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

  • Building Multi-Rail Payment Failover to Stop Latency Spikes and Double Debits
  • Preventing Downtime in Public Safety Systems: DevOps Lessons from Production
  • Source-Driven Development in Salesforce: Managing Metadata and API Versions
  • Building Secure AI LLM APIs: A DevOps Approach to Preventing Data Breaches

Trending

  • RAG Architecture Patterns: Proxy, Caching, and Routing
  • Constrained Decoding Models Explained: Encoders, Decoders and When to Use Them
  • Google Cloud KMS vs. AWS KMS: Java Encryption Guide
  • MQTT, Kafka, NATS, or Zenoh? Choosing Edge-to-Cloud Messaging by Traffic Pattern

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. Databases
  4. The Monitoring Layer of the DevOps Aggregation API Platform

The Monitoring Layer of the DevOps Aggregation API Platform

I'll keep profiling the APIs for the service providers in my lifecycle research until I get more of the DevOps-aggregate API definition mapped out.

By 
Kin Lane
·
Oct. 24, 16 · Opinion
Post on X (opens in a new tab) Share on LinkedIn (opens in a new tab)
12.5K 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

While spending some time going through my API monitoring research, I found myself creating an OpenAPI spec and APIs.json index for the DataDog API. I had the realization that this is the beginning of what I'm looking for when I talk about a DevOps aggregation API platform. DataDog is just the monitoring layer of this vision I have, but it has many of the other elements I'm looking for.

DataDog has all the monitoring elements present in their API platform, and they have all the platform integrations I'm envisioning in a DevOps aggregate API. We just need the same thing for design, deployment, virtualization, serverless, DNS, SDK, documentation, and the other critical stops along a modern API life cycle.

I'll keep profiling the APIs for the service providers in my lifecycle research until I get more of the DevOps-aggregate API definition mapped out. Hopefully, I will stumble across other providers like DataDog who are doing such an interesting job with the choreography and orchestration that will be needed to work across so many platforms. I appreciate API aggregation service providers who one, have an API, and two, share so much of the definitions behind their work.

The next thing that I will work on is profiling the metrics that DataDog has defined across the platforms they integrate with. Take a look at the metrics they have defined for each integration; there are some valuable patterns available in their work. I'd love to see a common set of API monitoring metrics emerge from across providers, something that if we standardize and share in a machine readable way, others will emulate, making interoperability much smoother when it comes to monitoring.

I just wanted to keep beating my drum about the fact that APIs aren't just about building applications; they are also critical to the API life cycle and making sure there are stable, scalable APIs to build applications on top of in the first place.

API DevOps

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

Opinions expressed by DZone contributors are their own.

Related

  • Building Multi-Rail Payment Failover to Stop Latency Spikes and Double Debits
  • Preventing Downtime in Public Safety Systems: DevOps Lessons from Production
  • Source-Driven Development in Salesforce: Managing Metadata and API Versions
  • Building Secure AI LLM APIs: A DevOps Approach to Preventing Data Breaches

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