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Category Archives for "Networking"

The future of storage is here

Sometime in the past couple of years, Gartner introduced a term called “Shared Accelerated Storage” (SAS) to describe what’s next for the industry after all-flash arrays. I’m not sure when they first used the term, but it was the very first bullet in its 2017 Storage Hype Cycle, indicating its relative newness as a market category.In its Hype Cycle, Gartner has a rather long and complicated definition of what SAS is. The easy way to think about it is that it brings the benefits of network-based systems and direct-attached systems together by leveraging a number of new technologies, most notably Nonvolatile Memory Express— or NVMe, as its more commonly known.  To read this article in full, please click here

Community Networks Can Bridge the Digital Divide, But Some Still Need to Be Convinced

Community networks can help bring connectivity to many of world’s population still without it, but some governments, ISPs, and some potential users need to be convinced of their benefits, connectivity experts said.

Community networks can bring huge economic, educational, and social opportunities to areas without Internet access, Raul Echeberria, the Internet Society’s vice president for global engagement, said Wednesday.

With nearly half the world’s population still lacking Internet access, “this is creating a huge gap of opportunities,” he said during a community networking roundtable discussion hosted by the Internet Society.

Through community network projects such as a year-old network in the mountainous region of Tusheti in the nation of Georgia, the Internet Society has seen the proof that existing technologies can bring Internet service to some of the most remote areas on Earth, Echeberria said.

After a year of operation, the Georgian network is providing new economic opportunities to inn keepers and other tourism-related businesses in the region, said Ucha Seturi, director of the community network project there. Demand for Internet service is growing, he added.

With the technology questions largely solved, a key piece of the puzzle for community networks is getting the buy-in of the unserved communities and Continue reading

Thanks, Arista! We’ll Leave a Light on for You

Wow.  Just, wow.  Here we were at Pica8, ten days away from announcing a screamingly simplified white box switching architecture for enterprise campus networks – one that makes legacy switch stack and chassis switch replacement with disaggregated white box switches ridiculously easy — when Arista suddenly pops up and says that the success white box switches are having in the data center is now well and truly annoying to them, so they are starting to plan a future expedition to the enterprise campus in search of replacing lost revenue.

But after blowing straight past total market validation for us – we already have a number of ongoing enterprise campus network deployments inside some of Cisco’s oldest and largest accounts – Arista then went on to articulate the changes they envision for their future campus network switching push and, in doing so, came very close to a one-to-one mapping with what we’ve just announced as an orderable solution with our new PicaPilot switch orchestration software (see link below). (I really must order a case of champagne for my friends over there.)

Just how close is the mapping?  Well, let’s start with solving the urgent requirement to simplify Continue reading

Thanks, Arista! We’ll Leave a Light on for You

Wow.  Just, wow.  Here we were at Pica8, ten days away from announcing a screamingly simplified white box switching architecture for enterprise campus networks – one that makes legacy switch stack and chassis switch replacement with disaggregated white box switches ridiculously easy — when Arista suddenly pops up and says that the success white box switches are having in the data center is now well and truly annoying to them, so they are starting to plan a future expedition to the enterprise campus in search of replacing lost revenue.

But after blowing straight past total market validation for us – we already have a number of ongoing enterprise campus network deployments inside some of Cisco’s oldest and largest accounts – Arista then went on to articulate the changes they envision for their future campus network switching push and, in doing so, came very close to a one-to-one mapping with what we’ve just announced as an orderable solution with our new PicaPilot switch orchestration software (see link below). (I really must order a case of champagne for my friends over there.)

Just how close is the mapping?  Well, let’s start with solving the urgent requirement to simplify Continue reading

AI boosts data center availability, efficiency

Artificial intelligence is set to play a bigger role in data-center operations as enterprises begin to adopt machine-learning technologies that have been tried and tested by larger data-center operators and colocation providers.Today’s hybrid computing environments often span on-premise data centers, cloud and collocation sites, and edge computing deployments. And enterprises are finding that a traditional approach to managing data centers isn’t optimal. By using artificial intelligence, as played out through machine learning, there’s enormous potential to streamline the management of complex computing facilities.Check out our review of VMware’s vSAN 6.6 and see IDC’s top 10 data center predictions. Get regularly scheduled insights by signing up for Network World newsletters. AI in the data center, for now, revolves around using machine learning to monitor and automate the management of facility components such as power and power-distribution elements, cooling infrastructure, rack systems and physical security.To read this article in full, please click here

Data center management: What does DMaaS deliver that DCIM doesn’t?

