Configuration as a Service and Redis Cache
Cache configuration and deployment
Who we are
Azure Cloud Studios
(A couple of Azure guys)
Tonight’s Presenters
Robert Dytmire
&
Ed Hunkin
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Agenda
Configuration as a Service
Why we think data beats config files for deploying, managing and scaling your services. We’ll be
discussing how we’re doing this and what enhancements we’re planning.
Caching in Azure
Who should use caching? What types of caching are available to us? How do you implement a
cache? What are some considerations when using caching?
AzStudio
A very quick tour of our Azure enterprise suite. We’ll be using AzStudio plugins to demonstrate
configuration and testing of a cache.
Implement a Cache - Walkthrough
Walk through the steps to impalement a Redis Cache. Configuring the cache in AzStudio. Using
the cache in a Redis Cache tester. Some tricks to pop and push more than the Azure stated
maximums. Life cycle of a cache item.
Q&A
Open the floor to questions.
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Configuration as a Service
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Configuration as a Service
Configuration as a Service
Replacing various configuration files with data services. Role asks for configuration data via a series
of service calls. Minimal configuration in the project code.
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Configuration as a Service
Configuration as a Service
Replacing various configuration files with data services. Role asks for configuration data via a series
of service calls. Minimal configuration in the project code.
Easier
Configuration changes are stored and managed via a centralized data store. Configuration changes
do not require re-deployment and in many cases do not require role recycling.
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Configuration as a Service
Configuration as a Service
Replacing various configuration files with data services. Role asks for configuration data via a series
of service calls. Minimal configuration in the project code.
Easier
Configuration changes are stored and managed via a centralized data store. Configuration changes
do not require re-deployment and in many cases do not require role recycling.
More Secure
The configuration tasks can be delegated to a completely different team. Configuration changes in
one environment can be delegated to the coder (Dev) but QA and Production can manage their
own implementations. Configuration can be segmented by major function.
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Configuration as a Service
Configuration as a Service
Replacing various configuration files with data services. Role asks for configuration data via a series
of service calls. Minimal configuration in the project code.
Easier
Configuration changes are stored and managed via a centralized data store. Configuration changes
do not require re-deployment and in many cases do not require role recycling.
More Secure
The configuration tasks can be delegated to a completely different team. Configuration changes in
one environment can be delegated to the coder (Dev) but QA and Production can manage their
own implementations. Configuration can be segmented by major function.
Better consistency
Ever wondered if your XML was well-formed? Missing an attribute? Is the section something that is
supposed to be in consistent and well understood? A database-driven interface eliminates a lot of
confusion. Database tables can enforce data consistency, security, and redundancy.
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Configuration as a Service
Configuration as a Service
Replacing various configuration files with data services. Role asks for configuration data via a series
of service calls. Minimal configuration in the project code.
Easier
Configuration changes are stored and managed via a centralized data store. Configuration changes
do not require re-deployment and in many cases do not require role recycling.
More Secure
The configuration tasks can be delegated to a completely different team. Configuration changes in
one environment can be delegated to the coder (Dev) but QA and Production can manage their
own implementations. Configuration can be segmented by major function.
Better consistency
Ever wondered if your XML was well-formed? Missing an attribute? Is the section something that is
supposed to be in consistent and well understood? A database-driven interface eliminates a lot of
confusion. Database tables can enforce data consistency, security, and redundancy.
Scales Well
Once you have your configuration schema, it’s very easy to scale for small, medium and large
projects. Your pattern is the same in all environments and all scales. Dev works and deploys the
same as production.
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Overview
Configuration Layer
Database Store
Configuration Tool (AzStudio)
Configuration Admins
API
SQL Connection
Service Call (REST / JSON)
Modules
Cache
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Data
Queue
Happy Coders
SMTP
Role / CaaS Process
01
Boot – What am I?
Upon booting, the role needs to
know what it actually is
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Role / CaaS Process
01
Boot – What am I?
Upon booting, the role needs to
know what it actually is
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02
Where am I?
The role now needs to know what
environment it is in
Role / CaaS Process
01
Boot – What am I?
Upon booting, the role needs to
know what it actually is
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02
Where am I?
The role now needs to know what
environment it is in
03
Download Modules
The role needs to download it’s
modules and start them.
Composition / Dependency injection
Role / CaaS Process
01
Boot – What am I?
Upon booting, the role needs to
know what it actually is
02
Where am I?
The role now needs to know what
environment it is in
03
Download Modules
The role needs to download it’s
modules and start them.
Composition / Dependency injection
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Modules Initialize
Each module contacts the
configuration service it needs for
information
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Role / CaaS Process
01
Boot – What am I?
Upon booting, the role needs to
know what it actually is
02
Where am I?
The role now needs to know what
environment it is in
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System Ready
All modules running. Role is now
fully functional
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03
Download Modules
The role needs to download it’s
modules and start them.
