Today’s IT environments are incredibly complex. Companies aim to protect their existing investments, which often include a mix of on-premises and even legacy systems, while simultaneously integrating cloud-based and hybrid systems to enable scalability. This results in significant IT sprawl, making it difficult for organizations to maintain a holistic view of their systems’ performance and health. Adding to this complexity, organizations generate massive amounts of data from a variety of sources and endpoints. Without the right tools, extracting actionable insights from this data can become an overwhelming task. In this exclusive interaction with Tech Achieve Media, Nalin Agrawal, Director – Solutions Engineering at Dynatrace, shares insights into the challenges and opportunities of managing modern IT infrastructure while also sharing his thoughts on how organizations can address these challenges, leverage real-time insights, and implement strategies to enhance efficiency and cost-effectiveness in today’s fast-paced digital landscape.
TAM: How are organizations balancing the need for comprehensive observability with the growing complexity of hybrid and multi-cloud environments?
Nalin Agrawal: This is one of the current challenges that has gained significant attention, especially after insights from Gartner and numerous industry events. It’s a topic many people are actively discussing.
To share some context, our CTO and Dynatrace as an organization focus on long-term strategies, planning for the next decade. Ten years ago, we identified AI as the key area of innovation, and we invested heavily in building AI capabilities. Today, that investment has matured, and our AI solutions are performing exceptionally well.
Looking ahead to the next ten years, our focus is on data. The first challenge is consolidating all data into one place, which is a massive undertaking. The next step is to effectively utilize that data, followed by reaching a point where the data actively works for you, providing insights and answers to complex questions.
In this context, we have invested in what we call a “data lakehouse.” If you observe, most companies today are working on some form of data lakehouse, data warehouse, or related data solutions. However, the challenges they face include ensuring consistent data ingestion, reliable storage, and maintaining data freshness.
These aspects are inherently complex, but we have successfully addressed this complexity with our proprietary solutions. In fact, if you look at the latest Gartner report, Dynatrace has been placed at the top. Notably, for the first time, Gartner has included security as a component of observability, which was previously not part of the framework. This recognition validates our vision and approach as an organization. To sum up, managing data complexity, consolidating it, and deriving actionable insights is the way forward. This is the strategy we are committed to pursuing.
TAM: What role does AI play in simplifying IT operations, and how is it impacting the speed and accuracy of issue detection and resolution?
Nalin Agrawal: For the past 25 years, organizations have faced a consistent challenge: building infrastructure and running applications on top of it. Initially, this meant using physical servers to run applications.
Then came the era of virtualization with hypervisors, promising to simplify everything—some even claimed it would solve all challenges. However, it introduced its own complexities. Next, we saw the rise of orchestration layers, followed by containerization and cloud technologies. Each new layer promised to resolve existing issues but often ended up adding more complexity to the mix.
The core challenge throughout this journey has remained the same: while infrastructure health has improved, application performance has lagged behind. End users have continued to face issues, leading to dissatisfaction.
This is where Dynatrace’s AI has made a breakthrough. Our AI can determine whether an application running on a given infrastructure is performing well. If not, it identifies the root cause. Is the issue with the application itself? The infrastructure? The code? The architecture? The resource sizing? Or perhaps a configuration error?
This capability represents a significant revolution. We call it deterministic AI or causal AI—focused on root cause analysis. This innovation enables organizations to pinpoint and address problems efficiently, ensuring better application performance and, ultimately, improved user satisfaction.
TAM: What are the biggest challenges in extracting actionable insights from the massive data generated by modern IT infrastructures, and how are these being addressed at scale?
Nalin Agrawal: Let’s break down the three key challenges:
1. Data Sources and Integration: The first challenge is that data comes from diverse sources—ERPs, CRMs, cloud infrastructure components, network devices, and more. Bringing all this data together in one place is a significant hurdle. For example, large banks generate 700 to 800 terabytes of data daily. To stay ahead, we focus on building systems capable of ingesting 50 to 60 petabytes of data in a single day and analyzing it within seconds. While this is the goal for many organizations, various complexities arise.
To explain, imagine you enjoy reading books of different genres, like science fiction. If all these books were combined into one massive book, finding specific topics would require an index. Creating and updating that index every time a new book is added would be time-consuming and take up a lot of space. Managing vast amounts of data works in a similar way, and this is where Dynatrace excels by simplifying and addressing such challenges.
2. Data Analysis and AI Integration: Analyzing such massive datasets manually is impossible. This is where AI plays a crucial role, helping to forecast and derive insights from the data. For example, in the insurance industry, businesses track critical metrics such as claim settlements, quotes generated, and orders processed. By analyzing historical data, AI can project future metrics. For instance, it can predict how many claims or orders to expect over the next three months, factoring in seasonality (e.g., January renewals or March investments). This enables businesses to optimize their infrastructure. They can scale up to meet demand during peak periods or scale down during quieter times, saving costs while maintaining performance.
