Welcome!

Microservices Expo Authors: Pat Romanski, Elizabeth White, Zakia Bouachraoui, Liz McMillan, Yeshim Deniz

Related Topics: @DevOpsSummit, Microservices Expo, Containers Expo Blog

@DevOpsSummit: Article

Sharding for Scale | @DevOpsSummit #BigData #DevOps #Microservices

Where you decide to shard for scalability impacts the complexity of the entire architecture

Sharding for Scale: In the App or in the Network?

Sharding has become a popular means of achieving scalability in application architectures in which read/write data separation is not only possible, but desirable to achieve new heights of concurrency. The premise is that by splitting up read and write duties, it is possible to get better overall performance at the cost of a slight delay in consistency. That is, it takes a bit of time to replicate changes initiated by a "write" to the read-only master database. It's eventually consistent, and it's generally considered an acceptable trade off when searching for higher and higher scalability.

While the most well-known cases of read/write separation and sharding are based on geography - east coast versus west coast, for example - there are other cases where localized sharding has also been put into play with great success. Generally these types of architectures base their sharding decisions on user names, splitting them up between databases based on statistical analysis of occurrences. This achieves greater scalability at the data layer by better distributing the rate at which writes (which are generally speaking a blocking action) occur, and thus achieving greater scale and concurrency for only a slight period of inconsistency.

The mechanism is, in theory, quite simple and is loosely based on an algorithmic principle taught in most computer science algorithm classes: hashing. Basically when a request comes in, the application looks at some piece of data - like the user name - and based on that data decides which of X databases to send it to. How that division is determined is not as relevant (to this discussion, anyway) as the action itself. It's like registration at an event or in college where you're split up based on the first letter of your last name. You remember, every one whose name starts with A-G go in this line, you others go over there, in those lines.

That's sharding. And it's most commonly implemented in the application, where the connection to a database is created and used to manage the data that is the lifeblood of every application and business today.

Now, I told you all that to share another approach to sharding; one that takes advantage of programmability in the network (data path programmability, to be precise).

Shard in the Network or the App?
In the first scenario, in which sharding occurs in the application, there's almost certainly (I'd be willing to bet real live money) a load balancing service in front. It's distributing requests to a pool (cluster) of application instances, each of which individually decides which database to talk to given the data available. If we insert some intelligence - some programmability - into that load balancing service, we move the sharding decision in front of the application.

Now when a request comes in, the load balancing service examines the data available and decides to which application instance the request should be sent. The data is likely the same - a user identity - but may be something more applicable to the service, say a product name or number extricated from the URL of a RESTful API fronting a microservice.

sharding - network versus application

Basically what you're doing is taking the block of code responsible for sharding from inside the application and moving it into the network.

In the diagram to your left (or at least it was on the left when I wrote this) illustrates. The reason the "apps" in the "network" illustration are colored is to highlight that each of them is dedicated to a specific database. The code - the app itself - is all the same. There's no difference except for the configuration that tells it "you are dedicated to database A-G".

This is starkly different from the "in the application" sharding example in which all instances are exactly the same, including the configuration, as each one may be at any time talking to any one of the databases, depending on the data received.

Now, I believe it's obvious (because I colored all the database connections) that when you shard in the application, the complexity of the network is pretty high, as well as the load on each database as it has to maintain connections with each and every application instance. Operational Axiom #2 tells us "as load increases, performance decreases" so it's likely we're seeing an impact on performance (in a negative way) from a sharding in the application architectural approach.

Conversely, the network complexity in the sharding in the network approach is fairly low (and straight forward) and actually simplifies the entire architecture. The load on the databases themselves remains lower because there is only one instance (or pool of instances) with which it needs to manage connections.

The negative of the "in the network" approach is that you have another component (service) that must be managed - that means application lifecycle management applies -  and there are likely separate configurations necessary for each of the pools (clusters) responsible for scaling out each application instance (because each pool only talks to one of the databases). But this negative also means that the code responsible for sharding is localized, it is itself a "network microservice" that is small and isolated, meaning it can be tweaked independently of the application code. That's a positive, especially if there might be a need to increase the level of sharding or change its core mechanism required to scale the application. That's one of the reasons microservices are growing more popular; the localization and isolation ensure the ability to change without disruptive impact on other services or applications.

Taking advantage of programmability in the network to achieve new levels of scalability while simplifying your architecture is another reason programmability in the network is an invaluable tool in your architectural toolbox.

