API Development

WSO2 APK + Moesif API Analytics: Drive API Performance and Adoption

WSO2 APK + Moesif API Analytics: Drive API Performance and Adoption

WSO2 APK (WSO2 API Platform for Kubernetes) provides a robust, Kubernetes-native platform for managing APIs. It’s purpose-built for cloud-native teams requiring fine-grained control over APIs in modern, distributed environments. With support for microservices architecture, secure ingress, and service discovery, APK solves the infrastructure side of the API equation.

But API success doesn’t end at infrastructure. Engineering and product teams also need to understand how APIs are used, by whom, and what drives value. True success hinges on delivering value from APIs and ensuring best possible customer experience. Without deep API analytics and behavioral insights, it becomes difficult to optimize performance, troubleshoot issues, and drive API adoption.

That’s where Moesif becomes essential. While APK powers secure, scalable delivery, Moesif powers insight and visibility with powerful monitoring, reporting, and analytics—empowering teams to monitor usage, resolve issues faster, and grow their API programs with data. Moesif enables access to crucial API analytics metrics by retrieving and utilizing data from API dashboards and reports.

In this article, we’ll demonstrate how integrating WSO2 APK with Moesif unlocks better performance, adoption, and long-term value from your APIs.

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Table of Contents

Introduction to API Analytics

API analytics is the process of collecting, analyzing, and interpreting data related to API usage, performance, and behavior. It provides valuable insights into how APIs are being used, which endpoints are most popular, and how to improve API performance and scalability. By leveraging API analytics, businesses can gain a deeper understanding of their API ecosystem, identify trends, and make data-driven decisions to enhance their API offerings.

What is API Analytics?

API analytics is a critical component of API management, enabling businesses to make data-driven decisions about their APIs. It involves collecting data on API usage, performance, and behavior, and using that data to identify trends, patterns, and areas for improvement. By understanding how APIs are being used, businesses can optimize their API strategies, improve user experiences, and drive growth. API analytics helps in monitoring key metrics such as response times, error rates, and usage patterns, providing a comprehensive view of API performance.

Benefits of API Analytics

API analytics offers numerous benefits, including:

  • Improved API Performance and Scalability: By analyzing usage metrics and identifying performance bottlenecks, businesses can optimize their APIs for better performance and scalability.

  • Enhanced Customer Experience: Understanding how users interact with APIs allows businesses to improve the overall user experience, leading to higher satisfaction and retention rates.

  • Increased Revenue and Business Growth: Data-driven insights enable businesses to identify new opportunities, optimize pricing strategies, and drive revenue growth.

  • Better Decision-Making and Strategic Planning: With comprehensive data on API usage and performance, businesses can make informed decisions and develop effective strategies for their API programs.

  • Improved Security and Compliance: API analytics helps in monitoring and identifying security vulnerabilities, ensuring compliance with industry standards and regulations.

  • Enhanced Agility and Responsiveness to Changing Market Conditions: By continuously monitoring API performance and usage, businesses can quickly adapt to changing market conditions and user needs.

What is WSO2 APK?

WSO2 API Platform for Kubernetes (APK) is an open-source, cloud-native API management platform designed specifically for Kubernetes environments. It allows organizations to manage the full API lifecycle—design, deployment, policy, enforcement, and security—while staying aligned with Kubernetes-native principles like declarative configuration and automated scaling. If you’re building microservices and you want agility and resilience, WSO2 APK fits naturally.

APK follows a modular architecture that separates the control plane from the data plane. The control plane defines API configurations and policies, while the data plane handles runtime traffic and enforcement. This separation enhances both performance and security, especially at scale.

APK supports multiple API types out of the box, including REST, GraphQL, and even AI workloads, giving you flexibility across consumer needs. It includes built-in support for deploying APIs directly inside Kubernetes clusters to take full advantage of the platform’s scalability and fault tolerance.

While APK provides basic monitoring capabilities, pairing it with a dedicated API analytics platform like Moesif allows you to understand both operational and business API metrics, empowering your teams to deliver more value from your APIs for customers.

What is Moesif API Analytics?

We’ve designed Moesif as a comprehensive API analytics and monitoring platform that provides deep insights into how customers are using your APIs and how the APIs are performing, all in real time. Moesif goes beyond basic monitoring to offer advanced analytics, as we’ll soon demonstrate in the article. Through Moesif, both engineering and product teams can understand user behavior, troubleshoot issues, and make data-driven decisions confidently. Moesif is built to handle the complexities of modern API programs, including ones with microservices architectures and deployed in Kubernetes environments.

