API Integration Challenges

🔗 How to Integrate Dynamics 365 with Third-Party APIs Using Azure Functions In many businesses, Dynamics 365 sits at the core of operations. But success often depends on how well it connects with other platforms—billing systems, shipping providers, marketing tools, and more. When these systems don’t communicate: ❌ Teams waste time on manual data entry ❌ Customers face delays ❌ Leaders work with outdated or incomplete information 👉 The fix? Azure Functions. Azure Functions provides a serverless, cost-efficient way to integrate Dynamics 365 with third-party APIs. Instead of building heavy integrations, you can deploy lightweight code snippets that run only when triggered—keeping costs low and workflows smooth. 💡 Why this matters: Real-time data sharing between systems Accurate and connected business operations Faster insights for decision-making Scalable without expensive custom development In my latest guide, I walk through the practical steps to set up this integration, starting with: ✅ Registering an application for secure authentication in Azure AD …and continuing through the full process. 📘 Full step-by-step guide here: 👉 https://lnkd.in/g_jHakDM #Dynamics365 #Azure #AzureFunctions #APIIntegration #DigitalTransformation #Microsoft

I’m thrilled to share my latest deep-dive: “Securing Salesforce Integrations with Heroku AppLink” — now live on Andy in the Cloud. 👉 https://lnkd.in/g6B-3D2j Why this matters: 🔐 Integrations are everywhere — pushing data, triggering workflows, connecting systems. But securing them? That’s where the challenge lies. In this post I walk through how Heroku AppLink (from Heroku / Salesforce) offers a robust-yet-developer-friendly authentication model for building secure integrations. ✅ Learn how to: • Configure user, user-plus & authorized-user auth modes. • Use working code samples (Node.js / APIs) to manage secure flows. • Maintain auditability, avoid over-permissive integration users, and fit into your org’s security posture. Who should read this? • Salesforce architects looking to extend their platform with Heroku-based services • Developers building integrations (web services, data ingest pipelines, third-party API orchestration) • IT/Security professionals wanting to tighten access and governance around Connected Apps and integration endpoints If you’ve ever wrestled with tokens, OAuth flows, or managing integration users — this one’s for you. Let’s elevate how we build connected systems. 🔗 Check it out, and let me know your thoughts: what stood out, what you’re doing differently, or what you’d like more detail on. I’ll happily dive deeper in the comments. Salesforce Heroku Salesforce Admins Salesforce Developers Salesforce Architects

Dear Developers, “What’s the best way to integrate Salesforce?” Wrong question. Ask this instead: “What’s the simplest method that meets the need — without overkill?” Because good integration isn’t about doing more. It’s about doing just enough — the right way. Here’s a quick guide to help you choose smart 👇 → REST / SOAP API For real-time, two-way sync Clean, fast, widely supported → Platform Events / Change Data Capture For async updates and automation at scale Decouple your systems, reduce friction → MuleSoft For complex enterprise integrations Use when dealing with 5+ systems, legacy apps, or on-premise data → Zapier / Workato / Boomi For fast, low-code integrations Best when speed matters more than full control → External Services + Flow For calling APIs without Apex Admin-friendly and scalable for lighter use cases → Salesforce Connect For real-time access to external data No duplication, no sync delays → Apex Callouts For full control over logic Use when you need headers, tokens, retries, or custom flows → Heroku Connect For syncing Salesforce with Heroku apps Great for dev teams building on Postgres → Kafka / Streaming API For real-time, high-volume event data When performance is key and queues matter Start small. Build only what’s needed. And let the business drive the architecture — not the other way around. If you're mapping your next integration, → Save this post → Or DM me — happy to help

An interesting data sync pattern emerged during testing: A sales rep entered a $2,500.50 deal in Salesforce... The Postgres database rejected it silently due to decimal precision. No error message. No warning. Silent failure. After analyzing Heroku Connect's architecture, here are the key technical findings: 1. Sync Behavior - Uses polling at regular intervals - Not real-time, but the changes update "eventually" - Changes may lag during high-volume periods 2. Data Integrity Considerations: - Silent failures with mismatched data types - Timezone vs timestamp inconsistencies - Boolean vs 1/0 flag discrepancies 3. Technical Architecture: - Requires Heroku-hosted Postgres (cannot host postgres anywhere else than on Heroku) - Limited to Salesforce <> Postgres sync - Custom database triggers can conflict with sync operations For enterprise architects considering bi-directional syncs: Map out your full requirements first. The architecture decisions you make today will impact your data reliability and data mobility tomorrow.

