Minimizing and automating the path from development and production is necessary in order to stay competitive and keep customers happy. As engineering teams strive to solve this by quickly and efficiently rolling out new features, updates, and bug fixes, continuous integration and deployment (CI/CD) has come to be regarded as an industry best practice. One of the most popular CI/CD solutions is Jenkins, an open-source job execution system.

At Ably, we run a large scale production infrastructure that powers our customers’ real-time messaging applications around the world. Like in most tech companies, this infrastructure is largely software-based; also like in most tech companies, much of that software is deployed and runs in Docker containers.

Every developer knows there are some utilities that are completely indispensable from their workflows. The programmer’s toolbelt, if you will. These toolbelts are usually different from person to person, but if there is one tool that everyone should use or at least know how to use, it is tcpdump. If you are unfamiliar, tcpdump is a tool that allows you to dump and inspect live network traffic being observed on a network interface.

Over the past ten years, Clubhouse and other innovative startups built software quickly. They started from scratch and blew past their incumbents. But the fact of the matter is that speed is no longer a differentiator. Everyone can move quickly. We’ve seen it as Facebook and Twitter quickly duplicated Clubhouse’s “innovative” functionality. Today, it’s all about agility—taking the momentum that you’ve already built up.

Often hailed as a game-changer, Kubernetes has altered the way that organizations deploy and manage their software, making the job of handling larger and more complex workloads easier. Yet, with its advantages of velocity and scale come new challenges, particularly in how developers approach debugging their code. The highly distributed nature of Kubernetes that makes it so effective for handling cloud-native software means that the traditional approaches to debugging are no longer applicable.

Adoption of service meshes like Istio is increasing. As a result, Speedscale has developed a webassembly plugin. We extended Envoy using Rust, and no changes are required to your Istio configuration. This allows us to leverage the same sidecars that you have deployed throughout your environment to inspect API traffic. Once we are listening through Istio, the typical Speedscale magic can take place. We can use the data to build integration/performance test suites and autogenerate service mocks.

Sometimes, the data you want to analyze lives in AWS S3 buckets by default. If that’s the case for the data you need to work with, good on you: You can easily ingest it into an analytics tool that integrates with S3. But what if you have a data source — such as logs generated by applications running in a Kubernetes cluster — that isn’t stored natively in S3? Can you manage and analyze that data in a cost-efficient, scalable way? The answer is yes, you can.

At Koyeb, our mission is to provide the fastest way to deploy applications globally. We are building a platform allowing developers and businesses to easily run applications, a platform where you don't need to think and deal with the resiliency and scalability of your servers: a serverless platform. Ironically, a serverless platform is actually full of servers. As a cloud service provider, we operate the infrastructure for you and abstract it as much as possible.

A service mesh is a software infrastructure layer for controlling communication between services and usually tasked with handling all the network logic required to make microservice applications work seamlessly in a cloud-native environment. It’s the perfect solution to your communications problems.