Data-center downtime is crippling and costly for enterprises. It’s easy to see the appeal of tools that can provide visibility into data-center assets, interdependencies, performance and capacity – and turn that visibility into actionable knowledge that anticipates equipment failures or capacity shortfalls.Data center infrastructure management (DCIM) tools are designed to monitor the utilization and energy consumption of both IT and building components, from servers and storage to power distribution units and cooling gear.[ Learn how server disaggregation can boost data center efficiency and how Windows Server 2019 embraces hyperconverged data centers . | Get regularly scheduled insights by signing up for Network World newsletters. ] DCIM software tackles functions including remote equipment monitoring, power and environmental monitoring, IT asset management, data management and reporting. With DCIM software, enterprises can simplify capacity planning and resource allocation as well as ensure that power, equipment and floor space are used as efficiently as possible.To read this article in full, please click here

AI boosts data center availability, efficiency

Artificial intelligence is set to play a bigger role in data-center operations as enterprises begin to adopt machine-learning technologies that have been tried and tested by larger data-center operators and colocation providers.Today’s hybrid computing environments often span on-premise data centers, cloud and collocation sites, and edge computing deployments. And enterprises are finding that a traditional approach to managing data centers isn’t optimal. By using artificial intelligence, as played out through machine learning, there’s enormous potential to streamline the management of complex computing facilities.Check out our review of VMware’s vSAN 6.6 and see IDC’s top 10 data center predictions. Get regularly scheduled insights by signing up for Network World newsletters. AI in the data center, for now, revolves around using machine learning to monitor and automate the management of facility components such as power and power-distribution elements, cooling infrastructure, rack systems and physical security.To read this article in full, please click here

Data center management: What does DMaaS deliver that DCIM doesn’t?

Data-center downtime is crippling and costly for enterprises. It’s easy to see the appeal of tools that can provide visibility into data-center assets, interdependencies, performance and capacity – and turn that visibility into actionable knowledge that anticipates equipment failures or capacity shortfalls.Data center infrastructure management (DCIM) tools are designed to monitor the utilization and energy consumption of both IT and building components, from servers and storage to power distribution units and cooling gear.[ Learn how server disaggregation can boost data center efficiency and how Windows Server 2019 embraces hyperconverged data centers . | Get regularly scheduled insights by signing up for Network World newsletters. ] DCIM software tackles functions including remote equipment monitoring, power and environmental monitoring, IT asset management, data management and reporting. With DCIM software, enterprises can simplify capacity planning and resource allocation as well as ensure that power, equipment and floor space are used as efficiently as possible.To read this article in full, please click here

AI boosts data-center availability, efficiency

Artificial intelligence is set to play a bigger role in data-center operations as enterprises begin to adopt machine-learning technologies that have been tried and tested by larger data-center operators and colocation providers.Today’s hybrid computing environments often span on-premise data centers, cloud and collocation sites, and edge computing deployments. And enterprises are finding that a traditional approach to managing data centers isn’t optimal. By using artificial intelligence, as played out through machine learning, there’s enormous potential to streamline the management of complex computing facilities.Check out our review of VMware’s vSAN 6.6 and see IDC’s top 10 data center predictions. Get regularly scheduled insights by signing up for Network World newsletters. AI in the data center, for now, revolves around using machine learning to monitor and automate the management of facility components such as power and power-distribution elements, cooling infrastructure, rack systems and physical security.To read this article in full, please click here

Data-center management: What does DMaaS deliver that DCIM doesn’t?

