Build your own Twitter – Part 2 – Azure Table Structures

Azure Table Store offers a very important scalability feature which should be used when working with timelines. The partitionkey in every table allows Microsoft to put entities on different servers. Let’s recheck the limits of Azure Table Store to make a right decision (http://azure.microsoft.com/en-us/documentation/articles/azure-subscription-service-limits):

  1. Azure Table Store returns 1000 entities per page. If the result contains more entities the client needs to query several times -> A timeline service should never page to render the first timeline
  2. Azure Table Store returns 2000 entities with 1KB of size per second as a guaranteed SLA –> A timeline service should never request more data per page to stay performant
  3. Azure Table Store allows to store up to 500TB per storage account, it could be stored in one table or different –> A timeline service should be able to handle several storage accounts, at least theoretically.

With all this limitations in mind it’s possible to build a table structure for the timeline service as follows:

  1. timelines
    The timlines table contains all timelines the system has registered. The partitionkey of this table is timeline identifier so every subjects timeline can be stored on different nodes. The partitionkey should be a key generated from the subjects  identification, e.g. liveid{{UID of LiveId-Token}}. This prevents the system to lookup an other table to get the timeline identifier when the subject tries to render them.In addition the event which should be stored on several timelines can be identified by his event identifier as the row key. This allows the system to also implement removal jobs because a multiple stored event can be identified as the single one.
  2. subjectFollowers
    the subjectFollowers are a list of subjects following a specific subject. The partitionkey of this table is also the subject identifier so it’s easy to get all followers of a subject. In addition the row key becomes important because it identifies the subject who is following someone else. This gives a system the option to find all followers of a specific subject and all subjects a specific subject is following very fast. Works well in both directions.

This simple data structure allows the service to handle hundreds of different timelines and relations. Especially the background worker can now identify on which timeline the event needs to be stored.

followers

Last but not least, when it comes to requesting the timeline content it will only be returned in pages of 250 elements to stay healthy with the performance. An other page can be requested at any time when the user starts paging.

Build your own Twitter – Part 1 – A timeline service with Azure Table Store

The Azure Cost Monitor and many other cloud services I’m working on, needed a timeline service to present aggregated events and actions similar to an audit trail. When I was thinking about this, it came to my mind that the requirements I had were very similar to a Twitter feed but with less features.

Let’s recap what is needed to build a timeline service in general:

  1. The Timeline
    The Timeline is associated with a subject and contains tons of events happened and triggered by other subjects the timeline owner follows.
  2. The Event
    The Event is the incident that happens in the real world and is stored in different timelines. This means every follower of a subject will get the event in his own timeline. So a single event can be stored in many different timelines.
  3. The Subject
    The Subject is someone or something which triggers an event. Normally it is a natural person with an own timeline but it could also be a piece of hard/software.
  4. The Target(s)
    The Targets are subjects with a timeline who are following other subjects. This means every subject becomes a follower or target as soon as it is following an other subject. Posting an event then means sending the message to the timeline of every subject following the sender.

The following picture should give a good overview about the entities in the timeline service:

Screen Shot 2015-03-21 at 10.40.15

Starting with this definitions in mind it’s possible to identify components needed for building a timeline service:

  • Storage for the timeline 
    The storage for the timeline needs to be able to offer a very fast read performance and an OK write performance. The performance should especially not be dependent from the amount of data in the system. I chose Azure Table Store for this because I can store the information in different partitions and get a clear read performance SLA for every partition. In addition to this it’s totally cheap and payable – also for startups.
  • Access broker to the storage 
    Normally NoSQL storage which can be used for timeline access needs a little helper to manage access. In general a RESTful web-service acts as an access broker and hands out pre-signed links to the timeline content. This ensures that no timeline data needs to go through the timeline service at all. Only the pre-authorised access links will be generated for the system. This also means that at the end the client SDK needs to handle the raw data for the timeline. This makes it a bit more complicated but it lets the performance stay in a good range. An other important operation needs to be implemented in the Access broker as well: Posting events to the subjects followers is a slow and complex operation the system needs to implement with a direct server call normally executed asynchronous with the help of a worker job.
  • Metadata storage for subject and targets
    Last but not least the combination of subject & targets needs to be stored somewhere in the backend. Azure Table Store can be used for this as well. All the operations to create a follow-ship can be implemented in the timeline service as well but not the rights & permission checks to post or create relations because the timeline service should be used machine-2-machine with API tokens.

The following graphic shows the technical architecture of a good scalable timeline service based on Azure services:

arch-timeline

The next part of this tutorial will focus on the correct and scalable table structure based on Microsoft Azure Table Storage.

Azure Cost Monitor sends notifications when Azure EA token has expired

Microsoft offers all EA customers the Azure EA portal to manage different accounts and subscriptions. In addition to this portal, every customer can issue up to two security tokens to 3rd party applications. This allows the applications to interact and work with the customers EA data like the Azure Cost Monitor is doing.

