Lorenzo Alberton
Presentations
Scaling teams, processes and architectures
Talk about the soft side of scalability, covering team management, process implementation and some solid technology-related principles. Based on 10 years of experience building scalable teams and scalable data platforms.
- Scaling teams, processes and architectures (9 December 2017)
- Monitoring at scale - Intuitive dashboard design (17 May 2013)
- Monitoring at scale - Intuitive dashboard design (14 May 2013)
- Scaling teams, processes and architectures (13 May 2013)
- Monitoring at scale - Intuitive dashboard design (23 February 2013)
- Extracting insights with the DataSift platform (4 June 2012)
- Scalable Architectures - Taming the Twitter Firehose (18 May 2012)
- Scaling Teams, Processes and Architectures (16 April 2012)
- Trees in the Database: Advanced Data Structures (18 May 2011)
- Graphs in the database: RDBMS in the social networks age (18 May 2011)
- Profile your PHP application and make it fly (14 May 2011)
- NoSQL Databases: What, When and Why (14 May 2011)
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).