messaging broker that helps different parts of a software application communicate with each other. Think of it as a middleman that takes care of sending and receiving messages so that everything runs smoothly. Since its release in 2007, it's gained a lot of traction for being reliable and easy to scale. It's a solid choice if you're dealing with complex systems and want to make sure data gets where it needs to go.

General Dynamics Information Technology (GDIT) is among the major systems integrators that have chosen D2iQ to create Kubernetes solutions for their U.S. military customers. I spoke with Todd Bracken, GDIT DevSecOps Capability Lead for Defense, about the reasons GDIT chose D2iQ and the types of solutions his group was creating for U.S. military modernization programs using the D2iQ Kubernetes Platform (DKP).

We kicked off the start of the Day 2 with our host Nigel Poulton as he prepared us with a quick rundown of the highlights from the first day before giving attendees a taste of what to expect from the rest of the event. After this point, Nigel brought Kelsey Hightower to the stage for his keynote session with Mark Boost and Dinesh Majrekar. If you missed our Day 1 recap, check it out here.

Docker’s power and versatility have cemented its place in developers’ and administrators’ toolkits. Along with this widespread adoption comes the critical need for effective logging in Docker containers. However, once you scale beyond a single container on a single machine, effectively capturing and working with logs from Docker presents a challenge. The native docker logs command quickly becomes inadequate, and you’ll need a more scalable solution.

Getting your applications running on Kubernetes is one thing: keeping them up and running is another thing entirely. While the goal is to deploy applications that never fail, the reality is that applications often crash, terminate, or restart with little warning. Even before that point, applications can have less visible problems like memory leaks, network latency, and disconnections. To prevent applications from behaving unexpectedly, we need a way of continually monitoring them.

Autoscaling the resources and services in your Kubernetes cluster is essential if your system is going to meet variable workloads. You can’t rely on manual scaling to help the cluster handle unexpected load changes. While cluster autoscaling certainly allows for faster and more efficient deployment, the practice also reduces resource waste and helps decrease overall costs.

As Kubernetes adoption surges across the industry, AWS EKS stands out as a robust solution that eases the journey from initial setup to efficient scaling. This fully managed Kubernetes service is revolutionizing how businesses handle containerized applications, offering agility, scalability, and resilience.

In our previous article about Database migrations we explained why you should treat your databases with the same respect as your application source code. Database migrations should be fully automated and handled in a similar manner to applications (including history, rollbacks, traceability etc).

Kubernetes, or K8s, is an open-source, portable, and scalable container orchestration platform. With K8s, you can reliably manage distributed systems for your applications, enabling declarative configuration and automatic deployment. Yet, K8s can be resource-intensive and costly, with a rather steep learning curve. But in 2019, a lighter, faster, and potentially more cost-effective alternative appeared: K3s. Still, K3s is not a magic wand that works for all Kubernetes deployments.