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API Management / Frontend Development

Why HTTP Caching Matters for APIs

When users encounter slow load times or delays in response from any web application or API, they are more likely to abandon it. Caching plays a crucial role in improving performance and efficiency. Here's how it works.
Oct 5th, 2023 3:00am by
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When users encounter slow load times or delays in response from any web application or API, they are more likely to become frustrated and abandon the application or website.

User attention spans are short, and a few seconds of delay can make a significant difference in whether a user stays or leaves.

Caching, a technique used to store copies of frequently accessed data, resources, or computed results in a temporary storage location (or cache), plays a crucial role in improving the performance and efficiency of web applications and APIs.

The purpose of caching is to serve subsequent requests for the same data or resources more efficiently by avoiding the need to recompute or retrieve the information from the source. It helps reduce server load, decreases network latency and enhances the overall user experience.

In web development, caching is widely used to optimize the performance of web applications, APIs, and websites. It is applied at various levels of the application stack, including the client-side (browser caching), server-side (server caching), and even intermediate points in the network (content delivery networks, or CDNs).

When a request is made for a resource, the caching mechanism first checks if the requested data is available in the cache. If it is present and hasn’t expired, the cached version is served, which significantly reduces the processing time and network latency.  If the resource is not in the cache or expired, the caching system must fetch the data from the source — a slower, more resource-intensive process.

Caching is particularly effective for resources that are relatively static or don’t change frequently, such as images, stylesheets, scripts and certain API responses. By serving these resources from cache, web applications can achieve faster load times and smoother user interactions.

HTTP caching is a specific implementation of caching for web applications and APIs that relies on the HTTP protocol. It allows web servers and clients to efficiently store and reuse responses to HTTP requests.

The HTTP caching mechanism involves the use of cache-control headers, entity tags (ETags), and expiration directives. These headers provide instructions to clients and intermediaries (e.g., proxies, CDNs) on how to handle caching for specific resources.

Advantages of HTTP Caching for APIs

In addition to helping websites load and respond faster, video streaming also benefits from caching. Streaming platforms cache video content on the user’s device or use edge caching through CDNs. This enables smooth playback without interruptions or buffering since the video data is readily available, reducing playback latency and ensuring a seamless viewing experience.

APIs also perform better thanks to caching. An API that provides product information for an online store can have high traffic and frequent requests for the same products. Caching the API responses allows subsequent requests for the same product details to be served from the cache, speeding up the process.

There are several macro reasons why HTTP caching matters for APIs:

  • Performance improvement. Caching allows frequently accessed data or responses to be stored closer to the client, such as in a browser or a CDN. When a subsequent request is made for the same resource, it can be served directly from the cache without the need to go back to the server, resulting in faster responses, lower latency and reduced network overhead.
  • Reduced server load. By serving cached responses, the server load is significantly reduced as it doesn’t need to process the same request repeatedly. The API can serve the cached response directly to subsequent requests with the same parameters, without involving the database or recalculating the data. This frees up server resources, allowing it to handle other requests or perform more computationally intensive tasks, and significantly reduces the back server’s workload.
  • Bandwidth optimization. Caching minimizes the amount of data that needs to be transferred over the network. Instead of transferring the complete response each time, only the changes or updates need to be sent.
  • Scalability. By offloading repetitive requests from the backend server, the server can handle a higher number of requests. As the application scales, more servers can be added to the infrastructure, and the caching system can efficiently serve cached responses across the newly added servers, bypassing the need for each server to generate the same response independently.
  • Handling traffic spikes. Caching can help mitigate the impact of sudden traffic spikes by serving cached responses instead of overwhelming the server with a high volume of requests. This improves the application’s resilience and prevents service disruptions during periods of increased demand.

However, caching is not always suitable for all types of data or API responses. Certain resources, such as real-time data or personalized content, may require dynamic retrieval on each request. Additionally, caching needs to be carefully managed to ensure that cached data remains fresh and consistent, especially for frequently changing resources.

To take advantage of caching in APIs, HTTP caching mechanisms such as cache-control headers (e.g., Cache-Control and Expires) and entity tags (ETags) can be employed to control caching behavior. These mechanisms allow developers to specify caching rules, cache expiration times, and handle cache invalidation effectively.