When you want to maximize the benefits of API analytics, it’s important to remember its three primary aspects—collecting, analyzing, and visualizing data related to API usage and performance. Moesif handles that entire process automatically in real time with minimal intervention. Once you set Moesif up, the analytics data collection happens automatically, and becomes available for you in the platform for analysis. Users can download raw data for offline analysis or integrate it into their own visualization tools.

Moesif gives you valuable information like the following:

  • How users interact with your APIs

  • The most popular endpoints, or in business terms, features

  • Areas where performance bottlenecks exist

  • How to improve the overall API experience.

Moesif excels in providing both product-centric and engineering-centric metrics. For product managers, Moesif offers insights into API usage patterns, user segmentation, adoption rates, and retention. This helps them understand the most valuable features, identify opportunities for new features, and track the success of their API products. For engineers, Moesif provides detailed information on API performance, including response time, error rates for API methods, and latencies. Developers can quickly identify and resolve bottlenecks, troubleshoot errors, and make sure the API platform continues to run smoothly.

Benefits of Using WSO2 APK and Moesif Together

By integrating Moesif with APK, you get a unified ecosystem that can perform both API management and API analytics. The power lies in how they complement each other , creating a complete solution to help you succeed in building, deploying, and managing your cloud products.

Extending APK’s Central Intelligence Hub with Actionable Insights

WSO2 APK’s control plane provides the foundation for managing the API lifecycle. However, the control plane’s built-in monitoring often lacks the depth you need for comprehensive analysis of API calls. This is where Moesif steps in. By seamlessly integrating with APK’s data plane, Moesif captures detailed, real-time information about every API call, including user actions like signups. We’re not only talking about surface-level data; Moesif can inspect request and response payloads and the entire context around them, providing granular visibility that APK alone cannot offer. This bridges the gap between managing APIs and truly understanding their usage.

Enhanced Observability

APK gives you the what of API activity—which APIs are being called, at what frequency, and with what basic success and failure rates. Moesif adds to it the why and how, ensuring APIs are functional and accessible. With Moesif, you can find definitive answers to questions like:

  • Why is a particular API experiencing high latency?

  • How are users interacting with different API endpoints?

Moesif’s advanced analytics, including customer segmentation, cohort analysis, and funnel analysis, provide answers to these critical questions. This combined observability empowers teams to move beyond reactive troubleshooting to proactive optimization.

Better Troubleshooting with More Context and Detail

When an API error occurs, WSO2 APK’s logs can indicate that a problem exists. How do you go from there? Moesif gives you the context you need for rapid and effective resolution of problems. As an engineer, you can immediately see the specific user, the exact request, the full response, and even the activities leading up to the error. This frees you from the time-consuming process of manually correlating data from multiple sources. The combination of APK’s infrastructure-level view and Moesif’s detailed API-level view fosters far better and refined troubleshooting processes.

Data-Driven Product Decisions

For product leaders, the integration offers a holistic view of the API program. WSO2 APK gives you peace of mind that the APIs are running smoothly, while Moesif reveals how those APIs are being consumed and contributing to business goals. Are users adopting new features? Which API endpoints are most valuable? Where are users encountering friction? Moesif’s insights, in conjunction with APK’s operational data, provide the complete picture necessary to make informed decisions about API roadmaps, feature development, and overall strategy.

Setting up Moesif with APK

You can set up WSO2 APK with Moesif in four simple steps following the instructions in Moesif WSO2 APK Plugin installation docs. Before you follow these steps, make sure you meet the following prerequisites:

  • An active Moesif account (sign up if you haven’t already)

  • Moesif Application ID

If you sign up, Moesif shows you your Application ID during the onboarding process. You can always get your Application ID anytime by following these steps:

  1. Log into Moesif Portal.

  2. Select the account icon to bring up the settings menu.

  3. Select Installation or API Keys.

  4. Copy your Moesif Application ID from the Collector Application ID field. 

Key Insights: Engineering and Product Metrics

Let’s go through some practical examples to illustrate how Moesif can help engineers and product leaders with valuable insights into their APIs.

Engineering-Focused Metrics

For engineering teams, Moesif provides the toolkit to monitor API performance, troubleshoot issues, and maintain reliability. Let’s explore some examples.

Analyzing Latency

Moesif can analyze latency and error rates of your API in different ways. For example, you can break down performance for individual API endpoints and thus identify bottlenecks that might be plaguing your customers.

