In Azure Cosmos DB, partitioning is what allows you to massively scale your database, not just in terms of storage but also throughput. You simply create a container in your database, and let Cosmos DB partition the data you store in that container, to manage its growth.
This means that you just work with the one container as a single logical resource where you store data. And you can just let the container grow and grow, without worrying about scale, because Cosmos DB creates as many partitions as needed behind the scenes to accommodate your data.
These partitions themselves are the physical storage for the data in your container. Think of partitions as individual buckets of data that, collectively, is the container. But you don’t need to think about it too much, because the whole idea is that it all just…
Azure Cosmos DB is Microsoft’s globally distributed, massively scalable, horizontally partitioned, low latency, fully indexed, multi-model NoSQL database.
If you start to elaborate on each of the bullet points in this soundbite opening, there’s a lot to discuss before you get to “multi-model NoSQL” at the tail end. Starting with “globally distributed,” Cosmos DB is – first and foremost – a database designed for modern web and mobile applications, which are (typically) global applications in nature. Simply by clicking the mouse on a map in the portal, your Cosmos DB database is instantly replicated anywhere and everywhere Microsoft hosts a data center (there are nearly 50 of them worldwide, to date). This delivers high availability and low latency to users wherever they’re located.
Cosmos DB also delivers virtually unlimited scale, both in terms of storage – via server-side horizontal partitioning, and throughput…
Developers with a background in relational databases are accustomed to achieving data integrity using transactions. Once a writer updates a bank balance and commits the transaction, it’s entirely unacceptable for a reader to ever be served the previous value, and a relational database ensures that this never happens. In the NoSQL world, this is referred to as strong consistency. Achieving strong consistency in a NoSQL database is more challenging because NoSQL databases by design write to multiple replicas. And in the case of Azure Cosmos DB, these replicas can be geographically spread across multiple Microsoft data centers throughout the world.
First, let’s understand consistency within the context of a single data center.
In one Azure data center, your data is written out to multiple replicas (four at least). Consistency is all about whether or not you can be sure that the data…
Welcome to part two of Exploring Buffer Overflows in C! If you have not taken the time to read the previous article I highly recommend doing so before going any further. In this post, I will be walking you through a simplified version of a buffer overflow exploit and will draw heavily on the vocabulary and theory discussed out in the last post. You can find Part One on Tallan’s Blog here. It also would be helpful to be familiar with hexadecimal numbers, which you can read about here. With that out of the way, let’s get to hacking.
Before We Begin
Before we can start we have to pick a target. Several methods exist to detect potential buffer overflows, ranging from manually reading the code to automated testing. Assuming you do have the source code of a program, searching for insecure…
Cybersecurity is one of the fastest evolving tech fields and the stakes are high. Mistakes can be in the order of millions of dollars. Computers have invaded all aspects of our everyday lives. Although this means I can access millions of cat pictures with the touch of a button, it is dangerous to assume that everyone using a computer is in it for the fuzzy felines. Credit cards, passwords, and social security numbers are moving across the internet just as quickly as cat pictures but with a lucrative black market. There is a lot to gain from a successful hack and hackers will be doing their best to break into the systems we rely on and use daily. Ranging from high-tech exploits such as 2018’s Spectre and Meltdown to low-tech exploits like phishing and social engineering, it is important for…
Let’s jump right back into the thick of this topic. In the first part of this blog series, we discussed why insurers should be empowering their customers to complain in fairly general terms. Check out the link to our Decision Maker’s Guide to Complaint Enablement for more background on this topic.
This post dives deeper into a few key metrics: retention rates, customer lifetime value, and quantity of feedback gathered. To do so, we’ll take a look at the financial impact of non-complainers. While you read, it may also be helpful to consider whether you are currently measuring or utilizing any data to achieve similar goals.
Before getting to specifics, here’s a quick recap of what was covered last time:
J.D. Power’s 2018 research tells us that the industry average score for providing a satisfying purchase experience is 839 out of 1,000.1
For most Microsoft IT professionals, migrating or updating a native mode SQL Server Reporting Services (SSRS) installation from one version to another is a rare, if not once-in-a-lifetime, event – and probably one you would prefer a root canal to. Because software upgrades of all types tend to get postponed as long as possible, if you find yourself finally tasked with such an upgrade, several unpleasant things are likely true:
The effort is in crisis mode, driven by software (SSRS, OS) going off support, hardware becoming unreliable, or a line-of-business application that must itself be upgraded but cannot be until SSRS is.
The current installation was not done by you and whomever did is long gone, so you are not that familiar with it and would frankly rather not be. SSRS is not your “thing”.
The current installation is poorly documented, if at…
Microsoft recently announced the end of support (EOS) for SQL and Windows 2008. What does that mean for you? Maybe nothing, but if your company is currently running either version you need to consider your options. There are two important dates to make note of – July 9th and January 14th. SQL Server 2008 support ends on July 9, 2019 and Windows Server 2008 support ends January 14, 2020. Option 1 is to migrate to Azure. When you’re ready to, you can modernize your applications. Option 2 is to continue to run on 2008 until support ends and then decide. We can help to weigh your options.
Are you ready to get started? We can help!
Here’s an interesting fact from a Forbes article published earlier this year, regarding end-consumers in the insurance industry:
“91% of non-complainers just leave”1
This tells us that there are two types of customers in the insurance world: complainers, and non-complainers. Among non-complainers, more than nine out of ten actively choose to take their business to another company. The insurer they leave behind must deal with the following consequences:
Loss of future revenue streams
Lack of insight into why the customer chose to leave in the first place
The significance these metrics have on bottom line revenue can’t be understated. These are customers that were already paying for a service – that had already gone through a decision-making process, chosen one insurer, and were so dismayed with some aspect of their service that they chose to begin this entire search process again.
But there’s a simple…
It’s taken a year for me to feel confident enough to even chime in, on a high level, about the products we’ve created, and the platforms we utilize. I can dabble in conversation about chatbots and Microsoft’s Cognitive Services. I understand now, more or less, what ‘the cloud’ is and its benefits. But, this is why teamwork makes the dream work, you know. My colleagues can build you a solution to any business challenge. Anything. You’ve got a problem, they’ll solve it.
But, now it’s my turn. I am going to express why what they can do matters.
You’ve all heard of Machine Learning. We partnered with RetailWire to produce a Webinar on ML for Retail back in April and that’s where my understanding really began to take shape. In a nutshell, Machine Learning can be set-up and do in minutes and…