News Roundup, March 27, 2020: What’s Happening in AIOps, ITOps, and IT Monitoring

While a fantasy fountain of magical water that “brings back youth” remains a myth, we’ve gathered a fountain of knowledge in our blog for your consumption. We prefer being older and wiser to callow youth anyway—so, drink deep of the latest in AIOps, ITOps, and IT monitoring.

1. Is AIOps a good fit for your business? Here’s how to decide.

AIOps tools automate the fast ingestion of volumes of data. Machine learning can analyze the data for predictions or alerts, leading to automation or better decisions. However, according to an article by The Enterprises Project, there are several considerations your organization must make before the decision to adopt AIOps tools can be made.

When deciding to adopt AIOps for your business, consider whether your IT operations organization is facing any of the following issues:

• The environment being monitored generates a large amount of data, but decision-making is difficult as a result.
• Your IT operations team has difficulties prioritizing different issues for resolution. They face a large volume of alerts, and many of those alerts are redundant.
• Your tech team is struggling to manage the software and infrastructure performance aspects in a real-time or proactive way, and this is impacting your customers.
• Your team can manage key operational problems with domain-specific tools, but there is no end-to-end visibility for a holistic IT operation approach.

Ultimately, it’s all about your company’s priorities. Be sure you take the time to identify what you’re hoping to get out of AIOps before you jump in.

2. AIOps is transforming application monitoring.

According to an article in APM Digest, application backend monitoring using AIOps is the key to acquiring visibility across an enterprise’s application stack, from the application layer and underlying infrastructure to third-party API services, web servers, and databases.

Whether your IT infrastructure is on-premises, in a public or private cloud, or a hybrid model, by tracking and reporting performance in real time, IT teams can ensure applications perform at peak efficiency—and guarantee a seamless customer experience.

What tasks can AIOps perform to acquire actionable data?

• Discover the data—This means gathering data across the enterprise’s network and infrastructure to take stock of its potential impact on applications, and then taking a top-down approach to gain insight into individual applications, their operational environments, and their business functions.
• Put the data into context—Once your data is accurate, complete, relevant, and consistent, it must be contextualized to deliver insights that drive recommendations and automated actions. An unclean “data swamp” that is full of unstructured garbage is of little help to an IT team.
• Act on data-driven insights—Application monitoring solutions that reside in the operating system and provide code-level performance, tracing, application topology mapping, and tracking can provide both incident automation and data-driven recommendations that enable IT teams to prevent issues and preempt the occurrence of potential backend outages.

3. There are five phases to AIOps.

According to an article by AI Authority, AIOps isn’t just another automation tool for enterprises; it’s a holistic strategy. Before starting on their AIOps journey, they should evaluate their current and potential capabilities through the following five phases of AIOps maturity:

• Reactive phase—During the reactive phase, events and logs are collected for reactive purposes. When teams attempt to work through siloed operations with little to no dialogue with the rest of the business, they cannot prove their value to business leaders, as they are stuck in reactive mode, rather than proactive.
• Integrated phase—In the integrated phase, silos begin to break down, and dialogue among IT teams and the business becomes more frequent and productive.
• Analytical phase—In the analytical phase of AIOps, teams see significant improvement across the board with more AI and ML capabilities. There’s more transparency of data among all stakeholders and the business, and teams have more defined baseline metrics.
• Prescriptive phase—In this phase, teams begin implementing machine learning and automation, giving them access to more analytics and data to track overall improvements.
• Automated phase—In the final phase of AIOps maturity, there is full automation with no human interaction, and teams can leverage machine learning based on prescriptive and predictive models.

It’s essential to keep the long-term AIOps strategy and goals at the forefront of your team’s mission throughout each phase of AIOps maturity. By doing this, your IT organization will be able to achieve the ultimate promise of fully automated operations in a sophisticated, strategic approach.

4. Here’s how to survive working remotely.

The rapid spread of the COVID-19 across the world has forced a trial by fire of remote work at scale, and it has the potential to have long-lasting impacts on the workforce. In response, an article by ITOps Times predicts an initial spike in help desk requests as people leave the office and need all of their software accessible from remote locations.

Three technologies that could enable this are:

• Cloud tech—providing the centralization and scale needed
• Natural language processing and AI—helping us better be able to interpret human language
• Automation—helping take the burden off IT workers

Ultimately, AI-driven help desks could drastically reduce the headaches caused by such an abrupt switch to a completely remote environment, right now, and where-ever the future of the workplace takes us.

5. IoT can protect workers.

An article in IoT For All sites the US Bureau of Labor Statistics finding that workers in construction, agriculture, and manufacturing are reported to have the highest incident rates across industries. Medical expenses for work-related injuries are scoring millions of dollars each year.

IoT can keep up with all processes happening on a work site. Even if your assets are outdated, they can be conjoined to IoT monitoring. A functioning smart environment consists of any number of Wi-Fi-enabled beacons attached to your assets or employees, and a computer with an application to process and display data.

Safety issues the IoT monitors include:

• Improper equipment useImproper equipment use—If a worker isn’t following the approved safety instructions, and there’s a possibility of misuse during the situation, the manager receives a warning about suspicious events or ‘out-of-tolerance’ actions.
• Damaged or malfunctioning machinery incidentsDamaged or malfunctioning machinery incidents—In parallel with tracking safety compliance of your machinery fleet, you can monitor your assets’ health.
• Exposure to hazardous substancesExposure to hazardous substances—Production processes that involve contact with hazardous substances may become less hostile to the workers by implementing real-time biological monitoring.
• Overdue emergency responseOverdue emergency response—As with chemical exposure, monitoring health parameters in a potentially toxic environment can be used to learn about an emergency even before it’s officially reported, or to prevent it if something goes wrong.

IoT-enabled environments in industrial facilities can deliver a significant contribution to a secure working space and employee well-being. There is hardly a parameter you can’t monitor and plenty of actionable insights to gain to ensure safety of your workers.

Who needs the fountain of youth when maturity is so valuable. Without it, we cannot learn from our workplace safety mistakes. Without it, we cannot improve our remote workplace practices.  It helps businesses realize their digital transformation. And it is the foundation for businesses to evolve to AIOps in the future.

Just getting started with AIOps and want to learn more? Read the eBook, “Your Guide to Getting Started with AIOps”>