Redis has 10 different data structures (String, Hash, List, Set, Sorted Set, Bit Array, Bit Field, Hyperloglog, Geospatial Index, Streams) plus Pub/Sub and many Redis Modules. In this talk, Dave will give 10 examples of how to use these data structures to scale your website. I will start with the basics, such as a cache and User session management. Then I demonstrate user generated tags, leaderboards and counting things with hyberloglog. I will with a demo of Redis Pub/Sub vs Redis Streams which can be used to scale your Microservices-based architecture.
10 Ways to Scale Your Website Silicon Valley Code Camp 2019Dave Nielsen
Redis has 10 different data structures (String, Hash, List, Set, Sorted Set, Bit Array, Bit Field, Hyperloglog, Geospatial Index, Streams) plus Pub/Sub and many Redis Modules. In this talk, Dave will give 10 examples of how to use these data structures to scale your website. I will start with the basics, such as a cache and User session management. Then I demonstrate user generated tags, leaderboards and counting things with hyberloglog. I will with a demo of Redis Pub/Sub vs Redis Streams which can be used to scale your Microservices-based architecture.
Add Redis to Postgres to Make Your Microservices Go Boom!Dave Nielsen
Slides for talk delivered at PostgresOpen 2018 in San Francisco https://postgresql.us/events/pgopen2018/schedule/session/538-add-redis-to-postgres-to-make-your-microservice-go-boom/
Running Analytics at the Speed of Your BusinessRedis Labs
The speed at which you can extract insights from your data is increasingly a competitive edge for your business. Data and analytics have to be at lightning fast speeds to seriously impact your user acquisition.
Join this webinar featuring Forrester analyst Noel Yuhanna and Leena Joshi, VP Product Marketing at Redis Labs to learn how you can glean insights faster with new open source data processing frameworks like Spark and Redis.
In this webinar you will learn:
* Why analytics has to run at the real time speed of business
* How this can be achieved with next generation Big Data tools
* How data structures can optimize your hybrid transaction-analytics processing scenarios
10 Ways to Scale Your Website Silicon Valley Code Camp 2019Dave Nielsen
Redis has 10 different data structures (String, Hash, List, Set, Sorted Set, Bit Array, Bit Field, Hyperloglog, Geospatial Index, Streams) plus Pub/Sub and many Redis Modules. In this talk, Dave will give 10 examples of how to use these data structures to scale your website. I will start with the basics, such as a cache and User session management. Then I demonstrate user generated tags, leaderboards and counting things with hyberloglog. I will with a demo of Redis Pub/Sub vs Redis Streams which can be used to scale your Microservices-based architecture.
Add Redis to Postgres to Make Your Microservices Go Boom!Dave Nielsen
Slides for talk delivered at PostgresOpen 2018 in San Francisco https://postgresql.us/events/pgopen2018/schedule/session/538-add-redis-to-postgres-to-make-your-microservice-go-boom/
Running Analytics at the Speed of Your BusinessRedis Labs
The speed at which you can extract insights from your data is increasingly a competitive edge for your business. Data and analytics have to be at lightning fast speeds to seriously impact your user acquisition.
Join this webinar featuring Forrester analyst Noel Yuhanna and Leena Joshi, VP Product Marketing at Redis Labs to learn how you can glean insights faster with new open source data processing frameworks like Spark and Redis.
In this webinar you will learn:
* Why analytics has to run at the real time speed of business
* How this can be achieved with next generation Big Data tools
* How data structures can optimize your hybrid transaction-analytics processing scenarios
What's new with enterprise Redis - Leena Joshi, Redis LabsRedis Labs
Redis Labs manages over 160k+ HA databases, 10k clustered databases, without data loss in spite of one node failure a day and one data center outage per month. Using Enterprise
Redis(RLEC), Redis Labs delivers seamless zero downtime scaling, true high availability with persistence, cross-rack/zone/
datacenter replication and instant automatic failover. Learn how. Join this session for a deep dive into how enterprise Redis makes for no-hassle Redis deployments and the roadmap for new Redis capabilities. Discover new cost savings with Redis on Flash for cost-effective high performance operations and analytics
Redis in a Multi Tenant Environment–High Availability, Monitoring & Much More! Redis Labs
Running any
application in a multi-tenant environment poses its challenges. This talk is focused around how we at Rackspace run Redis
in a multi-tenant environment, ensuring security, performance, fault tolerance and high availability. This talk will cover: an
architecture deep dive of multi tenant Redis on the cloud, management of sentinels, monitoring and operations of a large
scale Redis deployment,introducing new Redis versions,scaling, security, some lessons learnt. The target audience for this
talk is anyone who is interested in the deployment/operational aspect of running Redis. This is relevant not only for those
who want to run Redis themselves, but also interested in how a Redis provider might be doing it for them.
