Cross Cloud A2A Agent Benchmarking

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,"tags":["status","health"]}],"capabilities":{},"defaultInputModes":[],"defaultOutputModes":[]}

and local A2A call:

xbill@penguin:~/a2a-multicloud/benchmark-rust$makea2aSendingA2Astatusrequesttohttp://localhost:8104/...{"id":1,"jsonrpc":"2.0","result":{"contextId":"status-context-id","kind":"message","messageId":"971ff86d-7bfc-4046-858a-16e7857ba9d0","parts":[{"kind":"text","text":"ready"}],"role":"agent"}}

A2A Mersenne Prime Number Agent (Rust GCP)

This agent provides Rust agent that implements the Mersenne generation algorithm Hosted on GCP.

xbill@penguin:~/a2a-multicloud/benchmark-rust-gcp
make deploy
xbill@penguin:~/a2a-multicloud/benchmark-rust-gcp$ make endpoint
https://bench-rust-fgasxpwzoq-uc.a.run.app

Then get the Agent Card:

xbill@penguin:~/a2a-multicloud/benchmark-rust-gcp$make status
Checking Google Cloud Run service status for bench-rust...
NAME STATUS URL
bench-rust True https://bench-rust-fgasxpwzoq-uc.a.run.app
Checking deployed agent health at https://bench-rust-fgasxpwzoq-uc.a.run.app/.well-known/agent.json ...
Agent health check: PASSED (HTTP 200)

To check the Agent Card:

xbill@penguin:~/a2a-multicloud/benchmark-rust-gcp$makecardFetchingagentcardfromhttps://bench-rust-fgasxpwzoq-uc.a.run.app/.well-known/agent-card.json...{"name":"Mersenne Prime Agent Rust","description":"A rust agent that builds a list of the first n Mersenne primes and reports the elapsed time. Configured with model: Not specified.","protocolVersion":"0.3.0","version":"0.1.0","url":"http://0.0.0.0:8080","skills":[{"id":"find-mersenne-rust","name":"Find Mersenne Primes in rust","description":"Finds the list of the first n Mersenne primes in Rust, or calculates a specific Mersenne prime for a given exponent parameter.","tags":["math","benchmark"]},{"id":"check-status-rust","name":"Check calculation status in Rust","description":"Returns 'ready' if no calculation is active, and 'not ready' if a calculation is live.","tags":["status","health"]}],"capabilities":{},"defaultInputModes":[],"defaultOutputModes":[]}

To check that that remote agent can support A2A:

xbill@penguin:~/a2a-multicloud/benchmark-rust-gcp$makea2aSendingA2Astatusrequesttohttps://bench-rust-fgasxpwzoq-uc.a.run.app/...{"id":1,"jsonrpc":"2.0","result":{"contextId":"status-context-id","kind":"message","messageId":"108d0f7c-c2e6-4d1e-8306-843a6dcb999c","parts":[{"kind":"text","text":"ready"}],"role":"agent"}}

A2A Mersenne Prime Number Agent (Rust Azure)

This agent provides Rust agent that implements the Mersenne generation algorithm Hosted on Azure:

xbill@penguin:~/a2a-multicloud/benchmark-rust-azure$ make deploy
All requirements met.
Building the Docker image...
xbill@penguin:~/a2a-multicloud/benchmark-rust-azure$ make endpoint
https://a2a-app-penguin.icyplant-a768d75c.westus2.azurecontainerapps.io

Then get the Agent Card:

xbill@penguin:~/a2a-multicloud/benchmark-rust-azure$make status
mcp-aca-rust-azure is not running locally.
Checking Azure Container App status for a2a-app-penguin...
Name ProvisioningState FQDN
--------------- ------------------- ---------------------------------------------------------------
a2a-app-penguin Succeeded a2a-app-penguin.icyplant-a768d75c.westus2.azurecontainerapps.io
Checking deployed agent health at https://a2a-app-penguin.icyplant-a768d75c.westus2.azurecontainerapps.io/.well-known/agent.json ...
Agent health check: PASSED (HTTP 200)

