Currently, when a mobile or reactive app client disconnects mid-request (e.g. user backgrounds the app, loses network, or a timeout occurs), OutSystems logs the following errors in Service Center as 500-level errors: "The client is disconnected because the underlying request has been completed. There is no longer an HttpContext available." "Failed to send request due to unexpected error" These errors are thrown deep in the ASP.NET/IIS pipeline by the ErrorNotifierModule, below the OutSystems application layer. This means developers have no way to catch or suppress them using OutSystems logic — not through OnException handlers, not through error handling in Client/Screen/Data Actions, and not through any pattern available in Service Studio. Why this is a problem: These errors are not actionable by developers — there is no OutSystems-level fix that prevents them They pollute the error log in Service Center, making it harder to identify real application errors (we currently have an average of 60.000 daily errors like these) They generate false alerts in monitoring tools and APM integrations that consume OutSystems error logs They cause unnecessary noise in production environments, particularly for mobile apps used on unreliable network connections What we are asking for: OutSystems R&D to implement one or both of the following: Suppress specific known client-disconnect exception types (e.g. HttpException with error code 0x800703E3) in the ErrorNotifierModule before they are written to the error log, since these represent expected network-level events, not application bugs Provide a configurable filter mechanism in Service Center or Factory Configuration that allows platform administrators to define error message patterns that should be downgraded (e.g. to a warning) or excluded from the error log entirely Expected outcome: Developers and operations teams can maintain clean, actionable error logs that reflect real application problems — without being forced to implement infrastructure-level workarounds outside the OutSystems platform.

Service Studio already ships with a powerful but underdocumented headless execution mode. Through hands-on reverse engineering, we have confirmed and validated the following commands: -d (diff), -refresh, -u, -uu, -exportSettings, -importSettings, -cleanup, -removeChangeTracking, -runTests, -export, -import, and -silentrecover. These existing commands prove that Service Studio is architecturally capable of running fully headless, without opening a GUI. This proposal builds on that foundation to request ten new CLI commands that would unlock: AI-powered codebase analysis on .oml files without a running GUI CI/CD pipeline integration via GitHub Actions, Docker, and Linux environments Automated dependency management, publishing, and solution creation Programmatic introspection of modules, applications, elements, and SS_Keys These requests do not change the OutSystems platform concept or runtime. They expose what the IDE already does — through a command-line interface that can be scripted, automated, and run in containers. Proposed New Commands 1. ss list-apps — List Applications with Names and SS_Keys Problem: There is no headless way to enumerate the applications available on a server, along with their SS_Key (the GUID used by servicestudio:// deep links and LifeTime APIs). 2. ss list-modules — List Modules with Names and SS_Keys Problem: Modules are the atomic unit of development in OutSystems, but there is no headless way to enumerate them with their SS_Key GUIDs — the identifiers required for servicestudio:// protocol links and element navigation. 3. ss check-deps — Verify Module Dependencies Before Publish Problem: Before publishing a module, a developer needs to know if its dependencies are up to date, or if a producer module was published with breaking changes. The current workflow requires opening Service Studio, navigating to "Manage Dependencies," and manually inspecting each reference. There is no headless equivalent. 4. ss publish — Publish a Module Problem: There is no headless command to publish a module to a server. The current workflow requires opening Service Studio and clicking "1-Click Publish." This blocks full CI/CD automation. 5. ss republish — Republish a Module (Service Center Style) Problem: Service Center provides a "1-Click Publish" that recompiles and redeploys a module using its last published OML source, without requiring the source file on disk. This is critical for environment redeployments, disaster recovery, and CI/CD rollbacks — but it has no CLI equivalent. 6. ss list-elements — List All Elements of a Module by Name and SS_Key Problem: To use the servicestudio:// deep link protocol (e.g., to link directly to a specific action from a CI report or an AI analysis tool), you need the SS_Key of the element. Currently, the only way to get element keys is through direct database access or by reverse engineering internal API calls. 7. ss add-action — Add a Simple Action Using a Mermaid-Style Flow Definition Problem: Creating a simple server or client action in Service Studio requires opening the GUI, navigating to the correct module, and manually building the flow. For repetitive, pattern-based actions (logging, error handling, standard API calls), this is a barrier to AI-assisted code generation. 8. ss for Linux — Docker and GitHub Actions Support Problem: Service Studio is currently only available for macOS and Windows. This means CI/CD pipelines running on Linux (the default for GitHub Actions, GitLab CI, and most Docker containers) cannot use any Service Studio CLI commands. This is the single biggest blocker for full OutSystems DevOps automation. Request: Provide a headless Linux build of Service Studio — or a dedicated CLI package — that supports the full set of headless commands (existing + proposed) on: Ubuntu 22.04 / 24.04 (standard GitHub Actions runners) Alpine Linux (Docker optimization) Debian-based containers 9. ss delete-unused-refs — Delete Unused References from a Module Problem: Over time, modules accumulate references to producers that are no longer used — dead imports that slow down compilation, add maintenance overhead, and generate noise in -refresh / -u verification output. Service Studio can detect these via "Manage Dependencies," but there is no headless way to auto-clean them. 10. ss create-solution — Create Solutions Programmatically Problem: Solutions in OutSystems are the primary vehicle for managing and deploying groups of modules across environments via LifeTime. Creating and maintaining solutions is currently only possible through the Service Center UI. For teams managing complex multi-module deployments, the lack of a CLI solution creator is a significant DevOps gap. Why This Matters: The AI Analysis Use Case The combination of -listModules, -listElements, and the existing -d (diff) enables a use case that is currently impossible: AI-powered static analysis of OutSystems codebases without a running GUI. Current Gap: To analyze an OutSystems application with AI today, a developer must: Manually open each module in Service Studio Navigate through hundreds of screens, actions, and flows Copy/paste relevant information into an AI tool The AI agent can then generate a report like: "Action IsElegivelAntecipacaoDZero (key: 11ea244a-...) accesses the server on every screen load. Consider moving this to an Aggregate with proper caching. → [Open in Service Studio](servicestudio://-downloadAndOpen -eSpaceKey 6acebf97-... -elementKey 11ea244a-... -url bin.dev.myenvironment.com)" This is only possible if -listElements exposes SS_Keys in its output. Summary We are requesting 10 new headless CLI commands for Service Studio, with Linux support as the foundational requirement for CI/CD automation. The existing headless CLI (-d, -refresh, -u, -exportSettings, etc.) proves the architecture is ready. These new commands extend that foundation to cover the full development lifecycle — from introspection and dependency management, to publishing, solution creation, and AI-powered analysis. The OutSystems platform is already exceptionally powerful. These commands make that power accessible to modern DevOps and AI tooling workflows, without changing a single line of platform behavior.