Today, I would like to share a common problem of *Broken Data Pipelines* that have encountered in the past in my career. This disrupts critical decision-making processes, leading to inaccurate insights, delays, and lost business opportunities. According to me, major reasons for these failures are: 1) Data Delays or Loss Incomplete data due to network failures, API downtime, or storage issues leading to reports and dashboards showing incorrect insights. 2) Data Quality Issues Inconsistent data formats, duplicates, or missing values leading to compromised analysis. 3) Version Mismatches Surprise updates to APIs, schema changes, or outdated code leading to mismatched or incompatible data structures in data lake or database. 4) Lack of Monitoring No real-time monitoring or alerts leading to delayed detection of the issue. 5) Scalability Challenges Pipelines not being able to handle increasing data volumes or complexity leading to slower processing times and potential crashes. Over the period, I and Team Quilytics has identified and implemented strategies to overcome this problem by following simple yet effective techniques: 1) Implement Robust Monitoring and Alerting We leverage tools like Apache Airflow, AWS CloudWatch, or Datadog to monitor pipeline health and set up automated alerts for anomalies or failures. 2) Ensure Data Quality at Every Step We have implemented data validation rules to check data consistency and completeness. Use tools like Great Expectations works wonders to automate data quality checks. 3) Adopt Schema Management Practices We use schema evolution tools or version control for databases. Regularly testing pipelines against new APIs or schema changes in a staging environment helps in staying ahead in the game 😊 4) Scale with Cloud-Native Solutions Leveraging cloud services like Amazon Web Services (AWS) Glue, Google Dataflow, or Microsoft Azure Datafactory to handle scaling is very worthwhile. We also use distributed processing frameworks like Apache Spark for handling large datasets. Key Takeaways Streamlining data pipelines involves proactive monitoring, robust data quality checks, and scalable designs. By implementing these strategies, businesses can minimize downtime, maintain reliable data flow, and ensure high-quality analytics for informed decision-making. Would you like to dive deeper into these techniques and examples we have implemented? If so, reach out to me on shikha.shah@quilytics.com

There's a goldmine of productivity sitting in your Amazon flatfiles. Here's how to unlock it Managing thousands of products on Amazon is a nightmare. Especially when they keep changing their flatfile formats. Here's how we solved it: 1️⃣ Created a "Source of Truth" spreadsheet with all our product data 2️⃣ Built a custom Google Sheets script to auto-map our data to new Amazon formats 3️⃣ Now we just copy-paste headers, run the script, and upload The result? We save 5-10 hours every single week. That's 40+ hours per month we can spend on growth instead of data entry. Here's why this matters for your eCommerce business: ✅ Faster updates mean better product visibility ✅ Less time on admin = more time for strategy ✅ Reduced errors from manual data entry Want to implement this for your Amazon business?

