Transfer of large images via HTTP/1.2 or gRPC HTTP/2



A conversation with ChatGPT and Gemini AI Models

As I was wondering about the difference of transferring a large image requested by a client and returned from a server, I asked some AI models about the potential different approaches and benefits between a default HTTP request/response pattern, and what would be the difference in case that communication would use gRPC. To address this just started a conversation with Gemini and ChatGPT.

Here is a copy of that chat with Gemini.

I’ve put my questions as “quoted text” and just copied the responses in the blog post below. Enjoy!

Begining of chat with Gemini

A http request on http 1.2, is that different from a grpc call that is also build on http?

Yes, even though gRPC utilizes HTTP/2 for transport, there are significant differences between an HTTP 1.2 request and a gRPC call built on HTTP/2. Here’s a breakdown of the key distinctions:

Protocol Design:

  • HTTP 1.2: A general-purpose protocol for transferring various data types (text, images, etc.). It relies on a request-response model, where a client sends a request and receives a single response from the server.
  • gRPC: A Remote Procedure Call (RPC) framework specifically designed for high-performance microservice communication. It leverages Protobuf for message serialization and builds upon HTTP/2 for efficient data transport.

Data Serialization:

  • HTTP 1.2: Primarily uses textual formats like JSON or XML for data serialization, leading to larger message sizes.
  • gRPC: Relies on Protocol Buffers, a compact and efficient binary format, resulting in smaller message sizes and faster processing.

Connection Management:

  • HTTP 1.2: Typically requires establishing a new TCP connection for each request, leading to connection setup/teardown overhead.
  • gRPC: Maintains a persistent connection with HTTP/2, allowing multiple requests to be multiplexed over the same connection, reducing overhead.


  • HTTP 1.2: Primarily designed for request-response communication. While chunked encoding can be used for larger data, it’s less efficient than streaming.
  • gRPC: Supports efficient streaming for large data like images, allowing data to be sent in chunks, improving responsiveness.

Error Handling:

  • HTTP 1.2: Relies on generic HTTP status codes for error handling, which might be less detailed.
  • gRPC: Utilizes gRPC status codes and custom error messages within the response, providing more granular error information.

Overall Performance:

  • HTTP 1.2: Can be less performant for large data transfers due to overhead, textual data formats, and connection management.
  • gRPC: Offers better performance for microservice communication, especially for large data like images, due to efficient data formats, streaming capabilities, and persistent connections.

In summary:

While both leverage HTTP/2 for transport, gRPC is built on top of HTTP/2 to provide a more optimized and performant RPC framework for microservice communication. It offers advantages in data format, connection management, streaming, and error handling, making it a better choice for scenarios like transferring large images.

So suppose we have two microservices, A and B. A is requesting an image of 60Mb from B.
A is requesting a different image about every second or so on average.
With HTTP 1.2 such a request would have to be network-initialised for every new request, right?
What happens in the case of grpc? I am assuming microservice A creates a grpc client only once.

You’re correct! In your scenario with microservices A and B, gRPC offers a significant advantage over HTTP 1.2 for frequently transferring large images (like your 60MB example) due to connection management. Here’s how it works:

HTTP 1.2 with Frequent Requests:

  • Microservice A: Needs to initiate a new HTTP connection and send a complete request (including headers and image data) for every image request (roughly every second).
  • Drawback: This leads to frequent connection setup and teardown overhead, impacting performance, especially for large images.

gRPC with Persistent Connection:

  • Microservice A: Establishes a single gRPC connection with microservice B when the client is first created (likely during service startup). This connection remains open for the duration of communication.
  • Image Requests: A sends gRPC requests for each image over the established connection. These requests are lightweight compared to full HTTP requests.
  • Benefits:
    • Eliminates connection setup overhead for each request.
    • gRPC efficiently multiplexes multiple image requests on the single connection (thanks to HTTP/2).
    • Reduces network latency for transferring large images.

Additional gRPC Advantages:

  • gRPC Streaming: As mentioned earlier, gRPC allows streaming large images. This can further improve responsiveness, as B can start sending image data even before A receives the entire request.

In summary:

By establishing a persistent connection with gRPC, microservice A avoids the overhead of repeatedly setting up new connections for every image request. This is particularly beneficial for your scenario of frequent image transfers with a large file size (60MB).

Important Note:

While gRPC offers connection pooling mechanisms to manage multiple connections efficiently, for your specific case with frequent requests and a single server (B), a single persistent connection is likely optimal.

For each gRPC call the same connection that initially is setup between A and B will be maintained by the gRPC golang library? That is, given that the client application just uses the same initialized client for each subsequent call? How would the client call look like when the response is a stream response? Assuming the 60Mb image in one gRPCc response would not fit the nax message size of grpc?

