Making Micro-Integrations Have Major Impact

Integration shouldn’t be the bottleneck holding back innovation. That’s why we’re expanding Solace Micro-Integrations with new and enhanced connectivity to leading data platforms, databases, and cloud services, including Amazon S3, Databricks Zerobus, MongoDB, PostgreSQL, Snowflake, SAP HANA. We’ve also built AI assistance into our MDK.

These latest additions make it easier than ever to move data between enterprise systems, cloud platforms, analytics, and AI applications in real time, without the complexity of traditional, centralized integration architectures.

Applications went through a similar evolution a decade or so ago. Nobody builds monolithic application anymore – they build small, independent microservices, each doing one job. They’re deployed close to where they’re needed, and if they run into issues they don’t take down the whole system.

Integration is now going through this same shift for similar reasons: smaller pieces are easier to build, easier to change, and much harder to break all at once.

That’s what micro-integrations are: small, purpose-built components that sit right next to the systems they talk to, each one doing a single job, all of them talking to each other through an event mesh instead of directly to one another.

It sounds like a small change. It isn’t. This is what makes EDA achievable across the whole estate.

Micro-Integrations are More Than Just Connectors

Micro-integration connect systems – applications, databases, message queues, etc. – to the event mesh you’ve built with Solace Platform. They speak that system’s language: how to read from it, write to it, handle its protocol and its formats. That part alone would just be a connector.

What makes it an integration is what happens next. Between reading from the source and publishing to the mesh, the data passes through a small processing step that does something to it. A database change becomes a clean, structured event. A field gets renamed. A format gets converted and micro-integrations can publish to dynamic endpoints based on source data.

None of that is optional plumbing—it’s the work that turns “a record changed somewhere” into an event any system on the mesh can act on: an order shipping, a price changing, a customer’s risk profile shifting, described in terms the business already recognizes.

Take that step away and you’re left with a pipe: data moves from one place to another and hopes whatever’s on the other end can make sense of it. Leave it in, and by the time the data reaches the mesh, it already means something to the business.

And it runs in both directions. A source micro-integration pulls data off a system and publishes it to the mesh. A target micro-integration does the reverse: it picks up events on the mesh and delivers them into whatever needs them: a CRM, a data warehouse, a data lakehouse, or another application. Same building block, same mesh, opposite direction.

Don’t Mistake Micro-Integration for Basic Integration

A single micro-integration does one job, and that’s the point – but “one job” doesn’t mean “one micro-integration and you’re done.” Real integration work rarely fits into a single step: a change needs to be validated, transforemed, enriched with context, then routed to the right destination. Micro-integrations are decoupled from each other, but can be orchestrated to create a logical pipeline to cover exactly that, and the event mesh is what makes the chaining work: one micro-integration publishes its result as an event, the next one in line picks it up from the mesh and continues, and so on down the chain.

Nothing is wired directly to anything else – each step just talks to the mesh, the same way event-driven applications do. That’s event-driven architecture doing what it does best: loosely coupled steps, no direct dependencies, a change or a brief hiccup in one link that doesn’t take down the rest of the chain or other chains. A five-step flow ends up as five small, well-understood pieces working in sequence, each one easy to understand, change, or fix on its own.

Our Integration Hub includes a ton of micro-integrations you’ll find useful, but for specialty and custom systems, the Solace Micro-Integration Development Kit (MDK) lets you build your own micro-integrations on the same foundation Solace’s own micro-integrations are built on. They’ll behave the same way once they’re running –same lifecycle, same monitoring, same deployment model, and we just made it easier than ever with built-in AI assistance.

AI has Made Micro-Integrations Mission Critical

Until recently, “real-time” was a nice-to-have. A dashboard that updated every few seconds instead of every few minutes was impressive, not essential – the business ran fine on data that was a few hours, or a batch cycle, old.  Real-time data needs and Agentic AI changes that math.

An agent making a decision, retrieving context for a language model, or acting on a customer’s behalf is only as good as the data it’s working from at that exact moment. Feed it yesterday’s inventory count or last week’s account balance, and it will act confidently on something that’s already wrong.

Enterprises that already have real-time data flowing are the ones pulling ahead on agentic AI – putting more agents into production, and seeing more of those agents actually deliver value once they’re there. Agent success turns out to depend less on which model you picked and more on whether the data reaching it is current.

Getting there starts with one requirement: data has to move the moment something changes. Micro-integrations are how that requirement actually gets met – liberating data in real time and making it available to whatever needs it next, including a retrieval pipeline feeding a language model or an agent deciding what to do. The AI doesn’t care how the data got there. It cares whether it’s current.

Patterns That Make Sense for Micro-Integrations

Wondering whether this applies to you, and where to start? Here’s what comes up most often – the same handful of situations, across industries that otherwise have nothing in common.

• Legacy Integration Debt: A company running a legacy message bus – IBM MQ, TIBCO EMS – for a decade or more starts feeling the licensing cost and the ceiling on what it can support in real time. A micro-integration bridges the old broker to the event mesh in both directions, so migration happens application by application instead of one all-or-nothing cutover: new applications go straight onto the event mesh, old ones keep running until they’re ready to move, and the bridge gets retired once the migration’s done. Airports, banks, and transportation networks show up here more than most.
• Lightweight Integrations: Not every flow needs a full iPaaS platform in the loop. Teams running MuleSoft, Boomi, or SAP Integration Suite often still reach for something lighter on the flows that are genuinely simple and event-driven – a micro-integration handles that piece directly at the broker, while the iPaaS keeps doing what it’s actually built for: complex orchestration, transformation logic, and B2B flows. Utilities, logistics, and transportation companies use this pairing to get real-time speed on the flows that don’t need the heavier tool, without touching the ones that do.
• File-Based Integration: Plenty of enterprise data still moves as files – SFTP drops, batch exports, replication jobs – especially in retail, capital markets, aviation, and government settings. A micro-integration watches the drop location and turns a file’s arrival into an event the instant it lands on the mesh, with no change to the application producing it. What used to be a scheduled transfer window becomes something close to real time, and completely reusable by other applications and systems.
• Batch Processing: Business-critical data often sits in an operational database – Oracle, SQL Server, PostgreSQL – that only reaches analytics platforms or AI systems through a nightly export. A change-data-capture micro-integration watches the database’s transaction log directly, and the moment something changes, publishes it as an event. Banking, insurance, logistics, and manufacturing companies use this most to feed real-time analytics or AI pipelines without touching the source system at all.
• Edge Computing: Manufacturing floors, energy sites, and distributed retail networks generate a different kind of data problem: sensors and devices speaking MQTT or OPC-UA, or hundreds of physical locations each running the same local process. A micro-integration deployed right at the edge bridges the device protocol straight into the event mesh, queuing and replaying automatically if the connection drops, so device and location data joins the same real-time flow as everything else.

Find the Micro-Integrations You Need

Everything above is easier to believe once you’ve actually watched it happen. The fastest way in is our Integration Hub – a growing collection of micro-integrations that Solace and the community have already built, organized by system and connector type. If something in the patterns above sounded like your environment, there’s a decent chance it’s already there.