To check the Agent Card:

xbill@penguin:~/a2a-multicloud/benchmark-rust-azure$makecardFetchingagentcardfromhttps://a2a-app-penguin.icyplant-a768d75c.westus2.azurecontainerapps.io/.well-known/agent-card.json...{"name":"Mersenne Prime Agent Rust","description":"A rust agent that builds a list of the first n Mersenne primes and reports the elapsed time. Configured with model: Not specified.","protocolVersion":"0.3.0","version":"0.1.0","url":"http://0.0.0.0:8080","skills":[{"id":"find-mersenne-rust","name":"Find Mersenne Primes in rust","description":"Finds the list of the first n Mersenne primes in Rust, or calculates a specific Mersenne prime for a given exponent parameter.","tags":["math","benchmark"]},{"id":"check-status-rust","name":"Check calculation status in Rust","description":"Returns 'ready' if no calculation is active, and 'not ready' if a calculation is live.","tags":["status","health"]}],"capabilities":{},"defaultInputModes":[],"defaultOutputModes":[]}

To check that that remote agent can support A2A:

xbill@penguin:~/a2a-multicloud/benchmark-rust-azure$makea2aSendingA2Astatusrequesttohttps://a2a-app-penguin.icyplant-a768d75c.westus2.azurecontainerapps.io/...{"id":1,"jsonrpc":"2.0","result":{"contextId":"status-context-id","kind":"message","messageId":"5d6605f6-9926-481f-b807-8598b81b8cc1","parts":[{"kind":"text","text":"ready"}],"role":"agent"}}

A2A Mersenne Prime Number Agent (Rust AWS)

This agent provides Rust agent that implements the Mersenne generation algorithm Hosted on AWS:

xbill@penguin:~/a2a-multicloud/benchmark-rust-aws$ make deploy
Building the Docker image...
[+] Building 3.8s (10/13) 
xbill@penguin:~/a2a-multicloud/benchmark-rust-aws$ make endpoint
https://a2a-lightsail-rust-aws.6wpv8vensby5c.us-east-1.cs.amazonlightsail.com/

Then get the Agent Card:

xbill@penguin:~/a2a-multicloud/benchmark-rust-aws$make status
Checking AWS Lightsail service status for a2a-lightsail-rust-aws...
------------------------------------------------------------------------------------------------------------------------
| GetContainerServices |
+------------+--------+------------+-----------------------------------------------------------------------------------+
| Deployment | Power | State | URL |
+------------+--------+------------+-----------------------------------------------------------------------------------+
| ACTIVE | nano | DEPLOYING | https://a2a-lightsail-rust-aws.6wpv8vensby5c.us-east-1.cs.amazonlightsail.com/ |
+------------+--------+------------+-----------------------------------------------------------------------------------+
Checking endpoint health at https://a2a-lightsail-rust-aws.6wpv8vensby5c.us-east-1.cs.amazonlightsail.com/health...
Health status: HEALTHY (HTTP 200)

To check the Agent Card:

xbill@penguin:~/a2a-multicloud/benchmark-rust-aws$makecardFetchingagentcardfromhttps://a2a-lightsail-rust-aws.6wpv8vensby5c.us-east-1.cs.amazonlightsail.com/.well-known/agent-card.json...{"name":"Mersenne Prime Agent Rust","description":"A rust agent that builds a list of the first n Mersenne primes and reports the elapsed time. Configured with model: Not specified.","protocolVersion":"0.3.0","version":"0.1.0","url":"http://0.0.0.0:8080","skills":[{"id":"find-mersenne-rust","name":"Find Mersenne Primes in rust","description":"Finds the list of the first n Mersenne primes in Rust, or calculates a specific Mersenne prime for a given exponent parameter.","tags":["math","benchmark"]},{"id":"check-status-rust","name":"Check calculation status in Rust","description":"Returns 'ready' if no calculation is active, and 'not ready' if a calculation is live.","tags":["status","health"]}],"capabilities":{},"defaultInputModes":[],"defaultOutputModes":[]}

