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4 .Agenda
• Introduction
• Single-node patterns
• Multi-node patterns
• Batch processing patterns
5 .Introduction
• The development of containers and container
orchestrators has fundamentally changed
distributed system development.
• Patterns make the distributed systems easier
to debug, design and architect.
• Need new patterns to build reliable, scalable,
reusable, efficient distributed systems.
• Prereq: Docker, Kubernetes, microservice
• Reference: Designing Distributed Systems,
Brendan Burns
6 .Single-Node Patterns
• Sidecar
• Ambassador
• Adapter
7 .Sidecar
• Add HTTPS to a legacy service
• Dynamic configuration
• Istio - envoy
8 .Hands On: Deploying the topz Container
• A monitoring example:
$ docker run -d tomcat:9
$ docker run —pid=container:<tomcat container id> -p 9080:9080 brendanburns/
topz:db0fa58 /server --addr=0.0.0.0:9080
• http://localhost:9080/topz
• http://localhost:9080/topz
9 .Building a simple PaaS with sidecar
• Complete application in modular manner
• Our websites
• http://localhost:9080/topz
10 .Sidecar
• Common usage: adapt legacy applications where you no longer wanted to make
modifications to the original source code
• Modularity and reuse of the components used as sidecars
• Utility container
• Examples: (adapting, augment/extend)
11 .Sidecar - Focus and Discipline
• To achieve modularity and reusability
• Parameterizing your containers
• Environment variable:
• Command line
• API surface
• Documentation (Dockerfile)
13 .Using Ambassador for Service brokering
• Brokering services on public cloud (SaaS), private cloud, or BM.
14 .Using Ambassador to Shard Service
• Client-side ambassador
• Server-side ambassador
15 .Using Ambassador to Do Experimentation or Request Splitting
16 .Adapter
• Monitor
• Normalize
• Health monitor
• Logging
• Redirect to stdout
• Transform data into a single
structured representation
that can be consumed by
generic log aggregator. Ex.
Normalizing Different
Logging Formats with
Fluentd
17 .Single-Node Patterns Summary
• Sidecar: extend and augment existing application containers
• Ambassador: alter and broker how an application container communicates with the
external world
• Adapter: modify the interface of the application container so that it conforms to some
predefined interface that is expected of all applications
18 .Serving Patterns
• Multi-node, distributed
• Including:
• Replicated LB services
• Sharded services
• Scatter / Gather
• FaaS
• Ownership Election
19 .Warm-up: Mircroservice
20 .Replicated Load-Balanced Services
• K8S service
21 .Sharded Services
• Replicated services are generally used for
building stateless services, whereas sharded
services are generally used for building
stateful services.
• Replicated, sharded service
• Ex. Consistent HTTP Sharding Proxy
22 .Scatter / Gather
• In contrast to replicated and sharded
systems, with scatter/gather requests are
simultaneously farmed out to all of the
replicas in the system
• Can be seen as sharding the computation to
serve the request, rather than sharding the
data (although data sharding may be part of it
as well)
23 .Example: Distributed Document Search
24 .Scaling Scatter / Gather for Reliability and Scale
• Increased parallelism doesn’t always speed things up because of overhead on each node.
• Increased parallelism doesn’t always speed things up because of the straggler problem.
• The performance of the 99th percentile is more important than in other systems because
each user request actually becomes numerous requests to the service.
25 .Multi-Node Patterns Summary
• Replicated LB services: stateless replicated pattern, scalability in terms of rps, reliability
• Sharded services: sharded data pattern, scalability for the size of the data
• Scatter / Gather: scalability in terms of time, parallelism
26 .Batch Processing
• Work Queue
• Event-driven
• Coordinated
27 .Work Queue
File-based API pattern
28 .Work Queue
Great for enabling individual transformations of one input to one output
Ex. Implementing a Video Thumbnailer
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