As CFO of Virtana, I face many of the same challenges as every CFO of a SaaS or enterprise software company today: cost containment, surprises, and an ever-escalating AWS bill. We all need help keeping these things in check. These challenges become even more difficult when your organization goes hybrid cloud. Fortunately, there are tools out there to help our teams help us manage these costs.

As the world is increasingly reliant on technology, software developers, cloud architects, and DevOps practitioners bear a responsibility similar to that of the health industry or to airplane pilots, for example. In this reality, cloud monitoring isn’t optional, it’s a matter of being professional. What is optional, however, is what monitoring solution to go for. Obviously, the one that best fits your specific needs but which one is it?

With over 200 products offered by AWS, when designing a solution, such as a micro-services based system using a number of these services at its core, it becomes rather challenging to not only monitor them but on the onset of a problem troubleshooting it and resolving it within the least amount of time becomes a daunting task. Building a monitorable system requires a deep understanding of the failure domain of the critical components, which is a tall order for a fairly complex system.

Flexibility is one of the cloud’s biggest benefits, but also one of its biggest challenges. When you have different teams using resources in the cloud and deploying instances at the click of a button, your cloud environment could easily become chaotic. Without a definitive plan governing your cloud operations, your costs will inevitably spiral out of control. A cloud cost strategy is your action plan for managing costs and staying profitable while working and building products in the cloud.

Whether you are moving your applications to the cloud or modernizing them using Kubernetes, observing cloud-based workloads is more challenging than observing traditional deployments. When monitoring on-prem monoliths, operations teams had full visibility over the entire stack and full control over how/what telemetry data is collected (from infrastructure to platform to application data).

All too often, the Kelverion team hear that businesses are trying to deliver more services with less resource, all whilst meeting tight Service Level Agreements. There are many automation use cases to relieve this pressure, and this article explores the six use case examples driving automation adoption within service management.

The Seattle-based cloud services engineering team at ServiceNow has cultivated a culture of creativity, risk-taking, and problem-solving—despite the weight of their work being deployed at a global scale across some of the most complex regulated markets.

Experts from all industries admit the need to use and analyze data, especially generated in real-time. Therefore, business decision-makers need to know how these processes occur, under whose control they are and how to optimize them. But what technologies can help companies better cope with masses of data?

We are happy to provide an open-source Terraform module enabling automatic delivery of CloudTrail logs from S3 to a Kinesis Data Stream.