Operations | Monitoring | ITSM | DevOps | Cloud

Kubernetes is a powerful orchestration system, however, it can be really hard to configure its deployment process. Specific apps can help you manage multiple independent resources like pods, services, deployments, and replica sets. Yet, each must be described in the YAML manifest file.

Reliable systems are vital to meeting customer expectations. Downtime not only hurts a company’s bottom line but can be detrimental to reputation. Our goal at Gremlin is to help enterprises build more reliable systems using Chaos Engineering. Whether your infrastructure is deployed on bare metal in a corporate-owned data center or as Kubernetes-orchestrated microservices in a public cloud, chaos experiments can help you find system weaknesses early, before they affect customers.

Just like countless other business functions, cloud delivery has now shifted entirely to remote working for now and perhaps longer term. Canonical has been a remote-first company for some time, so we thought we’d take this opportunity to share some of the best practices we’ve learned along the way. Communication Effective communication between customers, engineers, and project managers is the most critical element of successful cloud delivery.

I’ve been writing about continuous cloud optimization for a while now, and recently, I’ve spoken with several organizations to understand any challenges they’re currently facing in their automation journey. Their insights would help us understand how we can improve our technology to better support them. I discovered two fundamental themes behind their challenges.

In classic Puppet deployment architecture, compile masters are widely used when the number of managed nodes goes up. Multiple compile masters sit behind a load balancer to take care of the additional workloads. It is not rare to see Puppet adopters launching the compile masters in the public cloud, such as Amazon Web Service (AWS) and Google Cloud Platform.

From smart thermostats and grocery store checkouts to public utility infrastructures and industrial manufacturing lines, the Internet of Things (IoT) is all around us—and growing larger every day. But with this rapid growth comes a number of operational challenges: IoT devices collect a large amount of data, and are often distributed across harsh, ever-changing environments.

A video chat with the developers who bring right-sized cloud costing information in real-time. It all started with a casual conversation about the cloud and infrastructure monitoring among the team at Galileo and our parent company, The ATS Group. From there, it quickly evolved into a discussion on how we can alleviate a source of frustration for many of our customers.

What software assets does your organization use? What sounds like a simple question is anything but. If we include every package and dependency that ends up in the code we produce then for most development teams the truthful answer is ‘we don’t know’. As we’ve said enough times already, that really isn’t good enough anymore. And that’s one of the core motivations behind Cloudsmith.

Many of the organizations use AWS as their cloud infrastructure, and in general they have multiple AWS accounts for production, staging, and development. Inevitably, this would result in losing track of various experimental AWS resources instantiated by your developers. Eventually, you will be paying AWS bills for resources which could have been identified and deleted in time. So, how should you go about identifying and deleting such unnecessary resources? aws-nuke to the rescue.