One executive goal that started to pick up steam before the pandemic was automation. Automation goes beyond DevOps. It encompasses efforts to reduce manual tasks and improve resiliency. Prior to the pandemic, many companies were performing Proof of Concepts (PoCs) using multiple tools to determine where automation could occur and which toolsets provided adequate coverage. You learned about Ansible Automation in Chapter 14, Building Pipelines for API Connect.

Pre-pandemic many companies were getting organized and gathering feedback on automation experience. While not fully implemented across the enterprise, some silos were showing the benefits of automation, but automation maturity has not been achieved. Various reasons for not reaching velocity are the need for skilled resources, the presence of undefined processes, cultural barriers, and the limitation of only looking at operational activities. The pandemic changed the focus.

During the pandemic, the initial efforts were forced. People needed to work from home, and that immediately put an emphasis on how quickly organizations were able to mobilize. Laptops needed to be procured, VPN and video conferencing became overwhelmed, and collaboration tools became predominately the means to communicate and connect remote resources. Those that had some automation benefited from those pre-pandemic efforts, but the need to have it done more quickly became apparent.

The reality of the pandemic and the associated changes that the organization made to keep their people safe and maintain business as usual were real eye-openers. Resiliency was redefined with greater clarity. Investing in automation throughout the organization became clearer and people and cultures began to change. Not only did they want more automation but they wanted the automation to be based on potential business changes. This is where AI plays a key role.

The role of AIOps

AIOps is used to enhance IT operations. With the myriad of data from events, logs, and other sources means the opportunity to ingest the information and allow machine learning to enable IT operations is possible. Some of the benefits you can achieve with AIOps are as follows:

• Improved response and resolution because AIOps can decipher root causes and suggest remediation faster than previous human troubleshooting.
• With AIOps machine learning, operations can be more predictive and proactive and will decipher alerts to identify critical events from lower-level events.
• With AIOps, operators can receive notifications based on thresholds and with relevant information to make a diagnosis and take corrective action faster.

From a Digital Transformation viewpoint, you may get a myriad of digital capabilities, so utilizing AIOps can help move past the complexities and relieve the burden on your IT teams. By taking this approach early on, you can avoid IT touchpoints and provide more agility and resilience as a part of the business goal.

While automation has been somewhat limited to on-premise data centers due to a hesitancy to perform automation on the complexity of cloud and multi-cloud resources, the utilization of AIOps can help alleviate the operational risks and concerns.

In Chapter 14, Building Pipelines for API Connect, we discussed automation for on-premise implementations but AIOps can certainly play a role.

Although the pandemic is continuing, the new normal has provided organizations clarity on how automation is a clear requirement. Extending that automation drumbeat into AIOps in the post-COVID era, you will see more adoption and capabilities going forward.

IBM, to bolster its capabilities with AIOps, has purchased Turbonomic. Turbonomic’s platform uses AI to monitor and manage containers, virtual machines, databases, servers, and storage.

AI and Digital Transformation

The future of AI-Driven Cross-Cloud application operations using Turbonomics, an Application Resource Management (ARM), and the use of Instana for Application Performance Management (APM) for automating the monitoring and management of their applications, Digital Transformation is now capitalizing on AI power to drive more innovation and efficiency.

So far, the discussion has been around Digital transformation and how it can be a focal point during the pandemic. As you know, Digital transformation is a focus on enabling better products, services, experience, and business cultural change. Moving applications and data to the cloud is but one method being portrayed. When it comes to data, new technology is leading to a shift of data and processing of data closer to the user or the edge. Edge computing will be discussed next.

Exploring 5G Edge computing

When discussing Digital Transformation, a majority of the descriptions describe moving toward cloud platforms to modernize and also take advantage of operational cost factors. When you consider cloud platforms, there are the predominant players that have huge capacities that correlate to economies of scale.

Visually, you might imagine the cloud as a hub and any integrations being the spokes. This is the classic hub and spoke model as shown in the following figure. So, if you are multi-cloud you may have multiple hubs. In the case of hybrid, your on-premise applications are part of the spokes if you are focusing on cloud deployments.

Figure 16.5 – Hub and spoke cloud

The pandemic accelerated the move to the cloud as a means to support working from home and expand the business outside the wall of private data centers. Now, if you were to look closely at the cloud models, you would find that although the cloud platforms have geographically disbursed cloud locations, there are consumers that are still considerable distances away from any of the hubs. Therefore, APIs that are connected to the hub are dependent on the closeness of hubs. If those APIs are based on mobile technology, then the need for speed is dependent on wireless performance and bandwidth. This is where 5G and its increased bandwidth is solving the problem.

The cloud models have been successful for many years and continue to be successful and are improving, but is there another extension to cloud computing on the horizon? Yes, there is. With the 5G rollout continuing, it’s now called 5G Edge computing.

To provide a little more context on why this is important you should understand the advantage of Edge computing. You’ll learn about that next.