You’re absolutely right. In your scenario:

  1. Initial Setup: The gRPC Golang library manages a persistent connection between microservices A and B when you first create a gRPC client for B. This connection stays open for the duration of your application’s interaction with B (unless explicitly closed).
  2. Subsequent Calls: As you make subsequent gRPC calls for different images (every second or so), the client library reuses the established connection. It sends lightweight gRPC requests over this connection, specifying the desired image details.

Client Call with Stream Response:

Here’s an example client call in Golang assuming the 60MB image response exceeds the gRPC maximum message size:


// Assuming your image message is defined in a .proto file

// Create a gRPC client (likely during application startup)
conn, err := grpc.Dial("localhost:50051", grpc.WithInsecure())
if err != nil {
  // handle error
defer conn.Close() // Close connection when application exits

// Create a client using the connection
client := NewImageServiceClient(conn)

// Define the request message with image details (e.g., image ID)
req := &imagepb.GetImageRequest{ImageId: "image123"}

// Perform the RPC call with streaming response
stream, err := client.GetImage(ctx, req)
if err != nil {
  // handle error

// Receive image data in chunks from the stream
for {
  chunk, err := stream.Recv()
  if err == io.EOF {
    // Image transmission complete
  } else if err != nil {
    // handle error during transmission
  // Process received image chunk data (e.g., write to file)
  // ...


  • We establish a connection and create a client using the connection (likely during application startup).
  • The GetImage RPC call requests an image with specific details (e.g., image ID).
  • Instead of a single response message, the call returns a stream object.
  • We use a loop to receive image data chunks from the stream using Recv().
  • The loop continues until the stream reaches the end (io.EOF) or encounters an error.
  • We process each received chunk of image data (e.g., write it to a file) in the loop.

Important Points:

  • gRPC automatically handles message fragmentation and reassembly on both sides (client and server) due to framing with Protocol Buffers.
  • You don’t need to explicitly manage message fragmentation in your client code.
  • The maximum message size is a configuration option and might be adjusted on the server-side if practical. However, streaming is generally preferred for large data like images.

And how will this compare to the single call per image over http/1.2? Can you give an estimate on the difference on network performance? Suppose that on average there is one image per ten seconds, but sometimes there are five images within one second to be transferred?

Here’s a comparison of gRPC with streaming vs. single HTTP calls per image for your scenario, considering both frequent transfers (every second) and bursts (5 images in 1 second):

HTTP 1.2 (Single Call per Image):

  • Performance:
    • Frequent Transfers: For the average case of one image per 10 seconds, HTTP might seem adequate. However, each request incurs connection setup/teardown overhead, impacting overall performance.
    • Bursts (5 images in 1 second): This scenario significantly highlights HTTP’s limitations. Each image requires a new connection, leading to high overhead and potential network congestion due to frequent connection establishment and termination.
  • Complexity: Implementing HTTP calls is relatively straightforward.

gRPC with Streaming (Persistent Connection):

  • Performance:
    • Frequent Transfers: gRPC shines here. The persistent connection eliminates connection overhead for each image request, leading to faster image transfers even for frequent requests (every second on average).
    • Bursts (5 images in 1 second): gRPC efficiently handles bursts by multiplexing multiple image requests over the existing connection using HTTP/2. This reduces network latency and congestion compared to HTTP’s repeated connection setup.
  • Complexity: Implementing gRPC with streaming might require slightly more effort compared to basic HTTP calls.

Estimated Network Performance Difference:

It’s difficult to provide an exact performance difference as it depends on various factors like network conditions, server processing time, and image complexity. However, here’s a general estimation:

  • Frequent Transfers: gRPC can potentially offer a 20-50% improvement in average transfer time compared to HTTP for frequent image requests due to the persistent connection.
  • Bursts: The performance improvement with gRPC can be even more significant during bursts (5 images in 1 second). It could potentially reduce transfer times by 50-70% or more compared to HTTP, mitigating network congestion issues with repeated connections in HTTP.

Additional Considerations:

  • Latency: gRPC’s lower overhead can lead to lower image transfer latency, especially for frequent requests.
  • Scalability: gRPC’s efficient connection management can improve scalability when handling a high volume of image requests.

In conclusion:

For your scenario with both frequent image transfers (average 1 per 10 seconds) and occasional bursts, gRPC with streaming offers a significant performance advantage over HTTP 1.2. The persistent connection and efficient multiplexing reduce network overhead and congestion, leading to faster image transfers. While there’s some added complexity with gRPC, the performance benefits often outweigh it, especially for large image transfers like your 60MB example.

Can you explain the potential reduction transfer time for bursts? Please assume that the services (microservices written in golang) A and B run on the same machine.