How Caching Minimizes Data Transfer

When a client requests a resource that is available in the cache, the server can serve the cached version directly, without transferring the entire resource over the network. This is especially important in terms of minimizing data transfer when requesting a resource.

In some caching strategies, especially for dynamic resources, the cache can store not only the complete response but also the individual elements or changes that make up the response. This approach is known as “delta caching” or “incremental caching.”

Instead of sending the complete response, delta caching sends only the changes or updates made to the cached version of the resource. The client can then apply these changes to the cached version, resulting in the latest version of the resource. This way, the transfer of data is further minimized, especially when dealing with large resources or data that changes only partially.

Delta caching is particularly useful for scenarios where resources change frequently, but the changes are relatively small compared to the complete resource. For example, in a collaborative document editing application, delta caching can be employed to send only the changes made by a user to a shared document, instead of sending the entire document every time it is updated.

How Caching Improves Resilience

Caching enhances application resilience by reducing the risk of service disruptions during periods of high demand. By serving cached responses, even if the backend servers experience temporary performance issues, the application can continue to respond to a significant portion of requests from the cache.

The caching layer acts as a buffer between the backend servers and the clients. It absorbs the impact of sudden spikes in traffic and helps maintain stable response times, even under challenging conditions.

Additionally, caching contributes to improved overall application availability. When backend servers are temporarily unavailable due to maintenance or other issues, the cached responses can still be served, ensuring that users can access critical resources without interruption.

How to Manage Cache Freshness and Consistency

Managing cache freshness and consistency is crucial to providing users with up-to-date information and a seamless experience. To achieve this, several strategies can be implemented

Cache-Control HTTP headers play a vital role in managing cache freshness. By using appropriate Cache-Control headers like max-age and s-maxage, developers can set expiration times for cached resources. These headers define how long the cached data remains valid and can be used by clients and intermediaries to determine when to revalidate the cache.

Additionally, headers like must-revalidate or proxy-revalidate can be used to ensure that the cache is revalidated with the origin server before serving cached data, preventing the delivery of stale content.

Conditional requests using “Last-Modified” and “ETag” headers enable efficient cache validation. When a client makes a subsequent request, it can include the If-Modified-Since or If-None-Match headers, containing the timestamp or ETag of the cached resource. The server then compares this information with the current version of the resource.

If the resource hasn’t changed, the server responds with a 304 Not Modified status, prompting the client to use its cached version, thus minimizing data transfer and latency.

Cache invalidation is essential to keep cached data up-to-date. Implementing cache invalidation mechanisms allows the application to update cached data when the original resource changes. Cache purge or cache-busting techniques can be employed to remove outdated or invalid data from the cache, ensuring that users receive the most recent information when requesting resources.

Cache replication across servers is necessary to maintain consistency in distributed caching systems. It ensures that cached data is accessible and synchronized across all cache instances, eliminating the risk of serving inconsistent information to different users.

Additionally, setting shorter cache expiration times for rapidly changing data helps reduce the likelihood of serving stale content, ensuring a more reliable user experience.

An Introduction to Cache-Control Headers and ETags

HTTP caching mechanisms are built on cache-control headers and entity tags (ETags), which provide instructions to clients and intermediaries (e.g., proxies, CDNs) on how to handle caching for specific resources.

Cache-Control headers and ETags play a crucial role in controlling caching behavior to ensure resources are efficiently cached and served. Here’s what they are and how they influence caching.

Cache-Control Headers

Cache-Control headers are used in HTTP responses to specify caching behavior for resources. They allow developers to control various aspects of caching, such as cache duration, cache validation, and cache revalidation. Common Cache-Control headers include the following:

Public: Indicates that the response can be cached by any client, including shared proxies.

Private: Specifies that the response is intended for a specific user and should not be cached by shared proxies.

Max-age: Sets the maximum time in seconds for which the response can be cached by the client or intermediary.

S-maxage: Similar to max-age, but applies only to shared proxies and overrides max-age for shared caches.

No-cache: Tells the client to revalidate the resource with the server before using a cached copy.

No-store: Instructs the client and all intermediaries not to store any part of the response.

Public and private directives allow servers to specify whether a resource can be cached by shared proxies or is intended for specific users.

Max-age and s-maxage define the maximum time a resource can be cached. Clients and intermediaries use these values to determine cache expiration.