Step-by-Step Guide to Expose SAP CPI Integration Flows as APIs via API Management using SAP Integration Suite's API Management (APIM). 1. Set Up SAP Process Integration Runtime Navigate to: SAP BTP Cockpit → Subaccount → Instances & Subscriptions Create a Service Instance: Service: SAP Process Integration Runtime Plan: API Instance Name: e.g., CPI_API_Instance Roles: Assign all roles (except security roles) Create Service Key: Click the ⋮ (3-dot menu) → Create Service Key → Save the credentials (Client ID, Client Secret, Token URL) 2. Design & Deploy a Sample iFlow In Integration Suite: Create Package: Design → Integrations & APIs → Create Package (e.g., Demo_API_Package) Build iFlow: Add an HTTP Sender Add a Content Modifier (set sample body content) Deploy the iFlow Test: Use Postman to send a request to the iFlow endpoint → Validate the sample response 3. Configure API Provider with OAuth2 In API Management: Create API Provider: Configure → API Providers → Create New Name: e.g., CPI_Provider Connection Type: Cloud Integration Host: Use the host from the Service Key created earlier Authentication: Select OAuth2 Client Credentials → Enter Client ID, Client Secret, and Token URL 4. Create & Deploy API Proxy Create API Proxy: Select the API Provider (e.g., CPI_Provider) Click Discover Choose your deployed iFlow Enable OAuth and provide credentials from the Integration Flow instance Proxy Name: e.g., flow-api-proxy Save & Deploy → Copy the Proxy URL for testing 5. Test Your API Open Postman → Paste the Proxy URL → Send a request → Confirm the response from your iFlow With this setup, your SAP CPI iFlows can now be managed as full-fledged APIs using API Management in SAP BTP.

Configuring ODATA v2 for SucessFactors integration : Configure SuccessFactors OData API Access Step 1: Generate OAuth2 Credentials Go to SuccessFactors Admin Center → Manage OAuth2 Client Applications. Click Register Client Application. Enter details: Application Name: Example_CPI_SuccessFactors_Integration Grant Type: Client Credentials (for system-to-system) Scope: Select required APIs (e.g., odata_api, user_api) Note down: Client ID Client Secret Token Endpoint URL (e.g., https://<your-api-server>.https://lnkd.in/gsstQRk8) Step 2: Verify API Permissions Ensure the technical user has access to the required OData entities (e.g., PerPerson, EmpEmployment). Configure SAP CPI for SuccessFactors OData V2 Step 3: Create a New iFlow Open SAP CPI → Design → Create Integration Flow. Name it (e.g., SF_OData_EmployeeSync). Step 4: Configure OData V2 Receiver Adapter Drag and drop an OData V2 Receiver Adapter. Click Edit and configure: Connection Address: https://<your-api-server>.https://lnkd.in/ghct2265 Authentication: OAuth2 Client Credentials Credential Name: Create a new OAuth2 Credential Token Service URL: https://<your-api-server>.https://lnkd.in/gsstQRk8 Client ID: (From Step 1) Client Secret: (From Step 1) Processing Query Options: Configure $select, $filter, $expand if needed. Step 5: Test Connection Click Test Connection to verify authentication. If successful, proceed to mapping. Configure OData Query Parameters (Optional) To optimize API calls, use these parameters in the OData Receiver Adapter: $select=userId,firstName,lastName - Fetches only required fields $filter=lastModified gt datetime'2024-01-01' - Gets only updated records $expand $expand=empEmploymentNav Retrieves nested employee data $top $top=1000 Limits records per call $orderby $orderby=userId desc Sorts results Implement Error Handling Retry Mechanism (for API Limits) In the OData Adapter, set: Retry Interval: 30 seconds Max Retries: 3 Exception Handling Use a Try-Catch block in the iFlow to log errors to a Data Store or send email alerts. Deploy & Monitor Deploy the iFlow. Test using Postman or a scheduler. Monitor in CPI Operations Dashboard: Check for HTTP 200 (success) or 429 (throttling). Log payloads for debugging. Best Practices  Use $batch for bulk operations (reduces API calls).  Cache OAuth Tokens to avoid hitting rate limits.  Externalize Credentials in Secure Parameters.  Log API Responses for troubleshooting. Example: Employee Sync iFlow Trigger: Timer (runs daily at 2 AM). OData Call: GET /odata/v2/PerPerson?$select=userId,email&$filter=lastModified gt datetime'2024-01-01' Transform: Convert JSON to CSV for SAP HCM. Send: To SAP S/4HANA via SOAP. Troubleshooting Tips  Error 401 Unauthorized: Check OAuth2 credentials.  Error 429 Too Many Requests: Implement retry logic.  Empty Responses: Verify $filter conditions.