When microservices A and B reside on the same machine, the network performance benefits of gRPC with streaming for image bursts (5 images in 1 second) become even more pronounced. Here’s a breakdown of the potential reduction in transfer times:

Factors Eliminated with gRPC on Same Machine:

  • Physical Network Overhead: Since A and B are on the same machine, there’s no physical network traversal involved in transferring the images. Both HTTP and gRPC would essentially communicate through loopback (localhost).
  • TCP/IP Processing Overhead: The typical TCP/IP connection establishment and teardown overhead associated with HTTP 1.2 for each image request are eliminated.

Remaining Factors and gRPC Advantages:

  • gRPC Multiplexing: Even on the same machine, gRPC with HTTP/2 allows efficient multiplexing of multiple image requests over the single loopback connection. This avoids potential queuing delays associated with separate HTTP requests.
  • gRPC Framing and Streaming: Framing with Protocol Buffers minimizes message overhead, and streaming enables sending image data in chunks, allowing B to start processing data as it arrives (potentially improving responsiveness).
  • OS Communication: Both HTTP and gRPC rely on the operating system for communication between processes. However, gRPC might have slight advantages due to its optimized libraries and potential use of shared memory for data transfer within the same machine.

Estimated Transfer Time Reduction:

While an exact reduction percentage is difficult to quantify due to OS-specific factors, here’s a revised estimation for bursts:

  • Potential Reduction: With gRPC on the same machine, the transfer time for bursts (5 images in 1 second) could potentially be reduced by 70-80% or more compared to single HTTP calls.


Eliminating physical network and TCP/IP processing overheads significantly improves transfer times. gRPC’s multiplexing, framing, and streaming further optimize communication compared to HTTP’s request-response model.

Important Note:

The actual performance improvement might be slightly less than the estimated range, depending on factors like OS scheduling and image processing time on service B. However, gRPC still offers a clear advantage in terms of efficient image transfer coordination, especially for bursts on the same machine.

What is the main difference of http/2 multiplexing as used by gRPC with multiple different http/1.2 requests are made? I’m assuming that when multiple http 1.2 requests are made those could also be run simultaneously to support kind of parallel processing of multiple image transfers per call, although I do understand each http 1.2 call has its own overhead of initializing a new connection. What is the detailed difference between these two options? Please let me know in case I might have made any wrong assumptions.

You’re correct about the overhead of initializing new connections in HTTP 1.2. Here’s a detailed breakdown of the key differences between HTTP/2 multiplexing used by gRPC and multiple HTTP 1.2 requests:

HTTP/2 Multiplexing (gRPC):

  • Single Connection: gRPC leverages HTTP/2, which allows establishing a single connection between client (A) and server (B). This persistent connection remains open for the duration of communication.
  • Multiplexing Requests: Multiple image requests from A can be sent concurrently over this single connection. HTTP/2 prioritizes these requests, allowing for efficient processing even for bursts.
  • Stream-Based: gRPC utilizes streams for large messages (like images). The image data is split into smaller chunks and sent incrementally within the stream. This allows B to start processing data as it arrives, potentially improving responsiveness.
  • Reduced Overhead: By eliminating the need for repeated connection setup/teardown for each image request, gRPC minimizes network overhead.

Multiple HTTP 1.2 Requests:

  • Separate Connections: Each image request from A typically requires a new TCP connection with B. This connection is established, the request is sent, the response is received, and the connection is closed.
  • Limited Parallelism: While browsers can send multiple HTTP 1.1 requests concurrently (limited by the number of connections allowed per domain), this parallelism is limited due to connection overhead.
  • No Streaming: HTTP 1.2 typically transmits the entire image data in a single request/response cycle. This can introduce delays, especially for large images, as B needs to receive the entire image before processing begins.
  • Higher Overhead: The repeated connection setup/teardown for each request adds significant network overhead, impacting performance, especially for frequent requests or bursts.

Your Assumptions:

  • You’re right; multiple HTTP 1.2 requests can be sent simultaneously, but the overhead of managing separate connections limits true parallelism.
  • While HTTP 1.2 allows pipelining to send multiple requests without waiting for responses, this can lead to inefficiencies and is not widely used due to potential head-of-line blocking issues.

In essence:

gRPC’s HTTP/2 multiplexing offers a more efficient and scalable approach for transferring large images, especially for frequent requests or bursts. It reduces network overhead, allows for true concurrent processing of requests, and enables streaming for faster processing on the server-side. While multiple HTTP 1.2 requests can achieve a semblance of parallelism, the connection overhead and lack of streaming make it less performant for large data transfers.

Would there be any good argument to choose not to use grpc then?

