Skip to main content

[Post Event] ISTAConf 2017, Sofia

Just finished my session at ISTAConf 2017 and I realize that we are not only talking about NoSQL and migration  strategy, but we even doing that. I just met some great guys from Sofia that started to migrate their relational database to MongoDB. What was awesome that they have in plan a migration from on-premises to Azure in the next 3-6 months for their system, so Azure Cosmos DB is the perfect suite for them.

It is the 7 edition of ISTA Conference, that started in 2011. Last time when I was here was 2 years ago and in comparison with that times they grow a lot. Not only during the keynotes, but also during the sessions the rooms are full with people that are curious to find more about what are the current trends and what future is preparing for us. What I like at ISTA is the format of the conference. Even if there are more than 750 participants, they don't have more than 3 tracks. allowing them to keep the quality of session at a high level.

At this conference I talk about Azure Cosmos DB, where beside the base concept I shared different use cases where Azure Cosmos DB might be a better option than Azure Tables, MongoDB cluster and even Azure SQL. If you want to check my slides, you can find them below.

Title: Power-up NoSQL with Cosmos DB
Abstract: NoSQL databases are here to stay. Extremely powerful and flexible NoSQL solutions improve our systems and have a direct impact on our business. Common discussions when you are using NoSQL solutions like DocumentDB or MongoDB are disaster recovery plans, backups, scalability, replication, clustering, security and many more. What if I would tell you a successful story on how we reduced all these topics to only one - Cosmo DB. Join this session if you want to find out how we deployed a worldwide NoSQL solution using Cosmos DB.
Slides:


Comments

Popular posts from this blog

Windows Docker Containers can make WIN32 API calls, use COM and ASP.NET WebForms

After the last post , I received two interesting questions related to Docker and Windows. People were interested if we do Win32 API calls from a Docker container and if there is support for COM. WIN32 Support To test calls to WIN32 API, let’s try to populate SYSTEM_INFO class. [StructLayout(LayoutKind.Sequential)] public struct SYSTEM_INFO { public uint dwOemId; public uint dwPageSize; public uint lpMinimumApplicationAddress; public uint lpMaximumApplicationAddress; public uint dwActiveProcessorMask; public uint dwNumberOfProcessors; public uint dwProcessorType; public uint dwAllocationGranularity; public uint dwProcessorLevel; public uint dwProcessorRevision; } ... [DllImport("kernel32")] static extern void GetSystemInfo(ref SYSTEM_INFO pSI); ... SYSTEM_INFO pSI = new SYSTEM_INFO(

Azure AD and AWS Cognito side-by-side

In the last few weeks, I was involved in multiple opportunities on Microsoft Azure and Amazon, where we had to analyse AWS Cognito, Azure AD and other solutions that are available on the market. I decided to consolidate in one post all features and differences that I identified for both of them that we should need to take into account. Take into account that Azure AD is an identity and access management services well integrated with Microsoft stack. In comparison, AWS Cognito is just a user sign-up, sign-in and access control and nothing more. The focus is not on the main features, is more on small things that can make a difference when you want to decide where we want to store and manage our users.  This information might be useful in the future when we need to decide where we want to keep and manage our users.  Feature Azure AD (B2C, B2C) AWS Cognito Access token lifetime Default 1h – the value is configurable 1h – cannot be modified

What to do when you hit the throughput limits of Azure Storage (Blobs)

In this post we will talk about how we can detect when we hit a throughput limit of Azure Storage and what we can do in that moment. Context If we take a look on Scalability Targets of Azure Storage ( https://azure.microsoft.com/en-us/documentation/articles/storage-scalability-targets/ ) we will observe that the limits are prety high. But, based on our business logic we can end up at this limits. If you create a system that is hitted by a high number of device, you can hit easily the total number of requests rate that can be done on a Storage Account. This limits on Azure is 20.000 IOPS (entities or messages per second) where (and this is very important) the size of the request is 1KB. Normally, if you make a load tests where 20.000 clients will hit different blobs storages from the same Azure Storage Account, this limits can be reached. How we can detect this problem? From client, we can detect that this limits was reached based on the HTTP error code that is returned by HTTP