DZone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Newsletter
Log In / Join
Refcards Trend Reports
Events Video Library
Refcards
Trend Reports

Events

View Events Video Library

Related

  • MCP Elicitation: Human-in-the-Loop for MCP Servers
  • Building Gateway Analytics: My Journey to Making API Traffic Data Useful
  • A Practical Guide to API Threat Analytics in Cloud Platforms
  • Designing Developer-Friendly APIs and SDKs: Strategies for Platform Success

Trending

  • Spring Security JWT Validation Best Practices
  • Idempotency Under Concurrency: Why Your Application Check Isn't the Last Line of Defense
  • How to Hide Sensitive Information Before You Share a File
  • You Do Not Need a PhD to Become an AI Engineer: The Essential Skill Stack

Draft This article hasn't been published, so readers can't see it.

In moderation This article is waiting for review, so readers can't see it yet.

Deleted This article has been deleted, so readers can't see it.

  1. DZone
  2. Data Engineering
  3. Data
  4. Increased Analytics at the API Client and SDK Level

Increased Analytics at the API Client and SDK Level

API providers are including more analytics services...but are the features more about data generation than they are about analytics?

By 
Kin Lane
·
Oct. 07, 16 · Opinion
Post on X (opens in a new tab) Share on LinkedIn (opens in a new tab)
4.2K Views

Join the DZone community Save articles, join the discussion, and download Refcards and Trend Reports with a free account.

Join for free Already a member? Log in

I am seeing more examples of analytics at the API client and SDK level, providing more access to what is going on at this layer of the API stack. I'm seeing API providers build them into the analytics they provide for API consumers and more analytic services from providers for the web, mobile, and device endpoints. Many companies are selling these features in the name of awareness, but in most cases, I'm guessing it is about adding another point of data generation which can then be monetized (IoT is a gold rush!).

Image title

As I do, I wanted to step back from this movement and look at it from many different dimensions, broken down into two distinct buckets:

Positives

  • More information. There will be more data that can be analyzed.
  • More awareness. We will have visibility across integrations.
  • Real-time insights. Data can be gathered on a real-time basis.
  • More revenue. There will be more revenue opportunities here.
  • More personalization. We can personalize the experience for each client.
  • Fault tolerance. There are opportunities for building in API fault tolerance.

Negatives

  • More information. If it isn't used, it can become a liability.
  • More latency. This layer slows down the primary objective.
  • More code complexity. This introduces added complexity for devs.
  • More security consideration. We just created a new exploit opportunity.
  • More privacy concerns. There are new privacy concerns facing end-users.
  • More regulatory concerns. In some industries, it will be under scrutiny.

I can understand why we want to increase the analysis and awareness at this level of the API stack. I'm a big fan of building in resiliency in our clients and SDKs, but I think that we have to weigh the positive and negatives before jumping in. Sometimes I think we are too willing to introduce unnecessary code, data gathering, and potentially opening up security and privacy holes chasing new ways we can make money.

I'm guessing it will come down to each SDK and the API resources that are being put to work. I'll be aggregating the different approaches I am seeing as part of my API SDK research and try to provide a more coherent glimpse at what providers are up to. By doing this, I'm hoping I can better understand some of the motivations behind this increased level of analytics being injected at the client and SDK level.

API Software development kit Analytics

Published at DZone with permission of Kin Lane. See the original article here.

Opinions expressed by DZone contributors are their own.

Related

  • MCP Elicitation: Human-in-the-Loop for MCP Servers
  • Building Gateway Analytics: My Journey to Making API Traffic Data Useful
  • A Practical Guide to API Threat Analytics in Cloud Platforms
  • Designing Developer-Friendly APIs and SDKs: Strategies for Platform Success

Partner Resources

×

Comments

Loading comments

The comments didn't load

Please try again in a moment.

Likes

Loading

The next likes didn't load. Please try again.

The likes didn't load

Please try again in a moment.

See who liked this

Log in or join DZone for free to see who liked this article.

Log in Join for free
  • RSS
  • X
  • Facebook

ABOUT US

  • About DZone
  • Support and feedback
  • Community research

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • Become a Contributor
  • Core Program
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 3343 Perimeter Hill Drive
  • Suite 215
  • Nashville, TN 37211
  • [email protected]

Let's be friends:

  • RSS
  • X
  • Facebook