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Code Wizards reported that Nakama Enterprise on Heroic Cloud sustained about 2 million simultaneously connected simulated clients across three AWS-backed tests in 2024. The peak was 2.05 million clients in a connection-and-heartbeat test; separate scenarios exercised chat fan-out and database-backed requests. Code Wizards CTO Martin Thomas said the system appeared capable of going higher, but the published results do not establish a maximum capacity or a universal limit for Nakama deployments.
At a glance: what the 2 million CCU result means
| Measure | Reported result |
|---|---|
| System tested | Nakama Enterprise on Heroic Cloud, using AWS infrastructure |
| Peak connected clients | 2,050,000 in the basic-stability scenario; 2,020,000 in the realtime-messaging scenario |
| Test design | Three four-hour scenarios, with the database restored to a common clean baseline between tests |
| Basic stability | 683 account creations per second and a reported 0% error rate in that scenario |
| Realtime messaging | 1.93 billion messages sent and 11.33 billion received; peak average rates of 44,700 sent and 270,335 received per second |
| Database-bound workload | About 22,300 requests per second; reported p95 server-request processing time below 26.7 ms |
| Main qualification | These were simulated clients and specific synthetic workloads, not a complete commercial game simulation |
The original announcement appeared on September 11, 2024. GamesBeat’s related page was updated June 18, 2025, but the benchmark itself was conducted in 2024, not in 2026. The detailed methodology and figures are published by Code Wizards; the results were also reported by GamesBeat and reproduced on Heroic Labs’ blog.
What was tested—and what CCU counts
CCU means concurrently connected users or clients. Here, the load came from simulated worker clients. The published account describes connections and generated activity; it does not show two million human players simultaneously playing a particular released game.
The product under test was Nakama Enterprise, Heroic Labs’ commercial enterprise offering, deployed on Heroic Cloud. The described Nakama estate used Amazon EC2, Amazon EKS and Amazon RDS. Code Wizards generated load with Artillery on AWS Fargate and used Amazon Aurora in its load-generation environment. The overall result therefore reflects the combined behavior of Nakama, databases, cloud resources, networking, client simulators and the chosen workloads—not Nakama software in isolation.
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The three scenarios each ran for four hours, and the database was restored to a common clean baseline between scenarios. That aids comparison, but it does not replicate a production database accumulated over years.
Scenario 1: connection, authentication and heartbeat stability
Setup
Code Wizards used 82 AWS Fargate worker nodes, each with four CPUs, with 25,000 clients per node. The simulated population ramped to 2 million CCU in about 50 minutes. Each client authenticated, created an account, received a session token, opened a realtime socket and exchanged heartbeat ping/pong traffic.
Result and meaning
The reported peak was 2,050,000 connected clients. Account creation reached 683 new accounts per second, and the report recorded a 0% error rate, including no authentication errors or dropped connections, for this scenario.
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This is meaningful evidence for connection management, authentication, sessions and heartbeat traffic under the tested conditions. It is not a test of a 2-million-player action game: clients did not all run a game simulation or continuously replicate gameplay state.
Scenario 2: realtime chat and message fan-out
Setup
The messaging test used 101 AWS Fargate nodes with eight CPUs each and 20,000 clients per node. After an approximately 50-minute ramp to 2 million CCU, clients joined one of 400,000 chat channels and sent randomly generated 10–100 byte messages at randomized intervals of 10–20 seconds.
Result and caveat
The peak connected-client count was 2,020,000. The test reported approximately 1.93 billion messages sent and 11.33 billion received, with peak average rates of 44,700 messages sent and 270,335 received per second.
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The report notes that an Artillery metrics-recording problem lost a data point near the end of the ramp-up. The parties said it did not appear to affect the rest of the scenario. The published figures do not provide message-latency distributions, regional performance, or results for voice, gameplay replication, moderation, packet-size extremes or highly uneven channel popularity.
Scenario 3: database-backed game operations
Setup
This scenario used 67 AWS Fargate nodes with 16 CPUs each and 30,000 clients per node, ramping to 2 million CCU in about 50 minutes. At authentication, each client received a wallet and inventory seeded with 1 million coins and 1 million items. Clients then periodically called one of two server functions: spend coins or grant an item. The interval was randomized between 60 and 120 seconds.
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At full ramp, the clients sustained approximately 22,300 requests per second. Reported server-request processing time remained below 26.7 milliseconds at the 95th percentile over the scenario window, with no unexpected spikes.
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This supports a specific database-write pattern and request frequency. It does not predict performance for arbitrary inventory schemas, larger transactions, complex queries, matchmaking, leaderboard writes or launch-day contention.
How credible is the claim?
Code Wizards conducted the test in collaboration with Heroic Labs and AWS. Code Wizards presents itself as technology-agnostic and experienced in game-backend benchmarking, while Heroic Labs published the results on its own blog. GamesBeat’s coverage is marked as a sponsored article presented by Code Wizards. No separate third-party audit or independently reproduced benchmark is identified in the available coverage.
That provenance does not erase the measured results, but it matters when interpreting them: this is a vendor-associated benchmark with a public methodology and reported metrics, not a neutral certification. The precise claim supported by the material is that a Code Wizards-led test of Nakama Enterprise on Heroic Cloud sustained roughly 2 million simultaneously connected simulated clients across three specified workloads.
