Financial Services Held Back by Soaring IT Complexity - Part 1

Gregg Ostrowski
AppDynamics
Learn more about Cisco

The COVID-19 pandemic broke established barriers to digital transformation in the financial services sector. Planning and budgetary constraints, integration challenges, executive sponsorship and many other traditional stumbling blocks have been blown away by the sheer necessity to push through innovation in response to the pandemic.

Recent AppDynamics research, Agents of Transformation 2021: The Rise of Full-Stack Observability, found that the speed of implementation for digital transformation programs in financial services has increased by three times over the past year, compared to pre-pandemic levels. This is particularly concerning since the financial services sector has historically led the way with digitization and been particularly innovative in the digital experiences it offers customers.

Pandemic-related restrictions and digital transformation have led to a surge in the number of people using online banking and financial services, many for the first time. In response, financial institutions have had to pivot their strategies for a digital-only approach. They've also had to enable large sections (and in some cases all) of their workforces to operate remotely.

In order to achieve this, financial institutions have prioritized and invested in digital transformation on a scale and at a speed never seen before. And, in many cases, technologists are still getting left behind even though the dependencies on technologists have never been greater.

Financial Institutions Surge Towards Cloud-First Strategy

Throughout the pandemic, we saw staggering levels of digital transformation across the financial services sector, in payments, cryptocurrency, foreign exchange, banking and insurance. And it's not just the nimble, evergreen fintechs that are leading the way; many of the most innovative, intuitive digital services and applications are coming from the established, global retail banks.

Much of this innovation at the top end of the market has been driven by an acceleration of cloud computing programs as big banks have significantly ramped up their use of cloud.

One contributing factor from the last 18 months is the massive improvement in the security of public cloud services. We're now seeing major banks and insurance companies becoming far more confident about putting their infrastructure into public clouds, in a way that they might not have prior to the pandemic.

Most financial institutions have now fully embraced a hybrid cloud or multi-cloud model in tandem with their on-premise infrastructures.

Cloud Ramp-Up Leads to Soaring Complexity in the IT Department

The trouble is this shift to the cloud has left many IT departments struggling to manage and optimize health and performance up and down the IT stack. Aside from losing visibility where their application data is hosted, they're also unable to monitor inside and outside of the applications, and technologists are powerless to respond to third-party connectivity issues. This is particularly true when it comes to microservices-based applications requiring observability into the services and underlying infrastructure for large, managed Kubernetes environments running on public clouds.

Our research found that 70% of technologists in the financial services sector are still relying on multiple, disconnected monitoring solutions. This means they don't have a single, unified view on IT performance across the full stack and can't identify issues early so they can be fixed before they impact end users. They're being overwhelmed by complexity and data noise and have no way of identifying what really matters.

Most technologists don't have this unified view on health and performance and so they have no way of knowing how technology decisions and actions are impacting end users. They're being forced to take a "best guess" approach, relying on gut feeling rather than hard data. Lacking the proper tools perpetuates the siloed based environments where technologists only see their slice of the application topology.

Linking IT Performance to Business Outcomes is Essential to Overcome Complexity

Beyond having unified visibility across the IT estate, many technologists in financial institutions are now also looking for a better understanding of how technology issues affect customers and the business. They want a business lens on performance issues so they have the right level of insight to make decisions and prioritize actions based on real-world impact.

Significantly, almost all technologists (96%) across financial services believe that this correlation of IT performance with business real-time data, is now important to drive innovation and deliver faultless digital experiences for end users. By setting the goal of a business outcome, all the teams involved have a clear picture of what their impact is, helping reduce the historically siloed approach.

Start with: Financial Services Held Back by Soaring IT Complexity - Part 2

Gregg Ostrowski is CTO Advisor at Cisco AppDynamics

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Financial Services Held Back by Soaring IT Complexity - Part 1

Gregg Ostrowski
AppDynamics
Learn more about Cisco

The COVID-19 pandemic broke established barriers to digital transformation in the financial services sector. Planning and budgetary constraints, integration challenges, executive sponsorship and many other traditional stumbling blocks have been blown away by the sheer necessity to push through innovation in response to the pandemic.