Back your App with MySQL & Redis, the Cloud Foundry Way- Kenny Bastani, PivotalRedis Labs
In this session, we will build a minimum viable Spring Data web service with REST API, add a MySQL backing service as the primary data store, and a Redis Labs backing service for caching. We will demonstrate performance metrics without Redis caching enabled and then with Redis caching enabled. I will also provide an intro-level explanation of the platform capabilities within Pivotal Web Services.
High-Volume Data Collection and Real Time Analytics Using Rediscacois
In this talk, we describe using Redis, an open source, in-memory key-value store, to capture large volumes of data from numerous remote sources while also allowing real-time monitoring and analytics. With this approach, we were able to capture a high volume of continuous data from numerous remote environmental sensors while consistently querying our database for real time monitoring and analytics.
* See more of my work at http://www.codehenge.net
Introduction to NoSQL (Use case, considerations to NoSQL). Presentation of Couchbase with update on Couchbase 4.5 and Couchbase mobile 1.2. Special thanks to Dipti Borkar who inspired a large part of this presentation.
Securing Your Enterprise Web Apps with MongoDB Enterprise MongoDB
Speaker: Jay Runkel, Principal Solution Architect, MongoDB
Level: 200 (Intermediate)
Track: Operations
When architecting a MongoDB application, one of the most difficult questions to answer is how much hardware (number of shards, number of replicas, and server specifications) am I going to need for an application. Similarly, when deploying in the cloud, how do you estimate your monthly AWS, Azure, or GCP costs given a description of a new application? While there isn’t a precise formula for mapping application features (e.g., document structure, schema, query volumes) into servers, there are various strategies you can use to estimate the MongoDB cluster sizing. This presentation will cover the questions you need to ask and describe how to use this information to estimate the required cluster size or cloud deployment cost.
What You Will Learn:
- How to architect a sharded cluster that provides the required computing resources while minimizing hardware or cloud computing costs
- How to use this information to estimate the overall cluster requirements for IOPS, RAM, cores, disk space, etc.
- What you need to know about the application to estimate a cluster size
Cassandra @ Sony: The good, the bad, and the ugly part 2DataStax Academy
This talk covers scaling Cassandra to a fast growing user base. Alex and Isaias will cover new best practices and how to work with the strengths and weaknesses of Cassandra at large scale. They will discuss how to adapt to bottlenecks while providing a rich feature set to the playstation community.
Practical Design Patterns for Building Applications Resilient to Infrastructu...MongoDB
Speaker: Feng Qu, Sr MTS, eBay
Level: 200 (Intermediate)
Track: Developer
Building applications resilient to infrastructure failure is essential to systems that run in distributed environments, including those with a MongoDB database. For example, failure can come from computer resources, such as nodes, network switches, or the entire data center. On occasion, MongoDB nodes may be marked down by Operations to perform administrative tasks, such as a software upgrade, adding extra capacity, etc.
In this session, we will discuss how to build resilient applications using appropriate design patterns suitable to enterprise class MongoDB applications.
What You Will Learn:
- How to manage updates within a resilient architecture.
- Design patterns for resilient applications.
- Practical advice for deploying resilient enterprise applications.
Webinar: Diagnosing Apache Cassandra Problems in ProductionDataStax Academy
This session covers diagnosing and solving common problems encountered in production, using performance profiling tools. We’ll also give a crash course to basic JVM garbage collection tuning. Viewers will leave with a better understanding of what they should look for when they encounter problems with their in-production Cassandra cluster.
Speaker: Michael Cahill, Director of Engineering (Storage), MongoDB
Level: 300 (Advanced)
Track: How We Build MongoDB
When the WiredTiger storage engine was created, the use case we had in mind was applications with modest numbers of collections. That led to various choices during the design, such as storing each collection in a separate file. However, MongoDB customers have an enormous variety of use cases, including multi-tenant applications where each user has a separate database and each database contains hundreds of collections.
To support these applications efficiently, we have evolved the storage layer with better testing, better analysis tools, and more scalable data structures and algorithms. This session will explain how we can now run workloads with over a million collections.
What You Will Learn:
- How MongoDB represents collections and indexes in the storage layer.
