In today's interconnected business landscape, APIs (Application Programming Interfaces) are the building blocks of modern software. They enable different applications to communicate, share data, and work together. At Oblytech, we specialize in building reliable, secure, and scalable APIs that help your business reach new levels of efficiency, innovation, and growth.
We build APIs around your unique business requirements and connect them cleanly with your existing systems. Our developers follow industry best practices and use modern technologies to create APIs that are reliable, efficient, and user-friendly.
We help you connect your applications, systems, and data sources through API integration. Whether you need to integrate with third-party platforms, legacy systems, or cloud-based services, we have the expertise to ensure smooth and efficient data exchange.
We specialize in building RESTful APIs, the industry standard for web-based APIs. Our RESTful APIs are lightweight, scalable, and easy to consume, making them ideal for modern web and mobile applications.
We prioritize the security of your APIs, implementing strong authentication, authorization, and encryption protocols to protect your data and prevent unauthorized access.
We provide comprehensive documentation and thorough testing to ensure your APIs are easy to understand, use, and maintain.
The decision usually starts with a breakage that someone in operations can describe in one sentence. An order status stops updating in the customer portal after a finance system change. A nightly export that feeds a planning spreadsheet begins to fail on a field nobody documented. A third-party platform gets a new version and three internal tools stop receiving records. The person who has to act is often an integration lead or an operations manager, and the question they need answered is whether the fix is a patch to each connection or a deliberate interface that every system talks through.
An API layer is the right answer when the same data crosses more than one boundary and the crossings are important enough to govern. It is the wrong answer for a single, stable link between two systems that will never change, where a scheduled file transfer with a checksum and a named owner may be enough. The point of building an interface is to make the contract explicit: what data is exposed, who may read it, how it is versioned and who is told when it changes. Without that contract, an API is just a faster way to create the same silent failure.
Many organizations already own tooling that can connect systems, including the API automation options on a service platform, and buyers often ask whether a custom API is needed at all. The honest answer depends on the number of endpoints, the volume of transactions, the logic that must run between them and the skills available to maintain it. The comparison below is a general guide to how the options differ in practice.
| Option | Best suited to | Where it becomes a burden |
|---|---|---|
| Built-in connector or prebuilt integration on a platform | Two well-supported systems with a standard data exchange and modest transformation | Heavy field mapping, unusual authentication or a need to call many services in a single transaction |
| Integration platform or middleware | Many systems with shared routing rules and a team that wants monitoring in one place | License cost that can grow with traffic, and logic that ends up buried in configuration nobody reads |
| Custom API layer | Business logic that must be owned in code, a need for a published interface other teams or partners consume, or unusual security requirements | No one takes responsibility for versioning, documentation and testing after launch |
The middle option is sometimes chosen by default and then regretted. A middleware platform is excellent for moving data between systems but is a poor place to hold a complicated pricing rule or a customer eligibility check that changes every quarter. Where the logic is significant, a custom service that the platform calls, rather than logic inside the connector, keeps the rule testable and visible.
A well-run API begins with a written contract. The custom software development page covers the wider build work. That contract is more than a list of endpoints. It sets out the purpose of each operation, the fields it accepts and returns, the error responses a consumer should expect, the rate and volume limits and the rule for changing it. The discipline required is the same whether the interface is internal or exposed to a partner, but the consequences of a broken contract are larger when an outside party depends on it.
Where the interface sits between a service platform and a sales system, the integration architecture on the sales side and the boundaries between the two platforms set the same questions about ownership. Writing these points down is also the fastest way to find out whether the business agrees on what the data means. A short workshop on the contract often surfaces a disagreement about the definition of an active customer or a closed order that would otherwise appear months later as a reporting error.
An interface that cannot be tested in isolation will be tested in production. The minimum useful test set covers the happy path, the malformed request, the timeout from the downstream system and the authorization failure. Contract tests, which check that a provider still satisfies what its consumers expect, catch a common breakage: a field renamed on one side without anyone telling the other. Documentation should be generated from the contract where tooling allows, so that the description and the behavior cannot drift apart without someone noticing.
Event flows that carry several steps are better handled with orchestration that makes each step and its failure handling visible, which is the subject of the ServiceNow workflow orchestration page. Monitoring belongs in the same plan. Each interface should expose the number of calls, the error rate by type, the latency and the age of the last successful transaction. The last measure is the one that matters most for quiet failures, because a feed can return success codes while carrying no new records.