More Stories By Lori MacVittie

Lori MacVittie is responsible for education and evangelism of application services available across F5’s entire product suite. Her role includes authorship of technical materials and participation in a number of community-based forums and industry standards organizations, among other efforts. MacVittie has extensive programming experience as an application architect, as well as network and systems development and administration expertise. Prior to joining F5, MacVittie was an award-winning Senior Technology Editor at Network Computing Magazine, where she conducted product research and evaluation focused on integration with application and network architectures, and authored articles on a variety of topics aimed at IT professionals. Her most recent area of focus included SOA-related products and architectures. She holds a B.S. in Information and Computing Science from the University of Wisconsin at Green Bay, and an M.S. in Computer Science from Nova Southeastern University.

Microservices Articles
Lori MacVittie is a subject matter expert on emerging technology responsible for outbound evangelism across F5's entire product suite. MacVittie has extensive development and technical architecture experience in both high-tech and enterprise organizations, in addition to network and systems administration expertise. Prior to joining F5, MacVittie was an award-winning technology editor at Network Computing Magazine where she evaluated and tested application-focused technologies including app secu...
In his general session at 19th Cloud Expo, Manish Dixit, VP of Product and Engineering at Dice, discussed how Dice leverages data insights and tools to help both tech professionals and recruiters better understand how skills relate to each other and which skills are in high demand using interactive visualizations and salary indicator tools to maximize earning potential. Manish Dixit is VP of Product and Engineering at Dice. As the leader of the Product, Engineering and Data Sciences team at D...
When building large, cloud-based applications that operate at a high scale, it’s important to maintain a high availability and resilience to failures. In order to do that, you must be tolerant of failures, even in light of failures in other areas of your application. “Fly two mistakes high” is an old adage in the radio control airplane hobby. It means, fly high enough so that if you make a mistake, you can continue flying with room to still make mistakes. In his session at 18th Cloud Expo, Lee A...
Containers and Kubernetes allow for code portability across on-premise VMs, bare metal, or multiple cloud provider environments. Yet, despite this portability promise, developers may include configuration and application definitions that constrain or even eliminate application portability. In this session we'll describe best practices for "configuration as code" in a Kubernetes environment. We will demonstrate how a properly constructed containerized app can be deployed to both Amazon and Azure ...
Modern software design has fundamentally changed how we manage applications, causing many to turn to containers as the new virtual machine for resource management. As container adoption grows beyond stateless applications to stateful workloads, the need for persistent storage is foundational - something customers routinely cite as a top pain point. In his session at @DevOpsSummit at 21st Cloud Expo, Bill Borsari, Head of Systems Engineering at Datera, explored how organizations can reap the bene...
Using new techniques of information modeling, indexing, and processing, new cloud-based systems can support cloud-based workloads previously not possible for high-throughput insurance, banking, and case-based applications. In his session at 18th Cloud Expo, John Newton, CTO, Founder and Chairman of Alfresco, described how to scale cloud-based content management repositories to store, manage, and retrieve billions of documents and related information with fast and linear scalability. He addresse...
The now mainstream platform changes stemming from the first Internet boom brought many changes but didn’t really change the basic relationship between servers and the applications running on them. In fact, that was sort of the point. In his session at 18th Cloud Expo, Gordon Haff, senior cloud strategy marketing and evangelism manager at Red Hat, will discuss how today’s workloads require a new model and a new platform for development and execution. The platform must handle a wide range of rec...
SYS-CON Events announced today that DatacenterDynamics has been named “Media Sponsor” of SYS-CON's 18th International Cloud Expo, which will take place on June 7–9, 2016, at the Javits Center in New York City, NY. DatacenterDynamics is a brand of DCD Group, a global B2B media and publishing company that develops products to help senior professionals in the world's most ICT dependent organizations make risk-based infrastructure and capacity decisions.
Discussions of cloud computing have evolved in recent years from a focus on specific types of cloud, to a world of hybrid cloud, and to a world dominated by the APIs that make today's multi-cloud environments and hybrid clouds possible. In this Power Panel at 17th Cloud Expo, moderated by Conference Chair Roger Strukhoff, panelists addressed the importance of customers being able to use the specific technologies they need, through environments and ecosystems that expose their APIs to make true ...
In his keynote at 19th Cloud Expo, Sheng Liang, co-founder and CEO of Rancher Labs, discussed the technological advances and new business opportunities created by the rapid adoption of containers. With the success of Amazon Web Services (AWS) and various open source technologies used to build private clouds, cloud computing has become an essential component of IT strategy. However, users continue to face challenges in implementing clouds, as older technologies evolve and newer ones like Docker c...