Composition / Dependency injection
04
Modules Initialize
Each module contacts the
configuration service it needs for
information
Why was all that Important?
Tonight’s Demo
Our Redis cache demo uses AzStudio, which is our CaaS tool / product. We wanted you to understand
the apparent non-standard configuration steps.
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Why was all that Important?
Tonight’s Demo
Our Redis cache demo uses AzStudio, which is our CaaS tool / product. We wanted you to understand
the apparent non-standard configuration steps.
Going Forward
If permitted, we’d like to demonstrate more CaaS and code automation techniques in future
presentations. Having this information will form a good foundation for more advanced techniques.
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Why was all that Important?
Tonight’s Demo
Our Redis cache demo uses AzStudio, which is our CaaS tool / product. We wanted you to understand
the apparent non-standard configuration steps.
Going Forward
If permitted, we’d like to demonstrate more CaaS and code automation techniques in future
presentations. Having this information will form a good foundation for more advanced techniques.
General Trends
Our team is convinced that CaaS will be an emerging trend in IaaS environments. It’s a natural
progression of the toolsets as they respond to this new paradigm.
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Caching in Azure
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When you need Caching
Speed
You do not want the overhead of querying an SQL server or other storage container. This is especially
true when data structure you’re referencing is complex, built from multiple queries or is small and easy
to cache in memory. In-memory caching is very good for small sets of frequently referenced data that
do not change very often.
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When you need Caching
Speed
You do not want the overhead of querying an SQL server or other storage container. This is especially
true when data structure you’re referencing is complex, built from multiple queries or is small and easy
to cache in memory. In-memory caching is very good for small sets of frequently referenced data that
do not change very often.
Reduce Load
Reduce DTU’s! You want your SQL server to be the accessed only when it is absolutely necessary to
read and write persistent data. Caching reduces redundant SQL work. Use caching to reduce loads
on these systems.
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When you need Caching
Speed
You do not want the overhead of querying an SQL server or other storage container. This is especially
true when data structure you’re referencing is complex, built from multiple queries or is small and easy
to cache in memory. In-memory caching is very good for small sets of frequently referenced data that
do not change very often.
Reduce Load
Reduce DTU’s! You want your SQL server to be the accessed only when it is absolutely necessary to
read and write persistent data. Caching reduces redundant SQL work. Use caching to reduce loads
on these systems.
Reduce Costs
It costs money to access SQL and other storage resources. Some resources, such as blobs and
queues have absolute upper limits on instance access per minute.
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When you need Caching
Speed
You do not want the overhead of querying an SQL server or other storage container. This is especially
true when data structure you’re referencing is complex, built from multiple queries or is small and easy
to cache in memory. In-memory caching is very good for small sets of frequently referenced data that
do not change very often.
Reduce Load
Reduce DTU’s! You want your SQL server to be the accessed only when it is absolutely necessary to
read and write persistent data. Caching reduces redundant SQL work. Use caching to reduce loads
on these systems.
Reduce Costs
It costs money to access SQL and other storage resources. Some resources, such as blobs and
queues have absolute upper limits on instance access per minute.
Persistent Shared Data
When you want multiple roles to access the same data quickly and cheaply. For example: Complex
session state data for your logged in users. Any data that is frequently accesses but produces
significant query load is a candidate.
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Caching Technologies Available in Azure
Local Cache
In-Role Cache
Instance Only
•
•
•
•
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No Lifetime Management
Concurrency considerations
Lightweight
Fastest
Role Shared
•
•
•
•
No Lifetime Management
Difficult to configure and
manage
Inconsistent operation
Depreciated
•
•
•
Managed Cache Service
Redis
Data Center
Data Center
Lifetime Management
Inconsistent operation
Depreciated. You cannot
create this service going
forward.
•
•
•
Lifetime Management
Microsoft Recommended
Stable
Have a Backup Plan
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Database Cache
Table Storage
Blob Storage
Re-Hydrate
Use a simple SQL table to
store a copy of your JSON
data.
Use table storage for fast
cache backup.
We like this solution better
than SQL.
Not as flexible.
If you use a consistent keying
strategy then store the JSON
as a blob.
Slowest but necessary. Your
code must know how to rehydrate its state from original
data.
AzStudio
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AzStudio
Unified Azure Configuration
One stop application that allows us to manage all aspects of configuration. Any Azure / C# module
can be configured for every environment.
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AzStudio
Unified Azure Configuration
One stop application that allows us to manage all aspects of configuration. Any Azure / C# module
can be configured for every environment.
Unified Application Management
Any application we deploy to Azure can be managed via this toolset. Plugins allow us to extend the
toolset for each client as necessary.
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AzStudio
Unified Azure Configuration
One stop application that allows us to manage all aspects of configuration. Any Azure / C# module
can be configured for every environment.
Unified Application Management
Any application we deploy to Azure can be managed via this toolset. Plugins allow us to extend the
toolset for each client as necessary.
