OK – let’s face it. Every Managed Service Provider (MSP) in the world is feeling the pressure to continuously improve their business. They need to be competitive. To be innovative. To be efficient and so on. In this post I will explain how Artificial Intelligence for IT Operations (AIOps) helps MSPs to tackle their biggest challenges.
MSP ChallengesBased on customer experience, I have listed the top three challenges of MSPs:
- Staying Competitive
A challenge for MSPs is the increasing commoditisation of the industry. With the rise of cloud providers such as AWS, Microsoft and Google it has become more difficult for managed service providers to differentiate their service offering. As an end-user, why should I choose for a MSP instead of AWS?
- Deliver High-Quality Services Across A More Complex Environment
With new technologies such as cloud, containers and microservices, managed service providers are challenged with a growing complexity of their IT landscape. This complexity can be defined across three dimensions:
- Volume: rapid growth in data volumes generated by the IT infrastructure and applications
- Variety: there is an increasing variety of data types (for example, metrics, logs, events and changes) generated by machines and humans
- Velocity: the increasing velocity at which data is generated as well as the increasing rate of change within IT architectures
This growing complexity makes it more difficult for MSPs to deliver the same quality of service to their end-users.
- Productivity and Efficiency
Handle more customer, with less resources. That’s what every MSP wants, right? Here at StackState we’ve seen two MSP challenges that are efficiency-related:
- First of all, we've seen customers who are having a hard time with the on-boarding of new applications. It's a painful process for them to know what systems are running where at the customer side and how to merge it with their existing IT landscape.
- Secondly, it’s hard to realize a quick time-to-value from new employees. New hires at MSPs have no idea what the IT landscape looks like and how systems across customer environments are connected.
Increase Operational Efficiency With AIOps
To stay relevant, MSPs need to demonstrate that they can consistently deliver high-performance solutions for their customers. In addition to this, it's important that they can scale the amount of systems and customers without increasing headcount.
And that's where AIOps enters the picture.
MSPs are using multiple monitoring tools to manage and monitor customer environments. Each tool serves a different need and monitors a different part of the IT landscape. As the complexity of your IT landscape grows, the volume and variety of data will also grow. How do you stay in control, without increasing headcount?
Steps towards AIOps
AIOps Use Cases For MSPsAIOps platforms play a critical role in reducing the complexity of a MSP IT landscape. AIOps enables you to consolidate different datasources into a single place, and scale it to understand your customer environments from every possible angle. We've seen the following and most popular AIOps use cases at MSPs worldwide:
- Reduce complexity. Monitor your customer’s cloud, on-prem and hybrid IT landscape in one place. By visualizing the topology of your entire IT landscape, you are able to understand dependencies across customer environments.
- Improve service quality. Be transparant towards your customers and provide them with dashboards that provides full-stack visibility. In addition to this, AI helps you to understand issues that affect your service quality and identify them before they cause a costly disruption for your customers.
Increase operational efficiency. Auto-discover components from customer environments and get a real-time understanding of its architecture. Having an understanding of what's running where will help to reduce the time to on-board new customer environments.
Scale and optimize human resourcing. On-board new employees quickly and realize a fast time-to-value. Create a shared understanding across teams and tools for efficient resourcing.