Modern workflows are primarily aimed at one thing—reducing operational complexities so that stakeholders can focus on initiatives that boost business and innovation. For IT teams, Artificial Intelligence and Machine Learning play key roles in bringing this goal to life. And even though AIOps is considered to be not yet in mature stages, there is no denying that IT teams that do not adopt AI processes will be left behind. By 2023, the market for AIOps tools is predicted to reach $11.02 B. This is a 34% compounded annual growth when compared to $2.55 B in 2018.
But upgrading legacy workflows require a heavy investment of both time and revenue. As a result, IT managers and other stakeholders are often hesitant to go all-in on digital transformation. SaaS as a delivery model is an optimal substitute. Scalable, cost-efficient, and upgradable—SaaS products provide modern IT teams with a gateway to enjoying the benefits of AI and ML at a reduced time-to-benefit ratio.
However, shrouded in a mountain of benefits is a chasm of unfulfilled promises and technical difficulties. IT executives that are sold SaaS solutions, after elaborately staged free demos, often face a sense of disillusionment when they implement the solution on-ground. Concerns about data quality, monitoring, and error detection are common pitfalls.
To bridge this gap, a team of experts at HEAL conducted an extensive study on all the popular AIOps SaaS products in the market. The data was benchmarked to ideal scenarios and expectations of ITOps managers. Here are our findings.
The Limitations of Traditional AIOps SaaS Solutions
Absence of Data-driven Action Recommendations
Quality of data is crucial to building great analytics. Therefore, it is essential to ensure IT data from events, tickets, metrics, and logs are properly validated. However, incomplete data, cluttering, and inconsistency are common in existing SaaS products. There also seems to be an absence of data-driven decisions for different types of outages.
Constrained Action Scoring and Prioritization
To stay competitive, AIOps teams must tackle key issues before they cause substantial damage. This makes prioritization of requirements a key capability of AIOps SaaS products. However, when benchmarked to enterprise standards, existing offerings fall short.
This in turn leads to high turnaround times and in extreme cases, long downtimes. The ability to predict timelines of interruptions, and the duration needed to fix the problem is also absent.
Roadblocks to Seamless Integration
While most SaaS products promise frictionless integration with existing software systems, the proof is just not in the pudding. Issues related to data transfer, weak data security, and compromised observability are common.
Other Challenges…
Our findings also reveal a gap in identifying capacity chokepoints in existing SaaS offerings. Owing to this, enterprises using said products face delays in their efforts to achieve a zero-downtime workflow.
Existing offerings are also limited in their simulations to find capacity requirements and lack the ability to deliver correlation between metrics.
The Free Trial Trap
Apart from operational challenges, the pricing of existing AIOps SaaS offerings is not transparent and fair. Most follow cookie-cutter models where key operational features are hidden behind a paywall. This leaves little choice for businesses when it comes to choosing a subscription model. Either they pay for a basic subscription with limited features or go for an overpriced premium offering stuffed with features they will rarely use.
And free trials are at the helm of this trend! They are meant to help IT leaders gauge the use case of a product, but in their present form are just a marketing gambit to upsell. Multiple features are locked during the trial period and there is limited access to important analytics. Businesses that want to unlock the premium features are compelled to get an annual subscription.
This trend presents two challenges for IT leaders. One, cost-to-benefit calculation can be done only after an annual plan is purchased. And two, true process constraints are realized only when monitoring teams start using it in daily operations. As a result, most SaaS offerings leave a bitter aftertaste for AIOps managers.
HEAL SaaS—A Solution Designed to Address all Problems
HEAL SaaS is a product that is designed to bridge all existing gaps and evolve with the requirements of IT teams. It brings the power of our HEAL product via a SaaS model. Available on the trusted, secure, and compliant Microsoft Azure Cloud, it is available for trial today. Businesses can access a free 30-day trial to test the product.
We have removed all caps on the platform during the trial period for teams to fully understand its capabilities. All features are unlocked and there is no limit on the volume of data ingested. Enterprises can use the product with no commitments and see value from Day One. Seamless integration via API connectors and instant support increases its effectiveness.
HEAL SaaS is also priced at least 25% less compared to other APM solutions and comes with no hidden charges. We have also kept our pricing models transparent and flexible, based on the teams’ monitoring maturity—startup, mid-sized, or enterprise. Moreover, the price distinction is based on volume and not features available. This means that every business gets the best value for investment.
Our goal is to bring the power of enterprise-level HEAL products to global IT teams and create a zero-downtime world. This is one of the most important steps in the endeavor.
For a free 30-day trial of HEAL SaaS, CLICK HERE.