Code Generation Toolset
We’ve taken our code blowers and turned them into Azure-Aware plugins. Single point of code
creation and template management.
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AzStudio
Unified Azure Configuration
One stop application that allows us to manage all aspects of configuration. Any Azure / C# module
can be configured for every environment.
Unified Application Management
Any application we deploy to Azure can be managed via this toolset. Plugins allow us to extend the
toolset for each client as necessary.
Code Generation Toolset
We’ve taken our code blowers and turned them into Azure-Aware plugins. Single point of code
creation and template management.
Super Flexible Plugin Architecture
Host app follows our best practices in Azure and allows plugins to quickly leverage this foundation.
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AzStudio
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Setting Up Redis Cache in Azure
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Create your Cache in Azure
Note: This is the new portal. Ensure you are
in the new “preview” portal
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Select your Pricing Tier
Watch Expenses!
Examine each offering, as it’s easy to select a caching size
that’s much more than you need. We find the B1 service
works pretty well for most businesses.
Also keep in mind you need THREE of these caches (Dev,
QA and Production) but your Dev and QA caches should be
B0 tier in almost all cases.
Scale up your cache before you federate. Carefully consider
if you need replication or an SLA, as those cost more.
Using the failsafe methods mentioned earlier are often
more cost effective.
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Create the Cache
Set your Resource Group and Location
This let’s Azure know where you want the physical instance located.
Select Create
A tile will appear on your portal that looks like this:
Wait for Deployment
The portal will inform you when your cache is ready. This takes a bit of
time.
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Take Note of Configuration
Configuration Strategy
You’ll want to have your configuration strategy planned out at this point. For this demonstration, we’re going to
use our CaaS strategy. There are many online tutorials on how to use configuration files and slightly different C#
to accomplish the same tasks.
Information you Need
Note the Hostname and access key. We find using secondary key to be the best practice.
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Create a Configuration String
Configuration String format:
[hostname],ssl=true,password=[accesskey]
Demo’s connection string would look like this:
presentation.redis.cache.windows.net,ssl=true,password=Mn4n/YsspnuKBSpK4VG/DXAa3TOuLlVP1mcmiADzN3B=
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Adding Redis Cache to your Project
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Install the Packages
Install Json.NET if you plan to serialize objects (we do) and StackExchange.Redis, the Redis cache C# library.
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Create a Caching Class
Create a Project and Class
In your C# code, add the StackExchange.Redis and Newtonsfot.Json references.
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AzStudio’s Caching Class
Static Class
We use a static class that manages different cache instances. The cache instances each maintain a persistent cache
connection and manage writing and reading from the Redis Instance.
The ConnectionMultiplexer is the key class. Connect uses your connection string and produces a connection
object. You should persist the connection object as it is meant to have a long life-cycle (it’s a heavy object to
create).
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Create Set Method
Now we have a connection. We can leverage the connection to write our own Get and Set methods. We like to
use JSON encoders to serialize our object in and out of the cache. This seems to work for us fairly well. You can
also serialize into a byte stream
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Create Get Method
Get is pretty straightforward. We attempt to read the cache. If we find the value in the cache we de-serialize it
into <T>. If the key is null or missing…or we encounter an exception de-serializing then it returns default(T).
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Quick Cache Facts
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Quick Redis Cache Facts
Maximum Key Size
You’ll want to keep your key size as small as possible. The Key and Value size count together A hard limit of 512
MB on key size.
Maximum Value Size
Max value is 512 MB for a serialized string. Keep in mind the key size counts towards this limit. But really, what are
you doing caching a 512MB string?!
Concurrent Connections?
Depends on cache size. Keep in mind that a 250MB cache runs on a A-0 size machine. The larger the cache size
the larger the dedicated box to host the cache will be, so load test your app. The absolute limit is 10K.
Note: We found that a 1GB cache size was sufficient to handle most of our smaller to mid-sized client’s modest
caching needs.
Lifespan
Set the MAXMEM policy in your cache settings, all settings. The default is volatile LFU. That is old values will be
deleted after several minutes or if the cache needs to make room, the Least Frequently Used item will be deleted.
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Live Demo
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Summary
Caching is Easy & Strategy is Less so
Azure makes setting up and accessing a cache very easy. How you implement caching in your project is less so.
Configuration can play a big role. Peak load, moving between environments simply, and coming up with a
consistent fallback strategy are all import considerations.
CaaS
Going forward, we see CaaS logically complementing IaaS. Consistent, data-checked and environment aware
configuration tools will become more consistent and powerful. We’d like to present on this subject in more depth
at a future date.
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What Next?
Takeaway
We will now pass out your take-away. Use this as a quick guide to help you with our challenge.
Challenge
We challenge you to write your own Redis Cache test project this week. Place load on the system.
See if you can break the I/O. Test the limits of different sizes. See what kind of performance you
get. Report back on the Azure Meet-Up Group message board.
Doing this yourself will educate you more than anything that I can stand here and yammer on
about.
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