3. Sustainability and Cost Efficiency: In today’s world, sustainability is a critical consideration. By optimizing infrastructure usage, businesses can reduce costs and minimize their carbon footprint. Dynatrace is helping organizations achieve these goals through advanced data analytics and AI-driven forecasting. These are just a few ways Dynatrace supports its customers, enabling them to manage and leverage their data efficiently while aligning with modern sustainability practices.
TAM: How critical is continuous application security in today’s cloud-first environments, and what innovations are reshaping this area?
Nalin Agrawal: In recent times, with India booming thanks to innovations like UPI and widespread digitalization, along with major infrastructure projects, we’ve become a global focal point. However, this rapid growth has also made us a prime target for cyberattacks.
To share some internal insights, several large organizations we work with are facing relentless attacks—sometimes as many as 5,000 within just a few hours. This shows how far things have progressed; the days of simple social engineering are largely behind us. Today, attackers are leveraging advanced methods, and their primary focus is on applications.
Why Target Applications?
The rise of cloud-based and container technologies, combined with the need to reduce time-to-market in a highly competitive environment, has created new vulnerabilities. Additionally, the emotional bond between consumers and organizations is diminishing. Everything revolves around mobile apps now, and the loyalty of customers hinges on the quality of service. If one service doesn’t meet expectations, switching to another is effortless.
Because of this ease of switching, organizations must ensure their services are always available, efficient, and secure. But the pressure to launch quickly often leaves no time to build everything from scratch. Developers frequently rely on third-party libraries—ready-made code written by others—which speeds up development but introduces potential risks.
Many of these third-party libraries are not built with the highest security standards, creating vulnerabilities. Security companies work hard to identify these vulnerabilities and notify organizations to patch or resolve them promptly.
The Evolving Threat Landscape
Modern attackers combine logic with data to identify vulnerabilities in an organization’s environment. Once found, they exploit these weaknesses to breach systems, steal data, or disrupt services. This makes the threat real-time and constant.
Traditional security products, however, operate differently. They perform periodic scans to identify vulnerabilities and alert organizations to take action. But this periodic approach has its limitations. For example, if an issue is patched now, the organization might only know whether it’s resolved after the next scheduled scan—often hours, or even months, later.
The Dynatrace Advantage
Dynatrace has revolutionized application security by making it real-time. We can instantly detect vulnerabilities and determine if they’ve been addressed effectively.
Key benefits include:
- Identifying whether vulnerabilities exist at the moment.
- Checking in real-time if corrective actions have resolved the issue.
- Monitoring whether someone is actively exploiting vulnerabilities or attempting to breach the system.
This real-time capability ensures that organizations are always ahead of attackers, unlike the old approach of delayed scans and periodic updates.
The era of periodic scanning is over. Real-time application security is not just important but it’s essential. And that’s precisely what Dynatrace delivers.
TAM: How is Dynatrace helping enterprises leverage AI-driven insights to improve the cost-effectiveness and performance of their IT operations amid rising digital experience demands?
Nalin Agrawal: Cost is always a factor, whether it’s at home or in the office—it’s the same everywhere, right? As we discussed earlier, the growing complexity of projects, the pressure to reduce time-to-market, and limited budgets, especially in the past two to three years, have made cost management even more critical.
It all starts with justifying the need for money. Organizations are willing to allocate budgets, but only if you can clearly demonstrate why it’s necessary and the potential benefits. And even after justifying the expense and securing the funds, at the end of the year, you’re expected to show the promised results. This heightened focus on cost stems from this scrutiny.
Often, those who can justify their projects well or those working on initiatives backed by influential decision-makers secure the funding. However, not every project gets the green light, which is why cost management has become such a prominent focus.
Why Governance Matters in Growth
Organizations are growing rapidly, making it a great time for business. Investments can yield significant returns if the right strategies are in place. However, with this high growth, a concerning trend has emerged: a lack of governance.
As businesses expand, additional resources are being added liberally to meet growing demands. But without governance, it becomes challenging to track how much is being used and whether these resources are optimized. This raises critical questions:
- What resources are we using?
- Are we using them efficiently?
- Can we optimize further to reduce costs?
The Role of Data and Analytics
Data collection and analytics can provide valuable insights to address these questions. For example, we worked with a customer who heavily relied on cloud resources. Cloud providers typically divide resources into zones across regions—north, central, or south India, for instance—and each zone comes with different costs.
Through analytics, we discovered that most of their cloud components were running in the costliest zone, while other, less expensive zones were underutilized. This insight started a conversation. It gave them visibility into their resource distribution and raised the question: Why are we running everything in high-cost regions when we could shift to more economical zones?
Driving Change Through Visibility
When top management starts analyzing this data and questioning their teams, it initiates a process of change. Although this shift takes time, it fosters a culture of cost-consciousness throughout the organization.
This is the power of data, analytics, and visibility. By providing a clear picture, organizations can identify inefficiencies, optimize resource use, and ultimately reduce costs—all while maintaining growth.
