As we close the year the time is ripe for technology predictions for the next year and beyond. Recently released reports share a familiar theme – Cloud continues to maintain one of the top spots – and certainly no surprise is expected there! However, the emphasis is no longer around adoption, or the choice of delivery models but on the confluence of emerging trends underpinning increased sophistication of cloud consumption and operation. Emerging trends around Microservices, Infrastructure as Code (IAS), DevOps, Hybrid Cloud Management, Software Defined Everything, and IT Operational Analytics are gaining traction as they form clarity and alignment towards improved automation within both cloud and datacenter environments.
Previously there was considerable dichotomy between datacenter and cloud automation. However emerging technologies are blurring the lines and facilitating cloud(s) and datacenter investments to coexist and evolve in unison. Imagine an everyday scenario that begins with a customer opening a service ticket to consuming infrastructure resources (compute, storage, network) to getting billed for such resources. All systems and infrastructure can now be rapidly deployed, integrated and operated via deterministic automation. Significantly reducing the traditional complexities requiring costly manual tasks and time around planning, provisioning and operating.
There is also a view that cloud native applications are inherently automation “ready”. While that may be so the demands of the enterprise will challenge these capabilities. Cloud usage within enterprises does not operate in isolation and has to contend with existing on-premise (data center) technologies, processes and skills. Furthermore, enterprises do not necessarily employ a single cloud. Companies are increasingly investing in more than one cloud provider, which is quickly leading to cloud sprawl that is necessitating improved and comprehensive automation.
Given such a heterogeneous landscape, automation has to be thought of holistically in order to be effective. The utopian view of automation is the “push button” approach for deploying, operating and monitoring all IT investments, with minimal human intervention for the business. In the distant future, maturity in artificial intelligence (AI) tools will allow self-discovery and prescriptive design of most automated tasks, negating the need for large amount of skilled resources. Until then upcoming platform and architectural innovations will provide the interface for deterministic tools that are programmable, template-based and can applied across diverse resources.
At Dimension Data automation is increasingly being relied upon for internal use and by clients, or partners. There have been a significant number of contributions pertaining to the Managed Cloud Platform, including integrations with market leading tools such as Chef, Terraform, ServiceNow, StackStorm, SaltStack, Ansible and SDK’s for .Net, Java, Go, and Python. You can find more details on the Dimension Data Developer Portal.
One of the initiatives where the company has done some extensive work is around IAC – “Infrastructure as Code”. According to Martin Fowler – a renowned author and developer – “Infrastructure as code is the approach to defining computing and network infrastructure through source code that can then be treated just like any software system. Such code can be kept in source control to allow auditability and reproducible builds (releases), subject to testing practices, and the full discipline of continuous delivery (CD).” IAC is also sometimes referred to as programmable infrastructure.
So let’s take a closer look at some of this technology. Terraform from Hashicorp is a popular tool of choice for IAC. At a glance, it provides a high-level declarative syntax and can co-exist with other proprietary and open source tools to provide a flexible and template-based blueprint of your entire infrastructure and applications.
A good place to start is a 3-part series series starting with a minimal configuration scenario walk through for provisioning resources on the Dimension Data MCP (Managed Cloud Platform). The series includes Terraform integration with DevOps (Configuration Management) tools such as Ansible for deploying application workloads like a Kubernetes cluster to manage Docker containers. Demonstrating a top to bottom automated deployment of a Microservices architecture on the Dimension Data cloud.
A well planned automation strategy will be the key differentiator for any technology driven company. The great news is that recent advancement have vastly improved the tools landscape. This blog site will strive to share the experiences and knowledge on how you can leverage automation technology to accelerate your journey in the cloud and datacenter.