Add a way to filter the logs by excluding keywords. Use case : one of our process calls an external API using ArdoHTTP and every call results in a SLOWEXTENSION log, thus flooding the general log with pages of useless logs. This makes trying to find significant logs very difficult and time consuming. Being able to filter out by keywords, ie SLOWEXTENSION, would solve this issue.

Introduce a configuration mechanism that allows to enable or disable Code Quality analysis for specific applications and libraries. This capability would make it possible to exclude test applications, sandbox applications, or temporary applications, preventing them from affecting overall code quality metrics. With this configurable approach, we would gain greater control over which artifacts are included in quality measurements, ensuring that reports remain accurate, relevant, and focused on production-relevant systems.

Hi Outsystems teams, Since the OS charing static entity for 1 AO, to save some cost for clients, in many projects, we hardly use static-entity even though it should use Static-entity for many purposes. We need to use alternative ways to implement the static concept, like using structure, hardcode... This led the development become more complex in design, implement, and more hard-code used, but we can't spend 1 AO for just 5 records stored in static-entity like status, type, etc... Actually many projects opened just to Delete all static entity from the code to save cost. From begining we've learnt how to use Static entity, and in real project we need to learn how to not use Static entity to save AO, this make static entity very dead. Can Outsystems consider to lower the price of AO somehow like count it 1 AO = 3 or 4 static entity, or consider make it free if there are < 10 record store in static entity, this would be a great thing for Outsystems developers and clients. Thanks :)

Be able to create a unit test for a Server / Service / Client (?) / Screen (?) action that shall be executed without developer intervention, for regression purposes.

