Backend systems run the services that API proxies access. In other words, they are the
fundamental reason for the very existence of APIs and the API Management Proxy layer.
Any API request that is routed via the Apigee platform traverses a typical path before it hits the backend:
The request originates from a client which could be anything from a browser to an app.
The request is then received by the Apigee gateway.
It is processed within the gateway. As a part of this processing, the request passes onto a
number of distributed components.
The gateway then routes the request to the backend that responds to the request.
The response from the backend then traverses back the exact reverse path via the Apigee gateway
back to the client.
In effect, the performance of API requests routed via Apigee is dependent on both Apigee and the
backend systems. In this antipattern, we will focus on the impact on API requests due to badly
performing backend systems.
Antipattern
Let us consider the case of a problematic backend. These are the possibilities:
The challenge in exposing the services on these backend systems via APIs is that they are
accessible to a large number of end users. From a business perspective, this is a desirable
challenge, but something that needs to be dealt with.
Many times backend systems are not prepared for this extra demand on their services and are
consequently under sized or are not tuned for efficient response.
The problem with an "inadequately sized" backend is that if there is a spike in API requests,
then it will stress the resources like CPU, Load and Memory on the backend systems. This would
eventually cause API requests to fail.
Slow backend
The problem with an improperly tuned backend is that it would be very slow to respond to any
requests coming to it, thereby leading to increased latencies, premature timeouts and a compromised
customer experience.
The Apigee platform offers a few tunable options to circumvent and manage the slow backend. But
these options have limitations.
Impact
In the case of an inadequately sized backend, increase in traffic could lead to failed
requests.
In the case of a slow backend, the latency of requests will increase.
Best practice
Use caching to store the responses to improve the API response times and reduce the load on
the backend server.
Resolve the underlying problem in the slow backend servers.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-26 UTC."],[[["\u003cp\u003eThis document focuses on how backend system performance impacts API requests routed through Apigee.\u003c/p\u003e\n"],["\u003cp\u003eAPI requests travel from the client, through the Apigee gateway, to the backend system, and then back, making overall performance dependent on both Apigee and the backend.\u003c/p\u003e\n"],["\u003cp\u003eInadequately sized backends can cause API requests to fail due to resource stress during traffic spikes, such as CPU, memory, and load limitations.\u003c/p\u003e\n"],["\u003cp\u003eSlow backends result in increased latency, premature timeouts, and a poor customer experience, even with Apigee's tunable options.\u003c/p\u003e\n"],["\u003cp\u003eCaching and resolving underlying issues in backend servers are best practices to improve API response times and reduce backend load.\u003c/p\u003e\n"]]],[],null,["# Antipattern: Allow a slow backend\n\n*You're viewing **Apigee** and **Apigee hybrid** documentation.\nView [Apigee Edge](https://docs.apigee.com/api-platform/antipatterns/slow-backend) documentation.*\n\nBackend systems run the services that API proxies access. In other words, they are the\nfundamental reason for the very existence of APIs and the API Management Proxy layer.\n\nAny API request that is routed via the Apigee platform traverses a typical path before it hits the backend:\n\n- The request originates from a client which could be anything from a browser to an app.\n- The request is then received by the Apigee gateway.\n- It is processed within the gateway. As a part of this processing, the request passes onto a number of distributed components.\n- The gateway then routes the request to the backend that responds to the request.\n- The response from the backend then traverses back the exact reverse path via the Apigee gateway back to the client.\n\nIn effect, the performance of API requests routed via Apigee is dependent on both Apigee and the\nbackend systems. In this antipattern, we will focus on the impact on API requests due to badly\nperforming backend systems.\n\nAntipattern\n-----------\n\nLet us consider the case of a problematic backend. These are the possibilities:\n- [Inadequately sized backend](#slow)\n- [Slow backend](#inad)\n\n### Inadequately sized backend\n\n- The challenge in exposing the services on these backend systems via APIs is that they are accessible to a large number of end users. From a business perspective, this is a desirable challenge, but something that needs to be dealt with.\n- Many times backend systems are not prepared for this extra demand on their services and are consequently under sized or are not tuned for efficient response.\n- The problem with an \"inadequately sized\" backend is that if there is a spike in API requests, then it will stress the resources like CPU, Load and Memory on the backend systems. This would eventually cause API requests to fail.\n\n### Slow backend\n\n- The problem with an improperly tuned backend is that it would be very slow to respond to any requests coming to it, thereby leading to increased latencies, premature timeouts and a compromised customer experience.\n- The Apigee platform offers a few tunable options to circumvent and manage the slow backend. But these options have limitations.\n\nImpact\n------\n\n - In the case of an inadequately sized backend, increase in traffic could lead to failed requests.\n - In the case of a slow backend, the latency of requests will increase.\n\nBest practice\n-------------\n\n - Use caching to store the responses to improve the API response times and reduce the load on the backend server.\n - Resolve the underlying problem in the slow backend servers.\n\nFurther reading\n---------------\n\n - [Apigee caching internals](/apigee/docs/api-platform/cache/cache-internals)"]]
