Skip to main content

APM in the API Economy - Part 1

Julie Craig

The following is an edited excerpt from Application Performance Management (APM) in the Digital Enterprise: Managing Applications for Cloud, Mobile, IT, and eBusinessby Rick Sturm (CEO, Enterprise Management Associates), Carol Pollard and Julie Craig (Research Director for Applications, Enterprise Management Associates). The book is available now from Amazon.

APM in the Digital Enterprise was published in March 2017 by Morgan Kaufmann, an imprint of Elsevier. The content covers the gamut of application management-related topics starting with the evolution of APM, to DevOps and Continuous Delivery, APIs and connected systems, User Experience Management, and Distributed/Componentized Applications (see the full table of contents here).

The book combines the knowledge of all three authors, each of whom has worked in the IT industry for 30 years or more. It is well worth a read for IT professionals involved in any stage of application delivery across the lifecycle, IT executives tasked with overseeing application delivery–related activities, and front-line personnel — developers, DevOps professionals, and operations teams — responsible for any aspect of application delivery. Members of the press and others who need to understand APM will also find the book a valuable resource.

This blog condenses some of the key concepts covered in Chapter 11, entitled Application Programming Interfaces and Connected Systems.

“Today, everything is connected to everything.”
—IT manager at a global bank

We live in a world of massively interconnected applications and supply chains. In recent years, the use of Application Programming Interfaces (APIs) has largely replaced technologies such as Electronic Data Interchange (EDI) and custom-written programs for development of new system integrations. APIs are now the de facto industry standard for integrating data and/or functionality across diverse application ecosystems.

The growth of public and hybrid cloud, mobile devices, containers, microservices, and Internet of Things (IoT) has accelerated the need for application and data integrations. Industry standards such as REST and SOAP have facilitated the process. APIs built over these protocols simplify, and, to some degree, standardize the integration process. They reduce the need for the bespoke integrations of the past — which were required to support exotic protocols and proprietary operational systems. In short, APIs have become the standard currency of exchange connecting applications, devices, and companies.

API Providers vs. API Consumers

There are two sides to the API coin: “providing” and “consuming.” Growing numbers of companies are consuming APIs to access data and functionality exposed by other entities. And a large number of companies are acting as API providers, exposing their own systems to those of customers, partners, and suppliers. Many companies are doing both, and some are monetizing access to data or internal systems as part of revenue generation.

The speed and breadth with which API ecosystems have proliferated is impacting APM in a big way. Applications relying on APIs to provide data or functions necessary to complete a transaction — an internet sale, for example — can be slowed or stalled by many of the same factors that can impact other tiered, distributed transactions. At the same time, however, APIs leverage new protocols, connection methodologies, and architectures that may not be supported by traditional APM products and methodologies.

In short, while APIs are the new standard of B2B and B2C interchange, they also introduce new management challenges that many companies are not equipped to address. Usage growth, for example, can be a major problem that can significantly impact performance. In July 2015, EMA published a report called Back to the Future with the API Economy: Management Strategies for a New Wave of Integrated Applications. While the study covered both API consumer and API provider use cases, an examination of the issues facing API providers was particularly interesting.

The top three challenges identified by respondents from companies providing APIs included:

■ High traffic volumes

■ Security of back-end systems

■ Identity and authentication management

As an example of issues relating to high traffic volumes, API providers most commonly indicated between 500,000 and 1 million transactions per month accessing their APIs. However, more than 50% reported 1 million or more transactions per month with a small fraction – 3%-- reporting 1 billion or more. In addition, 85% indicated that transaction volumes were increasing, most often between 10% and 20% per month. This massive growth can tax the resources of existing delivery systems. To make matters worse, many IT organizations do not, as yet, routinely take API-delivered services into account when doing capacity planning.

Participating in the API Economy doesn't stop with providing or consuming APIs. Security, access, metering, chargeback, and other API-related functions also become increasingly relevant as usage increases. And as the number of API provider and/or API consumer connections grows, as more users and applications connect, and as new API versions are created and deployed, the API Economy begins to look more like a maze to be navigated than a straightforward way to flexibly extend organizational borders.

Read APM in the API Economy - Part 2, covering API Management Tools.

Hot Topics

The Latest

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 ...

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

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 ...

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 ...

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 ...

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 ...

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 ...

