137,000+
listings migrated
NAS directory platform with continuous uptime during replatforming
91,000+
dynamic pages indexed
Content platform migrated from monolithic CMS to headless architecture
30
languages deployed
Korean manufacturer hub replacing legacy multilingual monolith
sub-200ms
real-time bid latency
Auction platform replacing 800ms+ legacy response times
Lighthouse 95+
performance score
Across all enterprise replatforming projects vs. legacy 30-50 scores
Architecture
Strangler fig decomposition with dual-write CDC replication from legacy PostgreSQL/SQL Server/Oracle to Supabase PostgreSQL. Next.js frontend deployed on Vercel edge network consumes legacy APIs via compatibility layer during transition, then switches to Supabase direct. Feature flags and CDN routing rules enable progressive traffic shifting and sub-60-second rollback at every phase.
企业项目失败的原因
So here's something I've watched play out at company after company -- monolithic architectures don't fail all at once They just slowly grind your feature velocity into the ground until one day you realize you haven't shipped anything meaningful in six months. Engineers leave. Good ones, specifically. Nobody wants to spend their career navigating a 200,000-line codebase where touching the billing module somehow breaks the user profile page. That's not an exaggeration. I've seen it.
And then there's the rewrite trap. Those 12-18 month feature freezes people warn you about? They're real. I watched product teams in Austin and Chicago sit completely idle -- just waiting -- while their best engineers disappeared into "the big migration" with nothing to show stakeholders for over a year. Meanwhile, competitors kept shipping. That gap compounds faster than most executives realize until it's already a serious problem.
But honestly, the monolith itself isn't always the villain. It's the deployment cycle it forces on you. Every single change -- doesn't matter how small -- has to go through the same pipeline, the same test suite, the same approval chain. One slow component poisons the whole thing. So what should take a day takes a sprint. What should take a sprint takes a quarter. You're not slow because your team is slow. You're slow because the architecture makes speed structurally impossible. There's a difference, and it matters when you're trying to figure out where to actually focus.
Vertical scaling will eat your budget alive And the really frustrating part? You see it coming from miles away. Traffic grows, the server maxes out, and your only move is a bigger box -- there's no dial to turn down when traffic craters at 3am. I've personally seen companies running six-figure annual hosting bills on infrastructure that's sitting idle 40% of the time. That's not bad luck. That's just what happens when there's no elastic pricing path. You end up permanently provisioning for peak load, paying for peak load, even at 3am on a Tuesday when nobody's using the thing.
Oracle and SQL Server lock-in is a slow bleed -- the kind you don't notice until it's serious Those license renewals aren't climbing 5% a year like some polite inflation adjustment. We're talking 15-25% increases, and there's basically zero negotiation room when your entire application is built around vendor-specific features and syntax. You're not really a customer at that point. You're captive. And here's how it compounds: every year you stay, the switching cost feels a little higher, so you stay another year. The trap tightens gradually.
Scattered authorization logic is the kind of technical debt that looks completely manageable until, suddenly, it isn't You've got access control decisions buried in controllers, middleware, service classes -- and nobody has a full picture of who can actually do what in the system. So when a security audit rolls around, it fails. Not because anyone was careless, but because the logic is distributed across code that nobody fully understands anymore. And implementing anything resembling zero-trust architecture? Basically impossible when permissions are this tightly coupled to application code.
我们交付的内容
Strangler Fig Decomposition
Rather than ripping everything out at once -- which, in my experience, never actually works -- we replace the monolith's surface area piece by piece using API compatibility layers. The legacy system and its modern replacement run side by side the entire time. No hard cutover. Automated traffic shifting moves load progressively, so you're not staging a war room at midnight and hoping for the best. This is the strangler fig pattern in practice. It's genuinely the only migration approach I'd trust for production systems where downtime isn't an option.
Dual-Write CDC Replication
Change Data Capture via Debezium streams every write from your legacy database to Supabase PostgreSQL in near-real-time. Nothing gets batched overnight. Nothing quietly falls through the cracks at 2am. And every 15 minutes, reconciliation checksums run automatically -- comparing row counts and aggregate values across both systems so we catch drift before it turns into an actual incident. In practice, that's what lets you run two databases in parallel with real confidence, rather than just crossing your fingers and hoping they're staying in sync.
Progressive Traffic Shifting
CDN-level routing rules handle the traffic shift gradually -- starting at a 5% canary and ramping to 100% over 2-3 weeks. That window gives you genuine production signal without betting the whole business on day one. But here's the real kicker: if something goes sideways, rollback is a single configuration change that takes effect in under 60 seconds. You're not redeploying anything. You're not calling engineers at midnight. One change, done.
Supabase Row-Level Security Migration
Authorization logic gets pulled out of monolith controllers entirely and moved into PostgreSQL RLS policies -- enforced at the database layer itself. Doesn't matter which access path hits the data. The policy applies regardless. That's a fundamentally different security posture than hoping every controller in a distributed codebase remembered to check permissions correctly. And it's the foundation you'll actually need if zero-trust architecture is anywhere on your roadmap.
