Operations | Monitoring | ITSM | DevOps | Cloud

Organizations are migrating an increasing amount of their infrastructure into the cloud. The cloud provides organizations with a number of benefits like greater scalability, improved reliability and faster time to value. However, these potential benefits can be offset if security is an afterthought.

Running an Artificial Intelligence (AI) infrastructure on premise has major challenges like high capex and requires internal expertise. It can provide a lot of benefits for organisations that want to establish an AI strategy. The solution outlined in this post illustrates the power and the utility of the universal Operator Lifecycle Manager (OLM) using Juju, a universal OLM, to create and manage on premise AI infrastructure.

One of the major concerns when moving to the cloud is how to approach AWS S3 security. Companies may have moved their workflows to Amazon, but are still cautious about moving their data warehouse. And that is totally understandable. We have all heard about data breaches in companies like Facebook, GoDaddy, and Pocket. It’s important that access to information is done properly, in a limited and controlled fashion, to avoid such breaches.

Running and troubleshooting production services requires deep visibility into your applications and infrastructure. Virtual machines running on Google Compute Engine (GCE) provide some system logs and metrics without any configuration required, but capturing application and advanced system data has required the installation of both a metrics agent and a logging agent.

In the 21st century, it’s quite easy to manipulate machines and computers. Our worries are no longer if something is doable, but if something can be perfected. Therefore, we mostly search for new ideas and ways to make our work impeccable. For example, if you’re using a particular software and you realize that the software is excellent, but it could be better in some ways that would allow you to work even faster, you’ll explore the alternatives.

The term cloud native is widely used when thinking about computing and software development, encompassing a wide range of concepts that are regularly used in technology. Let’s break it down and take a closer look – what does cloud native really mean?

One of the most powerful aspects of AWS is their Identity and Access Management (IAM) service. The obvious aspect of its power is that it controls who can do what with all the resources inside your AWS account. But the non-obvious side is how configurable it is. You can encode permissions that are so finely grained that a Lambda Function could, for example, be given just enough permissions to be able to read one attribute from one record for the current user of a DynamoDB Table.

There’s no question that the cloud offers efficiencies and innovation opportunities that are near impossible to replicate on-premise. In fact, Amazon reports that companies achieve 31% infrastructure cost savings, as well as 62% more efficient IT infrastructure management, when they move to AWS (and that doesn’t include the many other cost benefits — like improved security and on-demand services). But the extent of those efficiencies can vary.