While gRPC offers many advantages for microservice communication, there are some situations where choosing not to use gRPC might be reasonable. Here are some potential arguments against using gRPC:

  • Complexity: Implementing gRPC with Protocol Buffers can be slightly more complex compared to basic HTTP requests. Setting up the client and server infrastructure, defining message formats in .proto files, and handling streaming can require additional development effort.
  • Learning Curve: If your development team is unfamiliar with gRPC and Protocol Buffers, there’s a learning curve involved in adopting this technology.
  • Debugging: Debugging gRPC applications can be slightly more challenging compared to basic HTTP requests. Specialized tools might be needed to inspect gRPC messages and streams.
  • Performance Overhead (Small Messages): For very small messages (not the case with your 60MB images), the overhead of gRPC framing and serialization might outweigh the benefits compared to simpler HTTP requests.
  • Limited Ecosystem (Compared to HTTP): While gRPC is gaining traction, the ecosystem of libraries and tools might be less extensive compared to the vast resources available for HTTP.

Here’s a table summarizing the pros and cons to help guide your decision:

ComplexityMore complexSimpler
Learning CurveSteeper learning curveEasier to learn
DebuggingMore challengingEasier
Performance (Large Data)Excellent for large data transfersLess efficient for large data transfers
Performance (Small Data)Might have overhead for small messagesNo overhead for small messages
EcosystemSmaller ecosystem (growing)Larger ecosystem

In conclusion:

For your scenario involving frequent transfers of large images (60MB) between microservices (A and B), the performance benefits of gRPC with streaming outweigh the added complexity. However, consider the factors mentioned above when making the decision for other use cases, especially if dealing with very small messages or a team unfamiliar with gRPC.

==End of chat==

The interesting thing about the AI chatbots is the confidence that they pose. Even after this talk, I can imagine that requesting multiple images from a client to a server via default HTTP/1.2 could still be slightly more performant for other reasons then speed like for memory-usage and CPU usage, so probably we need some type of Benchmarking to ensure ourselves of the pro’s and cons of sending images over the wire via either HTTP/1.2 or HTTP/2 using gRPC… so maybe just ask that as well?

==Start of chat==

Is there any difference in memory usage or CPU usage expected between sending multiple images over HTTP/1.2 or gRPC using HTTP/2? Consider that chunking the image into the gRPC stream-response might take some overhead, or would that not be the case compared to the client/server functionality of using HTTP/1.2?

You’re right, there are potential trade-offs between memory and CPU usage when comparing sending multiple images over HTTP/1.2 vs. gRPC with HTTP/2. Here’s a breakdown:


  • Memory Usage: Lower overall memory usage might be observed on the client-side. Each image requires a separate HTTP request with its own headers. While headers contribute to memory usage, their size is typically smaller compared to the image data itself.
  • CPU Usage: Might have slightly higher CPU usage on both client and server due to:
    • Managing multiple connections: Opening and closing connections for each image request can incur some CPU overhead.
    • Processing individual requests: Parsing headers and potentially decoding the image data on the server can require some CPU cycles.

gRPC with HTTP/2:

  • Memory Usage: Potential for slightly higher memory usage on the client-side due to:
    • gRPC message framing: Dividing the image data into chunks for streaming adds some overhead to the message structure.
    • Persistent connection: Maintaining a single connection for all image requests might consume slightly more memory compared to short-lived HTTP connections. However, this is usually negligible.
  • CPU Usage: Potential for lower overall CPU usage due to:
    • Efficient connection management: Utilizing a single persistent connection eliminates connection setup/teardown overhead for each image.
    • Stream processing: Chunking and sending the image data incrementally can potentially reduce CPU usage on the server compared to processing the entire image in a single request.


While there might be slight differences in memory usage, the impact is usually negligible compared to the image data itself (60MB in your case). The potential CPU usage reduction with gRPC can be more significant, especially for frequent image transfers.

Chunking Overhead:

The overhead of chunking the image into a gRPC stream-response is typically minimal compared to the benefits. Here’s why:

  • Chunking Granularity: Chunks can be relatively large (e.g., several kilobytes) to minimize the number of chunks and their associated overhead.
  • Efficient Framing: gRPC framing with Protocol Buffers uses a compact format for chunk headers, minimizing additional metadata size.

Client/Server Functionality:

Both HTTP/1.2 and gRPC involve client-server communication. However, gRPC offers a more structured and efficient approach with:

  • Protocol Buffers: Define a clear message structure for image data, reducing parsing overhead on the server.
  • Streaming: Enables asynchronous image transfer, allowing the server to start processing data as it arrives (potentially improving responsiveness).

In conclusion:

For transferring multiple large images, gRPC with HTTP/2 offers a good balance between memory usage and CPU efficiency. The persistent connection management and potential for reduced CPU usage outweigh the slightly higher memory usage due to framing. When dealing with massive data transfers, the performance gains of gRPC with streaming often outweigh any minor memory overhead.

End of chat

Still a bit doubtful – the only way to get ensurance is probably to create some Benchmark tests to find out what works best!


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