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 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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

APM in the API Economy - Part 1

Julie Craig

The following is an edited excerpt from Application Performance Management (APM) in the Digital Enterprise: Managing Applications for Cloud, Mobile, IT, and eBusinessby Rick Sturm (CEO, Enterprise Management Associates), Carol Pollard and Julie Craig (Research Director for Applications, Enterprise Management Associates). The book is available now from Amazon.

APM in the Digital Enterprise was published in March 2017 by Morgan Kaufmann, an imprint of Elsevier. The content covers the gamut of application management-related topics starting with the evolution of APM, to DevOps and Continuous Delivery, APIs and connected systems, User Experience Management, and Distributed/Componentized Applications (see the full table of contents here).

The book combines the knowledge of all three authors, each of whom has worked in the IT industry for 30 years or more. It is well worth a read for IT professionals involved in any stage of application delivery across the lifecycle, IT executives tasked with overseeing application delivery–related activities, and front-line personnel — developers, DevOps professionals, and operations teams — responsible for any aspect of application delivery. Members of the press and others who need to understand APM will also find the book a valuable resource.

This blog condenses some of the key concepts covered in Chapter 11, entitled Application Programming Interfaces and Connected Systems.

“Today, everything is connected to everything.”
—IT manager at a global bank

We live in a world of massively interconnected applications and supply chains. In recent years, the use of Application Programming Interfaces (APIs) has largely replaced technologies such as Electronic Data Interchange (EDI) and custom-written programs for development of new system integrations. APIs are now the de facto industry standard for integrating data and/or functionality across diverse application ecosystems.

The growth of public and hybrid cloud, mobile devices, containers, microservices, and Internet of Things (IoT) has accelerated the need for application and data integrations. Industry standards such as REST and SOAP have facilitated the process. APIs built over these protocols simplify, and, to some degree, standardize the integration process. They reduce the need for the bespoke integrations of the past — which were required to support exotic protocols and proprietary operational systems. In short, APIs have become the standard currency of exchange connecting applications, devices, and companies.

API Providers vs. API Consumers

There are two sides to the API coin: “providing” and “consuming.” Growing numbers of companies are consuming APIs to access data and functionality exposed by other entities. And a large number of companies are acting as API providers, exposing their own systems to those of customers, partners, and suppliers. Many companies are doing both, and some are monetizing access to data or internal systems as part of revenue generation.

The speed and breadth with which API ecosystems have proliferated is impacting APM in a big way. Applications relying on APIs to provide data or functions necessary to complete a transaction — an internet sale, for example — can be slowed or stalled by many of the same factors that can impact other tiered, distributed transactions. At the same time, however, APIs leverage new protocols, connection methodologies, and architectures that may not be supported by traditional APM products and methodologies.

In short, while APIs are the new standard of B2B and B2C interchange, they also introduce new management challenges that many companies are not equipped to address. Usage growth, for example, can be a major problem that can significantly impact performance. In July 2015, EMA published a report called Back to the Future with the API Economy: Management Strategies for a New Wave of Integrated Applications. While the study covered both API consumer and API provider use cases, an examination of the issues facing API providers was particularly interesting.

The top three challenges identified by respondents from companies providing APIs included:

■ High traffic volumes

■ Security of back-end systems

■ Identity and authentication management

As an example of issues relating to high traffic volumes, API providers most commonly indicated between 500,000 and 1 million transactions per month accessing their APIs. However, more than 50% reported 1 million or more transactions per month with a small fraction – 3%-- reporting 1 billion or more. In addition, 85% indicated that transaction volumes were increasing, most often between 10% and 20% per month. This massive growth can tax the resources of existing delivery systems. To make matters worse, many IT organizations do not, as yet, routinely take API-delivered services into account when doing capacity planning.

Participating in the API Economy doesn't stop with providing or consuming APIs. Security, access, metering, chargeback, and other API-related functions also become increasingly relevant as usage increases. And as the number of API provider and/or API consumer connections grows, as more users and applications connect, and as new API versions are created and deployed, the API Economy begins to look more like a maze to be navigated than a straightforward way to flexibly extend organizational borders.

Read APM in the API Economy - Part 2, covering API Management Tools.

Hot Topics

The Latest

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 ...

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

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 ...

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 ...

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 ...

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 ...

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 ...

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 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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...