Tag Archives: another

For Sale – HP Proliant Microserver N54L AMD Turion II Dual Core 2.2GHz Barebones

I have swapped out my hard drives and ram into another unit so this system is now surplus to requirements.
Yours for £90 delivered
IMG_20191014_135336.jpgIMG_20191014_135347.jpgIMG_20191014_135426__01.jpg
Location
Shrewsbury
Price and currency
£90
Delivery
Courier
Prefer goods collected?
I have no preference
Advertised elsewhere?
Advertised elsewhere
Payment method
Bank Transfer, Paypal Friends and Family

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For Sale – Surface Go (8GB RAM/128GB SSD) inc. Black Type Keyboard

Purchased this recently on another forum but decided I have too many devices. I tested it fully and used it for a week or so, battery life and everything else working as expected.

Both the Surface Go and Type Keyboard are boxed and in good condition. It has been upgraded to full version of Windows 10 Home.

Screen is spotless, and the unit casing is fine bar a couple of hairline scratches where the keyboard has latched on, and a few minor ones on the back. Pics from previous sale are here, note this does not include the pen.

Looking for £350 including delivery (RMSD which will cost £20), this combo still retails for £610 new.

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For Sale – Surface Go (8GB RAM/128GB SSD) inc. Black Type Keyboard

Purchased this recently on another forum but decided I have too many devices. I tested it fully and used it for a week or so, battery life and everything else working as expected.

Both the Surface Go and Type Keyboard are boxed and in good condition. It has been upgraded to full version of Windows 10 Home.

Screen is spotless, and the unit casing is fine bar a couple of hairline scratches where the keyboard has latched on, and a few minor ones on the back. Pics from previous sale are here, note this does not include the pen.

Looking for £350 including delivery (RMSD which will cost £20), this combo still retails for £610 new.

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Elastic SIEM spring release will complete Endgame tie-in

Elastic Inc. is preparing another shot across the bow of IT monitoring and analytics competitor Splunk with the integration of endpoint security features it plans to complete in the next six months.

The Elastic SIEM will add initial integration with software from Endgame, the endpoint security firm Elastic acquired in June, in a release that will be available Nov. 1. This initial integration will pull Endgame telemetry into the Elastic back end, where it can be visualized alongside the rest of an organization’s information from Logstash, Beats and other data collectors, via Kibana.

In the next release, endpoint security data will be displayed in the Elastic SIEM user interface, and will be covered by the Elastic Common Schema, a specification that adds consistency to data collected from various sources. Users will also be able to take enforcement action on endpoints through the SIEM UI in the later release, such as isolating an infected host, killing a suspicious application process, or removing an attacker from a system.

Sebastian Mill, CTO of global development, InfoTrackSebastian Mill

The Elastic SIEM, available since June, appeals to Elastic Stack users who want a centralized monitoring, logging and data visualization platform for various types of data, whether for infrastructure and application performance monitoring or security operations. This convergence of data monitoring tool sets reflects a convergence between security and IT operations teams under DevOps.

“We have over 100 developers across three countries,” said Sebastian Mill, CTO of global development at InfoTrack, a legal practice software maker based in Australia, with offices in the U.K. and U.S. “All of them can log in and see how their app is performing, and Elastic makes it easier for us to provide security to our DevOps teams as well.”

Security monitoring is particularly complex in a geographically distributed infrastructure where hundreds of millions of logs are collected from systems on a daily basis. InfoTrack, which uses the Elastic SIEM, plans to add endpoint security integration when it becomes available, and use Elastic’s machine learning tools to refine security analysis on its data.

It’s … really interesting to us that we cannot just alert and monitor, but also take action, and [avoid] alert fatigue from various different tools.
Sebastian MillCTO of global development, InfoTrack

“With endpoints, the number of assets will increase exponentially,” Mill said. “It’s also really interesting to us that we cannot just alert and monitor, but also take action, and [avoid] alert fatigue from various different tools.”