I would like to suggest a logic clarification (or modification) to the training for the archiving. It's possible there has been an oversight, or the training may lead to a dangerously wrong solution, or I'm just an idiot. (More than one option may apply.) https://learn.outsystems.com/training/journeys/web-developer-exam-2993/data-archiving-best-practice/odc/7017 Here is the current logic in question: Text below it it, whole section pasted for clarity: Set Archive Threshold - Sets the number of records to archive by iteration. This threshold can be defined using a Setting, so it can be adjusted without redeploying the app. Set StartTime - Sets a local variable with the current time when the execution starts. CheckRecordsToArchive - Validates if there are records left to archive, according to the conditions defined using the control columns. Has Records to Archive? - Validates the output of the previous query and executes the archive branch if there are records to archive. MoveIntoArchiveStorage_InBulk - Executes a bulk INSERT INTO SELECT statement from the primary storage to the archive storage, combined with a clause to limit the amount of archived records (using the Archive Threshold set in 1). It implements the archive condition. MainStorage_SetArchivedFlag_InBulk - Executes a bulk UPDATE to set the IsArchived flag of the records archived in the previous step. Can Process More? - Validates if the current execution duration is approaching the Timer’s timeout (using an expression like DiffMinutes(StartTime, CurrTime()) < 15, for a default timeout of 20 minutes). If there’s still time, it continues checking for more records to archive. This approach helps prevent the Timer from timing out and having to repeat work. CommitTransaction - Commits the transaction to make all changes permanent in the database. WakeArchiveData - Re-wakes the Timer to check if there are still records to archive. My suggestion it that something should be added to step 6 " MainStorage_SetArchivedFlag_InBulk " to explicitly clarify that they should not use the exact same logic (where clause) used in step 5 to select items in step 6, because the data may have changed , leaving the data in query different. This will result in the wrong records being flagged as archived, and subsequently getting deleted by the clean-up process. They need to do some sort of check (inner join?) against the archive table. I understand this is an edge case, but we all know one in a million edge cases tend to happen within a week of functionality going live. Maybe there is an assumption that someone will know to do it this way, and I'm just being dumb, but the wording of the guidelines would tend to lead to someone reusing the same query logic, especially as an inner join query would be assumed to be much slower....? Does anyone from OutSystems training, or in fact, their business processes team, have any thoughts on this. It this a flaw in the training content, or in the archiving logic that was envisioned? Or am I just barking up the wrong tree here? (I'm guessing this scenario is used in the exam as well.)

I don't know if there is somewhere else for this... https://learn.outsystems.com/training/journeys/web-developer-exam-2993/best-practices-for-building-screens/odc/6729 There's explicit instruction elsewhere in the training NOT to use Check###Role() on the enabled button, but to only use it on the visible property, because you can just hit F12 and enable the button.

💡 A new input parameter, (defaulted to false obviously,) to REST calls called " ContinueOnError ", which causes the rest method to return successfully, but with 3 additional fields (or even a structure) returned with " Success ", " HTTPResponseCode " and " TextContent " fields. 📉 Some REST APIs return " failure " HTTP Response Codes for valid responses, such as " 404 Not Found " if the record doesn't exist. (Lets ignore the debate about using 404 for record not found *AND* page not found.) 🕞 In the context, this may not be an a error, but it's going to end up in the generic error handler where you are going to be parsing the text of the error message to try to see what actually went wrong, and possibly displaying a load of technical junk to the user. 📜 Even within a single error code, there could me a range of causes, with the details being in the response as JSON. 🔍 Now obviously , I know you can do all this with code in OnAfterResponse , but you can't set that on a API method level, only on the connection , so you're going to have some pretty ugly code in OnAfterRespose to work out which API of ten calls you made and whether it's really an error. 🎯 I suggest it would be far better to have an option to allow the API call to continue to the next step in the procedure, then check the response to see if it succeeded, and work out if we need to raise an error, retry, or just continue, based on the response. Edit to add: This doesn't seem like it should be particularly hard to implement. Edit to also add: Added icons because everyone else uses them

OutSystems provides strong local debugging (breakpoints, step‑through execution) and logs, and in ODC it already supports distributed traces at a technical level. However, from a developer’s point of view, there is still a significant gap between raw observability data and actionable troubleshooting. I’m proposing a developer‑centric, end‑to‑end request trace experience that makes it easy to understand what happened for a single user action: from the UI event, through server logic, to database operations and external integrations, without manual correlation. Service Studio debugging works well within a module, but once a request crosses: UI → Server Actions Aggregates → Integrations Async flows / Timers developers must manually jump between: Debugger Logs Integration error screens External system logs This fragmentation slows down root‑cause analysis and increases support effort, especially for intermittent or environment‑specific issues. Logs show facts / data, but not context. Logs record events, but: Developers must manually infer which UI action triggered which server/integration call Correlating logs across layers requires custom correlation IDs or naming conventions Performance issues often require guesswork to identify the slow component Traces technically capture request lifecycles, but developers don’t yet have a single, intuitive “story view” of a request that ties everything together in a one‑click request trace view that: Starts from a user action (e.g., button click, screen load) Shows the full execution chain across: UI action Server actions Aggregates / queries Integration calls Async operations (where applicable) Presents timing, failures, and context in a single timeline This is not about adding more logs, but about connecting existing observability data into a developer‑friendly narrative.