Paramountcy of Data Monitoring In A Sea of Application Vulnerabilities

CTO of Dynatrace

In the present world, technical advancements frequently skip over antiquated practices and directly into cutting-edge treatments. In order for organizations to develop and thrive, digitalization is increasingly essential as processes are made more effective, lucrative, and productive.

Adopting the cloud must be flexible because more than half of surveyed organizations in the Asia Pacific are increasing their usage of digital technology. How do businesses manage the enormous flow of data security in the face of such rapid digital change and an increase in the volume of data being produced?

Since they are hosted and made accessible across several networks and clouds, cloud-native apps are vulnerable to security flaws and cyberattacks. When confronted with coordinated cyberthreats coming from everywhere, a tremendous quantity of data is at risk. So, how can companies maintain this cloud migration rat-race while safeguarding one of their most important assets, data? CIO World Asia Spoke with Rafi Katanasho, CTO of Dynatrace about the paramountcy of data monitoring in a sea of application vulnerabilities.

The Downside of Technology Leapfrogging

Asia has seen a huge technological shift that has helped it quickly advance its digital capabilities. However, there is a significant digital gap in the area. The UN Economic and Social Commission for Asia and the Pacific claims that while the pandemic broadened the unequal capacity for change, it also hastened digital adoption. This gap can be closed thanks to technological leapfrogging, but watch out for an excess of technologies that overlap.

Leapfrogging can lead to tool sprawl, which can reduce the visibility of the technological stack when product functions are only sometimes employed. A mishmash of overlapping technologies leads to user annoyance, security threats, operational inefficiencies, technological debt, and a lack of insight into the organization’s processes and operations, in addition to being a financial waste.

Tool rationalization is the solution to this problem. There are a few options you may take, such as using best-of-breed or a single pane of glass. Without the proper skill and vendor support, systems in the latter category run the risk of fast becoming obsolete and producing unacceptable returns on investment.

In the end, these issues negate any advantages that businesses could anticipate from technological advancement. Therefore, the most practical and viable route is to use all-in-one solutions that are built on cutting-edge AI, analytics, and automation capabilities.

Instead of just being another tool, such a platform might assist reveal the opportunities and possible commercial effects of the organization’s tool rationalization efforts.

Cruciality of adaptability and innovation for the growth of business

The pandemic demonstrated how disruption may occur at any time and shatter conventional wisdom. At the same time, problems present chances to advance the company through improved client experiences, innovative and competitive offerings, and a rise in business value.

Asia’s digital boom is a prime example of how opportunity may come from upheaval. For instance, McKinsey says that despite being behind North America and Europe until 2020, Asia has had the greatest worldwide rate of digital adoption.

This is a blatant indication that businesses are afraid of the development in end-user expectations since the nature of the supply of digital services keeps evolving to meet needs. It can be challenging to meet these constantly changing expectations, which is why enterprises require precise information about end users’ digital experiences.

Opportunities, however, can only be taken advantage of if the company is nimble and adaptable enough to ride the wave of upheaval. The ability to accomplish more with less depends on having purpose-built data and AI technologies throughout the whole stack, which is no minor task.

3 key trends in the security and data space

Data-driven models are essential for simplifying corporate operations since data is accumulating at an unprecedented rate. We forecast the following will have a significant influence on digitalization as firms attempt to push the boundaries of what’s feasible through observability, security, and business analytics:

1.Observability is an attribute, not a process

Utilizing all of the value that data has to offer depends on observability and necessitates full access to metrics, traces, and logs. In many contexts where end users struggle with siloed tools, having siloed solutions that only give access to one or two of these sources thwarts effective observability. With a single AI-powered observability platform that can rapidly give solutions including all telemetry data, Dynatrace assists businesses in overcoming this challenge.

2.Context-enriched analysis

It will continue to be possible to uncover new sources of corporate value and efficiency by identifying context based on commonalities, restrictions, pathways, and communities. Contextual data collection, archiving, and use necessitate expertise in developing data pipelines, X-analytics methods, and AI cloud services that can handle many data kinds.

3.DevOps is not just for IT

Making the company quicker and more efficient requires, among other things, encouraging improved communication and teamwork. Working in separate teams that employ various tactics is a thing of the past, never to be seen again. Faster and better releases may be rolled out as a result of open dialogue. Successful businesses nowadays link everyone to enhance important factors like the end-user experience. To be effective, organizations must be able to distribute resources effectively, set boundaries, and have visibility into their total consumption and expenses, for instance.

Staying ahead of competitors in terms of security and risk management

Architectures that are cloud-native and multi-cloud are the foundation of today’s digital revolution. End-to-end observability is therefore crucial. Additionally, it unlocks value from all application security data, enabling exact answers to be retrieved from the growing number of observability data coming from contemporary clouds.

The Dynatrace platform, which combines intelligent automation with a novel method for safeguarding cloud-native apps at runtime, delivers the type of deep observability that supports Development Security Operations (DevSecOps) at scale. This enables a full audit that detects attack pathways and decides on countermeasures, allowing for a rapid examination of logs pertinent to a security issue.