Aside from ensuring each service is working properly, one of the most challenging parts of managing a cloud-based infrastructure is cost monitoring. There are countless services to keep track of—including storage, databases, and computation—each with their own complex pricing structure. Monitoring cloud costs is quite different from other organizational costs in that it can be difficult to detect anomalies in real-time and accurately forecast monthly costs.

Since 2014 when AWS launched AWS Lambda and kickstarted the serverless movement, going serverless has grown exponentially for organizations of all sizes from one-man start-ups to huge listed global enterprises. While there are some challenges to this new architecture, the ways moving to serverless can transform a business often far outweigh these.

The Cloud Is a No-Brainer… Most companies by now have a “to the cloud” initiative that’s at one stage or another of maturity. It’s a great way to make better use of all your resources—people, time, and money. And it gives you more flexibility. You don’t have to size your entire application architecture for important but short-lived peaks, such as Black Friday for retailers or year-end ERP closing for large manufacturers, to name just a couple examples.

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.

Microsoft recently announced general availability of Azure VM Insights, aka Azure Monitor for VM. This service is basically a set of features that allow you to monitor your VMs in more detail, from collecting the telemetry from your VM to displaying it meaningfully – all with a single click. I am satisfied with Azure VM Insights for the most part, but I also have some mixed feelings about it. Read on to find out why.

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.

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.

While the secret of change is to focus all your energy not on fighting the old, but on building the new, adaptability is about the powerful difference between adapting to cope and adapting to win. Enterprises that overlook modernization are sure to fail in fulfilling critical compliance and security problems thus, endangering both, their businesses and customers.