APIs (Application Programming Interfaces) have become the driving force behind digital transformation and integral to modern software architectures. As API adoption grows, effectively monitoring and analyzing API performance and usage has become critical.
This comprehensive guide will explain everything you need to know about API analytics, including:
- Key capabilities and metrics provided by API analytics platforms
- Leading solutions compared across key criteria
- Use cases showing how companies leverage API analytics
- Best practices for selecting and implementing API analytics
- Sample analytics dashboards and reports
What is API Analytics and Why Does it Matter?
API analytics refers to the practice of monitoring and analyzing the performance, availability and usage of APIs. Key capabilities provided by API analytics solutions include:
Performance Monitoring: Tracking metrics like uptime, latency, error rates to measure reliability and speed of APIs
Traffic Analytics: Analyzing volume, geography, variation and other trends related to API requests
Adoption Analytics: Reporting on consumption from different developer apps and partners over time
Business Analytics: Tying API usage to business KPIs like revenue to demonstrate impact
Robust API analytics provides transparency and visibility that enables organizations to:
- Resolve performance issues quickly
- Inform capacity planning and scaling
- Identify opportunities for improvement
- Engage developers and partners
- Quantify business value of APIs
Key API Analytics Metrics and KPIs
Common metrics and key performance indicators (KPIs) provided by API analytics platforms include:
Reliability KPIs
- Uptime/Availability: Percentage of time API available to service requests
- Error Rates: Percentage of requests resulting in error responses
- Latency: Average and p95 response times for API calls
Traffic KPIs
- Request Volume: Total number API requests over time
- Bandwidth: Data bandwidth consumed by API traffic
- Cache Ratio: Percentage of responses served from cache
- Calls by Geography: Requests segmented by geography
Adoption KPIs
- Daily Active Apps: Number of unique apps with active usage each day
- Integrations Created: New apps registered and provisioned
Business KPIs
- Revenue Impact: Business revenue attributed to API usage
- Cost Savings: Development and operational cost reduction
Comparing Leading API Analytics Solutions
There is a wide variety of API analytics platforms available, from open source tools to commercial solutions. Here we compare some of the most popular options across key selection criteria:
| Solution | Commercial/Open Source | Hosted/On-Prem | Ideal For | Key Differentiators |
|---|---|---|---|---|
| Azure API Management | Commercial | Cloud | Enterprises on Azure | Tight integration with Azure ecosystem |
| Moesif | Commercial | Cloud | Startups/SMBs | Great ease of implementation and reports |
| APImetrics | Commercial | Cloud | Performance monitoring | Real user monitoring from 150+ data centers |
| AppDynamics | Commercial | On-prem/Cloud | Performance management | End-to-end transaction tracing |
| Grafana | Open Source | On-prem/Cloud | Flexible analytics | Broad monitoring for metrics databases |
| Apache APISIX | Open Source | Self-hosted | Open source API gateway | Great for Kubernetes environments |
This table highlights just a sample of the diverse options on the market. The "ideal for" column calls out the typical buyer each platform best serves. Open source platforms require more hands-on implementation but avoid software licensing costs. Hosted cloud platforms provide faster time-to-value but some enterprises prefer on-premises ownership and control.
Real-World API Analytics Use Cases
Here are a few examples of how leading companies leverage API analytics across different functions:
Monitoring Platform Reliability
Uber relies on APIs to power everything from rider defections to food deliveries. By leveraging Moesif for API analytics, Uber monitors availability across countries, enabling them to rapidly detect and troubleshoot any platform issues before significant user impact.
Informing Capacity Plans
Visa manages over 65,000 API calls per second globally during peak seasons. Using API analytics, Visa segments traffic by geography and channel to forecast capacity demands during major shopping events like Black Friday and Cyber Monday.
Quantifying Business Value
The Weather Company analyzes API usage trends to identify and recruit partners in underserved industries. Backed by usage data, their API team made the case for specialized insurance and retail APIs projected to drive over $100M in ecosystem revenue.
Monitoring Partner Integration
When Lowe‘s launched an API partner program, they leveraged API analytics to monitor partner app registrations, token usage and API call trends. This visibility helps them identify high-value partners for technical co-innovation and marketing opportunities.
Correlating Performance to User Experience
By correlating mobile app load times with backend API performance, Walgreens identified serialization issues causing latency spikes. Rapid resolution of these API issues improved mobile conversions by over 20%.
These examples showcase innovative ways leading companies apply API analytics to critical initiatives.
Best Practices for Selecting API Analytics Solutions
If you are evaluating options for adding API analytics capabilities, keep the following best practices in mind:
Define Must-Have Use Cases
Document the critical reasons you need visibility into APIs and key questions you need to answer. This drives tool requirements.
Prioritize Capabilities vs. Data Sources
Leading analytics platforms have connectors for most common data sources. Place more weight on core analytics features.
Validate Scalability
Evaluate ability to handle peak traffic volumes and data retention policies. Over 70% of tool failures stem from underestimated capacity needs.
Review Built-in vs. Custom Reports
Prebuilt reports and dashboards accelerate time-to-insight but custom reporting flexibility ensures a solution can grow with evolving needs.
Test Ease of Investigation
Validate the tool allows easy drilling into logs, traces and raw data to troubleshoot issues identified by reports.
Assess Training and Support
The effectiveness of an analytics platform relies heavily on internal teams knowing how to use it. Assess enablement services and documentation.
Sample API Analytics Dashboards
Here are screenshots illustrating the rich graphical dashboards and reports provided by leading API analytics vendors:
Grafana metrics dashboard showing geographic traffic and latency heatmaps
Azure API Management showing trends for call volume, response code analysis and cached calls over time
Moesif showing API traffic by version, response times by endpoints, and anomalies
The ability to easily create customized, shareable dashboards with graphical visualizations accelerates gaining visibility into API metrics.
Key Takeaways
As APIs continue to drive digital transformation, API analytics and monitoring is critical for reliability, planning and proving business value. This guide provided an overview of:
- Core capabilities and metrics provided by API analytics solutions
- How leading companies leverage analytics across key use cases
- Best practices for evaluating and selecting tools
- Examples of rich out-of-the-box reporting
With metrics-driven visibility and insights into API performance and usage, organizations can proactively optimize platforms, delight customers and align investments to high-value integrations.