Endgame helps Elastic catch up with its chief competitor, Splunk, which already offers endpoint security monitoring and enforcement features in its Enterprise Security product. So far, the Elastic SIEM’s chief appeal for enterprise users has been cost, as the SIEM product is not licensed separately from Elastic Stack, and Elastic has typically charged less for data collection and retention than Splunk, although Splunk introduced new pricing models, including $10,000 “Rapid Adoption” packages, last month.

Elastic SIEM users wary of endpoint security costs

Elastic also plans to take a competitive approach to cost with endpoint security in the Elastic SIEM, though some enterprise users are more concerned about how data collection costs and network bandwidth demands will shake out with many more endpoint assets to monitor. Endpoints are any devices attached to a network, which also includes laptops, desktops and even API endpoints on servers.

“It becomes very interesting to see how much data will be sent into Elastic, where Elastic will ultimately make its money, and how much will stay on the client,” said John Gerber, principal cybersecurity analyst at Reston, Va., systems integrator SAIC, who has worked as a dedicated consultant at Elastic customer Oak Ridge National Laboratory (ORNL) since 2001.

“One has to question [the] balance of keeping [data] local and calculating at the endpoint, versus sending [it] to the central log area for analysis, and how that model will be affected by Elastic’s pricing,” he said. “It will be interesting to see what develops as Endgame and Elastic work these issues out.”

Endgame’s agent can store data locally on the endpoint when it is disconnected and then stream it back to the Elastic Stack when a network connection is available, which organizations can use to optimize bandwidth, Elastic officials said.

The Elastic Common Schema also does some pre-analysis of data before it’s ingested, which eases some of the performance requirements for ingestion into the central data repository and analysis once it’s there. Users also have a choice about whether they attach endpoints to the Elastic SIEM if they are concerned about data collection and storage costs.

On the licensing front, as of its Nov. 1 release, Elastic will not charge separately for Endgame for users of its Elastic Enterprise license. Users of this license level will get Endgame agents with no additional fee.

However, ORNL’s Gerber said he believes Endgame will require a license upgrade for his organization to Elastic Enterprise from Elastic Stack Platinum.

“Organizations will need to decide if they switch their license completely to Enterprise, split their licenses, or stay with [a lower] license while they wait for their current endpoint protection license to expire and Endgame to get integrated in Elastic,” he said.

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For Sale – Gaming PC, i7 7700k, 16GB DDR4, GTX 1080ti, 240GB SSD, 1TB HDD

Is this the PC we are speaking about via PM that I have already agreed to buy on another thread??

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Amazon buys NVMe startup E8 Storage to boost public cloud

Another NVMe flash startup has been acquired — this time by a public cloud storage giant.

Amazon confirmed it will acquire E8 Storage and deploy its rack-scale flash storage in the Amazon Web Services (AWS) public cloud.

Amazon said the transaction includes “some assets” that include hiring the E8 Storage team. E8 Storage CEO Zivan Ori reportedly will join Amazon in an unspecified executive capacity.

Israeli news outlet Globes first reported the story, citing unnamed sources who estimated Amazon will pay between $50 million and $60 million to acquire E8 Storage. A separate report by Reuters said the purchase price is much less, citing another source with knowledge of the deal. Amazon did not publicly disclose the acquisition price.

Amazon’s move comes two weeks after its public cloud rival Google bought file storage software startup Elastifile and nearly one month after holding company StorCentric acquired NVMe array hopeful Vexata.

The Amazon-E8 Storage marriage signals growing interest in NVMe flash. There is widespread industry belief that the NVMe protocol will eventually replace traditional SCSI-based storage. SCSI traffic makes several network hops along the network. By contrast, NVMe allows applications to talk directly to storage across multilane PCIe devices.

For Amazon, the deal highlights the competition it faces from enterprises seeking an AWS-like alternative that costs less than AWS and is managed on premises. It will be worth watching to see if Amazon integrates E8 Storage gear with AWS Nitro compute instances, which use NVMe as the underlying media with Elastic Block Store.