To check that that remote agent can support A2A:

xbill@penguin:~/a2a-multicloud/benchmark-rust-aws$makea2aSendingA2Astatusrequesttohttps://a2a-lightsail-rust-aws.6wpv8vensby5c.us-east-1.cs.amazonlightsail.com/...{"id":1,"jsonrpc":"2.0","result":{"contextId":"status-context-id","kind":"message","messageId":"1245ea8c-e8d3-436a-8e27-0b25e90a8a42","parts":[{"kind":"text","text":"ready"}],"role":"agent"}}

MCP Master/Orchestrator Agent (Local Rust)

The final agent follows a slightly different pattern. It provides a minimal agent with several functions (Tools/Skills).

To build-

make
xbill@penguin:~/a2a-multicloud/rust-master$ make lint
Linting the Rust project...
 Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.09s

To get the local endpoint:

xbill@penguin:~/a2a-multicloud/rust-master$ make endpoint
http://localhost:8100

Then use the A2A inspector:

and check the A2A Agent card:

xbill@penguin:~/a2a-multicloud/rust-master$makecardFetchingmasteragentcardfromhttp://localhost:8100...{"name":"master_agent","description":"Master A2A Agent that coordinates prime agents (including rust_agent, gcp_agent, aws_agent, and azure_agent) using model: gemini-2.5-flash.","protocolVersion":"0.3.0","version":"0.1.0","url":"http://0.0.0.0:8100/","skills":[{"id":"coordinate-agents","name":"Coordinate sub-agents","description":"Delegates requests to appropriate sub-agents for weather, time, events, prime calculations, and general greetings.","tags":["coordinator","a2a"]},{"id":"calculate-mersenne-prime","name":"Calculate Mersenne Prime","description":"Calculates Mersenne prime of n using connected sub-agents.","tags":["mersenne","prime","a2a"]}],"capabilities":{},"defaultInputModes":[],"defaultOutputModes":[]}

and A2A status:

xbill@penguin:~/a2a-multicloud/rust-master$ make a2a
Sending A2A status request to http://localhost:8100/...

Antigravity CLI with MCP Connection

The Master Agent starts a FastMCP server interface. This allows Antigravity CLI to be used as a MCP client:

xbill@penguin:~/a2a-multicloud/.agents$moremcp_config{"mcpServers":{"rust-master":{"command":"cargo","args":["run","--manifest-path","/home/xbill/a2a-multicloud/rust-master/Cargo.toml","--quiet","--","--stdio"],"env":{"GOOGLE_GENAI_USE_VERTEXAI":"1","GOOGLE_CLOUD_PROJECT":"aisprint-491218","GOOGLE_CLOUD_LOCATION":"us-central1","GENAI_MODEL":"gemini-2.5-flash","MODEL_NAME":"gemini-2.5-flash"}}}}

The MCP tools can be reviewed:

MCP Servers
Plugins (~/.gemini/antigravity-cli/plugins)
 ✓ google-dev-knowledge Tools: search_documents, answer_query, get_documents
 ✓ rust-master Tools: ask_master_agent, calculate_mersenne_prime, check_agents_status

The agent status can be checked with a MCP call to the Master Agent:

●くろまる rust-master/check_agents_status(Call check_agents_status MCP tool) (ctrl+o to expand)
 I ran the check_agents_status tool from the rust-master MCP server. The check succeeded, confirming that all sub-
 agents are healthy and online:
 • AWS (Remote): ✅ ONLINE (HTTP 200)
 • GCP (Remote): ✅ ONLINE (HTTP 200)
 • Azure (Remote): ✅ ONLINE (HTTP 200)
 • Rust (Local): ✅ ONLINE (HTTP 200)
 ### Summary of Work:
 1. Inspected Makefile & Scripts: Reviewed target definitions ( make status , make a2a ) and script configurations.
 2. Checked Endpoint Health: Verified the agent URL parameters and credentials from .env .
 3. Executed MCP Status Tool: Invoked the lazy-loaded MCP tool check_agents_status from the rust-master 
 coordinator, confirming all remote and local calculation sub-agents are online and ready to accept tasks.