No-cache forces the client to revalidate the resource with the server before using cached data, ensuring the client always receives fresh data.

No-store prevents caching of sensitive or confidential data to enhance security.

Entity Tags (ETags)

ETags provide a way to validate cached resources without transferring the entire resource. They are unique identifiers assigned to resources by the server.

When a client makes a request, the server includes the ETag in the response headers. Clients include the ETag in subsequent requests, and the server compares it to the current version of the resource. If the resource hasn’t changed, the server responds with a 304 Not Modified status, and the client can use its cached copy, reducing bandwidth and latency.

The client can then use the ETag in subsequent requests to check if the resource has changed on the server.

Best Practices for Cache Configuration and Cache Invalidation

To optimize caching behavior and prevent serving stale data, consider the following best practices

  • Use proper Cache-Control headers. Set appropriate Cache-Control headers based on the resource’s characteristics. Use public for resources that can be cached by shared proxies, and private for resources specific to individual users.
  • Set appropriate cache durations. Set sensible max-age and s-maxage values based on the frequency of resource updates and the expected freshness requirements of the content.
  • Avoid overcaching. Be cautious about caching resources that change frequently, such as real-time data. Use shorter cache durations or must-revalidate to ensure fresh data is served.
  • Use ETags for validation. Employ ETags for resource validation, especially for larger resources. ETags reduce data transfer by allowing clients to check resource freshness without downloading the entire resource.
  • Implement cache invalidation. Define a cache invalidation strategy to update cached data when resources change. Use cache purging or cache busting techniques to remove outdated data from the cache.
  • Combine ETags with Last-Modified. Use ETags in combination with the Last-Modified header for more robust cache validation. The server can revalidate the resource if the ETag matches but the Last-Modified date differs.
  • Test and monitor caching behavior. Regularly test and monitor caching behavior to ensure it aligns with the application’s requirements. Use technology like browser developer tools or HTTP caching proxies to inspect caching headers and responses.

Scenarios Where Caching May Not Be Suitable

While caching is an effective strategy for improving performance, there are certain scenarios where caching may not be suitable or can lead to undesirable outcomes. Some of these scenarios include:

  • Real-time data. Caching is not appropriate for real-time data that changes rapidly and frequently. Examples of real-time data include stock market prices, live chat messages, or live tracking data. Caching such data can lead to outdated information being served, which can be misleading or even harmful in critical applications.
  • User-specific or personalized content. Caching user-specific content, such as personalized recommendations, user settings, or user-specific data, can result in incorrect data being served to different users. Such personalized content should be generated on the fly for each user’s unique context and should not be cached in a way that is shared across different users.
  • Sensitive data. Caching sensitive or confidential information, such as personally identifiable information (PII), financial data, or login credentials, can pose significant security risks. Storing such data in the cache increases the exposure of this information and may lead to unauthorized access.
  • Large files or resources. Caching large files, such as videos or high-resolution images, can consume significant storage space in the cache and lead to cache eviction issues or slower cache lookups. It may be more efficient to rely on other content delivery mechanisms for serving large files.

To handle real-time data and personalized content, caching strategies need to be adapted in the following ways:

  • Cache expiration and eviction. For real-time data, set short cache expiration times or use the no-cache directive to ensure the cache always checks with the origin server for fresh data. Personalized content should avoid caching at the individual user level but can be cached for anonymous users, with personalized components inserted dynamically on the client side.
  • Cache segmentation. Personalized content can be cached at a segment level, where non-user-specific parts are cached, and the personalized components are assembled on the fly during the request-response cycle. This approach balances caching benefits while maintaining data accuracy.
  • Dynamic updates. For data that changes frequently, use technologies like WebSocket or Server-Sent Events (SSE) to push real-time updates to the clients. This way, the clients can receive live updates without relying on cached data.


Optimizing performance and user experience is critical for the success of web applications and APIs. Users today have high expectations for fast, seamless and responsive interactions. Slow load times and unresponsive interfaces can lead to user frustration, abandonment and negative brand perception.

It’s essential to strike a balance between caching and data freshness. Real-time data and personalized content should be managed carefully to ensure users receive up-to-date information. Cache configuration and cache invalidation strategies should be carefully designed to avoid serving stale data and to maintain data accuracy.

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