By acquiring E8 Storage, Amazon gains a storage operating system optimized for NVMe flash, said Eric Burgener, a research vice president of storage at analyst firm IDC.

“E8 has an NVMe-over-TCP implementation integrated in its software. It’s not that Amazon couldn’t have built that, but E8 already built it and it works. TCP is clearly the future of NVMe-over-fabrics-attached storage. That’s where the volume is going to be,” Burgener said.

Ori and Alex Friedman founded E8 Storage in 2014. Both previously had worked in management positions at IBM Storage. Friedman was E8’s vice president of R&D. E8 Storage emerged from stealth in 2016, with a dense block-based array that combines 24 NVMe SSDs in a 2U standard form factor.

The E8 Storage software targets analytics and similarly data-intensive workloads that require extreme performance and ultralow latency. E8 received more than $18 million in total funding, including a $12 million Series B round in 2016.

In addition to E8 arrays, customers have also been able to buy E8 Storage software on reference architecture with servers by Dell, Hewlett Packard Enterprise and Lenovo. The vendor this year added parallel file storage to target high-performance computing.

E8 Storage was an early entrant in end-to-end NVMe flash. The E8 architecture is based on industry-standard TCP over IP. Other NVMe startups include Apeiron Data, Excelero and Pavilion Data Systems.

Burgener said he wouldn’t be surprised to see more consolidation in NVMe storage. After ceding ground early, Burgener said legacy storage vendors have aggressively pushed into NVMe.

“Most of the majors have gotten their marketing acts together around selling NVMe for mixed workload consolidation, but they also want to go after the same kind of dedicated workloads” first targeted by NVMe startups, Burgener said.

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Graph processing gives credit analysis firms an edge

Graph databases have emerged as yet another way to connect data points — but graph processing requirements for big data have sometimes kept them out of the reach of real-time, operational analytics.

Startup TigerGraph has come along recently with its take on graph processing, one the company said will prove to be a fit in fintech and other applications that seek to disrupt business as usual.

Led by former Teradata Hadoop engineer Yu Xu, TigerGraph came out of stealth in 2017, claiming such notable users as Visa and the online payment platform Alipay for its graph database technology. The software has been used by these players, for example, to speed up credit checks and other traditionally time-consuming financial processes. 

Credit worthy

According to the company, TigerGraph supports a massively parallel processing architecture in which graph nodes — the company uses the less common term “vertices” — exhibit both compute and storage features; employs a parallel loader to speed data ingestion; and has fashioned a GSQL analytics language to produce parallel graph queries.

IceKredit has found those features useful in its efforts to expand the availability of credit ratings and risk assessments, according to Minqi Xie, vice president and director of modeling and business intelligence at the financial technology company.

“We have very large data sets with hundreds of millions of [nodes], and we need to mine the relationships at depth,” said Xie, who works to ensure IceKredit provides useful online credit ratings and risk monitoring services for companies and individuals.

Xie indicated IceKredit uses graph analytics to uncover connections within data sets that can identify patterns of risk. Such patterns must be uncovered more and more quickly in the fast-moving fintech space, where credit approvals that once took a week are now accomplished in minutes.

“TigerGraph made it feasible for us to leverage the features from relationship networks for real-time scoring,” he said.

Developer view of graph data
TigerGraph graph database development centers around graph nodes, or, in the company’s parlance, vertexes. Users can define vertex types and edge types to model a data schema, which can be loaded into working graphs.

Graph processing cuts through data molasses

Like others, Gaurav Deshpande, a longtime IBM data hand who earlier this year became vice president of marketing at TigerGraph, points to graph processing as superior to relational database schemes when it comes to representing interconnected relationship between data points.

