1. New study finds most business executives want ITOps to help improve their competitive position.
The Digital Enterprise Journal reported that 52% of business executives believe the impact of IT operations on business goals needs to be more explicit, and 57% of organizations want to make IT more strategic. Most critically, they are looking for IT operations to help improve their organization’s competitive advantage. Executives reported $126,000 were lost per hour of IT downtime and an average estimated revenue loss of $2,129,000 per month caused by slowdowns in application release times.
Now how can IT operations address these losses? The study identifies these eight key areas where IT operations should concentrate:
- Validating technology investment
- Removing risk from modernization and transformation strategies
- New productivity enablement
- Pinpointing the location of the problem
- Unified view into IT and business performance
- Business insight that you can’t get from other tools
- Speed and agility
- Ease of use and time-to-value
2. You can apply chaos engineering to ITOps.
According to this article in DevOps.com, chaos engineering, usually practiced by DevOps team, can also be used by ITOps teams. Not sure what chaos engineering is exactly? Chaos engineering is “the discipline of experimenting on a system in order to build confidence in the system’s capability to withstand turbulent conditions in production.”
It’s used by DevOps teams to set up experiments to run software under demanding conditions and monitor performance. Chaos engineering can also benefit ITOps teams by providing a systematic approach to identify vulnerabilities in the microservices environment and visibility into performance and event metrics to address those vulnerabilities in situ before they can compromise operations.
3. Data is top thing to consider if you’re just getting started with AIOps.
According to Joe the IT Guy, the top capability you should consider when choosing an AIOps tool is machine learning. Want machine learning to be effective? Then there’s got to be lots of data. And before you even think about getting started with AIOps, you should get your data as clean as possible. Why? Because dirty, noisy data will cause you nothing but trouble when training those machine learning models.
You’ll be using data that comes from multiple sources, but they should be grouped and analyzed together. Because siloed data can be ineffective when trying to determine the root cause(s) of problems. AIOps can enable you to see across your organization. Big data analytics can help to automatically find, progress, and even resolve issues.
4. The total cloud ITSM market size is expected to grow to $10,383 million by 2024.
According the Yahoo Finance, cloud ITSM market size is expected to go from $4,425 million in 2019 to $10,383 million by 2024, at a Compound Annual Growth Rate (CAGR) of 18.6% during the forecast period.
Due to the increasing popularity of cloud services, organizations have been compelled to move on-premises ITSM to cloud. The ITSM market is made of solutions for service portfolio management, problem and incident management, change and release management, service desk software, and analytics tools. And in the last five years, cloud computing has gained much publicity, with growing enterprise acceptance of SaaS. Cloud solutions are being viewed as an opportunity to quickly and flexibly deliver business-enabling IT services at a reduced cost.