Recent AppDynamics research, Agents of Transformation 2021: The Rise of Full-Stack Observability, found that the speed of implementation for digital transformation programs in financial services has increased by three times over the past year, compared to pre-pandemic levels. This is particularly concerning since the financial services sector has historically led the way with digitization and been particularly innovative in the digital experiences it offers customers.

Pandemic-related restrictions and digital transformation have led to a surge in the number of people using online banking and financial services, many for the first time. In response, financial institutions have had to pivot their strategies for a digital-only approach. They've also had to enable large sections (and in some cases all) of their workforces to operate remotely.

In order to achieve this, financial institutions have prioritized and invested in digital transformation on a scale and at a speed never seen before. And, in many cases, technologists are still getting left behind even though the dependencies on technologists have never been greater.

Financial Institutions Surge Towards Cloud-First Strategy

Throughout the pandemic, we saw staggering levels of digital transformation across the financial services sector, in payments, cryptocurrency, foreign exchange, banking and insurance. And it's not just the nimble, evergreen fintechs that are leading the way; many of the most innovative, intuitive digital services and applications are coming from the established, global retail banks.

Much of this innovation at the top end of the market has been driven by an acceleration of cloud computing programs as big banks have significantly ramped up their use of cloud.

One contributing factor from the last 18 months is the massive improvement in the security of public cloud services. We're now seeing major banks and insurance companies becoming far more confident about putting their infrastructure into public clouds, in a way that they might not have prior to the pandemic.

Most financial institutions have now fully embraced a hybrid cloud or multi-cloud model in tandem with their on-premise infrastructures.

Cloud Ramp-Up Leads to Soaring Complexity in the IT Department

The trouble is this shift to the cloud has left many IT departments struggling to manage and optimize health and performance up and down the IT stack. Aside from losing visibility where their application data is hosted, they're also unable to monitor inside and outside of the applications, and technologists are powerless to respond to third-party connectivity issues. This is particularly true when it comes to microservices-based applications requiring observability into the services and underlying infrastructure for large, managed Kubernetes environments running on public clouds.

Our research found that 70% of technologists in the financial services sector are still relying on multiple, disconnected monitoring solutions. This means they don't have a single, unified view on IT performance across the full stack and can't identify issues early so they can be fixed before they impact end users. They're being overwhelmed by complexity and data noise and have no way of identifying what really matters.

Most technologists don't have this unified view on health and performance and so they have no way of knowing how technology decisions and actions are impacting end users. They're being forced to take a "best guess" approach, relying on gut feeling rather than hard data. Lacking the proper tools perpetuates the siloed based environments where technologists only see their slice of the application topology.

Linking IT Performance to Business Outcomes is Essential to Overcome Complexity

Beyond having unified visibility across the IT estate, many technologists in financial institutions are now also looking for a better understanding of how technology issues affect customers and the business. They want a business lens on performance issues so they have the right level of insight to make decisions and prioritize actions based on real-world impact.

Significantly, almost all technologists (96%) across financial services believe that this correlation of IT performance with business real-time data, is now important to drive innovation and deliver faultless digital experiences for end users. By setting the goal of a business outcome, all the teams involved have a clear picture of what their impact is, helping reduce the historically siloed approach.

Start with: Financial Services Held Back by Soaring IT Complexity - Part 2

Gregg Ostrowski is CTO Advisor at Cisco AppDynamics

Related Links

Hot Topics

Related Vendors

The Latest

Escaping Pilot Purgatory: How AI Becomes an Operational Advantage

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Closing the Gap in Modern Tech and the Tools Meant to Monitor Them

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

MEAN TIME TO INSIGHT Podcast - Episode 23: NetOps Labor Shortage

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Why FinOps Rewrote Its Mission and What It Signals for Technology Management

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Clearing the Path to AI: Why Vendor Consolidation Matters Now

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Cold Data, Hot Problem: Why AI Is Rewriting Enterprise Storage Strategy

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

Observability at a Crossroads: AI, Economics, Complexity and the Enduring Power of Open Source

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

Explainability Is the New Battleground in AI-Powered Observability

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

Empowering the Human Side of the Autonomous IT Age

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI Scale Is Outpacing Infrastructure - and IT Leaders Are Running Out of Time

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.