Auth Bridge Layer
Nobody gets logged out. That's the whole point. We build a bridge layer that translates legacy session cookies to JWT tokens during the transition, so existing sessions keep working while the new auth system comes up underneath them. Credentials migrate with bcrypt-compatible hashing. From a user's perspective, it's completely invisible -- because their experience doesn't change at all. Pretty straightforward goal, honestly. The complexity lives in the implementation, not in what users actually see.
90-Day Post-Launch Monitoring
Cutover isn't the finish line -- not even close. We define explicit SLAs covering data integrity verification, performance benchmarking, and incident response for three full months after final cutover. So if something surfaces at week six, there's already a clear process and a team actively on it. Not a conversation about whether it falls within scope. That distinction matters more than most people expect.
常见问题
你如何在单体到 Jamstack 迁移期间实现零停机？
我们使用绞杀者模式配合双写数据复制运行其下方。新的 Next.js 前端首先通过使用遗留 API，同时我们通过 CDC 流在后台将数据迁移到 Supabase。流量通过 CDN 路由逐步转移——首先 5% 金丝雀，然后在几周内受控地扩展到 100%。到我们翻转 DNS 时，两个系统都完全同步。实际切换需要分钟，不是小时。回滚是单一配置更改。就是这样。
重新平台化 Rails 或 .NET 单体的典型时间线是什么？
通常 12-20 周覆盖大多数项目——但这个范围根据单体复杂性、数据库大小和你承载的下游集成数量而移动。我们用一个 2 周付费发现阶段开始，产生完整的迁移图和风险评估，所以没有惊喜在项目中期浮出。时间线真正压缩的原因是前端和数据迁移工作流并行而非顺序运行。你不是在等待第一阶段关闭才能打开第二阶段。
你如何在双写复制期间处理数据完整性？
自动对账每 15 分钟运行一次，比较行数、聚合校验和和引用完整性跨遗留数据库和 Supabase。我们不翻转写路径直到对账连续 72 小时清晰通过——不是大约 72，不是 70 加好的解释。切换后，遗留数据库在解除授权前保持只读模式 30 整天。如果我们需要它，它在那里。我们从未需要使用它。但那个安全网很重要，我永远不会跳过它。
你能将我们的自定义认证系统迁移到 Supabase Auth 吗？
可以——没有人被登出，这是人们实际关心的。我们构建一个桥接层在过渡期间将遗留会话 cookie 转译为 JWT 令牌。Supabase Auth 本地处理 JWT、OAuth2、SAML 和魔法链接。凭证与 bcrypt 兼容哈希迁移。桥接通常运行 2-4 周——足够长以使所有活跃会话自然过期并针对新系统重新认证。用户不会注意到任何它。那是目标。
如果切换期间出现问题会发生什么？
这里没有什么是二进制的。每个集成点由功能标志控制，所以你永远不处于回滚意味着灾难性全有或全无决定的位置。将 Next.js 前端回滚到遗留系统是在 60 秒内生效的 CDN 路由更改。数据库回滚通过反向复制流将写入路由回遗留系统。但这里是——我们在每个生产切换前在分阶段测试完整的回滚程序。这不是我们在晚上图形化的东西。那会很疯狂。
迁移后我们将节省多少基础设施费用？
通常第一年内托管和维护成本减少 40-50%。遗留单体需要垂直扩展——更大、越来越昂贵的服务器——加上许可证数据库如 SQL Server 或 Oracle，加上整个工作是保持灯亮的专属运维团队。Jamstack 架构完全翻转这个模型：边缘分散的静态资源、空闲时扩展为零的无服务器计算和 Supabase 的弹性定价托管 PostgreSQL。我们在发现期间建模预计数字，所以你从特定于你基础设施的真实数字而不是行业平均值工作。
我们需要重写所有业务逻辑吗？
不——而且"同时重写所有东西"真的不是策略。绞杀者模式意味着业务逻辑增量和有目的地移动。关键路径首先到 Supabase 边缘函数或 Next.js API 路由。低风险遗留逻辑可在 API 兼容层后面保持运行数月，同时我们处理更高的优先级。我们基于实际性能影响和维护负担序列——不是某个任意的完成定义清单。
查看此能力的实际应用
Headless CMS Development
Content platform architecture used to replace monolithic CMS backends during replatforming engagements
Enterprise Next.js Development
Next.js frontend architecture deployed as the modern replacement layer in strangler fig migrations
Supabase Backend Development
Supabase PostgreSQL architecture including RLS, Edge Functions, and Auth used as the target platform for data migration
Performance Optimization
Lighthouse 95+ optimization applied post-migration to ensure the new platform dramatically outperforms the legacy system
Multilingual Website Development
30-language deployment architecture that replaced a legacy monolith's brittle i18n implementation
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