Every API is a door, and the security design determines who can walk through it. Authentication should be strong enough for the data behind it, and authorization should be granted per consumer rather than shared through a single account. Secrets belong in a managed store, not in configuration files that are copied between environments. Where personal data is exchanged, the logging design must avoid writing the payload into a log that many people can read. Encryption in transit is the baseline. Sector obligations and data-protection rules add requirements on retention and on which regions data may pass through, and those requirements should be recorded in the contract, not left to the developer who builds the connector.
Not always. A scheduled, well-monitored transfer can be enough when the data is simple and changes rarely. An API becomes worth its cost when the connection needs to be called on demand, when several consumers rely on it, or when the business rule between the systems matters.
Publish a versioned contract, keep the previous version running for an agreed period and give partners a clear notice rule. Changes that remove or retype fields should never ship under the same version number.
The team that owns the systems on either end should agree on one owner for the interface itself. Shared ownership with no named person usually means that no one is responsible when the interface fails at night.
It is better when the work is routing and standard transformation across many systems. It is worse when the value sits in rules that need code-level testing. Many mature setups use both, with the platform handling transport and the custom service holding the logic.
The decision usually comes down to a contract-first API project, a monitoring fix on the current links, or a platform change. Discuss your integration requirements with our team. Scope and price depend on how many interfaces are in play and how much of their logic has to be rebuilt.
API development and integration services cover the design, build, testing and go-live of the interfaces that move data between applications, along with the work needed to keep those interfaces running after launch. A scope is ready to price once every data flow has a trigger, a volume and an owner, since flow count often drives effort more than endpoint count.
In most projects the work runs in five stages: inventory, design, build and test, cutover and operation. A plain list of each system pair, the direction the data travels, how often it moves and the person who is contacted when a run fails is often the most useful document the project produces, and it is cheap next to rebuilding a connector scoped in one meeting.
Use these steps to scope the work before asking for a quote:
A common scoping mistake is to size a project from the number of endpoints in a diagram. The diagram usually leaves out the retry logic, the reconciliation between systems and the reports that depend on the data arriving in the right order. Those items often take longer than the endpoints, and they are the first thing cut under budget pressure, so they belong in the scope on day one.
Cutover needs its own line in the plan. Running the old and new paths side by side for an agreed period, comparing record counts and sample records each day, and only then switching the source makes the change reversible. Teams that skip the parallel run usually find the defect when a finance user notices a missing invoice, not when the monitoring fires. The REST and SOAP guide covers the protocol choices that shape the parallel run.
Use a webhook when the receiving system has to react to a change within moments and the sender can call out when it happens. Use polling when a delay of one interval is acceptable or the source cannot send events. Both patterns lose data when nobody has planned for a missed call, and that planning is where much of the work sits.
With polling, the consumer asks on a schedule whether anything has changed since its last check. It sets the interval, retries a failed read and can rebuild a lost window by asking again. The costs are latency equal to the interval, many empty reads and a load on the source that grows with every consumer. The change marker needs care: a last-modified timestamp can miss rows saved late with an earlier time, so the job should overlap its window slightly and tolerate duplicates.
A webhook removes the wait and most of the empty calls, but the receiver must answer quickly, accept the same message twice and handle messages that arrive out of order. Signature checks, a log of every payload received and a way to replay a range of events are the parts teams often skip and then need in the first bad week. If the receiver is down when the message is sent, the sender’s retry rules decide whether the event survives at all.
| Question | Polling | Webhook |
|---|---|---|
| How soon is a change seen? | No sooner than the next poll | Close to the moment of the change |
| Who recovers a missed change? | The consumer re-reads its window | The sender’s retry rules and any replay option |
| What the receiver must handle | Its own schedule and source limits | Duplicates, out-of-order messages, signature checks |
Many integrations use both. A webhook carries the change someone is waiting for, and a scheduled reconciliation compares counts to catch what the webhook dropped. Agree on its window and its owner before go-live. For the platform side of outbound calls, see how outbound REST messages work, and for the wider choice of pattern, Integration Hub integration patterns. A webhook that fires on every change can also flood a receiver the way raw monitoring events do, which is the problem alert correlation addresses.
Guides from the Oblytech ServiceNow library that explain the practice behind this page.