Historically, almost all the graph database vendors have focused on operational capabilities.
Philip Howardanalyst, Bloor Research

But, Deshpande remarks, how quickly these connections can be analyzed can be an obstacle.

Traditionally, he said graph databases “weren’t ‘operational’ when it came to data volumes beyond 50 to 100 GBs. Performance slowed down. When you got to more than 500 GBs, performance was like molasses.”

Such systems were useful for visualizing data, but “they were nothing that could be used operationally,” Deshpande said. The parallelizing tactics TigerGraph applies to its graph database, he indicated, are intended to bring graph processing technology closer to operations.

Complex analytics at scale

TigerGraph is looking to join the ranks of still fairly limited graph NoSQL database makers that employ a number of diverse approaches to implementing the technology. These include vendors such as Neo4J, IBM, and Cambridge Semantics. Among others are Amazon and Microsoft, which have taken steps to bring graph processing technology more mainstream with, respectively, AWS Neptune and Azure Cosmos cloud offerings.

“Historically, almost all the graph database vendors have focused on operational capabilities. They support a certain level of analytics and query processing but not complex analytics at scale,” said Philip Howard, analyst at Bloor Research.

“TigerGraph, on the other hand, is specifically targeted at precisely those sorts of use cases, so you can’t really compare it with most of the other suppliers,” he said.

There are some precedents, however, and signs of change. Bloor noted supercomputer maker Cray offers graph analytics as part of its portfolio. And he sees others ready to follow suit.

For Sale – Lenovo ThinkPad 13 Gen 2 i3 7100U 4GB + Warranty

Selling another Lenovo ThinkPad 13 , this one is different from the one I previously sold with a shorter warranty. Condition is great, no signs of wear as its been docked

i3 7100U

4GB – Upgradable too not soldered

180B SSD

From today 150 days remaining

Lenovo Thinkpad 13 20J1 Core i3-7100U 4GB 180GB SSD 13.3 Inch Windows 10 Professional Laptop – Laptops Direct

Price and currency: 300
Delivery: Delivery cost is included within my country
Payment method: bank transfer
Location: dorset
Advertised elsewhere?: Advertised elsewhere
Prefer goods collected?: I have no preference

______________________________________________________
This message is automatically inserted in all classifieds forum threads.
By replying to this thread you agree to abide by the trading rules detailed here.
Please be advised, all buyers and sellers should satisfy themselves that the other party is genuine by providing the following via private conversation to each other after negotiations are complete and prior to dispatching goods and making payment:

  • Landline telephone number. Make a call to check out the area code and number are correct, too
  • Name and address including postcode
  • Valid e-mail address

DO NOT proceed with a deal until you are completely satisfied with all details being correct. It’s in your best interest to check out these details yourself.

For Sale – Lenovo ThinkPad 13 Gen 2 i3 7100U 4GB + Warranty

Selling another Lenovo ThinkPad 13 , this one is different from the one I previously sold with a shorter warranty. Condition is great, no signs of wear as its been docked

i3 7100U

4GB – Upgradable too not soldered

180B SSD

From today 150 days remaining

Lenovo Thinkpad 13 20J1 Core i3-7100U 4GB 180GB SSD 13.3 Inch Windows 10 Professional Laptop – Laptops Direct

Price and currency: 300
Delivery: Delivery cost is included within my country
Payment method: bank transfer
Location: dorset
Advertised elsewhere?: Advertised elsewhere
Prefer goods collected?: I have no preference

______________________________________________________
This message is automatically inserted in all classifieds forum threads.
By replying to this thread you agree to abide by the trading rules detailed here.
Please be advised, all buyers and sellers should satisfy themselves that the other party is genuine by providing the following via private conversation to each other after negotiations are complete and prior to dispatching goods and making payment:

  • Landline telephone number. Make a call to check out the area code and number are correct, too
  • Name and address including postcode
  • Valid e-mail address

DO NOT proceed with a deal until you are completely satisfied with all details being correct. It’s in your best interest to check out these details yourself.