- The system resources involved in accessing multiple collections and indexes from different client connections.
- The system limits MongoDB may hit as you add more collections, and how to increase or work around those limits.
Big Data Day LA 2016/ NoSQL track - Analytics at the Speed of Light with Redi...Data Con LA
Spark is in-memory, Redis is in-memery. The Spark-Redis connector gives Spark access to Redis' data structures as RDDs. Redis, with its blazing fast performance and optimized in-memory data structures, reduces Spark processing time by up to 98%. In this talk, Dave will share the top use cases for Spark-Redis such as time-series, recommendations and real-time bid management.
What's new with enterprise Redis - Leena Joshi, Redis LabsRedis Labs
Redis Labs manages over 160k+ HA databases, 10k clustered databases, without data loss in spite of one node failure a day and one data center outage per month. Using Enterprise
Redis(RLEC), Redis Labs delivers seamless zero downtime scaling, true high availability with persistence, cross-rack/zone/
datacenter replication and instant automatic failover. Learn how. Join this session for a deep dive into how enterprise Redis makes for no-hassle Redis deployments and the roadmap for new Redis capabilities. Discover new cost savings with Redis on Flash for cost-effective high performance operations and analytics
Redis in a Multi Tenant Environment–High Availability, Monitoring & Much More! Redis Labs
Running any
application in a multi-tenant environment poses its challenges. This talk is focused around how we at Rackspace run Redis
in a multi-tenant environment, ensuring security, performance, fault tolerance and high availability. This talk will cover: an
architecture deep dive of multi tenant Redis on the cloud, management of sentinels, monitoring and operations of a large
scale Redis deployment,introducing new Redis versions,scaling, security, some lessons learnt. The target audience for this
talk is anyone who is interested in the deployment/operational aspect of running Redis. This is relevant not only for those
who want to run Redis themselves, but also interested in how a Redis provider might be doing it for them.
Back your App with MySQL & Redis, the Cloud Foundry Way- Kenny Bastani, PivotalRedis Labs
In this session, we will build a minimum viable Spring Data web service with REST API, add a MySQL backing service as the primary data store, and a Redis Labs backing service for caching. We will demonstrate performance metrics without Redis caching enabled and then with Redis caching enabled. I will also provide an intro-level explanation of the platform capabilities within Pivotal Web Services.
High-Volume Data Collection and Real Time Analytics Using Rediscacois
In this talk, we describe using Redis, an open source, in-memory key-value store, to capture large volumes of data from numerous remote sources while also allowing real-time monitoring and analytics. With this approach, we were able to capture a high volume of continuous data from numerous remote environmental sensors while consistently querying our database for real time monitoring and analytics.
* See more of my work at http://www.codehenge.net
Introduction to NoSQL (Use case, considerations to NoSQL). Presentation of Couchbase with update on Couchbase 4.5 and Couchbase mobile 1.2. Special thanks to Dipti Borkar who inspired a large part of this presentation.
Securing Your Enterprise Web Apps with MongoDB Enterprise MongoDB
Speaker: Jay Runkel, Principal Solution Architect, MongoDB
Level: 200 (Intermediate)
Track: Operations
When architecting a MongoDB application, one of the most difficult questions to answer is how much hardware (number of shards, number of replicas, and server specifications) am I going to need for an application. Similarly, when deploying in the cloud, how do you estimate your monthly AWS, Azure, or GCP costs given a description of a new application? While there isn’t a precise formula for mapping application features (e.g., document structure, schema, query volumes) into servers, there are various strategies you can use to estimate the MongoDB cluster sizing. This presentation will cover the questions you need to ask and describe how to use this information to estimate the required cluster size or cloud deployment cost.
What You Will Learn:
- How to architect a sharded cluster that provides the required computing resources while minimizing hardware or cloud computing costs
- How to use this information to estimate the overall cluster requirements for IOPS, RAM, cores, disk space, etc.
- What you need to know about the application to estimate a cluster size
Cassandra @ Sony: The good, the bad, and the ugly part 2DataStax Academy
This talk covers scaling Cassandra to a fast growing user base. Alex and Isaias will cover new best practices and how to work with the strengths and weaknesses of Cassandra at large scale. They will discuss how to adapt to bottlenecks while providing a rich feature set to the playstation community.