What “could have gone higher” does—and does not—say
Code Wizards CTO Martin Thomas’s view that the system could have gone higher is an assessment of observed headroom, not a measured maximum. The public figures do not quantify remaining capacity. They do not establish that every Heroic Cloud plan, every self-hosted Nakama cluster or every game workload can reach 2 million CCU, nor do they constitute an SLA or service guarantee.
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Why 2 million CCU is not 2 million gameplay sessions
A connected client can be mostly idle, exchanging heartbeats only occasionally. Chat adds message delivery and fan-out, while the database scenario adds a specific rate of simple server operations. A real game may add frequent authoritative simulation, state replication, matchmaking, larger payloads, unevenly popular channels, or custom server code. Those behaviors can move the bottleneck to CPU, database I/O, network egress, serialization, hot keys or shard imbalance.
The public account does not publish geographic distribution or latency by region; exact EC2, EKS, RDS, Aurora and Fargate instance types; database sizing, storage, bandwidth or autoscaling policy; full Artillery scripts or raw telemetry; or a cost-per-player calculation. It also does not report matchmaking, authoritative matches, leaderboards, tournaments, parties, purchases, large-scale game-state synchronization, failover, regional outage recovery, rolling upgrades or disaster recovery. The related coverage says readers can contact Heroic Labs for the full architecture, graphs and further performance numbers.
Which studios should care about the result?
The benchmark is most relevant to teams evaluating persistent realtime connections, authentication and session management, chat or other message fan-out, and a managed database-backed backend at large scale. Nakama is an open-source game backend/server framework with features including authentication, storage, chat, multiplayer, matchmaking, leaderboards, tournaments, parties, purchase validation and notifications. Its clients and engine integrations include Unity, Unreal Engine, Godot and custom C++ implementations; see the Nakama project.
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Keep the product roles distinct: Nakama is the backend software, Nakama Enterprise is the commercial offering used in the test, Heroic Cloud is Heroic Labs’ managed deployment and operations platform, and Satori is its separate LiveOps product, not the core Nakama backend. Heroic Cloud describes managed deployments with dedicated servers, databases, load balancers, monitoring, backups and scaling, with usage-based billing and optional support or SLA plans in its service overview.
When to run your own proof of concept
A game-specific load test is particularly important if the project depends on high-frequency gameplay replication, authoritative match servers, large binary payloads, complex economy operations, strict p99 latency targets, regional data residency, multi-region active-active operation, or sudden traffic spikes. Test the game’s real request mix, player geography, data shape and burst patterns rather than extrapolating from a heartbeat or chat test.
- Include login bursts, token refresh, reconnects and the surge after an outage.
- Model hot channels, popular inventories and uneven match or shard distribution, not only uniform clients.
- Exercise the custom Go, TypeScript or Lua server code used in production.
- Test database failover, node loss, autoscaling delay and cross-region consistency where they matter.
- Measure p50, p95 and p99 latency, error rates, resource saturation and recovery—not only peak connected clients.
Managed Heroic Cloud, self-hosting, or GameLift?
| Option | What it is suited to | Trade-off to assess |
|---|---|---|
| Heroic Cloud | Managed Nakama infrastructure, database and operations; Heroic Labs lists dedicated resources, backups, monitoring, load balancing, SSL and scaling. | Pricing depends on configuration and usage; the public page presents a configuration-driven monthly estimate rather than one universal Nakama price. Large deployments may need a sales discussion. See Heroic Labs pricing. |
| Self-hosted Nakama | Teams wanting control over cloud account, topology and operations; the open-source server can be deployed on AWS, Google Cloud, Azure, DigitalOcean, Heroku or private infrastructure. | The 2M result is not a self-hosting guarantee. The team owns infrastructure, databases, monitoring, upgrades, backups, security and incident response. |
| Amazon GameLift Servers | Managed hosting for dedicated game servers and sessions; AWS lists Nakama as a backend partner, so the products can also complement one another. | GameLift is not a drop-in replacement for Nakama’s full backend and social feature set. Compare the actual session-hosting and backend requirements; see AWS’s partner listing. |
Heroic Labs’ pricing page states no DAU, MAU or CCU limits for its listed service, but that is not evidence of unlimited practical capacity: hardware, workload and budget remain constraints. The 2024 benchmark does not disclose enough infrastructure and traffic-cost detail to derive a trustworthy cost per CCU or total test bill.
Quick Recap
Questions to ask before choosing a production configuration
- Which exact Nakama Enterprise version and configuration were tested, and which version is proposed for production?
- Which AWS region or regions and exact EC2, EKS, RDS, Aurora and Fargate instance types were used?
- Was the database single-region, multi-AZ or multi-region, and what were its CPU, memory, connection-pool, disk-I/O and network ceilings?
- What were p50, p95, p99 and maximum latencies for each operation?
- Were clients evenly distributed across nodes and channels, and how did the system behave under skewed traffic?
- How did the cluster behave during node loss, database failover, rolling upgrades and recovery?
- What was the total cloud cost for each scenario, and what capacity-planning method applies to the proposed workload?
- Can the full Artillery scenario files, raw telemetry and Grafana dashboards be reviewed, and what support and uptime commitments apply to the proposed plan?
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