and the agent can be verified:

> ask_master_agent what do you do
●くろまる rust-master/ask_master_agent(Call ask_master_agent MCP tool) (ctrl+o to expand)
 I called the ask_master_agent tool with the query "what do you do".
 Here is the response from the Master Agent:
 │ "I am a Master A2A Agent. I can delegate tasks to specialized sub-agents (Rust, GCP, AWS, or Azure agents) to
 │ calculate Mersenne primes or check exponents."
 ### Summary of Work:
 1. Invoked the MCP Tool: Called ask_master_agent on the rust-master server with the prompt what do you do .
 2. Presented the Results: Relayed the master agent's self-description as a coordinator for distributed multi-cloud
 Mersenne prime calculations.

So What is all this Doing?

All of the setup and configuration allows you to start debugging and visualizing Agent flows using the A2A protocol. The remote Agents haven been validated using the A2A Inspector. The Master Agent acts as a co-ordinator to delegate Mersenne Prime Calculations to remote A2A agents cross cloud.

Time to Starting Running some Numbers!

Now that the individual Agents have been validated — open antigravity and use the MCP tool to start the session:

> what does calculate_mersenne_prime do?
●くろまる Search(Grep search run_a2a_benchmark) (ctrl+o to expand)
 I will view the definition of run_a2a_benchmark (which implements calculate_mersenne_prime ) in rust- 
 master/src/main.rs .
●くろまる Read(/home/xbill/a2a-multicloud/rust-master/src/main.rs) (ctrl+o to expand)
 The calculate_mersenne_prime(n) tool executes a distributed benchmark to find and verify Mersenne primes (2p - 1)
 for exponents from 1 to n.
 ### How it Works:
 1. Assigns Tasks Round-Robin: It iterates through the exponents 1 ≤ i ≤ n and checks the readiness of the connected
 sub-agents (GCP, AWS, Azure, and Local) using a round-robin schedule.
 2. Delegates Computation: Once a ready agent is found, the master agent sends the exponent i to it via the A2A
 protocol. The sub-agent calculates whether 2i - 1 is prime.
 3. Aggregates Timings & Results: It measures the ready check time and the calculation time for each exponent.
 4. Saves Metrics: The benchmark results, including timing data and calculated primes, are compiled into a summary
 markdown table and persisted to disk (e.g., in benchmark_results.json).
 ### Summary of Work:
 1. Source Code Review: Inspected the main.rs function in rust-master/src/main.rs to extract the exact
 program flow and role of each agent.
 2. Explained Mechanics: Highlighted the round-robin task assignment, remote A2A calls, and metrics compilation
 features.

Start the Benchmarking Session

Once all the agents have been started — the Master agent on port 8100 is connected over MCP with Antigravity CLI:


> run the calculate_mersenne_prime with 100
 I will execute the calculation of Mersenne primes up to exponent 100 by querying the Master Agent's HTTP MCP route.
●くろまる Bash(curl -s -X POST -H "Content-Type: application/json" -d '{"jsonrpc": "2.0", "id": 1, "method": ...) (ctrl+o to
expand)
 I will wait for the distributed calculation up to exponent 100 to complete.
 The distributed calculation up to exponent n = 100 has completed successfully!
 ### Distributed Mersenne Prime Generation Report
 • Timestamp: 2026年06月02日T13:40:04-04:00 
 • Cumulative Duration: 55,625.57 ms (~55.6 seconds)
 #### Generated Mersenne Primes
 • 22 - 1 = 3 (via AWS Lightsail)
 • 23 - 1 = 7 (via Azure Container Apps)
 • 25 - 1 = 31 (via GCP Cloud Run)
 • 27 - 1 = 127 (via Azure Container Apps)
 • 213 - 1 = 8,191 (via GCP Cloud Run)
 • 217 - 1 = 131,071 (via GCP Cloud Run)
 • 219 - 1 = 524,287 (via Azure Container Apps)
 • 231 - 1 = 2,147,483,647 (via Azure Container Apps)
 • 261 - 1 = 2,305,843,009,213,693,951 (via GCP Cloud Run)
 • 289 - 1 = 618,970,019,642,690,137,449,562,111 (via GCP Cloud Run)
 ──────
 ### Coordinated Exponent Assignments
 Exponent | Assigned Agent | Ready Check Time | Calc Time | Result
 --------------------|------------------------|----------------------|----------------------|----------------------
 1 | GCP (Cloud Run) | 662.32 ms | 658.00 ms | not prime
 2 | AWS (Lightsail) | 418.86 ms | 117.14 ms | 3
 3 | Azure (Container Apps) | 330.12 ms | 366.37 ms | 7
 4 | Rust (Local) | 30.34 ms | 12.07 ms | not prime
 5 | GCP (Cloud Run) | 651.16 ms | 667.50 ms | 31
 6 | AWS (Lightsail) | 119.91 ms | 103.80 ms | not prime
 7 | Azure (Container Apps) | 337.03 ms | 338.40 ms | 127
 8 | Rust (Local) | 30.31 ms | 13.20 ms | not prime
 9 | GCP (Cloud Run) | 628.36 ms | 621.74 ms | not prime
 10 | AWS (Lightsail) | 108.49 ms | 113.11 ms | not prime
 11 | Azure (Container Apps) | 336.13 ms | 324.22 ms | not prime
 12 | Rust (Local) | 21.45 ms | 15.00 ms | not prime
 13 | GCP (Cloud Run) | 629.91 ms | 662.56 ms | 8191
 14 | AWS (Lightsail) | 111.40 ms | 119.59 ms | not prime
 15 | Azure (Container Apps) | 325.95 ms | 336.56 ms | not prime
 16 | Rust (Local) | 36.22 ms | 13.74 ms | not prime
 17 | GCP (Cloud Run) | 678.16 ms | 635.27 ms | 131071
 18 | AWS (Lightsail) | 111.02 ms | 115.05 ms | not prime
 19 | Azure (Container Apps) | 343.99 ms | 306.91 ms | 524287
 20 | Rust (Local) | 24.83 ms | 25.15 ms | not prime
 21 | GCP (Cloud Run) | 612.20 ms | 610.21 ms | not prime
 22 | AWS (Lightsail) | 103.64 ms | 121.31 ms | not prime
 23 | Azure (Container Apps) | 362.88 ms | 361.34 ms | not prime
 24 | Rust (Local) | 25.12 ms | 14.09 ms | not prime
 25 | GCP (Cloud Run) | 646.72 ms | 641.75 ms | not prime
 26 | AWS (Lightsail) | 98.67 ms | 109.74 ms | not prime
 27 | Azure (Container Apps) | 380.92 ms | 319.36 ms | not prime
 28 | Rust (Local) | 24.17 ms | 17.71 ms | not prime
 29 | GCP (Cloud Run) | 596.21 ms | 615.23 ms | not prime
 30 | AWS (Lightsail) | 110.32 ms | 102.89 ms | not prime
 31 | Azure (Container Apps) | 393.16 ms | 325.54 ms | 2147483647
 32 | Rust (Local) | 20.81 ms | 14.46 ms | not prime
 33 | GCP (Cloud Run) | 616.02 ms | 610.53 ms | not prime
 34 | AWS (Lightsail) | 98.09 ms | 113.49 ms | not prime
 35 | Azure (Container Apps) | 331.80 ms | 396.37 ms | not prime
 36 | Rust (Local) | 27.76 ms | 26.81 ms | not prime
 37 | GCP (Cloud Run) | 626.58 ms | 641.85 ms | not prime
 38 | AWS (Lightsail) | 108.36 ms | 110.98 ms | not prime
 39 | Azure (Container Apps) | 343.18 ms | 341.17 ms | not prime
 40 | Rust (Local) | 30.80 ms | 21.23 ms | not prime
 41 | GCP (Cloud Run) | 606.28 ms | 637.02 ms | not prime
 42 | AWS (Lightsail) | 106.25 ms | 116.14 ms | not prime
