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MAKING SESSION STORES MORE INTELLIGENT WITH MICROSERVICES

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Luisa Fiorillo|Redis
Luisa Fiorillo|Redis
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WHITE PAPER
Making Session Stores more Intelligent
with Microservices
Kyle Davis, Technical Marketing Manager, Redis
CONTENTS
What is a session store? 2
What is an intelligent session store? 2
Why does any service need a session store? 2
Why a microservice? 4
Transport Mechanisms 5
From submitted to calculated data 6
Bloom Filters 7
HyperLogLog 7
Bit Counting 7
Session Store Patterns 8
Content Surfacing 8
Activity Pattern Monitoring & Personalization 9
Group Notifications 10
Putting it all together 11
Conclusion 13


2
What is a session store?
Simply put, a session store is a “chunk” of data that is connected to a user of
a service, stored separate from the primary
database in order to provide stickiness without direct, constant access to the
database. “User,” in this case, is loosely defined.
A user could be as simple as a mere visitor to a webpage, a user with an account
in a phone app or even another service that
accesses data via an API.
A session is often persisted between requests through a cookie. The server gives
the client the cookie and the client stores it,
then sends subsequent request back with this cookie. The server then uses the
cookie string as a token for which data can be
associated with the user.
Often times, the session data is the most frequently used by a single user (and
that user alone). The session data is also often
a critical requirement for rendering a page or view.
Many times, session data is ephemeral and duplicated in some other data store.
However, as we will explore in this document,
this doesn’t always have to be true.
What is an intelligent session store?
In this document we will be exploring session stores that move beyond “dumb”
stores of data. This intelligent data in a session
store might be calculated, inferred or otherwise not directly supplied by the
user of the service. In this way, you can store the
traditional session data (username, preferences or other common stateful data)
alongside intelligent data.
Some examples of the intelligent data we’ll be using are:
• Group notifications - providing a single notification to a specific slice of
users
• Content surfacing data - a dataset that can be leveraged for users to be
pointed to additional content
• Activity data - information about the users’ behavior and usage of the service
• Personalization data - data that can be used to make the service more specific
and relevant to each user
Why does any service need a session store?
In a very simple world, one does not need a session store. In this very simple
example, you have the entire internet connected
to your single server, that is then backed by a single database. On every page
view, the web server connects to the database
and grabs the requisite information.
This might work great for small use cases, but when your website becomes busy,
you’re likely to start having problems with
the database becoming slow. After all, querying—or worse,writing to most
databases is very resource intensive as compared
to the duties of a web server. To remedy this situation, you alter your website
code to start using a file-based session store.
This is the simplest of the session store strategies—effectively, individual
sessions are stored in text files that reside on your
webserver. The web server software would then read or manipulate the session
data file directly.















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