Welcome!

Machine Learning Authors: Yeshim Deniz, Liz McMillan, Pat Romanski, Elizabeth White, Corey Roth

Related Topics: Machine Learning , Java IoT, Microservices Expo, Microsoft Cloud, Open Source Cloud, Agile Computing

Machine Learning : Article

TraceView Data API

Announcing the TraceView Data API

I’m excited to announce a new feature to TraceView – the Data API!

In a nutshell, the Data API exposes all of those high-level metrics you’re collecting in TraceView over REST, formatted as JSON. Now you can take that data, jam it into your own system and do whatever you need to make sure everybody in your organization sees what they need, when they need it. We’ve also wrapped our configuration API into the same place, so you can interact with all our services in one place.

If you’re itching to get to it, head on over to the docs. If you’re still not convinced, read on! Let’s take a look at what you can do with this.

Latency and Volume
Before you do anything, you need to know how your app is doing right now, and that starts with two questions. How much traffic do I have, and how fast is it? The easy way to look at this is just to plot them:

1
2
$ export API_KEY=xxx # For TraceView, tracing TraceView!
$API_KEY&time_window=week" | python extract.py

Latency Volume

(Check out this gist for the full scripts. I’m using the wonderful matplotlib to generate these plots, by the way. I also recommend gnuplot, if you weren’t poisoned by Matlab in a previous life, like some of us.)

This is actually our backend trace-processing machinery – a RabbitMQ based system with a bunch of Python Celery workers feeding off of it. You can see the periodic change in volume, as most of our customers are based in the US and Canada.

An interesting bit about this particular data set in that there’s variation in the response times, and it seems related to the amount of traffic we get. Let’s plot those against each other, and see what that looks like:

Capacity

These look pretty correlated! In an ideal world, we’d see a flat line in latency, no matter the traffic. This seems to show that we actually get a bit slower as the number of traces we process increases. This means there’s some sort of resource contention here, either CPU, memory or disk usage on one of the machines. In our case, the app page tells that story for us.

Dashboard

The only layer that’s actually increasing in time with volume is our Cassandra layer. This is pretty common; most of the components in this system scale horizontally, except for writes to the DB. Even with Cassandra’s stellar write performance, we still see a bit of a slowdown. Time to add more machines to the ring!

What are you going to build? Sign up for a free trial of TraceView today!

Related Articles

More Stories By TR Jordan

A veteran of MIT’s Lincoln Labs, TR is a reformed physicist and full-stack hacker – for some limited definition of full stack. After a few years as Software Development Lead with Thermopylae Science and Techology, he left to join Tracelytics as its first engineer. Following Tracelytics merger with AppNeta, TR was tapped to run all of its developer and market evangelism efforts. TR still harbors a not-so-secret love for Matlab-esque graphs and half-baked statistics, as well as elegant and highly-performant code. Read more of his articles at www.appneta.com/blog or visit www.appneta.com.

CloudEXPO Stories
"Space Monkey by Vivent Smart Home is a product that is a distributed cloud-based edge storage network. Vivent Smart Home, our parent company, is a smart home provider that places a lot of hard drives across homes in North America," explained JT Olds, Director of Engineering, and Brandon Crowfeather, Product Manager, at Vivint Smart Home, in this SYS-CON.tv interview at @ThingsExpo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
Modern software design has fundamentally changed how we manage applications, causing many to turn to containers as the new virtual machine for resource management. As container adoption grows beyond stateless applications to stateful workloads, the need for persistent storage is foundational - something customers routinely cite as a top pain point. In his session at @DevOpsSummit at 21st Cloud Expo, Bill Borsari, Head of Systems Engineering at Datera, explored how organizations can reap the benefits of the cloud without losing performance as containers become the new paradigm.
In this presentation, you will learn first hand what works and what doesn't while architecting and deploying OpenStack. Some of the topics will include:- best practices for creating repeatable deployments of OpenStack- multi-site considerations- how to customize OpenStack to integrate with your existing systems and security best practices.
In an era of historic innovation fueled by unprecedented access to data and technology, the low cost and risk of entering new markets has leveled the playing field for business. Today, any ambitious innovator can easily introduce a new application or product that can reinvent business models and transform the client experience. In their Day 2 Keynote at 19th Cloud Expo, Mercer Rowe, IBM Vice President of Strategic Alliances, and Raejeanne Skillern, Intel Vice President of Data Center Group and GM, discussed how clients in this new era of innovation can apply data, technology, plus human ingenuity to springboard to advance new business value and opportunities.
The current age of digital transformation means that IT organizations must adapt their toolset to cover all digital experiences, beyond just the end users’. Today’s businesses can no longer focus solely on the digital interactions they manage with employees or customers; they must now contend with non-traditional factors. Whether it's the power of brand to make or break a company, the need to monitor across all locations 24/7, or the ability to proactively resolve issues, companies must adapt to the new world.