 43 | Azure (Container Apps) | 339.94 ms | 318.64 ms | not prime
 44 | Rust (Local) | 21.90 ms | 12.41 ms | not prime
 45 | GCP (Cloud Run) | 628.11 ms | 640.00 ms | not prime
 46 | AWS (Lightsail) | 100.35 ms | 112.84 ms | not prime
 47 | Azure (Container Apps) | 343.33 ms | 323.55 ms | not prime
 48 | Rust (Local) | 19.90 ms | 28.04 ms | not prime
 49 | GCP (Cloud Run) | 643.14 ms | 664.11 ms | not prime
 50 | AWS (Lightsail) | 113.88 ms | 103.43 ms | not prime
 51 | Azure (Container Apps) | 364.66 ms | 317.36 ms | not prime
 52 | Rust (Local) | 22.84 ms | 14.70 ms | not prime
 53 | GCP (Cloud Run) | 617.28 ms | 651.10 ms | not prime
 54 | AWS (Lightsail) | 103.60 ms | 114.45 ms | not prime
 55 | Azure (Container Apps) | 340.59 ms | 323.87 ms | not prime
 56 | Rust (Local) | 26.55 ms | 11.62 ms | not prime
 57 | GCP (Cloud Run) | 635.30 ms | 625.28 ms | not prime
 58 | AWS (Lightsail) | 106.18 ms | 117.21 ms | not prime
 59 | Azure (Container Apps) | 328.18 ms | 336.98 ms | not prime
 60 | Rust (Local) | 16.18 ms | 17.11 ms | not prime
 61 | GCP (Cloud Run) | 621.01 ms | 642.30 ms | 2305843009213693951
 62 | AWS (Lightsail) | 106.05 ms | 115.97 ms | not prime
 63 | Azure (Container Apps) | 322.90 ms | 346.61 ms | not prime
 64 | Rust (Local) | 25.02 ms | 13.26 ms | not prime
 65 | GCP (Cloud Run) | 610.11 ms | 627.14 ms | not prime
 66 | AWS (Lightsail) | 105.60 ms | 107.45 ms | not prime
 67 | Azure (Container Apps) | 337.70 ms | 323.28 ms | not prime
 68 | Rust (Local) | 15.38 ms | 20.14 ms | not prime
 69 | GCP (Cloud Run) | 625.35 ms | 643.10 ms | not prime
 70 | AWS (Lightsail) | 108.00 ms | 108.02 ms | not prime
 71 | Azure (Container Apps) | 323.01 ms | 331.95 ms | not prime
 72 | Rust (Local) | 31.18 ms | 28.03 ms | not prime
 73 | GCP (Cloud Run) | 647.98 ms | 627.10 ms | not prime
 74 | AWS (Lightsail) | 107.88 ms | 112.41 ms | not prime
 75 | Azure (Container Apps) | 351.71 ms | 340.42 ms | not prime
 76 | Rust (Local) | 21.00 ms | 25.80 ms | not prime
 77 | GCP (Cloud Run) | 624.00 ms | 647.06 ms | not prime
 78 | AWS (Lightsail) | 97.09 ms | 111.97 ms | not prime
 79 | Azure (Container Apps) | 337.90 ms | 346.54 ms | not prime
 80 | Rust (Local) | 24.42 ms | 13.95 ms | not prime
 81 | GCP (Cloud Run) | 624.80 ms | 631.11 ms | not prime
 82 | AWS (Lightsail) | 108.87 ms | 107.81 ms | not prime
 83 | Azure (Container Apps) | 332.57 ms | 322.07 ms | not prime
 84 | Rust (Local) | 19.99 ms | 16.02 ms | not prime
 85 | GCP (Cloud Run) | 622.47 ms | 651.63 ms | not prime
 86 | AWS (Lightsail) | 112.12 ms | 107.24 ms | not prime
 87 | Azure (Container Apps) | 332.57 ms | 340.05 ms | not prime
 88 | Rust (Local) | 24.79 ms | 29.77 ms | not prime
 89 | GCP (Cloud Run) | 646.21 ms | 667.60 ms | 618970019642690137449562111
 90 | AWS (Lightsail) | 102.15 ms | 113.82 ms | not prime
 91 | Azure (Container Apps) | 343.99 ms | 342.82 ms | not prime
 92 | Rust (Local) | 29.97 ms | 13.91 ms | not prime
 93 | GCP (Cloud Run) | 661.59 ms | 662.92 ms | not prime
 94 | AWS (Lightsail) | 112.50 ms | 112.80 ms | not prime
 95 | Azure (Container Apps) | 328.13 ms | 337.41 ms | not prime
 96 | Rust (Local) | 26.83 ms | 24.57 ms | not prime
 97 | GCP (Cloud Run) | 636.67 ms | 601.39 ms | not prime
 98 | AWS (Lightsail) | 105.62 ms | 112.77 ms | not prime
 99 | Azure (Container Apps) | 327.66 ms | 327.75 ms | not prime
 100 | Rust (Local) | 31.73 ms | 18.09 ms | not prime
 ──────
 ### Summary of Work:
 1. Invoked Calculation via HTTP Endpoint: Executed the calculate_mersenne_prime call with n = 100 against the
 Master Agent's HTTP POST interface.
 2. Aggregated Results: Processed the response containing two additional large Mersenne primes (261 - 1 and 289 - 1)
 and the complete assignment distribution.