You have several prebuilt latency analysis types to get started, including a P90 latency analysis type, along with a maximum and a minimum. You can of course define your own custom analysis by configuring the metrics. For example, here, we use Moesif Time Series  to define a custom P99 metric and break the analysis down across API endpoints.

A P99 performance analysis in Moesif

Monitoring API Error Rates

API errors directly affect customer experience. Especially, in a microservices architecture, you have various components that communicate with one another. Errors can originate from anywhere and it propagates through the system. Moesif’s Live Event Log captures every activity in real time so you have the best visibility into what’s happening.

Moesif also captures all the contextual information like headers and payloads, giving you a broader context for each API call and custom actions. Consider you have an AI product that uses a third-party AI API. These APIs often have custom error messages. Without Moesif, you’ll miss out on that context.

Here’s an example that gives a breakdown of 5xx server errors in a time series analysis. It plots the metric on a per-hour basis and chooses the past 12 days as the period of time to analyze for. Using Group By, the example also categorizes the analysis by response status codes to easily understand the exact error types.

Analyzing hourly 5xx server errors over a 12-day period.

Here’s another cool thing this example does—folding the time series: notice the active-state button beside the analysis period Last 12 Days. The folding or wave-slicing technique helps visualize the periodicity of a time series graph, for example, if you want to understand recurring error patterns or periodic anomalies. In this case, we look for a particular hour where errors rise to especially high levels. This can help you investigate issues like the following:

  • Peak load times overwhelming the API

  • Scheduled maintenance or batch jobs that cause temporary disruptions

  • Time-dependent errors in external services that the API relies on

Let’s see another example:

This example breaks down all errors by their respective HTTP status codes. Moesif’s powerful grouping and segmentation utilities allow you to break down metrics by different criteria and look at them from different perspectives. In this example, we can easily observe and get an idea about the distribution of errors in the API in real time. Let’s say you observe an increasing number of `401 Unauthorized` errors. That can indicate a security issue. If you see a spike in `502 Bad Gateway` errors, it can point to issues in your WSO2 APK instance.

To build a successful API product, you must thoroughly understand your customers and how they consume your API’s services. You need to look at different metrics in various ways to decisively gauge the business impact of your APIs so you can drive growth through precise API product strategy. Let’s go through some examples and demonstrate how Moesif can help.

Analyzing API Adoption

By understanding API adoption trends, you can easily answer product-critical questions like these:

  • Are our newly released APIs gaining traction?

  • Which user segments are adopting them the fastest?

With clear adoption metrics, you can make data-backed decisions to improve marketing efforts and craft better API roadmaps.

Take this example for instance: You’ve recently released a major version of your API, v4. You want to compare its uptake among existing customers relative to the latest release of the prior version. 

The following time series analysis captures API traffic over the last 30 days, categorizing requests by company domains and API versions. To accurately measure API call volume, the analysis applies a Rolling Window function for a more refined trend analysis.

Visualizing API adoption by company.

Analyzing User Engagement

Successful API products prioritize understanding how developers move from onboarding to meaningful engagement. Moesif’s funnel analysis in the customer analytics suite makes it easy to measure this journey—from initial sign-up to first successful call and beyond.

In the following example, we visualize a three-step funnel in a GenAI API product:

  1. Sign-in

  2. First embedding request

  3. 100+ tokens consumption

Funnel analysis in Moesif.

Each step represents a deeper level of engagement, helping teams track both time-to-first-hello-world and time-to-value. With Moesif, you can see exactly how many users complete each step, how long it takes them, and where they drop off. 

This data helps you:

  • Identify onboarding friction and optimize documentation or SDKs.

  • Benchmark the average time-to-first meaningful usage.

  • Spot behavioral patterns that correlate with retention or churn.

Understanding API Usage

If you want to efficiently plan resources and scale, you must understand how customers engage with your APIs. Moesif gives your teams the necessary means to track API traffic volume, pinpoint high-usage endpoints, and analyze long-term trends. With these insights to guide you, you can optimize infrastructure costs and allocate efficiently while avoiding unnecessary over-provisioning. On a strategic level, product teams can double down on this data to strategize API expansion efforts.

And if you’re working with AI-driven applications in APK, Moesif has your back with real-time tracking of AI consumption. You can monitor token usage, analyze API demand, and troubleshoot AI traffic with ease. Since Moesif captures request-response data with deep context, you can filter and break down API usage by factors like rate limits, token consumption, and cost efficiency.

