Hope Powers, Vice President – ANZ, Dynatrace, explains how to increase rates of automation of manual tasks can streamline multi-cloud management.
Cloud computing platforms have grown to become an integral component of many organization’s IT infrastructures. The flexibility and cost savings they offer have made them a compelling choice.
Increasingly, however, organizations are coming to realize that their cloud requirements cannot be adequately served by a single provider. They are migrating their digital resources on to multiple clouds, each best suited to a particular workload.
This trend is causing the overall pace of cloud adoption to increase. Indeed, research company IDC forecasts that total worldwide spending on cloud services will top US$1.3 trillion by 2025.
Growing complexity
While making use of multiple clouds can deliver significant technical and business benefits, they come at the cost of increased complexity. IT teams find themselves having to manage different workloads in different environments and ensuring everything functions as a cohesive whole.
IT operations (ITOps) teams find they have to spend more time on day-to-day management rather than focusing their attention on more innovative projects. Dynatrace research has found ITOps teams spend almost half (42%) of their time on manual, routine work ‘just to keep the lights on’ across their infrastructure.
Clearly a more sustainable approach to infrastructure management is required. The approach needs to be one that improves visibility of multi-cloud environments and automates many manual tasks to free up IT teams.
Increased complexity can also have a detrimental impact on the customer experience. If outages are occurring on a more regular basis or overall performance declines, customers are more likely to seek an alternative.
For this reason, it is vital that IT teams have complete visibility of their organization’s entire IT infrastructure. Unfortunately, in many cases, this visibility has so far proved to be elusive and much more work is still required.
The challenge of management
The management challenges caused by the adoption of a multi-cloud strategy occur for a range of reasons.
Firstly, each cloud platform comes with its own native monitoring tools, such as Amazon CloudWatch or Azure Monitor. ITOps teams therefore need to learn to operate an increasing number of monitoring tools, each with its own unique features.
These tools also need to be layered on top of traditional monitoring solutions to track activity across the entire infrastructure. Dynatrace research has found that, on average, organizations rely on seven different monitoring solutions to manage their multi-cloud environments.
The Kubernetes factor
A second factor that makes observability more elusive is the frequency of change within multi-cloud environments. While platforms such as Kubernetes give organizations the ability to scale their multi-cloud resources rapidly to match demand, the constant change makes it difficult for teams to monitor and manage performance effectively.
Typical Kubernetes environments also produce large volumes of data, which is impossible for ITOps teams to sift through manually. Adding further complexity, in their efforts to alleviate ‘tool sprawl’, teams often adopt a DIY approach to infrastructure monitoring, using open-source observability solutions to stitch together multiple tools. This generates wasted manual effort and is difficult to maintain.
Automation is the key
The answer to overcoming these challenges is to increase rates of automation of manual tasks. This will empower IT teams with a new approach to infrastructure monitoring, harnessing AIOps (Artificial Intelligence for IT operations) to streamline processes.
Taking this approach will eliminate blind spots by continuously discovering and instrumenting multi-cloud infrastructure as an organization’s IT environment changes. As a result, IT teams can achieve end-to-end observability without needing to invest time and effort in manual monitoring processes.
The approach will also help to automatically triage alerts and query observability data to surface the precise insights that IT teams need to deliver reliable digital experiences to users and customers. With this approach, AIOps can enable teams to understand the cause of any issues across a multi-cloud infrastructure and prioritize issues by business impact.
This, in turn, means that IT teams can focus on solving critical issues first and then focus effort on tasks that accelerate an organization’s Digital Transformation. Yet this will only be possible if the teams can consolidate observability data in one place. A consolidated view creates a single source of truth that provides the full context needed to drive effective automation.
Supporting innovation
As organizations continue their adoption of multi-cloud IT architectures, ensuring that their overall IT infrastructure is running smoothly is becoming critical to supporting both internal activity and customer services.
By embracing automation and putting it to work across the IT infrastructure, IT teams can ensure all systems are operating at maximum efficiency at all times. Then, the business benefits promised by a multi-cloud strategy will have been realized.
