Talks

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Monitoring at scale - Intuitive dashboard design

At a certain scale, millions of events happen every second, and all of them are important to evaluate the health of the system. If not handled correctly, such a volume of information can overwhelm both the infrastructure that needs to support them, and people who have to make a sense out of thousands of signals and make decisions upon them, fast. By understanding how our rational mind works, how people process information, we can present data so it's more evident and intuitive. This talk will explain how to collect useful metrics, and to create the perfect monitoring dashboard to organise and display them, letting our intuition operate automatically and quickly, and saving attention and mental effort to activities that demand it.

Monitoring at scale - Intuitive dashboard design

At a certain scale, millions of events happen every second, and all of them are important to evaluate the health of the system. If not handled correctly, such a volume of information can overwhelm both the infrastructure that needs to support them, and people who have to make a sense out of thousands of signals and make decisions upon them, fast. By understanding how our rational mind works, how people process information, we can present data so it's more evident and intuitive. This talk will explain how to collect useful metrics, and to create the perfect monitoring dashboard to organise and display them, letting our intuition operate automatically and quickly, and saving attention and mental effort to activities that demand it.

Scaling teams, processes and architectures

When we think about scalability, we only focus on the technical details, forgetting two equally important aspects, people and processes. In this talk we'll cover the fundamental elements of scalability, both organisational and technical, with sound and proven principles and some advice on how to shape your organisation, set the right processes and design your application

Monitoring at scale - Intuitive dashboard design

At a certain scale, millions of events happen every second, and all of them are important to evaluate the health of the system. If not handled correctly, such a volume of information can overwhelm both the infrastructure that needs to support them, and people who have to make a sense out of thousands of signals and make decisions upon them, fast. By understanding how our rational mind works, how people process information, we can present data so it's more evident and intuitive. This talk will explain how to collect useful metrics, and to create the perfect monitoring dashboard to organise and display them, letting our intuition operate automatically and quickly, and saving attention and mental effort to activities that demand it.

Extracting insights with the DataSift platform

Handling lots of real-time streams of information, when Twitter alone is producing 340+ million tweets a day and 40 million links to news and media, can be a daunting task, and actually turning this into valuable insights might be even tougher. This talk will cover how the DataSift platform makes this task easy, and will show some concrete use cases of how the social media data can be used for customer intelligence.

Scalable Architectures - Taming the Twitter Firehose

Handling lots of real-time streams of information, when Twitter alone is producing 330+ million tweets a day and 35 million links to news and media, can be a daunting task. This talk will cover how to develop a platform that can deal with billions of items per day, perform complex analysis and serve thousands of customers in real-time, by dissecting a large scale architecture into small components and explaining what processes to put in place, what pitfalls to avoid and how to keep the system running. We will walk through several scalability patterns, clever techniques and cutting-edge technologies, high-throughput message queues, nosql databases, monitoring tools, each accompanied by one or more concrete examples.

Scaling Teams, Processes and Architectures

Generic presentation about scalability challenges. First London Scalability Meetup. Quick overview of the DataSift architecture.

Trees in the Database: Advanced Data Structures

Despite the NoSQL movement trying to flag traditional databases as a dying breed, the RDBMS keeps evolving and adding new powerful weapons to its arsenal. In this talk we'll explore Common Table Expressions (SQL-99) and how SQL handles recursion, breaking the bi-dimensional barriers and paving the way to more complex data structures like trees and graphs, and how we can replicate features from social networks and recommendation systems. We'll also have a look at window functions (SQL:2003) and the advanced reporting features they make finally possible. The first part of this talk will cover several different techniques to model a tree data structure into a relational database: parent-child (adjacency list) model, materialized path, nested sets, nested intervals, hybrid models, Common Table Expressions. Then we'll move one step forward and see how we can model a more complex data structure, i.e. a graph, with concrete examples from today's websites. Starting from real-world examples of social networks' and recommendation systems' features, and with the help of some graph theory, this talk will explain how to represent and traverse a graph in the database. Finally, we will take a look at Window Functions and how they can be useful for data analytics and simple inline aggregations, among other things. All the examples have been tested on PostgreSQL >= 8.4

