Software-as-a-service (SaaS) is an old friend that has been an established business model since the 1960s. It is a broad term referring to everything from platform to software and various other technology ecosystems that are offered to customers on a consumption pay-per-use model.
In 2019, the SaaS market was estimated to be worth $141 billion. The 2020 market is projected to reach the $157 billion mark. When compared with figures from 2014 when the industry was said to be worth $63.19 billion, the growth is exponential.
There are a couple of front-runner vendors that moulded the original SaaS concept and changed the future of industries like sales operations and service management. Market uptake was quick and the service proliferated covering: software (SaaS) platforms (PaaS) and infrastructure (IaaS) as a service, as well as many other derivatives. One area that might be considered resistant to the model, until recently, is that of IT operations management.
However, this is changing with the increased focus on AIOps (artificial intelligence for IT operations), which helps to drive intelligent insights and automated remediation).
Why is the time right for a new model?
In the early stages of the introduction of cloud and SaaS models, organisations found it difficult to embrace a new model, as:
- First, it required a paradigm shift from a capital expenditure model to one of an operational expense which meant that businesses had to account for and manage software and platforms that were traditionally seen as capex investments.
- Security and data sovereignty were, and in some instances still are, the main barriers to moving to cloud.
- Cloud and SaaS offerings were traditionally viewed as great platforms for development and testing but not for production environments that require stability with solid high availability.
Fast-forwarding to today’s attitudes, we see cloud and SaaS providers have proven their platforms can be trusted for stability and security. It is now commonplace for business-critical production workloads to be found in cloud and SaaS platforms.
Leading cloud providers have strict governance and policies in place to safeguard data in transit as well as data processed and stored on the platform.
Leading cloud providers have strict governance and policies in place to safeguard data in transit as well as data processed and stored on the platform.
Leading AIOps providers have embraced a SaaS-first approach, meaning these platforms are architected with cloud in mind.
What should this model look like?
Gartner gives a clear picture of this in its definition of AIOps and there is no reason why AIOps cannot be implemented as a SaaS or hybrid platform; hybrid meaning that selective components live on cloud platforms and others on-premises.
SaaS platforms offer many operational benefits like included software updates, highly available architectures, multi-tenancy and a hands-off approach to infrastructure and software maintenance. This means business execs can focus on operational use of the platform to optimise business value, instead of spending time maintaining the software and infrastructure ecosystem.
The selected platform should offer multi-domain monitoring that provides scale and full stack visibility. This platform should take a big data and analytics approach to allow operations teams to handle much greater complexity and leverage all the data the monitoring solutions generate without being overwhelmed by the volume, speed and complexity of all of the data sources. The platform essentially should augment the operations team and assist them to handle the data they cannot get to timeously, or at all.
The platform should cover and unify:
- Digital experience management
- Application performance management
- Traditional and modern infrastructure management
- Traditional and modern network management
Moreover, the platform must leverage analytics, AI and machine learning, to process data, look for anomalies, give context and insights, and drive automated action. Businesses need to ensure the platform they choose can collect more than just event data. The optimal platform should be able to collect and contextualise event, metric, topology, logs and text data; both structured and unstructured.
Automation should be a core capability for user-assisted automation and fully automated remediation.
There are many technologies involved to deliver this capability and that in itself becomes another driver for consuming AIOps through a SaaS model instead of on-premises. The pressures on current infrastructure implementation and support teams are immense as they attempt to deal withconstantly changing landscapes and the many components required to deliver microservices, container estates, big data and analytics systems.
By leveraging the benefits of AIOps though a SaaS platform means businesses get all the benefits without the burden of building and maintaining such an ecosystem.
How to ensure a platform can be trusted
Some tick-boxes of what to look for when selecting the platform:
- Industry standards certified.
- Proven facilities – secure and controlled.
- Data ownership and control.
- Tenant and data segregation.
- A secure architecture that supports hybrid environments.
- 24/7/365 security operations centre with strict security systems and controls.
Where to start? Look for a partnership: it is a journey like many change programmes but it does not need to be long and complex, it can be iterative. Make sure to select an AIOps partner that has extensive experience in IT operations: monitoring, multi-tenant software and security solutions.
With the right framework, you can move the high-value, lowest effort elements to a SaaS model.
But what if things change? Choose an AIOps platform that aligns to and continuously evolves at the rate that business and IT change.
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