Practical Design Patterns for Building Applications Resilient to Infrastructu...MongoDB
Speaker: Feng Qu, Sr MTS, eBay
Level: 200 (Intermediate)
Track: Developer
Building applications resilient to infrastructure failure is essential to systems that run in distributed environments, including those with a MongoDB database. For example, failure can come from computer resources, such as nodes, network switches, or the entire data center. On occasion, MongoDB nodes may be marked down by Operations to perform administrative tasks, such as a software upgrade, adding extra capacity, etc.
In this session, we will discuss how to build resilient applications using appropriate design patterns suitable to enterprise class MongoDB applications.
What You Will Learn:
- How to manage updates within a resilient architecture.
- Design patterns for resilient applications.
- Practical advice for deploying resilient enterprise applications.
Webinar: Diagnosing Apache Cassandra Problems in ProductionDataStax Academy
This session covers diagnosing and solving common problems encountered in production, using performance profiling tools. We’ll also give a crash course to basic JVM garbage collection tuning. Viewers will leave with a better understanding of what they should look for when they encounter problems with their in-production Cassandra cluster.
Speaker: Michael Cahill, Director of Engineering (Storage), MongoDB
Level: 300 (Advanced)
Track: How We Build MongoDB
When the WiredTiger storage engine was created, the use case we had in mind was applications with modest numbers of collections. That led to various choices during the design, such as storing each collection in a separate file. However, MongoDB customers have an enormous variety of use cases, including multi-tenant applications where each user has a separate database and each database contains hundreds of collections.
To support these applications efficiently, we have evolved the storage layer with better testing, better analysis tools, and more scalable data structures and algorithms. This session will explain how we can now run workloads with over a million collections.
What You Will Learn:
- How MongoDB represents collections and indexes in the storage layer.
- The system resources involved in accessing multiple collections and indexes from different client connections.
- The system limits MongoDB may hit as you add more collections, and how to increase or work around those limits.
Big Data Day LA 2016/ NoSQL track - Analytics at the Speed of Light with Redi...Data Con LA
Spark is in-memory, Redis is in-memery. The Spark-Redis connector gives Spark access to Redis' data structures as RDDs. Redis, with its blazing fast performance and optimized in-memory data structures, reduces Spark processing time by up to 98%. In this talk, Dave will share the top use cases for Spark-Redis such as time-series, recommendations and real-time bid management.
LinkedIn leverages the Apache Hadoop ecosystem for its big data analytics. Steady growth of the member base at LinkedIn along with their social activities results in exponential growth of the analytics infrastructure. Innovations in analytics tooling lead to heavier workloads on the clusters, which generate more data, which in turn encourage innovations in tooling and more workloads. Thus, the infrastructure remains under constant growth pressure. Heterogeneous environments embodied via a variety of hardware and diverse workloads make the task even more challenging.
This talk will tell the story of how we doubled our Hadoop infrastructure twice in the past two years.
• We will outline our main use cases and historical rates of cluster growth in multiple dimensions.
• We will focus on optimizations, configuration improvements, performance monitoring and architectural decisions we undertook to allow the infrastructure to keep pace with business needs.
• The topics include improvements in HDFS NameNode performance, and fine tuning of block report processing, the block balancer, and the namespace checkpointer.
• We will reveal a study on the optimal storage device for HDFS persistent journals (SATA vs. SAS vs. SSD vs. RAID).
• We will also describe Satellite Cluster project which allowed us to double the objects stored on one logical cluster by splitting an HDFS cluster into two partitions without the use of federation and practically no code changes.
• Finally, we will take a peek at our future goals, requirements, and growth perspectives.
SPEAKERS
Konstantin Shvachko, Sr Staff Software Engineer, LinkedIn
Erik Krogen, Senior Software Engineer, LinkedIn
An overview of the Amazon ElastiCache managed service, with examples of how it can be used to increase performance, lower costs and augment other database services and databases to make things faster, easier and less expensive.
Technical overview of three of the most representative KeyValue Stores: Cassandra, Redis and CouchDB. Focused on Ruby and Ruby on Rails developement, this talk shows how to solve common problems, the most popular libraries, benchmarking and the best use case for each one of them.
This talk was part of the Conferencia Rails 2009, Madrid, Spain.
http://app.conferenciarails.org/talks/43-key-value-stores-conviertete-en-un-jedi-master
In this talk from the Dublin Websummit 2014 AWS Technical Evangelist Danilo Poccia discusses NoSQL technology.
Includes an introduction to NoSQL DB and a discussion of when it is time to consider NoSQL.
Danilo also introduces Amazon DynamoDB as a NoSQL solution and talks through several case studies of customers that are using Amazon DynamoDB today.
