SnapLogic API Management FAQ
Here’s a list of technical FAQs we get from customers. Hopefully this helps you and if you can’t find the answer, feel free to respond to the post and I’ll try to answer! SnapLogic API Manager allows you to manage and secure all your APIs in a unified platform with Data Integration and iPaaS capabilities. Load Balancing and Distribution Yes, SnapLogic platform can scale horizontally and the APIM Gateway can be distributed across different server nodes/clusters. For our Cloudplex (Cloud API Gateway) we also can provision a load balancer to handle traffic distribution. What API security and governing policies do you have (as of March 2023): Anonymous Authenticator API Key Authenticator Authorize By Role Authorized Request Validator Callout Authenticator Client Throttling CORS Restriction Early Request Validator Generic OAuth2 IP Restriction Json Validator OAuth2 Client Credential Request Size Limit Request Transformer SQL Threat Detector XML DTD Validator XML XSD Validator API Testing: We currently offer real-time API testing through the try it out feature. Rate limiting: Yes, we do offer rate limiting and you can customize it to your needs. i.e. 250 anonymous requests per hour Observability: Yes, you can track requests, request errors, error(%), target errors, latency and Top API by requests. You can also export the API log data for further analysis on other data analytics platforms. Can you create APIs with a spec? Yes, you can either create, import from a json/yaml to create APIs. Or via a template OpenAPI Spec from within SnapLogic API Manager. Can you manage and secure 3rd-party APIs? Yes, you can manage and secure 3rd-party APIs and pipelines (APIs) you’ve created with SnapLogic API ManagerSnapLogic API Management Higher Education Case Study
Ever wonder how you can manage hundreds of APIs that enable +30,000 students on campus? Check out this case study with Boston University and their success with SnapLogic API management. SnapLogic Making the Faculty and Academia Even Smarter at Boston University Find out why Boston University selected SnapLogic to optimize the university’s application submission process for the Admissions and Financial Aid offices.
SnapLogic REST API Design - Best Practices
This document provides a guide on best practices for REST API design within the SnapLogic Platform. The REST API design guidelines are a collection of API design patterns and principles that all API teams within an organisation should adhere to when developing APIs. The definition and implementation of API design guidelines are among the most influential drivers of an API strategy — fostering a consistent approach to the creation of an API platform across the enterprise. Author and contributors; Roberto Oliva and Chris Ward
Integrating with REST APIs + OAuth when no native Snap is available
Hi, I’m looking into some API integrations with some services that are not supported by native snaps, but do offer a rich REST API and support OAuth. The wiki docs on the REST Snap have some details but its a quite daunting process to try and blindly hook up the OAuth2 steps and get the account working in a pipeline. Maybe I’m being lazy, but arent there any walkthrus or has someone done this before and willing to share how to set up integration with: Domo Microsoft Graph API (for Azure AD) Maybe even ElasticSearch Thanks, Mike
Problems with the Snaplogic "Import a Project" API
I exported a project as a zip file and saved it locally, but I’m having trouble getting the Snaplogic Import a Project API to work. I’ve tried to get this API to work on Postman and as a Python script, but I keep getting a 400 - BAD REQUEST response and the error “Expecting body argument for endpoint import_project: file_handle”. So I assume something is wrong with how I’m trying to send the file, but I can’t figure out what. Here is an example of a Python script I’ve tried: import requests from requests.auth import HTTPBasicAuth import os pod_path = 'elastic.snaplogic.com' import_path = 'Partners/Company/x_Imported' url = f'https://{pod_path}/api/1/rest/public/project/import/{import_path}' params = {'duplicate_check': 'true'} headers = {'Content-Type': 'multipart/form-data'} dirname = os.path.dirname(__file__) filename = os.path.join(dirname, 'project_files/xImport.zip') file_obj = open(filename, "rb") files = {'file': ('xImport.zip', file_obj, 'application/zip')} r = requests.post(url, auth=HTTPBasicAuth( <username>, <password>), headers=headers, params=params, files=files) Any ideas about what’s wrong with this script?
Creating APIs with SnapLogic Pipelines and Ultra Tasks
Overview API (Application Program Interface) is an old concept repurposed to mean a modern web service based on the REST protocol and increasingly using the JSON data format. These modern APIs have become the franca lingua of the digital economy, by facilitating lightweight, performant communication between applications across an enterprise or across the internet. Typically RESTful APIs perform operations on “resources” (Customers, Orders, People, etc). By convention, the type of operation is identified using the most common HTTP verbs such as POST (create), GET (read), PUT (update), DELETE SnapLogic provides Ultra Tasks as the means by which a Pipeline can be exposed as a secure, high-availability, low-latency, sub-second request/response API. For example, the following is a Pipeline that embodies a Customer API exposed using an Ultra Task: Once the Ultra Task is enabled, the associated Pipeline stays resident in memory on the Snaplex node(s) it was configured to execute on. The number or Instances can be configured to accomodate the expected concurrent API request volume. The API can then be called securely from an external application (Postman REST client in this case): This is an example of an API GET (read) request for a specific Customer identified by the ID “1001” Designing the Pipeline Ultra Tasks deliver the components of the HTTP request message to its associated Pipeline as fields in the JSON document: content: The request body for POST or PUT requests headers: For example, the ‘User-Agent’ HTTP header can be referenced in the input document as $[‘user-agent’] uri: The original URI of the request. method: The HTTP request method. query: The parsed version of the query string. The value of this field will be an object whose fields correspond to query string parameters and a list of all the values for that parameter. For example, the following query string: foo=bar&foo=baz&one=1 Will result in a query object that looks like: { "foo" : ["bar", "baz"], "one": ["1"] } task_name: The name of the Ultra task. path_info: The part of the path after the Ultra task URL. server_ip: The IP address of the feed-master that received the request. server_port: The TCP port of the feed-master that received the request. client_ip: The IP address of the client that sent the request. client_port: The TCP port of the client that sent the request. In the above Customer API example: A Mapper Snap is used to parse the ID from the portion of the URL after the base path provided by the Ultra Task (demo-fm.snaplogic.io/api/1/rest/feed-master/queue/MyOrg/MyProjectSpace/API/Customers)… In this case “/1001”: A Router Snap is used to conditionally direct execution to the appropriate subflows designed in accordance with the RESTful CRUD operations described above: Additional Reference https://en.wikipedia.org/wiki/Representational_state_transfer http://doc.snaplogic.com/ultra-tasksREST Get Slow
Hey guys, I have built a simple REST Get process to grab some data from an API. There are about 100 URLs to call but it is taking ages. 100 URLs takes about 7 mins whereas in another software application the 100 calls takes about 25s! I have tried using the REST Get snap in a child pipeline and increasing the pool size but I’m still not getting anywhere the speed I would expect. Any suggestions?
