每个方案均提供完全独立的硬件、超低延迟和 24/7 的稳定运行，以支持您的关键业务运营。
体验为最严苛的工作负载打造的无与伦比的可靠性、速度和性能
我们的 6 个地点中的每一个都可以让您更接近欧洲、美洲或亚洲的目标受众。
15 个不同版本的 Linux 和 Windows 适合您的项目。 也可以进行定制操作系统查询。
我们专门选择第 2 层和第 3 层数据中心，以确保没有人能够物理访问我们的服务器基础设施。
我们的服务器由戴尔、惠普、SuperMicro 和瞻博网络等领先的企业硬件制造商提供支持。
您是否需要针对[插入特定用例或环境]的强大托管解决方案？ 我们的 Blueservers 16 核专用服务器非常适合您的需求，提供无与伦比的性能和可靠性。
这款专用服务器采用 Intel Xeon 或 AMD EPYC 处理器，具有 16 个核心，时钟速度为 2.1 - 3 GHz，确保高效、快速地处理您的所有任务。
该服务器配备高达 1TB 的 RAM，旨在轻松处理要求苛刻的任务和应用程序，确保无缝性能满足您多样化的计算需求。
特别有效：
该服务器在最重要的地方提供一流的性能。
5/5 来自 26 用户
Stable storage performance is critical for our databases. Disk input and output remain predictable under load, keeping queries fast and backups running smoothly.
We run multiple services, queues, and databases on one server. Dedicated resources allow fine tuning without hitting artificial limits or contention problems.
The service feels designed for real production workloads. Hardware quality, network stability, and consistent performance removed hosting from our list of daily concerns.
As a CTO at a subscription based SaaS company, I track infrastructure costs closely. With BlueServers, pricing stays predictable as usage grows, so forecasting is straightforward and surprises are rare.
At our analytics company, we process large event streams and serve live dashboards. BlueServers runs batch jobs and real time queries together without slowing reports or making the interface feel laggy.
Our team runs a SaaS product with CI pipelines and several microservices. BlueServers stability cut emergency fixes dramatically. We ship features instead of restarting services or chasing performance issues.
Traffic spikes used to change how the system behaved. With dedicated capacity, response times remain consistent in the evenings and planning feels much more reliable.
Our API handles high request volume throughout the day. BlueServers keeps throughput stable over long periods and avoids slowdowns during bursts, deployments, and heavy logging activity.
Physical servers removed noisy neighbor problems completely. CPU and RAM stay consistent during parallel workloads, container builds, and background jobs. Performance is predictable because resources are not shared.
