Operations | Monitoring | ITSM | DevOps | Cloud

The myriad of different fields that make up robotics makes QA practices difficult to settle on. Field testing is the go-to, since a functioning robot is often proof enough that a system is working. But online tests are slow. The physical environment must be set up. The entire system has to be in a workable state. Multiple runs are needed to build confidence. This grinds development to a halt.

A headline in a recent Register article jumped off my screen with the claim: “No, Kubernetes doesn’t make applications portable, say analysts. Good luck avoiding lock-in, too.” Well, that certainly got my attention…for a couple of reasons. First, the emphasis on an absolute claim was quite literally shouting at me. In my experience, absolutes are rare occurrences in software engineering. Second, it was nearly impossible to imagine what evidence this conclusion was based on.

In an ever-changing world, the future of work is changing as well, and it has accelerated some areas of automation that we were already moving toward. I sat down with our guest speaker, Leslie Joseph, Principal Analyst Serving Application Development and Delivery at Forrester Research, for a webinar to discuss these questions and get a better understanding around how automation plays an important role in supporting companies through crises and preparing them for an uncertain future.

So that’s the summer gone (hopefully, that heat was awful). Or winter if that’s where you are. Seasons change and so does the state of robotics. Fortunately, that’s what we’re here for. Before we get into it, as ever, If you’re working on any robotics projects that you’d like us to talk about, be sure to get in touch.

So what exactly is observability? Is it just a new-fangled term for 'monitoring'? Well, no. Observability goes further than mere monitoring. Observability involves the combination of 3 pillars – Metrics, Logs, and Tracing – to give a much more in-depth view of what your application is doing. Observability offers proactive insights into how your application and/or infrastructure are likely to behave, whereas monitoring is only reactive in nature.

The cloud gets all the press today, and while organizations are moving more and more of their applications and associated infrastructure into the cloud, there is still a lot of “down below” on-premises. A recent cloud computing survey from IDG shows that a clear majority of companies plan to use cloud services for over half of their infrastructure and applications.

More and more companies are beginning to turn to DevOps and the cloud as a way to improve their software teams. Whilst it used to be that development and operations were seen as separate, that view has now changed. Linking the two leads to better communication, faster development times, and the ability to stay on top of things.

Deploying Docker images to Kubernetes is a great way to run your application in an easily scalable way. Getting started with your first Kubernetes deployment can be a little daunting if you are new to Docker and Kubernetes, but with a little bit of preparation, your application will be running in no time. In this blog post, we will cover the basic steps needed to build Docker images and deploy them to a Kubernetes cluster.

Observability is an indispensable concept in continuous delivery, but it can be a little bewildering. Luckily for us, there are a number of tools and techniques to make our job easier! One way to aid in improving observability in a continuous delivery environment is by monitoring and analyzing key metrics from builds and deploys. With tools such as Prometheus and their integrations into CI/CD pipelines, gathering and analysis of metrics is simple. Tracking these things early on is essential.

In today's world, the need for organisations to have comprehensive cybersecurity solutions in place has never been greater. New vulnerabilities are exposed on a daily basis, and data breaches pose not only monetary but reputational risk.