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If You're Not Monitoring Your APIs, You're Not Monitoring Your Applications

Denis Goodwin

The world we monitor has changed. This change all starts with shifts in software development, the Internet, and the expectations of end users — each evolving rapidly and because of each other. Software development has moved from one development team building end-to-end applications for a mostly homogenous set of users to many teams assembling software components into an application for a more diverse set of users.

The software development shift is driven in part by the growth of the Internet which demands scalable solutions that cannot be built and delivered by a single team and requires a distributed architecture. The reason we build all of this is to serve the needs of a variety of end users. Now, they have high expectations for software performance, led by the prevalence of consumer applications such as Facebook, Instagram, Twitter, YouTube, where everything is fast and mostly seamless.

The Impact of APIs on Application Performance

It is the confluence of these shifts that puts API performance front and center.

The way that software development becomes faster and more scalable is by using APIs to glue together components into applications. More scalable software development and delivery means more time to build the features that attract users. However, the assembled components delivered over a distributed architecture means that it can be tricky to provide the performance that end users expect since there are so many variables.

Since APIs Are Critical To Application Delivery, You Have To Monitor Them

The nature of how and what you monitor has to follow the same path as software development and delivery. Briefly, when software was developed end-to-end and was primarily distributed over a single network, you monitored the network by ping testing everything to make sure it was operating. As software moved outside the intranet, to the Internet, we began to monitor the entire application flow and find problems along the application delivery chain.

Today, there are a variety of monitoring methods that measure performance and availability of web applications from the back-end to the front-end, all to help operation teams manage software and developers to fix problems fast. The monitoring piece, which has been least implemented to date, is direct monitoring of APIs.

The picture that you currently have of your application performance goes blurry every time there is an API involved. If you don’t monitor the API, you can’t tell if a performance problem is in your application, the network, or the API itself. If you don’t monitor your third party APIs, you can’t tell if they are performing properly and within specifications, or if you should replace the API with one that can.

If you don’t monitor your APIs, you impact your Mean Time to Repair, which directly affects your bottom line.

Just as application creation and delivery has changed, application monitoring must change with it.

Denis Goodwin is Director of Product Management, APM, AlertSite UXM, SmartBear Software.

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If You're Not Monitoring Your APIs, You're Not Monitoring Your Applications

Denis Goodwin

The world we monitor has changed. This change all starts with shifts in software development, the Internet, and the expectations of end users — each evolving rapidly and because of each other. Software development has moved from one development team building end-to-end applications for a mostly homogenous set of users to many teams assembling software components into an application for a more diverse set of users.

The software development shift is driven in part by the growth of the Internet which demands scalable solutions that cannot be built and delivered by a single team and requires a distributed architecture. The reason we build all of this is to serve the needs of a variety of end users. Now, they have high expectations for software performance, led by the prevalence of consumer applications such as Facebook, Instagram, Twitter, YouTube, where everything is fast and mostly seamless.

The Impact of APIs on Application Performance

It is the confluence of these shifts that puts API performance front and center.

The way that software development becomes faster and more scalable is by using APIs to glue together components into applications. More scalable software development and delivery means more time to build the features that attract users. However, the assembled components delivered over a distributed architecture means that it can be tricky to provide the performance that end users expect since there are so many variables.

Since APIs Are Critical To Application Delivery, You Have To Monitor Them

The nature of how and what you monitor has to follow the same path as software development and delivery. Briefly, when software was developed end-to-end and was primarily distributed over a single network, you monitored the network by ping testing everything to make sure it was operating. As software moved outside the intranet, to the Internet, we began to monitor the entire application flow and find problems along the application delivery chain.

Today, there are a variety of monitoring methods that measure performance and availability of web applications from the back-end to the front-end, all to help operation teams manage software and developers to fix problems fast. The monitoring piece, which has been least implemented to date, is direct monitoring of APIs.

The picture that you currently have of your application performance goes blurry every time there is an API involved. If you don’t monitor the API, you can’t tell if a performance problem is in your application, the network, or the API itself. If you don’t monitor your third party APIs, you can’t tell if they are performing properly and within specifications, or if you should replace the API with one that can.

If you don’t monitor your APIs, you impact your Mean Time to Repair, which directly affects your bottom line.

Just as application creation and delivery has changed, application monitoring must change with it.

Denis Goodwin is Director of Product Management, APM, AlertSite UXM, SmartBear Software.

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...