Big Data Exchange (BDX) has officially opened a new data centre in the Paya Lebar area of Singapore, more than three months after acquiring the facility from Telstra.

Branded as SIN1, the new facility houses 1,800 racks with a 7.3MW power capacity, holding certificates such as UpTime Tier 3+ Design, SS564 GreenMark Gold Plus, TVRA, ISO27001 and PCI-DSS.

Going forward, BDX plans to upgrade the facility to increase power usage effectiveness and drive higher efficiency, with the city-state housing the highest megawatt per capita across the world.

“The BDX expansion into Singapore is an important addition to the BDX portfolio,” said Braham Singh, CEO of BDX. “After a successful acquisition and months of preparation, we are thrilled to officially launch the SIN1 facility.”

According to Singh, customers will have the ability to “easily integrate” both physical and virtual infrastructures via the BDX Single Pane into a managed hybrid ecosystem, connecting the new Singapore location through a highly automated cluster of data centres globally via BDX SoftConnect.

“The strategic proximity within the Asia Pacific region offers great geographical and connectivity advantages to meet the increasing internet and cloud exchange needs of our customers,” he added.

BDX operates data centres across Hong Kong, mainland China and Singapore, backed by the provision of hybrid cloud, connectivity and colocation solutions as a carrier-neutral provider.

The acquisition in April came two months after BDX announced the construction of a new data centre in Nanjing, China, which launched in June. Collectively, BDX now operates eight data centres in cities across two continents, including Nanjing, Guangzhou, Hong Kong, Singapore and London.

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Telstra is running deep learning algorithms over its Networks data to predict equipment failures before they occur and to find ways to address voice and SMS scams.

Data science (Networks) team manager Tim Osborne revealed the project, which is codenamed Telstra AI Lab or TAIL, in a presentation to IBM’s Think 2020 conference overnight.

TAIL is operating on a still-evolving applied data science platform pieced together with IBM’s assistance.

It uses a mix of existing Cisco UCS C240s and new IBM Power System AC922s for compute, and a Kubernetes-based stack on top, including Kubeflow, which is used to run machine learning algorithms on Kubernetes.

Osborne said TAIL was supported by a team of 25 data scientists and date engineers, who worked “with network engineering folks end-to-end across the business, looking to solve some of their most challenging problems with data science.”

He characterised the earlier challenges that TAIL is working on as network optimisation, power optimisation, and fraud and other telco-related scams.

“Network optimisation for us is about being able to be predictive and to detect and diagnose things that we couldn’t see,” he said.

“[It’s about] being able to drive proactive outcomes in our operations, proactive outcomes for our customers, and also trying to think about how we have networks that are self-organised.

“Being able to use a deep learning algorithm to understand machine code and figure out what all that means, so that we can fix something before it fails, is really cool, and that’s what we’re doing at the moment.”

On the power optimisation side, Osborne said the company is exploring heating, ventilation and air conditioning (HVAC) optimisation, though he did not elaborate on the specifics.

He also said TAIL is being used to crack down on telecommunications scams, an area where Telstra and other carriers have faced regulatory pressure over the past year.

“There are a lot of scams going on globally in the mobile space – people sending scams with SMS; people calling up and asking you to call back, and it’s very expensive to call. We’re employing countermeasures [against these now]. 

“We’re also interested in people that are exploiting our products – using our products and costing us a lot of money that shouldn’t be in their pockets, [that] shouldn’t be taken from our shareholders, [and] shouldn’t be impacting our customers.

“We’ve found a great way to prevent those things from happening.”

The work dates back less than six months, with Osborne revealing that Telstra had engaged IBM to stand up an applied data science platform to enable TAIL to operate.

“We had the people, the smarts; we had the use cases, the opportunities were there for us; and we had the data,” he said. “We just didn’t have a platform.

“Going back to December 2019, we started a partnership with IBM. This partnership has been absolutely exemplary. 

“We have symbiotic end states. IBM was very interested in getting more experience and exposure to using their platforms with Kubernetes and Kubeflow, and we were very interested in using those and scaling that up within our business. 

“We now have an incredible machine learning platform, [and] our data scientists are now fed and watered.”

Osborne said the data science platform enabled his team to perform rapid investigations and to scale up to production use cases quickly, based on the needs of the Networks business.

“As we become more popular, which is what’s happening in the business at the moment, we can add more machines, we can put more into the cluster and scale up the resources as we need it to be,” he said.

