How "Predict-and-Prevent" Monitoring Software is Helping Enterprises
March 30, 2021

Girish Muckai
HEAL Software Inc.

Share this

It isn't uncommon for IT departments to be overwhelmed by alerts each week, causing alarm fatigue and making it hard for them to prioritize troubleshooting. Therefore, disruption of operations is often the first signal of IT problems, leaving enterprises to rely on an outdated break-and-fix model. This can result in significant financial and productivity losses.

Most artificial intelligence for IT operations (AIOps) tools on the market claim to use machine learning (ML) models and artificial intelligence (AI) algorithms to detect and flag incidents, perform correlation between unrelated events and provide a variety of potential root causes. However, this means remedial actions are always after the fact; and the tools are not able to eliminate downtime.

While the "break and fix" model has been the norm for most enterprises, new monitoring technology has started to take its place. The recent paradigm shift in IT operations and the diagnosis of application health has changed the focus of IT operations from quick detection and problem fixing to preventive healing, where digital enterprises prevent problems before they occur.

Preventive healing uses AI and ML to stop any possible outage by acting before it occurs. This enables IT departments to detect a likely outage, shifting teams to a "predict and prevent" approach versus the outdated "break and fix" method.

More so than simply preventing outages, predictive systems also bring value to the greater business. This technology can analyze business growth data in order to model future states of the ecosystem and determine where the capacity bottlenecks are. This data makes it possible to optimize resource deployments, reducing both capital and operating costs. Moreover, the ML model can be trained and refined further with these additional insights.

Businesses are also able to make smarter business decisions and save valuable resources when leveraging preventive healing software. Under the traditional "break and fix" model, which is focused on mitigating risk and containment, enterprises are left throwing money at problems and over-deploying resources to avoid outages. This can include paying for excess capacity to ensure redundancy, as well as assigning valuable development teams to fix problems. Shifting to "predict and prevent" allows the IT department to use their resources to support imminent problems.

Preventive healing can also help address alarm fatigue. IT teams often have a lot on their plate, so when a new alarm sounds, it can be difficult for them to address as there can be a host of potential problems. Relying on manpower to cross-analyze all the systems can make finding a problem like looking for a needle in a haystack. Preventive healing with AI technology can automatically detect anomaly signals and find the source so that a problem can be fixed before it occurs. If it cannot fix the problem, it can identify the root cause for the IT professionals, minimizing time and energy wasted on discovering issues. Early identification not only helps eliminate customer disruptions but can free the IT team up to focus on other pressing items.

Preventive healing software for IT operations uses unsupervised and supervised ML models to learn how a system works under normal circumstances and creates a dynamic baseline for the entire system and workload behavior, thereby predicting and preventing problems. However, not all software is the same.

Here are four key capabilities to look for when choosing a preventive healing software:

1. Predictive and Preventive

Some AIOps software can intelligently detect anomalies and leverage healing actions and remedial workflows to bring system parameters back to normal before an issue occurs.

2. Collective Knowledge

Because software is often connected, it is helpful to seek out a solution that is equipped with its own agents to collect workload, behavior, configuration and log data, and is comprised of a suite of APIs and connectors to integrate with most APM vendors and content formats.

3. Situational Awareness

Preempting an outage or issue is complex and requires detailed algorithms and 24x7 monitoring, well beyond the scope of even the best IT professionals. Some technology uses contextual data at the time of the anomaly – including forensic data capturing the state of the processes/queries running on the system at the time. This data can be used to determine causation and ensure that responses are coherent and complete.

4. Remedial and Autonomous

New technology can provide remedial actions in two scenarios: By 1) scaling up to handle the workload and 2) triggering autonomous correction of underlying issues that cause anomalies. Look for a solution that has intelligent ML engine techniques to ensure it always delivers the best response to the problem.

As IT continues to move to a multi-cloud environment, it is the perfect time for adopters and decision-makers to assess the gaps in their current IT offerings. Moving from the "break and fix" to "predict and prevent" model is the only way to provide confidence that a company's IT infrastructure is up and running all the time and applications are available 24x7.

Girish Muckai is Chief Sales and Marketing Officer at HEAL Software Inc.
Share this

The Latest

November 21, 2024

Broad proliferation of cloud infrastructure combined with continued support for remote workers is driving increased complexity and visibility challenges for network operations teams, according to new research conducted by Dimensional Research and sponsored by Broadcom ...

November 20, 2024

New research from ServiceNow and ThoughtLab reveals that less than 30% of banks feel their transformation efforts are meeting evolving customer digital needs. Additionally, 52% say they must revamp their strategy to counter competition from outside the sector. Adapting to these challenges isn't just about staying competitive — it's about staying in business ...

November 19, 2024

Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey ...

November 18, 2024

SLOs have long been a staple for DevOps teams to monitor the health of their applications and infrastructure ... Now, as digital trends have shifted, more and more teams are looking to adapt this model for the mobile environment. This, however, is not without its challenges ...

November 14, 2024

Modernizing IT infrastructure has become essential for organizations striving to remain competitive. This modernization extends beyond merely upgrading hardware or software; it involves strategically leveraging new technologies like AI and cloud computing to enhance operational efficiency, increase data accessibility, and improve the end-user experience ...

November 13, 2024

AI sure grew fast in popularity, but are AI apps any good? ... If companies are going to keep integrating AI applications into their tech stack at the rate they are, then they need to be aware of AI's limitations. More importantly, they need to evolve their testing regiment ...

November 12, 2024

If you were lucky, you found out about the massive CrowdStrike/Microsoft outage last July by reading about it over coffee. Those less fortunate were awoken hours earlier by frantic calls from work ... Whether you were directly affected or not, there's an important lesson: all organizations should be conducting in-depth reviews of testing and change management ...

November 08, 2024

In MEAN TIME TO INSIGHT Episode 11, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Secure Access Service Edge (SASE) ...

November 07, 2024

On average, only 48% of digital initiatives enterprise-wide meet or exceed their business outcome targets according to Gartner's annual global survey of CIOs and technology executives ...

November 06, 2024

Artificial intelligence (AI) is rapidly reshaping industries around the world. From optimizing business processes to unlocking new levels of innovation, AI is a critical driver of success for modern enterprises. As a result, business leaders — from DevOps engineers to CTOs — are under pressure to incorporate AI into their workflows to stay competitive. But the question isn't whether AI should be adopted — it's how ...