Observing life inside the Open Source Cloud-Native Stack

The future of cloud computing is uncertain. In the first era of cloud, the monolithic IT stacks of yesteryear (and even older archaic notions of client-server) started to give way to the new era of Software-as-a-Service (SaaS) computing applications and services, supported as they are by Platform-as-a-Service (PaaS) computing models and Infrastructure-as-a-Service (IaaS) beneath.

The web was truly matured at this point, sometime in the first decade of the new millennium. While some people are still able to recall the term “information superhighway” or the web, not many others do. It was now a matter of Internet Protocol (IP-based transmission among cloud datacenters. This served as the ideal breeding ground for cloud hyperscaler Cloud Services Providers (CSPs) big-three (AWS Google & Microsoft).

Cloud-native cloud

Cloud computing, a key trend in the past decade, evolved to the point that organizations began to look at the possibility of avoiding the tedious cloud migration phase. They suggested that we build cloud native instead. They did.

We can identify other key trends within modern IT stacks as we get used to the cloud-native environment. There are many DevOps (developer + system operations coalition), a lot of dynamic microservices, and containers-based architectures (smaller components of technology). The emphasis is on optimizing user experience without worrying too much about the infrastructure or operating systems that support any digital capability.

Open source is also very popular.

Why is there so much open source?

“Cloud PaaS ecosystems are unique in that many of the key solutions, such as Red Hat OpenShift [a technology that provides container orchestration services], are based upon open-source projects such as Cloud Foundry or Kubernetes. These solutions are becoming more advanced because of the community approach to development. This is due to the contributions of many of the most innovative people in their fields, such as Cloud Foundry and Kubernetes. These projects are not only for grassroots developers – major contributors to open-source software come from large commercial vendors around the world,” stated Eric Horsman. He is also global director of strategic alliances at software intelligence platform Dynatrace.

Red Hat is well-known as a major player in many open-source projects due to its investments in making them market-ready products such as the OpenShift container platform orchestrated by Kubernetes and Red Hat Enterprise Linux, their operating system.

OpenShift (RHEL), and Red Hat Enterprise Linux(RHEL), allow organizations to run containerized apps in a modern hybrid cloud environment. They support workloads that range from on-premises datacenters and public cloud platforms to edge devices in IoT.

IDC projects that the RHEL ecosystem in terms of Red Hat Linux will generate more than $100 million in revenue by 2022 and grow to $138 billion in 2026. Another study shows that 37% of organizations using OpenShift to deploy hybrid and multicloud Kubernetes systems, exceeds the third.

Do not fall off the edge.

Despite all this, microservices and container architectures can offer greater agility to organizations, but they can also create new complexity that must be managed.

“The constant changes in these environments make it difficult for teams maintain observability across their entire infrastructure stack. Microservices have also led to smaller agile delivery teams that update application functionality less frequently and with shorter release cycles. “This increases the risk of human error which could allow bugs to be introduced into production,” stated Dynatrace’s Horsman. It’s vital that organizations continue to use OpenShift Enterprise Linux and Red Hat Enterprise Linux. This ensures that their teams are able to observe these dynamic technology stacks.

This technology proposition suggests that organizations require modern observability tools that can automatically inspect containers and give code-level visibility to microservices running within them. These solutions should also be able to monitor the underlying infrastructure, from the datacenter right up to the edge of the IoT. These solutions require Artificial Intelligence (AI), which can provide precise answers to teams about the causes of any problems, and not just the masses of data that they have to analyze for insight.

We see with our eyes but not with our minds

It is important to remember that not only do you need observability data, but it is also about making sure that every employee in your organization has it. In the past, access to observability data was granted on a team by team basis.

“Anyone who needs to know the inner workings a service or application would need to open a support ticket asking operations teams for access to relevant metrics, logs and trace data. This would require operations teams to make complex configuration changes to instrument the application, and give the appropriate privileges to the internal users,” explained Dynatrace’s Horsman.

He concludes that the complex configuration process referred to above is obsolete and a huge waste of time for both the operations team and their customers. Horsman argues that organizations should look to automate their onboarding process to allow new employees access through self-service.

A cloud-native utopia

The continued push to the cloud is ultimately about increasing efficiency in IT operations and allowing software engineering teams to be more focused on innovation than maintaining power.

Organizations should support this ethos by providing their employees with the skills they need to cut bureaucracy and eliminate manual labor, as well as encourage agility in the transition to modern cloud-native delivery.

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