When working at scale, the only way to properly handle true scale is to work with horizontal scaling options. Some services (like CosmosDBCosmosDB for instance) do this out of the box and abstract it away from the user/customer. Though sometimes this is something you need to facilitate yourself… In terms of Azure Storage, we’re very open in regards to our limitations. For example, at this point in time, we’re currently facing a maximum egress of 50Gbps per storage account. Where this is more than enough for a lot or customers, at times we need to scale beyond this. Here the solution at hand is to see the storage account as a “scale unit”, and use it for horizontal scaling. So if you need 200GBps, then you can partition your data across four storage accounts.
In today’s post, we’re going to take a look at how you can aggregate these metrics into a single pane of glass. Because, at the end of the day, your operations team does not want to have a disaggregated view of all the components in play.
All Azure teams are constantly looking to evolve their services. Please note that the limits mention in this post are linked to the point in time when the article was written. As many of you know, Azure keeps evolving at vast pace, so the limits might already have been changed. If you are wondering, always check the following page for the most current limits that are linked to GA (“General Available”) services!
Continue reading “Aggregating Metrics from multiple Azure Storage Accounts” →
At the last Ignite conference, three new additions joined the Data Box family. In today’s post we’ll take one of those out for a spin, being the “Data Box Gateway“. This one comes as a virtual appliance that you can run on top of your own physical hardware.
So where does it fit into the picture?
- Cloud archival – Copy hundreds of TBs of data to Azure storage using Data Box Gateway in a secure and efficient manner. The data can be ingested one time or an ongoing basis for archival scenarios.
- Data aggregation – Aggregate data from multiple sources into a single location in Azure Storage for data processing and analytics.
- Integration with on-premises workloads – Integrate with on-premises workloads such as backup and restore that use cloud storage and need local access for commonly used files.
Let’s take it for a spin!
So let’s make it a bit more tangible and see what the user experience is in setting it up & using it. Start by searching the Azure Marketplace for Data Box Gateway.
Continue reading “Taking the Azure Data Box Gateway (preview) out for a spin!” →
In the summer of 2018, the 2nd generation of the Azure Data Lake Storage was announced. In today’s post, we’ll delve into the authentication & authorization part of this service. We’re going to see how we can leverage AAD to tighten security around our Data Lake.
To help us in this storyline, we’ll be looking to solve the following use case. A customer has stored a lot of data on its Data Lake, and is looking to provide a “partner” access to a subset of the data. In this use case, what would we need to to to achieve this goal?
Azure Data Lake Storage : Access Control Model
The first part of our puzzle is looking at the “Access Control Model“… In essence there are four ways to provide access to the data lake ;
- Shared Key ; The caller effectively gains ‘super-user’ access, meaning full access to all operations on all resources, including setting owner and changing ACLs
- SAS Tokens ; The token includes the allowed permissions as part of the token. The permissions included in the SAS token are effectively applied to all authorization decisions, but no additional ACL checks are performed.
- Azure RBAC ; Azure Role-based Access Control (RBAC) uses role assignments to effectively apply sets of permissions to users, groups, and service principals for Azure resources. Typically, those Azure resources are constrained to top-level resources (e.g., Azure Storage accounts). In the case of Azure Storage, and consequently Azure Data Lake Storage Gen2, this mechanism has been extended to the file system resource.
- ACL ; And last, but not least, we have the access control list we can apply at a more fine-grained level.
Continue reading “Azure Data Lake Storage (Gen2) : Exploring AAD B2B & ACL hardening” →