Computing environments are becoming increasingly labyrinthine, as businesses adopt hundreds or even thousands of cloud services, often selected by central IT or siloed departments. The problem is worsened by integration efforts that lag far behind rapid, ongoing innovation, including the regular addition of customer-facing apps and functionality.
Six in 10 chief information officers (CIOs) expect that this digital transformation will continue to accelerate. Most IT environments are now multi-cloud and change by the minute, with code quality also slipping given the constant pressure for innovation. Alarmingly, some 63% of CIOs now say their hybrid and multi-cloud setup is so complex that no human team could manage it, according to the research by the software intelligence company Dynatrace.
“The need to constantly innovate, and to transform employee and customer experiences, means systems are getting more deeply complex, and in essence, impossible for many companies to manage,” says Alois Reitbauer, chief technology strategist at Dynatrace. “Businesses are risking a real loss of tech control as they drown in the shifting sea of corporate technology.”
Problems emerging for businesses include unexplained process failure, new deployments causing latencies and outages, and service users not being able to complete transactions. That is aside from damaging security problems, with 71% of security heads recently warning they are not fully confident their codes are free from vulnerabilities before going live. All these problems can quickly erode business revenue and reputation.
Companies’ typical response to these challenges include introducing application performance monitoring (APM), but this often results in far more warnings being generated than can be addressed. The average number of corporate security alerts presented by an APM-based approach is 2,168 per month, and seven in 10 CIOs say their teams are left submerged in manual tasks as a result.
“Businesses end up with a deluge of information that they don’t know what to do with,” Reitbauer explains. “Their monitoring might highlight tens or even hundreds of systems connected to any one problem, meaning a huge amount of work then has to be done to find where the root cause lies and how to fix it, a situation worsened when there are multiple other problems taking place simultaneously.” Many businesses persist with legacy monitoring technology, having stitched together up to 10 monitoring systems, on average delivering observability into only 11% of their IT infrastructure.
Dynatrace’s software intelligence platform is designed for the velocity, volume, and complexity of modern cloud environments, and it is transparent and unbiased. It provides clear factual explanations and actionable priorities based on impact
In addition, the information most businesses find on their systems lacks context. “It’s a bit like having a clinician check someone’s temperature, finding it’s high, but not being given any indications as to events that might reveal the underlying cause,” Reitbauer notes. “They’d have to ask all sorts of questions to get the broader picture and find out what the problem is.” Such questions often then fail, because biases in human thinking typically mean a focus on instinct or recent experiences, which can lead even the sharpest IT professionals to overlook the real causes.
As a result, many businesses are now turning to Dynatrace’s automatic and intelligent observability, which has artificial intelligence for IT operations (AIOps) at the core. Dynatrace’s unified platform is easy to use and rapidly assesses a range of possible questions, analyses what is happening across complex cloud environments in full context and assesses user experience. It sifts through the information to derive clear answers and prioritise urgent remedial action. In the case of security risks, suspicious actions are immediately blocked. “The technology is designed for the velocity, volume and complexity of modern cloud environments, and it is transparent and unbiased. It provides clear, factual explanations and actionable priorities based on business impact,” Reitbauer explains.
A retail business experiencing slow technology performance since a new app deployment, for example, can use Dynatrace to find exactly where and how problems are growing, and determine how teams can optimise the user experience. Meanwhile, a financial firm can detect emerging flaws in user experience and identify remedies, helping teams transition from reactive to proactive. And a life sciences organisation with IT security concerns can visualise potential impact and enable teams to collaborate in response.
As IT infrastructures become ever more sprawling, it is time for businesses to implement intelligent observability and regain control of complex cloud environments. They can do so by moving from a deluge of alerts to a unified platform-based approach. This enables teams to automatically identify root causes, resolve issues quickly, and reduce time spent on manual tasks so they can prioritise innovation.
To learn more about how Dynatrace can help your business, visit dynatrace.com/trial and follow us on Twitter @dynatrace
Q&A: With companies drowning in the complexity of their systems, Alois Reitbauer, chief technology strategist at Dynatrace, explores how businesses can regain control
today
What are the daily frustrations that you see IT, CloudOps and DevOps teams experiencing without reliable observability?
Often people don’t realise the problems they are having in their apps. They may not even know that users can’t log in or that an app isn’t working properly. When they do identify a problem, they may not understand it among the thousands of data points in front of them. This effectively means they are losing control of the technology they use.
Do companies face a challenge choosing the right observability system?
Yes. Typically, companies have acquired several application performance monitoring systems that don’t interact or provide rapidly actionable data in context. Instead, it’s better to start with desired outcomes and ask: “How should problems be identified and resolved?” Usually, this will lead to intelligent root cause and impact analysis, with responses automatically prioritised. This is where smart, AI-powered observability comes in.
What are the benefits of intelligent observability?
Automated problem identification and resolution massively improve decision making while saving a great deal of time and money. AI and automation should be high on every company’s priority list. As more businesses get observability right, it will gradually become the norm for developers to be able to simply create and run technology that works powerfully and reliably, and to quickly remediate problems when they arise.
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