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Managed Hosting Platform: Blue/Green Deployments

Posted by Mark Nessen on Jan 17, 2018

Blue. Green. Red. Black. No, I'm not just talking about colors. I'm talking about a specific deployment technique we use at Kingland that allows for near zero downtime and the ability to easily rollback to a previous release if there are too many issues with the latest release. 

Blue/green is a deployment technique where there are two identical sets of infrastructure. One set/environment - blue - has the current production release installed. The other Cloud deployment for new releasesset/environment - green - has the next production release installed. To keep things running smooth, a load balancer sits in front of the two environments and is pointed at the blue environment. When the green environment has the latest release installed, has been smoke tested and is ready for production, the load balancer is changed to point to the green environment. Any transactions occurring in the blue environment are allowed to finish, but all new transactions are directed to the green environment. In the event there is an issue with the release in the green environment, the release is rolled back by changing the load balancer to point to the blue environment.

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Topics: Managed Services, Cloud Computing

Text Analysis: Building neural networks to answer questions about complex data

Posted by Kyle Hansen on Jan 16, 2018

At Kingland, we use a variety of Artificial Intelligence (AI) techniques for text analysis as we build cognitive and enterprise data management solutions. One of the most sophisticated is the neural network. Inspired by (but certainly not the same as) human biology, neural networks can learn to answer questions about complex data by observing and storing examples of subtle patterns in the connections between nodes, which are loosely analogous to neurons in the human brain. Most neural networks have multiple layers, with information flowing from one layer to the next (and back again in some cases), often transforming the input into more and more abstract representations as it progresses through the layers.

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Topics: Cognitive Computing, Artificial Intelligence

The Skepticism and Optimism of Artificial Intelligence

Posted by Tony Brownlee on Oct 25, 2017

In the last 30 days I've had many conversations with executives about cognitive, or artificial intelligence (AI) capabilities. I think we've made tremendous progress with our cognitive computing suite at Kingland over the last 7 years and it's fun to show people what we've done and where we're headed. The surprising thing to me, though, is the amount of skepticism I still hear from these leaders. When it comes to AI, there's almost a "too good to be true" cautiousness in the discussions. I think this is driven from the sheer volume of attention AI is getting as these leaders are asked daily to join the "AI Club". At the same time, though, I hear an incredible amount of optimism. Executives are thinking "maybe AI is one of the key investments I need to make to really make a difference." The efficiency, the automation, the chance to deliver something innovative for their company; all of these breed optimism.

I'd like to explore both sides of this skepticism / optimism coin. Let's look at one of the most popular questions I get:  "So...is that really AI"? 

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Topics: Cognitive Computing

How Kingland uses Natural Language Processing to Give you Comprehension, Context, and Control of your Data

Posted by Brian Noyama on Oct 23, 2017

There is a lot of hype around Cognitive Computing. In the past month, a Google search discovered nearly 16,000 articles devoted to the topic. For perspective on the hype, Forbes contributor Bernard Marr wrote, "Today another revolution is underway with potentially even further reaching consequences... Cognitive computing, machine learning, natural language processing - different terms have emerged as development of the technology has progressed in recent years. But they all encapsulated the idea that machines could one day be taught to learn how to adapt by themselves..." 

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Topics: Cognitive Computing

Microservices: What's in it for me?

Posted by Trond Gjendem on Sep 15, 2017

In prior posts, I have discussed what microservices are, how the cloud enables microservices, and how microservice architecture is a great fit for our agile project approach. So you may ask yourself, “sounds like microservices is a great way for Kingland to develop software, but what is in it for me as a potential customer?”

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Topics: Microservices

Executives: Don't Fall into the Cognitive Computing Trap

Posted by Tony Brownlee on Aug 24, 2017

Executives are faced with an evolving challenge related to the "cognitive era."  There is an unending, growing pressure from competitors, analysts, and vendors to invest in artificial intelligence (AI) and machine learning (ML), or "cognitive." Be wary. The cognitive trap is this: executives know there is tremendous potential with cognitive computing and they also know they have goals for their business for next year, so they simply combine them and assume cognitive MUST be the answer to their goals. My advice is don't fall into the trap of letting the "legend" of cognitive take over, but focus on value instead. 

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Topics: Cognitive Computing

How Kingland uses Containers to Pass Savings to Clients

Posted by Brian Noyama on Aug 7, 2017

As the complexity and size of software grows, we sometimes run into conflicting dependencies that can increase the cost and lower the quality of a solution for a potential client. Fortunately, using modern software architecture principles, the Kingland Platform sidesteps this problem by using Containers, and we maintain a competitive edge by passing on our savings to our clients. 

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Topics: Kingland Way

Databases: One Size Does Not Fit All

Posted by Trond Gjendem on Aug 2, 2017

Kingland Systems has made use of traditional relational database systems since our very first security broker application rolled out in the early 1990s. For the most part, these relational database systems have worked well for us, especially when we manage predictable data with simple and consistent relationships. However, increasingly our applications are managing large volumes of interconnected data as well as semi-structured or unstructured data that relational database systems are not so well equipped to deal with An example is the hierarchy of companies and subsidiaries (entities). 

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Topics: Hierarchy data

5 Challenges to Disclosing Financial Interests for Independence Compliance

Posted by Alex Olson on Jul 19, 2017

Over the past few years, public accounting firms have invested in having financial institutions provide them files of holdings and transactions, which is commonly referred to as broker data import (BDI) and financial interest integration (FII). These files are then imported into their personal independence system to enhance ease-of-use and robust disclosure. By automating the import of brokerage data, compliance is increased dramatically and user satisfaction with the process goes up dramatically. To the extent that a process can be put in place to reduce the need for a user to log into a system and accomplish the goals of that process, the better. Also, by automating the process, disclosure of financial interests are automated. No longer are there situations where a person forgets to disclose - the system does it automatically every day. Regulators have been pushing organizations to move beyond policy to automated controls that provide compliance with the policy. Automatically importing the data is a powerful response.

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Topics: Personal Independence

Overcome a Common Personal Independence Gap that Blinds Organizations to Potential Conflicts

Posted by Alex Olson on Jul 11, 2017

The tracking of personal financial interests for independence purposes has been done by the larger accounting networks for years. However, a common gap among independence regimes is to tie what people are working on with the restriction status for that individual. Multiple factors are at play in most large accounting networks, including: 

  • The personal independence tracking system has securities (what someone owns), and many of the personal independence tracking systems do not have corporate family tree information (entities relate to entities). 
  • Staff assignments and time reporting are performed by member-firm level systems that have minimal global integration. 
  • Legacy systems make integration difficult. 
  • Unaligned and misaligned data permeates across systems, which clouds the ability to connect the dots between a user's holding and a user's staff assignment and time entry. 
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Topics: Personal Independence