Data-center downtime is crippling and costly for enterprises. It’s easy to see the appeal of tools that can provide visibility into data-center assets, interdependencies, performance and capacity – and turn that visibility into actionable knowledge that anticipates equipment failures or capacity shortfalls.Data center infrastructure management (DCIM) tools are designed to monitor the utilization and energy consumption of both IT and building components, from servers and storage to power distribution units and cooling gear.[ Learn how server disaggregation can boost data center efficiency and how Windows Server 2019 embraces hyperconverged data centers . | Get regularly scheduled insights by signing up for Network World newsletters. ] DCIM software tackles functions including remote equipment monitoring, power and environmental monitoring, IT asset management, data management and reporting. With DCIM software, enterprises can simplify capacity planning and resource allocation as well as ensure that power, equipment and floor space are used as efficiently as possible.To read this article in full, please click here

AI boosts data-center availability, efficiency

Artificial intelligence is set to play a bigger role in data-center operations as enterprises begin to adopt machine-learning technologies that have been tried and tested by larger data-center operators and colocation providers.Today’s hybrid computing environments often span on-premise data centers, cloud and collocation sites, and edge computing deployments. And enterprises are finding that a traditional approach to managing data centers isn’t optimal. By using artificial intelligence, as played out through machine learning, there’s enormous potential to streamline the management of complex computing facilities.Check out our review of VMware’s vSAN 6.6 and see IDC’s top 10 data center predictions. Get regularly scheduled insights by signing up for Network World newsletters. AI in the data center, for now, revolves around using machine learning to monitor and automate the management of facility components such as power and power-distribution elements, cooling infrastructure, rack systems and physical security.To read this article in full, please click here

Data-center management: What does DMaaS deliver that DCIM doesn’t?

Data-center downtime is crippling and costly for enterprises. It’s easy to see the appeal of tools that can provide visibility into data-center assets, interdependencies, performance and capacity – and turn that visibility into actionable knowledge that anticipates equipment failures or capacity shortfalls.Data center infrastructure management (DCIM) tools are designed to monitor the utilization and energy consumption of both IT and building components, from servers and storage to power distribution units and cooling gear.[ Learn how server disaggregation can boost data center efficiency and how Windows Server 2019 embraces hyperconverged data centers . | Get regularly scheduled insights by signing up for Network World newsletters. ] DCIM software tackles functions including remote equipment monitoring, power and environmental monitoring, IT asset management, data management and reporting. With DCIM software, enterprises can simplify capacity planning and resource allocation as well as ensure that power, equipment and floor space are used as efficiently as possible.To read this article in full, please click here

Regular Expression for Network Engineer Part-2

This post is continuation of the  Regular Expression for Network Engineer Part-1 , here  we  have a look for the different methods to find out the pattern in string.

Findall() – returns  list of all the  matches the pattern in a string  without overlapping

  • EXAMPLE

[code language = “Python”]

re.findall(pattern, string[, flags])

In [118]: ip
Out[118]: ‘10.10.1.10,29.10.1.10,10.10.1.20,192.168.1.0,172.16.10.1,10.10.10.121’

In [119]: out= re.findall(r'(10.10.10.\d+)’ ,ip)
In [120]: out
Out[120]: [‘10,10.10.1’, ‘10.10.10.121’]

#Above example help us to find out all the IP’s of subnet 10.10.10.0/24 from group of ip’s.

[/code]

Match()-return a match object when pattern is found at the beginning of string, if no pattern is found ,result in None.

  • EXAMPLE

[code language = “Python”]

In [189]: text
Out[189]: ‘Cisco IOS Software, 7200 Software (C7200-SPSERVICESK9-M), Version 12.2(33)SRE, RELEASE SOFTWARE (fc1)’

In [190]: out = re.match(r”Cisco”,text)
In [191]: out
Out[191]: <_sre.SRE_Match object; span=(0, 5), match=’Cisco’>
In [192]: out = re.match(r” Software”,text)
In [193]: out
In [194]: out = re.search(r” Software”,text)
In [195]: out
Out[195]: <_sre.SRE_Match object; span=(9, 18), Continue reading