Under the hood

IBM’s AI technical specialist Adam Makarucha said the applied data science platform was deployed over December and January.

It has initially been built on top of native Kubernetes but there are plans to move it to Red Hat’s OpenShift container management platform, now that version 4.3 of OpenShift supports Power System.

On the hardware side, Marakucha said there is a “total of six machines, six nodes.”

“It doesn’t seem like a lot of compute, but what is key in this deployment is each one of these nodes has GPU acceleration,” he said.

“That really means that the total amount of compute and power in this machine actually far exceeds what you would expect out of a six node system. In fact, it’s probably in the order of 160 nodes in total performance.

“There is a total of 237.6 Teraflops of [GPU] single precision performance in this platform.”

Marakucha said that although Telstra wanted to use the Power System AC922s, it also wanted to reuse Cisco UCS hardware and other equipment and services it had already invested in.

“We could have just gone down the route of using an x86 based cluster but Telstra wanted to bring in the AC922s specifically because of the advantage they have for doing deep learning on very large data sets and large models,” Marakucha said.

While such mixed environments could be hard to manage, he said, Kubernetes was able to take on much of that.

Marakucha also said that the environment had been configured to set some limits on the amount of resource a single data scientist could use at any one time, to prevent it becoming monopolised.

“If you’re a data scientist out there, you probably do what I do when I do any data science: I try and get as many cores and as much compute as I possibly can, even if I’m not going to use it all at the same time,” he said.

“Lots of the data scientists in this environment were doing the same thing, which meant we quickly ran out of compute, because we were consuming all the cores. 

“So what we did is we hard locked the number of cores down to two and this meant we had flexibility because Kubernetes is nice in that if you ask for a request of two cores, you are guaranteed that as a minimum but it allows you to scale to more if there is more available.

“We’ve just locked some configurations to prevent over-provisioning.”

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Company chief executive Andrew Penn announced on Tuesday that having recognised the importance of cash flow to business, Telstra will pay invoices from 85 per cent of its suppliers within 20 days before the end of this year.

“This will mean small and medium businesses across the country will have cash in their hands sooner,” Mr Penn said.

Back in 2017, Telstra made a commitment to pay suppliers that are small businesses within 30 days. However, under this new arrangement the giant will move to 20-day payment terms for any supplier with invoices of up to $2 million annually.

“When we started this process in 2017, we used the Australian Bureau of Statistics’ definition as to what a small business was. Three years later, these definitions have shifted as part of our ever-diversifying economy,” Telstra chief financial officer Vicki Brady said.

“Our new methodology for paying invoices within 20 days captures more businesses than ever, and we encourage governments and the small business ombudsman to create a new standard, consistent definition of small business to ensure everyone is playing by the same rules.”

‘Fantastic news for small business’

The small business ombudsman was quick to commend the company, calling the move “a fantastic result for the small business community”.

“Telstra is leading by example with its commitment to faster payment times, and there’s no reason why other big businesses shouldn’t adopt the same practices,” Australian Small Business and Family Enterprise Ombudsman (ASBFEO) Kate Carnell said.

“Cash flow is always king for small businesses and never more so than now, particularly for small businesses in bushfire-affected communities.

“Telstra’s efforts will make a considerable difference to 85 per cent of its suppliers. These are mostly small businesses that no longer need to accept a supply chain finance option to be paid as they should be.”

Ms Carnell opined that given that the definition of a small business continues to be a major point of confusion, a unified approach would benefit Australian small businesses greatly.

“My office is committed to continuing to work with the business community to agree on a standardised definition.

“Overall, Telstra is showing real corporate leadership, and other businesses are encouraged to follow its lead.”

Telstra in hot water

Just last week, Telstra found itself in hot water, when The Australian revealed that the telco had partnered with tech firm Taulia to create a payday lending scheme, which would offer suppliers a cut on the invoices in exchange for prompt payments.

The Australian further found that Taulia uses artificial intelligence and big data mining to calculate just how much of a cut suppliers are willing to and could take.

At the time, the ASBFEO responded with a warning, telling big businesses that the practice of using supply chain finance products that mine big data to manipulate small businesses is unacceptable.

“It’s clearly not OK for big businesses to use their dominant position and access to technology to further squeeze small business margins,” she said at the time.

The ASBFEO is expected to release the findings of its review into supply chain financing before the end of April.

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