Devoxx London 2017 – Rethinking Services With Stateful Streams

Friday, May 12th, 2017

Devoxx London 2017 – Rethinking Services withstatefulstreams from Ben Stopford

Slides from Strata Software Architecture: The Data Dichotomy – Rethinking data and services with streams

Wednesday, April 5th, 2017

Strata Software Architecture NY: The Data Dichotomy from Ben Stopford

QCon 2017: The Power of the Log

Wednesday, March 8th, 2017

VIDEO (currently attendees only) HERE

This talk is about the beauty of sequential access and append only data structures. We’ll do this in the context of a little known paper entitled “Log Structured Merge Trees”. LSM describes a surprisingly counterintuitive approach to storing and accessing data in a sequential fashion. It came to prominence in Google’s Big Table paper and today, the use of Logs, LSM and append only data structures drive many of the world’s most influential storage systems: Cassandra, HBase, RocksDB, Kafka and more. Finally we’ll look at how the beauty of sequential access goes beyond database internals, right through to how applications communicate, share data and scale.

The Power of the Log from Ben Stopford



Streaming, Databases & Distributed Systems – Bridging the Divide

Wednesday, November 23rd, 2016

This talk introduces Stateful Stream Processing and makes a case for SSP as a general approach to data computation in distributed environments.

Slides, alone, can be found here:

Streaming, Database & Distributed Systems Bridging the Divide from Ben Stopford


Slides from Codemesh & BigDataLdn

Friday, November 4th, 2016

Streaming, Database & Distributed Systems Bridging the Divide from Ben Stopford

Data Pipelines with Apache Kafka from Ben Stopford

Slides for JAX London

Wednesday, October 12th, 2016

Same title, but different content to the QCon one.

JAX London Slides from Ben Stopford

Slides from QCon: Microservices for a Streaming World

Monday, March 7th, 2016

Full talk can be found HERE

Abstract for Code Mesh 2015

Monday, July 20th, 2015

Contemporary Approaches to Data at Scale (tbc)

We use a host of tricks these days for handling data at scale. Disk structures are tuned to specific workloads. Streams are used to create continuous pipelines of processing. Hardware offers incredible diversity in terms of latency and throughput.

The tools available: Cassandra, Postgres, Hadoop, Kafka, Hazelcast, Storm etc all come with tradeoffs unique to themselves. We’ll look at these as individual elements. We’ll also look at compositions that leverage these individual sweet spots to create more powerful, holistic platforms.

Abstracts for Øredev 2015

Thursday, July 9th, 2015

The Future of Data Technology (6th Nov 15.40)

No longer does one-size-fit-all when it comes to data technology. At least not for many of today’s use cases. Will this ever change? Will we continue to diversify? Will we go full circle? Certainly ours is an industry in flux. NoSQL, Big Data and stream technology, containerisation, commodity PCIe storage, non-volatile memory and a host of other forces will shape the data technologies of the future. 

In this talk will make a case for what the future may look like, what challenges we’ll encounter and how it will likely change the applications we build. 

Elements of Scale: Composing And Scaling Data Platforms (5th Nov 14.20)

Today there are a host of data-centric challenges that need more than a single technology to solve. Data platforms step in, blending different technologies to solve a common goal. 

But to compose such platforms we need an understanding of the tradeoffs of each constituent part: their sweet spots, how they complement one another and what sacrifices they make in return.

This talk is really a grand tour of these evolutionary forces. We’ll cover a lot of ground, building up from disk formats right through to fully distributed, streaming and batch driven architectures. In the end we should see how these various pieces come together to form a pleasant and useful whole. 

Abstract for JAX London 2015

Thursday, July 9th, 2015

Intuitions for Scaling Data-Centric Architectures (14th Oct 11.20)

This talk will examine the various intuitions and trade-offs needed to scale a data-centric application or architecture. Building from the fundamentals of data locality, immutability and parallelism, attendees will gain a sense for how fully blown architectures can be sewn together. The result: a balance of real-time storage, streaming and analytics that plays to the relative strengths of different component parts.