Review Performance

The results of the benchmark are graphed:

Results

Antigravity CLI summarized the results of the Agent Benchmarking:

> summarize key results cross cloud
▸ Thought Process
 Analyzing Cross-Cloud Results
 Here is a cross-cloud summary of the key findings, focusing on architecture, network latency, authentication overhead,
 and calculation behaviors:
 ### 1. Latency & Network Transit Comparison
 The total round-trip time (RTT) for a single round of checks and calculation varies heavily by cloud service model:
 • AWS (Lightsail): ~232 ms RTT (120ms Ready Check + 112ms Calculation)
 • Strengths: Lightsail container instances behave very similarly to standard VMs, offering quick, persistent HTTP
 response times and low network hops.
 • Azure (Container Apps): ~679 ms RTT (341ms Ready Check + 338ms Calculation)
 • Characteristics: Azure Container Apps run inside a managed Kubernetes framework (K8s/Envoy ingress), adding
 slight container routing and warm-up latency.
 • GCP (Cloud Run): ~1,275 ms RTT (635ms Ready Check + 640ms Calculation)
 • Characteristics: Serverless scaling latency, combined with authentication checks, leads to the highest round-
 trip time.
 ──────
 ### 2. The Authentication Overhead (The "Why")
 There is a massive latency difference between GCP and the other clouds, caused by security configurations:
 • GCP Cloud Run: Requires secure OIDC identity authentication. For every single network call, the master agent calls 
 gcloud auth print-identity-token as a local subprocess. Spawning this CLI subprocess on every check and call
 introduces an extra ~300ms to ~500ms of local delay.
 • AWS & Azure: These sub-agents are deployed with publicly accessible HTTP endpoints that do not require OIDC tokens,
 avoiding any local CLI token generation overhead.
 ──────
 ### 3. Latency Symmetry (Network vs. Compute)
 Across all cloud providers, the Ready Check Time and Calculation Time are nearly identical:
 • AWS: ~120 ms vs ~112 ms
 • Azure: ~341 ms vs ~338 ms
 • GCP: ~635 ms vs ~640 ms
 Insight: This symmetry proves that network transport and handshake/auth overhead (ping and TLS/IAM checks) constitute
 over 95% of the latency. The actual math workload (calculating exponent primality) is extremely fast and has
 negligible latency impact at these exponent sizes.
 ──────
 ### 4. Cross-Cloud Protocol Success
 • The master agent successfully coordinated with all three major cloud providers (GCP, AWS, Azure) and the local
 runner.
 • Multi-cloud work distribution successfully validated Mersenne prime candidates, returning identical results
 regardless of which cloud hosting provider did the execution.
 ### Summary of Work:
 1. Analyzed Authentication Mechanics: Explored the main.rs subprocess overhead in the coordinator codebase.
 2. Evaluated Latency Patterns: Compared ready checks vs. calculation times to deduce that network transit and
 security handshakes dominate overall duration.

