As a prime API gateway, Azure API Management (APIM) enables the smooth flow of information between services and their consumers. However, APIM has some challenges, such as poor API response times, which result in user experience issues, application instability, and service disruptions. Understanding the reasons why APIs perform poorly and devising appropriate solutions is vital to maintaining good API functionality.
This article will analyze some of the most common issues associated with the slow performance of APIs in Azure APIM and suggest practical ways of solving and optimizing poor-performing APIs. It will also highlight the importance of performance monitoring for avoiding repetitive underlying problems and how tools like Site24x7 can help you achieve it.
Common causes of slow API response times in APIM
Understanding why APIs are slow is the first step towards resolution. We have highlighted a set of common reasons for slow API response times in Azure APIM to help you troubleshoot better.
- Back-end service latency: Slow database queries or un-optimized back-end processing increases API response times.
- An overloaded API gateway: High traffic spikes can exceed API gateway limits, causing delays or dropped requests.
- Inefficient policies and transformations: Unnecessary processing, such as excessive logging or data transformations, adds latency.
- Networking and connectivity issues: Slow communication between the cloud, on-premises, or external services increases response times.
- API rate limiting and throttling: Strict rate limits can unintentionally delay or block valid transaction requests.
- Inefficient caching strategies: Not caching frequently requested data leads to repeated back-end queries and slower responses.
Now, let's explore some common reasons for slow response times using a few generic transaction requests as examples. These requests can include payment processing, order placement, profile updates, form submissions, ticket bookings, and search queries.
1. Back-end service latency
A user submits a transaction request, but due to inefficient database queries, the back end takes longer than expected to retrieve and update records, causing a noticeable delay in the API response. If the API back end is slow to process requests, the overall response time increases, leading to delays.
2. An overloaded API gateway
A sudden surge in users submitting transaction requests causes the API gateway to hit its processing limits, leading to delayed responses or dropped requests. When API calls exceed the APIM service's capacity, processing delays and throttling occur.
3. Inefficient policies and transformations
The API applies multiple transformation policies to every incoming transaction request, including redundant XML-to-JSON conversions. These extra processing steps introduce latency before the request even reaches the back end. Poorly configured API policies—such as excessive logging, unnecessary transformations, or complex processing rules—can also impede response times.
4. Networking and connectivity issues
The transaction request is routed through a hybrid cloud setup that involves an on-premises database. Slow communication between the cloud API and the on-premises database increases the response time. Latency in Azure Virtual Network (VNET) integration, hybrid connections, or external dependencies can also contribute to slow responses.
5. API rate limiting and throttling
When a user makes several transaction requests in a short period of time, a strict rate limiting rule is triggered. While the user's requests are valid, indicating the user is not abusing the system, the requests are delayed or blocked. Therefore, in attempts to mitigate abuse, rate limiting policies can sometimes impede a legitimate user and their requests.
6. Inefficient caching strategies
Instead of caching common validation results for transaction requests, the API repeatedly queries the back end for the same data. This increases the load and slows down response times, even when the information hasn't changed. Not utilizing response caching forces APIs to process repeated requests, adding an unnecessary back-end load.
Step-by-step strategies to resolve slow API response times
1. Analyzing and solving the latency time for the back-end service
- Determine the response time for the service request from the back end in Azure Application Insights.
- Optimize the speed of execution for the database queries and associated indexes.
- Add more back-end instances to cope with higher loads while still guaranteeing a responsive service.
2. Optimizing API gateway performance
- Monitor your APIM instance load using Site24x7's integration with Azure Monitor metrics, including Azure Event Hubs events, gateway requests, capacity units, and back-end latency indicators.
- Upgrade the APIM pricing tier if traffic consistently exceeds the available capacity.
- Use autoscaling to allocate resources dynamically based on the API load.
3. Improving procedures and policies about the API
- Use the Azure API Inspector to track policies with timers to analyze their lagging execution times.
- Eliminate unnecessary transformations like the overuse of converting XML into JSON and vice versa.
- Reduce the processing overhead in policy tracing that is not enabled for inefficient policies by default.
4. Optimizing performance for hybrid connectivity networks
- Locate network delays by checking the latency for Azure Private Link and VNET integration.
- Decrease the latency for on-premises and cloud services using ExpressRoute on hybrid connections.
- Lower cross-region latency through regional APIM deployment.
5. Making adjustments to throttling and rate limiting
- Use Azure APIM Analytics to monitor rejected API calls to confirm legitimate users are not affected.
- Incorporate dynamic rate limiting based on the user type rather than static limits.
- Reconfigure API throttling policies and the number of allowed calls to strike a balance between API performance and protection.
6. Caching for improved response times
- Reduce unnecessary calls to the back end for frequently retrieved API responses by enabling response caching.
- For advanced caching strategies, incorporate Azure Cache for Redis.
- To ease the back-end load, set the time to live to refresh the data at selected intervals while ensuring data freshness.
Addressing slow API responses is important, but preventing performance issues requires continuous oversight. Adding Site24x7's REST API monitoring along with your other monitoring layers gives you precisely that. While our monitoring tool for Azure focuses on APIs within the Azure ecosystem, our REST API monitoring extends visibility to APIs deployed anywhere, whether they are hosted in Azure, on other cloud platforms, or on premises. It ensures high uptime and availability, detects latency spikes, monitors third-party dependencies, and tracks performance trends and functional accuracy in a variety of environments.
How Site24x7 helps optimize APIM performance
- Real-time API latency monitoring: Monitor request and response times across exposed and accessible API endpoints, particularly those that are publicly accessible, to detect slowdowns early. Note that internal API endpoints may not be monitored if they are not exposed to external networks.
- Automated anomaly detection: Identify sudden spikes in API latency and processing delays before they affect users.
- Custom alerts for API performance deviations: Receive immediate alerts when response times cross defined thresholds.
- End-to-end transaction tracing: Gain deep visibility into API calls, back-end services, and policy execution times.
- API availability monitoring: Ensure high uptime and detect failures with proactive API health checks.
Conclusion
Performance issues in APIM aren't always rooted in one specific layer. They could stem from back-end service delays, inefficient policy execution, a gateway overload, or even regional network latency. Pinpointing the exact cause requires comprehensive visibility into every moving part of your API infrastructure.
This is where Site24x7's Azure monitoring plays a critical role. It offers deep observability into your Azure APIM instance by tracking key metrics like back-end response times, cache hit ratios, policy evaluation durations, rate limiting thresholds, and throttled requests—all in real time. These insights help DevOps and platform teams quickly identify where slowdowns are occurring, whether within the API gateway, in the back-end services, or due to misconfigured policies.
Site24x7's REST API monitoring acts as a complementary layer to extend this observability beyond Azure. It simulates real-world API calls from global endpoints, monitors availability, measures latency, and validates response payloads, ensuring your APIs deliver consistent performance across regions and external dependencies. In addition to traditional RESTful endpoints, Site24x7 also supports monitoring gRPC calls (which are essential for high-performance, low-latency service-to-service communication) and GraphQL queries (which enable efficient data retrieval tailored to client needs). This ensures comprehensive coverage across modern API architectures, regardless of the protocol.
Include Site24x7 in your monitoring strategies and empower your teams to proactively detect, isolate, and resolve API performance issues before they affect users, making Site24x7 a powerful ally in maintaining high-performing APIs within Azure ecosystems and beyond.