Graphs in the database: RDBMS in the social networks age

Despite the NoSQL movement trying to flag traditional databases as a dying breed, the RDBMS keeps evolving and adding new powerful weapons to its arsenal. In this talk we'll explore Common Table Expressions (SQL-99) and how SQL handles recursion, breaking the bi-dimensional barriers and paving the way to more complex data structures like trees and graphs, and how we can replicate features from social networks and recommendation systems. We'll also have a look at window functions (SQL:2003) and the advanced reporting features they make finally possible. The first part of this talk will cover several different techniques to model a tree data structure into a relational database: parent-child (adjacency list) model, materialized path, nested sets, nested intervals, hybrid models, Common Table Expressions. Then we'll move one step forward and see how we can model a more complex data structure, i.e. a graph, with concrete examples from today's websites. Starting from real-world examples of social networks' and recommendation systems' features, and with the help of some graph theory, this talk will explain how to represent and traverse a graph in the database. Finally, we will take a look at Window Functions and how they can be useful for data analytics and simple inline aggregations, among other things. All the examples have been tested on PostgreSQL >= 8.4

Profile your PHP application and make it fly

Making an application scale and go faster is often seen as a wizardly task. We read the micro-optimisation tricks posted in tech blogs and apply them with unconditional trust and great hope, and then wonder why performances haven t improved that much ( Wait, I even replaced print with echo !!! ). In this talk we ll see how we can take easy, practical steps we can apply over and over that really make a difference, by analysing what our application does under the hood, measuring how and where the different resources are used, eliminating the real bottlenecks and restructuring critical components to handle growing loads.

NoSQL Databases: What, When and Why

NoSQL databases get a lot of press coverage, but there seems to be a lot of confusion surrounding them, as in which situations they work better than a Relational Database, and how to choose one over another. This talk will give an overview of the NoSQL landscape and a classification for the different architectural categories, clarifying the base concepts and the terminology, and will provide a comparison of the features, the strengths and the drawbacks of the most popular projects (CouchDB, MongoDB, Riak, Redis, Membase, Neo4j, Cassandra, HBase, Hypertable).

Modern Algorithms and Data Structures - 1. Bloom Filters, Merkle Trees

The first part of a series of talks about modern algorithms and data structures, used by nosql databases like HBase and Cassandra. An explanation of Bloom Filters and several derivates, and Merkle Trees. Podcast

NoSQL Databases: What, When and Why

NoSQL databases get a lot of press coverage, but there seems to be a lot of confusion surrounding them, as in which situations they work better than a Relational Database, and how to choose one over another. This talk will give an overview of the NoSQL landscape and a classification for the different architectural categories, clarifying the base concepts and the terminology, and will provide a comparison of the features, the strengths and the drawbacks of the most popular projects (CouchDB, MongoDB, Riak, Redis, Membase, Neo4j, Cassandra, HBase, Hypertable).

Graphs in the database: RDBMS in the social networks age

Despite the NoSQL movement trying to flag traditional databases as a dying breed, the RDBMS keeps evolving and adding new powerful weapons to its arsenal. In this talk we’ll explore Common Table Expressions (SQL-99) and how SQL handles recursion, breaking the bi-dimensional barriers and paving the way to more complex data structures like trees and graphs, and how we can replicate features from social networks and recommendation systems. We’ll also have a look at window functions (SQL:2003) and the advanced reporting features they make finally possible.

Profile your PHP application and make it fly

Making an application scale and go faster is often seen as a wizardly task. We read the micro-optimisation tricks posted in tech blogs and apply them with unconditional trust and great hope, and then wonder why performances haven’t improved that much (“Wait, I even replaced ‘print’ with ‘echo’!!!”). In this talk we’ll see how we can take easy, practical steps we can apply over and over that really make a difference, by analysing what our application does under the hood, measuring how and where the different resources are used, eliminating the real bottlenecks and restructuring critical components to handle growing loads.

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Lorenzo Alberton

Lorenzo Alberton Lorenzo PHP5 ZCE - Zend Certified Engineer has been working with large enterprise UK companies for the past years and is now Chief Tech Architect at DataSift. He's an international conference speaker and a long-time contributor to many open source projects. Lorenzo Alberton's profile on LinkedIN View Lorenzo Alberton's Twitter stream

Lorenzo Alberton - Sun Certified MySQL 5 Developer

Tags

AJAX, Apache, Book Review, Charset, Cheat Sheet, Data structures, Database, Firebird SQL, Hadoop, Imagick, INFORMATION_SCHEMA, JavaScript, Kafka, Linux, Message Queues, mod_rewrite, Monitoring, MySQL, NoSQL, Oracle, PDO, PEAR, Performance, PHP, PostgreSQL, Profiling, Scalability, Security, SPL, SQL Server, SQLite, Testing, Tutorial, TYPO3, Windows, Zend Framework