Starting this week the Azure Cost Monitor analyses the existing Azure EA security tokens and is able to detect when a token has expired. As soon an expired token is detected the owner of the contract will get an information via mail:

blog-azure-cost-ea-token-expired

In addition, the Azure Cost Monitor is now able to warn about tokens that will expire very soon. The owner of the affected contract will get an information via mail as well:

blog-azure-cost-ea-token-will-expire

This new feature should help you as a contract owner to stay in sync every day. It also helps us to have our system stay healthy and performant every day. Please update the tokens directly when you get this kind of notifications. Additional information on how to renew a token can be found in our knowledge base here.

We hope this feature makes it simple to maintain your Azure Cost Monitor account and makes it much easier for you to manage and control all costs. Any questions, wishes or ideas? Try our feedback portal or drop a mail to tickets@azurecostmonitor.uservoice.com.

Azure Table Store: How to backup safely

Microsoft Azure Table store is an amazing, simple, cheap and powerful service of the Microsoft Azure cloud. The service is something between a real NoSQL database and a simple KVP-store. I did many projects in the last time where the Azure Table Store was just a fast read cache or also the whole persistency backend.

As soon as the tables in Azure contain important data for the application provided to customers it’s necessary to think about backup. Microsoft guarantees that the data can not be corrupted on the storage (check out my article about the different storage account options) but accidental deletion, data corruption during automated processes or just by mistake can still happen. Where people are working shit sometimes happens, nobody can change this.

Backing up table stores is not that easy as backing up blob storage based on the idea of stamp copies. Every table needs to be replicated into another table or exported to the blob account. In my current project we searched for the perfect solution and finally came up with the following stack of services: We are using the Azure Cloud Backup from RedGate to export all tables in a GEO redundant storage account. With this solution we get a daily backup of our tables in parallel to Azure SQL backups based on the Microsoft built in features. The backups are stored into a GEO redundant storage account which helps to ensure that we have access to this backups even when one datacenter of Microsoft burns 🙂 or just looses power.

This setup in combination with the Microsoft Backup support for Azure SQL is very powerful and gives everybody the good feeling of being able to recover when chaos happens.

ngHelperAirbrake: Airbrake for AngularJS

Airbrake is a well known exception tracker which is used from thousands of users. A cool thing is that the Airbrake team also supports browser based javascript exception. Integrating these kind of javascript code gives AngularJS developers sometime a headache. The newest member of the ngHelper collection, the ngHelperAirbrake component makes it super simple and easy to integrate Airbrake in an existing AngularJS application.

It’s a bower component and works well with scaffolding tools like Yeoman. Installing the component is possible with the following command line:

bower install ng-helper-airbrake –save

After that the component is registered in the bower.json of the project. Moving up the dependency entry to the position right after the inclusion of angular ensures that the Airbrake-Shim is loaded as early as possible when doing a full page reload.

“dependencies”: {
“angular”: “~1.3.8”,
“ng-helper-airbrake”: “~0.1.0”,

ngHelperAirbrake offers the $airbrake angular service which allows to configure the different Airbrake settings. The documentation at our project page describes how to set the right configuration: https://github.com/ngHelper/ngHelperAirbrake

After configuring the project everything works as expected and Airbrake receives exception from the AngularJS application.

Pit-Falls when you integrate Twitter, Facebook or other social networks

Today I received a request from a platform to vote for a specific product. I was willing todo this, because I’m using it every day and I’m really happy with that.

With this kind of sentences discussions about failed social media integration start. In a world where many people are very concerned about their own data privacy a “but” follows very fast:

Currently I can’t do that because the website enforces me to authorise via Twitter or Facebook. This would be doable if they only request the rights they really need. I will not allow every system to post in my name because that’s very personal.

At the end of the story you as a service provider loose a customer on the click path for only one reason: You tried to get more rights as you typically need to operate your application. And from my own experience the right to post in the name of someone requires a strong trustworthy relationship.

Screen Shot 2015-03-06 at 07.32.16

Neither Twitter nor Facebook enforces any developer to request more rights than they really need. I did a lot of Twitter integrations and whenever you are doing this please check the FAQ of the identity provider of your choice clearly and follow the principal of minimal privileges.

Following this ideas you will loose less people on click path to your voting system!

Update expired Azure EA tokens easily

The Microsoft Azure EA portal issues an Azure EA security token for API access to the cost & usage data. This token expires every 6 month and because of that needs to be renewed in the Azure Cost Monitor on a regular basis. The Azure Cost Monitor team started the project about 5 months ago what means that the first Azure EA security tokens will expire soon. Because of that, we are pleased to announce the launch of the token update wizard which makes it as easy as possible to renew expired Azure EA tokens:

azure-ea-token-settings

From today, the dashboard of the Azure Cost Monitor warns every user when the token is expired to ensure that every administrator always stays informed:

azure-ea-token-warning

If you don’t update an expired token, the system stops syncing data from the Azure EA portal. As soon as the token is valid again the system is able to sync data from the Azure EA portal and is doing that automatically within the next sync cycle over night. We will also get the missed data from the days the token was expired. So no worries when you were in vacation or absent for a couple days.

We hope this feature makes it simple to maintain your Azure Cost Monitor account and makes it much easier for you to manage and control all costs. Any questions, wishes or ideas? Try our feedback portal or drop a mail to tickets@azurecostmonitor.uservoice.com.