As an example, here we perform a Segmentation analysis to rank the top customers by API call volume. We also observe the average input token usage and related costs for each customer over the past 7 days.

Analyzing top customers based on their input token consumption for an AI API.

Analyzing HTTP Payload

One of Moesif’s most powerful debugging features comes from its detailed request and response payload analysis. When error messages lack sufficient detail, engineers can examine the full API data exchange to dig out the root cause of issues.

If your API handles deeply structured payloads, Moesif makes it easy to navigate, filter, and focus on the most relevant piece of data so you can have a precise and efficient troubleshooting process. For example:

{
  "request_id": "req-xyz-987",
  "timestamp": "2024-11-09T14:45:00Z",
  "response": {
    "status_code": 429,
    "headers": {
      "Retry-After": "60",
      "X-Model-Version": "gpt-4-turbo"
    },
    "body": {
      "error": {
        "code": "rate_limit_exceeded",
        "message": "Token limit exceeded.",
        "retry_after_seconds": 60,
        "usage": {
          "current_tokens_used": 498500,
          "allowed_limit": 500000
        }
      },
      "ai_output": {
        "summary": "The document discusses a fox jumping over a dog.",
        "tokens_used": 750,
        "confidence_score": 0.92
      }
    }
  }
}

To give you an idea what you can achieve with Moesif’s HTTP body analytics, here are some more examples and sample use cases:

  • Consider building an AI-powered medical image analysis API, integrated into WSO2 APK. The system has to process MRI scans, X-rays, and CT images to detect anomalies like tumors and  fractures. For accurate diagnoses, the AI model requires high-resolution image data, patient history, and additional metadata like scan modality and radiologist notes. As a result, payloads can get large and complex, often including base64-encoded images, structured metadata, and deep learning model parameters. With Moesif’s Live Event Log, developers can monitor these payloads in real time. They can troubleshoot image upload failures, optimize API request sizes, and guarantee compliance with medical data regulations.

    Filtering API events by context size in an AI API.

    With Moesif’s granular capture of request-response data, you can analyze their full context and make sure your AI app performs optimally, even when handling large inputs.

  • By using key count operators, you can identify payloads with a high number of keys. This allows you to detect large or overly complex API requests that might slow down performance.

  • Moesif allows you to define custom metrics tailored to your API traffic for insights into user behavior and business performance. For example, in an e-commerce API, tracking the average cart value (ACV) can help pricing strategies and discount optimizations. It’s not your run-of-the-mill metric, but understanding how cart values fluctuate over time gives product teams actionable insights. With Moesif, you can create a scripted field to extract the cart total directly from request or response payloads, for example, Request.Body.cart.total_amount or Response.Body.order_summary.total_price.

AI Explain: AI-Powered Insights

Moesif has introduced AI-driven features into its analytics suite for smarter intelligence, giving you deeper insights from your analysis minimal effort:

  • Smart Search gives you quick navigation across dashboards, workspaces, and alert rules, so you can enjoy a more streamlined workflow.

  • AI Explain, an AI-powered conversational assistant, provides instant insights across API analytics, customer analytics, and alerting, making investigating issues faster and more intuitive.

With these AI-enhanced tools, Moesif simplifies API analytics for both technical and business teams. For engineers, AI Explain serves as an intelligent assistant, summarizing API usage trends and helping detect anomalies. As a result, you have minimal troubleshooting time during incidents. Instead of manually parsing complex data, teams receive concise explanations of what’s happening. Product teams can leverage AI-driven insights to track user adoption trends, identify unusual usage patterns, and measure feature impact.

For instance, in a WSO2 APK-powered embeddings API, AI Explain can analyze adoption trends over time from a time series analysis, providing clear insights into growth, retention, and usage patterns:

Visualizing API growth for an embeddings API.

Then, you interact with Ask AI to quickly analyze and interpret the data:

An example chat session in Ask AI.

Conclusion

Managing and delivering APIs at scale takes more than just a capable gateway. WSO2 APK lays the foundation with Kubernetes-native control and flexibility, but true API success requires visibility into how these APIs drive adoption, retention, and revenue. That’s where you need Moesif. By pairing APK with Moesif, you have the insights to resolve issues faster, optimize, and grow strategically—turning every API call into a growth opportunity.

To see for yourself how, sign up today for a free trial, no credit cards required.

Learn More About Moesif Deep API Analytics with Moesif 14 day free trial. No credit card required. Try for Free

, ,

Abu Sakib

Abu Sakib

Technical Writer at Moesif. Previously @Arcion Labs and @Dgraph Labs.

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