GCP Remediation

To improve the GCP numbers- the Auth token is preset:

 export GCP_ID_TOKEN=$(gcloud auth print-identity-token)

Then the benchmark is re-run. There is a slight variance on each run:

 Here is a summary of the performance and distribution metrics comparing the cloud providers and the local environment
 from the Mersenne prime calculation run (exponents 1 to 100):
 ### Overall Performance Metrics
 Environment | Tasks Ass... | Cold Start Ready... | Avg Warm Ready T... | Avg Calculation T... | Compute Perform...
 ------------------------|------------|-------------------|-------------------|--------------------|------------------
 Rust (Local) | 25 | 12.23 ms | 21.63 ms | 11.37 ms | #1 (Fastest)
 AWS (Lightsail) | 25 | 544.26 ms | 107.94 ms | 110.79 ms | #2
 GCP (Cloud Run) | 25 | 484.59 ms | 127.31 ms | 135.49 ms | #3
 Azure (Container Apps) | 25 | 20,711.57 ms | 348.39 ms | 354.26 ms | #4 (Slowest)
 ──────
 ### Key Findings
 1. Cold Starts & Overhead (Ready Time):
 • Azure (Container Apps) experienced a significant initial cold start latency of ~20.7 seconds on its very first
 assignment (exponent 3). Even once warm, its ready time overhead (~348 ms) remained roughly 3x slower than AWS
 and GCP.
 • AWS (Lightsail) and GCP (Cloud Run) showed excellent and comparable warm ready times of 108 ms and 127 ms
 respectively, with minor startup penalties (~500 ms) on their first task execution.
 2. Compute Performance (Calculation Time):
 • Local Rust is the fastest (~11.4 ms average) because it runs bare metal without any network traversal, agent
 orchestration, or cloud virtualization overhead.
 • AWS outperformed both GCP and Azure, running calculations in 110.79 ms average.
 • GCP followed closely behind AWS at 135.49 ms average.
 • Azure was the slowest cloud computing node, taking 354.26 ms average—roughly 3x slower than AWS and 2.6x slower
 than GCP.
 3. Mersenne Primes Discovered by Agent:
 • GCP (Cloud Run): Discovered 5 primes (Exponents: 5, 13, 17, 61, 89)
 • Azure (Container Apps): Discovered 4 primes (Exponents: 3, 7, 19, 31)
 • AWS (Lightsail): Discovered 1 prime (Exponent: 2)
 • Rust (Local): Discovered 0 primes (Since tasks were assigned in a round-robin format, the local agent was
 assigned exponents that are multiples of 4 (4,8,12,...), none of which are prime).

Final Results

After adjusting the OIDC token for GCP- the benchmark was re-run:

Summary

The goal of the demo/article was to get basic Agents implemented across multiple clouds and benchmark the Agent performance finding Mersenne primes.

The key to the solution was the A2A (Agent to Agent) protocol. One local and three remote agents were presented — covering various combinations of deployment clouds.

Finally — a Master/Orchestrator agent was started to connect and delegate to the other agents via the A2A protocol. Antigravity CLI was used to connect to the Master Agent over MCP and execute the benchmarks.