At blitz.io, for a while there, we were only relying on CouchDB clusters as the primary NoSQL database with some in-memory caching. As we grow (rapidly) and scale out, there are aspects of what we collect and store that are transient and real-time. While CouchDB is awesome for the map/reduce, replication and incremental view indexes, the real-time queues (emails, counters, stats, etc) natural lend themselves to, yup, redis. We are in the process of rolling out geo-located redis instances as part of our global infrastructure.
How to win in the age of cyber war
While the bad news is that experts are declaring that we have entered the age of cyber war, the worse news as we enter 2012 is that security systems and professionals are just not able to keep up. Security attacks are increasing in their complexity and intensity every day. These range from inter-state attacks (like the one on Raytheon this year and the ones from China that are being investigated by the U.S. government) to cyber-crime (that includes countless malware and DDOS attacks against businesses and consumers).
Validating Application Detection Signatures
In the new world of next-generation networks, pretty much every leading network equipment manufacturer (NEM) today has application-awareness built into their products. Whether it’s an application firewall, serving gateway or edge router, they’re all using deep packet inspection (DPI) to look deep into the network traffic to identify the specific application.
For example, Cisco has Application Visibility & Control, Juniper has AppSecure, Palo Alto Networks has App-ID, Sandvine has Traffic Identification and Tellabs has Application Identification.
Each vendor has their own proprietary database comprised of hundreds or thousands of application signatures and on finding a match, their system can then take action based on the defined policy (e.g. block an application, apply QoS, etc…)
Before these new application signatures are released however, testing is needed to ensure the accuracy of the detection. One of the major challenges is to avoid the false positive, in which an application is misclassified.
Dear Angry Nerds, meet Blitz the Bird Thrower
This is a repost of my Atlassian’s guest blog, announcing a Bamboo plugin for blitz.io.
The pig of a problem
We all know what happens when your app performs like a pig. You lose users, customers and revenue. Your app is slow, the failing pigs don’t amuse your customers and you hear about it as the trending topic on Twitter. In most cases you don’t even know that it’s slow until you push the app into production, multiple times a day. How can you identify performance bottlenecks earlier in the cycle? And, if you don’t discover them how to you find and fix them as fast as possible?
Enter Blitz – a performance testing tool, built by Nerds that were angry at how the existing tools weren’t keeping pace with the new Application Development Lifecycle that has Continuous Integration as its center piece.
4 full bars but no buzz?… start doing DPI
Ever been in a situation where you have four full bars but can’t make a call? I have, and that’s what made me realize that signal strength is but one of many factors that affect connectivity. Fancy wireless techniques like spatial beam forming and frame aggregation between the cell tower and the phone sounds really cool but if the network is congested at the back end then magic on the radio side won’t amount to much for the user. Full Post »
Using real apps to test billing and charging on 4G/LTE networks
The hype, and in many cases concern around DPI has always been strong. It has triggered provocative debate on the Internet around privacy, end user rights, the role of the operator, and the extent to which they can monitor what applications we send and receive on the Internet.
The truth is that DPI isn’t just an emerging technology; it’s actually a reality, showing up on traditional fixed line networks, enterprise networks and most recently on mobile networks. Recently, Telefonica announced the deployment of Sandvine’s network policy control solutions to provide visibility across the network for some 250 million subscribers across 20 countries.
Mu App Quadrant #3 – Skype Voice on Mac (OS X) Expends at Least 28% More for Consumers and Operator Networks than on Other Devices
In the previous versions of the Mu App Quadrant we first compared the most popular video services, and then specifically focused on Netflix across multiple endpoints. Now, in this third edition we have looked at Skype. Not only is it one of the most popular voice apps on the internet with over 30 million users online at peak times, it’s also one of the biggest bandwidth guzzlers, due in part to the P2P nature of its architecture.
blitz.io: Geo-located Traceroutes with Heroku, AWS and CouchDB
Okay, not the greatest, ground-breaking, coolest, earth-shattering feature ever. Let’s just get that out of the way. But, in the process of troubleshooting various latency issues for our customers, we found ourselves logging on to various EC2 instances of blitz.io to run traceroutes to our users sites/apps to diagnose problems. We are developers, hanging out in TextMate, vim and our terminals and the ability to take a local Unix command and run it remotely while staying in our zone (shell) was important. So …
Driving Real Application Traffic Through Junosphere Virtual Infrastructure
Today, Juniper announced Junosphere™ Lab, an innovative on-demand service that gives service providers and enterprises immediate and low cost access to a virtualized environment for designing and testing networks. Very cool stuff – leveraging the power of the cloud and helping customers dramatically reduce their TCO while accelerating the time to model networks.
Real Traffic in a Virtual Environment
So when you spin up a network environment and model a production topology, you’ll then need a way to create realistic application traffic to understand its impact across the network. That’s where we come in.
Mu Studio Performance has been integrated into the Junosphere Lab so you can just as easily spin up (and tear down) virtual instances of our performance testing solution to quickly and accurately recreate a mix of applications that represent the production environment – that is, real users on real devices, running real applications.
Categories: Cloud, DPI, EC2, Firewall, iPhone, IPS, Performance, Scalability, Scale, Studio, Testing, Uncategorized
Ensuring the Accuracy of the Mu TestCloud Application Tests
In a previous blog I discussed how we had started to build out the test content for different kinds of applications across categories like P2P, video, chat and social media in our Mu TestCloud store. Fast-forward to today, and we’ve now got well over 2,000 tests, with coverage for hundreds of different apps. We’ve also got lots of customers who are actively using these ready-to-run tests for a wide range of use-cases – everything from verifying application detection signatures to validating application policies, as well as billing and charging.
But regardless of their domain, there are two common questions that customers are curious to understand:
1. How do we select the applications in the first place?
2. How do we ensure the accuracy of the tests?
So for this blog I’m going to give you a behind-the-scenes view into our test content creation process.
