«We’re bringing out a new application monitoring system to the DevOps space. It manages large enterprise applications that are distributed throughout a node in many enterprises and we manage them as one collective,» explained Kevin Barnes, President of eCube Systems, in this SYS-CON.tv interview at DevOps at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.

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With the advent of software defined networks (SDN), NFV (network function virtualization), and new network equipment, networks are being upgraded at a faster pace than ever before.  But dropping a new piece of equipment into a live network environment is a lot like playing Russian roulette – you have no way of knowing if a bullet is in the chamber or not. Luckily, network test labs can help you spot network problems before anyone pulls the trigger to go live.

Let’s examine the various elements that make up a good network test lab, and then we will review some key pointers to make sure you get the most out of the testing stages.

Four components of a good test lab

The four key pieces that make up a good network test lab include Layer 1/2 switching; abstraction; sandboxing; and visibility. Layer 1/2 switching is necessary to enable large groups of testers to set up their own isolated network configurations for testing. Otherwise, people will be required to manually re-cable network equipment, and will quickly run into conflicts over scheduling and resources.

One of the exciting new options for automatic physical network re-configuration involves using Layer 2 switching, either physical or SDN, to mimic Layer 1 switches. Emulating expensive Layer 1 switches with layer 2 networks can lower costs while still producing the same results. Layer 2 switching is applicable for most network tests, except in cases of extreme performance testing.

Since the network of the future will be a mixture of physical and software-defined, or all software defined, it is important to set up an abstraction between the physical network and the SDN. A good network test lab defines processes and selects tools that work consistently, whether or not the network components are physical, mixed, or all software-defined. Otherwise, users will have to rewrite tests and reset configurations whenever they use a software-defined network component rather than a physical network component.

For example, most virtualisation solutions can deploy VMs and set a simple network connection to a VM. However, they cannot tell if a VM is implementing a network device with multiple interfaces and ports, in which case the virtualisation solution cannot properly configure the rest of the network to connect to those ports. Therefore it’s critical to deploy network test tools that can recognise those port configurations. 

Sandboxes are another critical component of a good network test lab. Sandboxes allow testers to automate the network environment in which they run their test cases. Sandboxes provide tools for each tester to set up the proper network configurations and run their own tests in an isolated configuration.

In addition, sandboxes enable testers to incorporate all of the devices being tested, any traffic generators, and their tests into a single automation sequence. Sandboxes also create the necessary context for a complete audit trail of all the configurations, tests and results together.

The last key part of a successful network test lab involves getting visibility into all the lab resources in order for testers to quickly and easily access whatever resources are needed. Visibility also ensures that testers can quickly identify test failures and respond accordingly.

Likewise, lab managers need visibility as to when and how the test lab resources have been used, including the historical trending for all physical and virtual resources. Visibility tools allow lab managers to monitor each user and the amount of lab resources that they consume.

Two final steps to get the most from network lab tests

Automation and network path checking are both important elements to make any network test lab successful. Automation is key because the network setup, configuration and teardown tend to be time consuming and error prone. In fact, manual setup mistakes are often the main reason why tests fail, not the actual test errors themselves.

Manual steps also create unneeded bottlenecks that delay test cycle times. Users can save time and reduce errors by applying automation to the configuration of the network environment, the orchestration of traffic generators, and the actual tests.

The final step is to include network path checking as part of automation. After users have configured a network for automated testing, they still need to pre-validate that the network is properly connected and steering traffic correctly. Network path checking also creates an audit trail for each validation, which really should be done prior to running any tests.

Don’t shoot yourself in the foot, or even worse, don’t shoot yourself in the head by playing Russian roulette with your network. Remember to combine the four main components of an effective test lab with strong systems for automation and network path checking, and you will be on your way to test lab success. 

«Software-defined storage is a big problem in this industry because so many people have different definitions as they see fit to use it,» stated Peter McCallum, VP of Datacenter Solutions at FalconStor Software, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.

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Cloud technology can create positive business outcomes for businesses – but only if the organisation is willing to foster business transformations that leverage what the cloud offers.

That is the key finding from a report published by The Economist and sponsored by Google on how trust in cloud computing correlates with business performance.

The report, which is based on a global survey of more than 450 executives in 10 countries across five continents, finds 38% of enterprise IT is currently based on cloud-based technology, with the figure expected to grow to 45% by 2019. Despite this, trust in cloud technology remains muted, with only 16% of those polled indicating ‘very high trust’ in the cloud.

Despite this comparative lack of trust – although more than half (52%) of those polled noted an increase in overall cloud trust –  almost all (99%) of respondents report use of at least some cloud services in their organisation. Respondents who say their company has higher trust in the cloud report much better outcomes in both financial and non-financial success metrics.

Yet trust in the cloud does not grow organically. The report advocates three primary elements that will help businesses engage further:

• C-suite support for cloud initiatives. The survey argues that at organisations with low levels of cloud trust, management is the most common barrier to the adoption of cloud technologies. “The C-suite alone cannot instil trust in cloud technology, but without its help such confidence may not develop,” the report notes.
• Introducing cloud services with an eye to building trust. High profile improvements can help build trust across an organisation, the report notes, as well as simpler, quick win solutions. This was one of the keys to Siemens building their trust in cloud.
• Go further than simply educating employees. Training in new tools is one thing, but for ‘deep change management’, as the report puts it, pushing people to use their new tools in a creative way will be more fruitful.

You can find the full report here (no registration required).

In his session at @DevOpsSummit at 19th Cloud Expo, Yoseph Reuveni, Director of Software Engineering at Jet.com, will discuss Jet.com’s journey into containerizing Microsoft-based technologies like C# and F# into Docker. He will talk about lessons learned and challenges faced, the Mono framework tryout and how they deployed everything into Azure cloud.
Yoseph Reuveni is a technology leader with unique experience developing and running high throughput (over 1M tps) distributed systems with extremely low latency (under 10ms). He is working at Jet.com as a Director of Software Engineering leading key initiatives around service containerization, scaling and geo-redundancy. His extensive knowledge integrating docker, mesos, kafka, and many more pieces of the big data stack resulted in numerous performance boosts and operational cutoffs. Yoseph holds an MSc from the Hebrew University of Jerusalem in Math.

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It’s 2016: buildings are smart, connected and the IoT is fundamentally altering how control and operating systems work and speak to each other. Platforms across the enterprise are networked via inexpensive sensors to collect massive amounts of data for analytics, information management, and insights that can be used to continuously improve operations.
In his session at @ThingsExpo, Brian Chemel, Co-Founder and CTO of Digital Lumens, will explore:
The benefits sensor-networked systems bring to a variety of business applications, like employee productivity, efficiency, energy savings

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As companies gain momentum, the need to maintain high quality products can outstrip their development team’s bandwidth for QA. Building out a large QA team (whether in-house or outsourced) can slow down development and significantly increases costs. This eBook takes QA profiles from 5 companies who successfully scaled up production without building a large QA team and includes:
What to consider when choosing CI/CD tools
How culture and communication can make or break implementation

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Whether your IoT service is connecting cars, homes, appliances, wearable, cameras or other devices, one question hangs in the balance – how do you actually make money from this service? The ability to turn your IoT service into profit requires the ability to create a monetization strategy that is flexible, scalable and working for you in real-time. It must be a transparent, smoothly implemented strategy that all stakeholders – from customers to the board – will be able to understand and comprehend.

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