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What is Kappa Architecture?

Kappa Architecture is a software architecture pattern. Rather than using a relational DB like SQL or a key-value store like Cassandra, the canonical data store in a Kappa Architecture system is an append-only immutable log. From the log, data is streamed through a computational system and fed into auxiliary stores for serving. Kappa Architecture is a simplification of Lambda Architecture. A Kappa Architecture system is like a Lambda Architecture system with the batch processing system removed. To replace batch processing, data is simply fed through the streaming system quickly.
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Getting Started With Apache Camel and the Internet of Things

When I was first introduced to Java Enterprise Integration, the ServiceMix platform was transitioning to OSGi (ServiceMix Version 4.0). From its origins in embedded systems and mobile devices, the OSGi standard promoted many qualities that were advantageous to the Enterprise (flexible, modular, lifecycle management, services, security) so under this umbrella the tenants of the stack Apache Camel, Apache ActiveMQ, and Apache CXF flourished. "Apache ServiceMix is a flexible, open-source integration container that unifies the features and functionality of Apache ActiveMQ, Camel, CXF, and Karaf into a powerful runtime platform you can use to build your own integrations solutions. It provides a complete, enterprise ready ESB exclusively powered by OSGi." Fast forward a number of years, and now the Internet of Things (IoT) is proliferating across embedded devices. Small single-board computers such as the Raspberry Pi and BeagleBone have made the entry into building an IoT solution…

From Lambda to Kappa: A Guide on Real-time Big Data Architectures

When it comes to real-time big data architectures, today… there are choices. Today, there is more than just Lambda on the menu of choices, and in this blog series, I'll discuss a couple of these choices and compare them using relevant use cases. So, how do you select the right architecture for our real-time project? Let's get started.
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This article is…

From Lambda to Kappa: A Guide on Real-time Big Data Architectures

When it comes to real-time big data architectures, today… there are choices. Today, there is more than just Lambda on the menu of choices, and in this blog series, I'll discuss a couple of these choices and compare them using relevant use cases. So, how do you select the right architecture for our real-time project? Let's get started.
I guess you came to this post by searching similar kind of issues in any of the search engine and hope that this resolved your problem. If you find this tips useful, just drop a line below and share the link to others and who knows they might find it useful too.

Stay tuned to my blogtwitter or facebook to read more articles, tutorials, news, tips & tricks on various technology fields. Also Subscribe to our Newsletter with your Email ID to keep you updated on latest posts. We will send newsletter to your registered email address. We will not share your email address to anybody as we respect privacy.

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What You Need to Know About Real Time Architectures for IoT / Time Series Problem Sets

In previous posts, I discussed that not a single time series database or product rules all solutions, however, there are some common patterns that are reusable to allow a time series solution to scale to the problem set…with one key caveat — integration. It would be a bit presumptuous to propose a single technology such as Phoenix/HBase or InfluxDB as the be-all and end-all for every time series use case, because as I discussed previously, they are not. The problem set is too broad. Instead, what I would like to explore is leveraging architectural patterns and practices for time series. In this and the next few posts, I will focus on the lambda and kappa (event sourcing) architectures, specifically optimizing them for time series. These patterns use a combination of technology that allow them to scale to the need of the problem, but additionally provide a level of flexibility and protection that one product on its own would have a tough time replicating.
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Unit-Tests in Objective-C - Flying Kiwis

Every language has their own rules. It does not matter if you look at the syntax, language features or type of language. Everything changes and at the same time it stays the same. In our themed app we will be using swift, but since Objective-C is the origin of iOS development, we make a little detour, to see how specifics are done here. I'm not a big fan of XCTest. Don't get me wrong, it does it's job just fine.. but that's it.. just fine. Understanding the whole state of the app and action we are trying to test, depends on our ability to name tests. In general we suck doing so. An alternative are frameworks based on RSpec. They add syntactic sugar to our tests and might just make the difference of searching 2 hours understanding the test, or fixing the problem.
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How to use Chaos in your iOS Tests

There are also other versions which use an infinite amount of monkeys instead of time. As app developers, we have a similar situation. Our apps are used by a large number of users (okay they are numbered and not monkeys but still.. it's similar) who are using our app in ways we can never imagine. As a result, they will find bugs we've never anticipated. So what can we do to prevent this?
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I guess you came to this post by searching similar kind of issues in any of the search engine and hope that this resolved your problem. If you find this tips useful, just drop a line below and share the link to others and who knows they might find it useful too.

Stay tuned to my blogtwitter or facebook to read more articles, tutorials, news, tips & tricks on various technology fields. Also Subscribe to our Newsletter with your Email ID to keep you updated on latest posts. We will send newsletter to your registered email address. We will not share your email ad…