Redis is an open source advanced key-value store, created by antirez. Here is a quick overview of this awesome NoSql DB.
Like a swiss knife, Redis will help you by many ways : LRU cache, high scores, UID generator, queues, social feeds, autocomplete …
Speed up your Symfony2 application and build awesome features with RedisRicard Clau
Redis is an extremely fast data structure server that can be easily added to your existing stack and act like a Swiss army knife to help solve many problems that would be extremely difficult to workaround with the traditional RDBMS. In this session we will focus on what Redis is, how it works, what awesome features we can build with it and how we can use it with PHP and integrate it with Symfony2 applications making them blazing fast.
Peek behind the scenes to learn about Amazon ElastiCache's design and architecture. See common design patterns of our Memcached and Redis offerings and how customers have used them for in-memory operations and achieved improved latency and throughput for applications. During this session, we review best practices, design patterns, and anti-patterns related to Amazon ElastiCache.
Redis Streams plus Spark Structured StreamingDave Nielsen
Continuous applications have 3 things in common: They collect data from sources (ex: IoT devices), process them in real-time (example: ETL), and deliver them to machine learning serving layer for decision making. Continuous applications face many challenges as they grow to production. Often, due to the rapid increase in the number of devices or end-users or other data sources, the size of their data set grows exponentially. This results in a backlog of data to be processed. The data will no longer be processed in near-real-time.
Redis Streams enables you to collect both binary and text data in the time series format. The consumer groups of Redis Stream help you match the data processing rate of your continuous application with the rate of data arrival from various sources.
Apache Spark’s Structured Streaming API enables real-time decision making for Continuous Applications.
In this session, Dave will perform a live demonstration of how to integrate open source Redis with Apache Spark’s Structured Streaming API using Spark-Redis library. I will also walk through the code and run a live continuous application.
BigDL Deep Learning in Apache Spark - AWS re:invent 2017Dave Nielsen
In this talk, you will learn how to use, or create Deep Learning architectures for Image Recognition and other neural network computations in Apache Spark. Alex, Tim and Sujee will begin with an introduction to Deep Learning using BigDL. Then they will explain and demonstrate how image recognition works using step by step diagrams, and code which will give you a fundamental understanding of how you can perform image recognition tasks within Apache Spark. Then, they will give a quick overview of how to perform image recognition on a much larger dataset using the Inception architecture. BigDL was created specifically for Spark and takes advantage of Spark’s ability to distribute data processing workloads across many nodes. As an attendee in this session, you will learn how to run the demos on your laptop, on your own cluster, or use the BigDL AMI in the AWS Marketplace. Either way, you walk away with a much better understanding of how to run deep learning workloads using Apache Spark with BigDL. Presentation by Alex Kalinin, Tim Fox, Sujee Maniyam & Dave Nielsen at re:invent.
Redis as a Main Database, Scaling and HADave Nielsen
Iskren Chernev, an Independent developer, uses a lot of Redis. In this talk, Iskren will look at a particular Redis use-case -- using it as the main database (not cache). Iskren will show how to achieve reasonable guarantees about data integrity, speed, high-availability in an event of failure and infinite horizontal scalability. This particular approach has proven successful in managing clusters of up to 2400 nodes, and storing data north of 7TB before replication. We'll cover ways to separate your data appropriately into many nodes, performing different types of migrations (from another database, from one cluster to another, scaling migrations and migrating out of Redis), moving nodes without downtime, some configuration tips and monitoring.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
6. Redis Top Differentiators
Simplicity ExtensibilityPerformance
NoSQL Benchmark
1
Redis Data Structures
2 3
Redis Modules
6
Lists
Hashes
Bitmaps
Strings
Bit field
Streams
Hyperloglog
Sorted Sets
Sets
Geospatial Indexes
7. Performance: The Most Powerful Database
Highest Throughput at Lowest Latency
in High Volume of Writes Scenario
Least Servers Needed to
Deliver 1 Million Writes/Sec
Benchmarks performed by Avalon Consulting Group Benchmarks published in the Google blog
7
1
Serversusedtoachieve1Mwrites/sec
8. “REDIS IS FULL OF DATA STRUCTURES!”
2 Simplicity: Data Structures - Redis’ Building Blocks
9. Simplicity: Redis Data Structures – ’Lego’ Building Blocks
Lists
[ A → B → C → D → E ]
Hashes
{ A: “foo”, B: “bar”, C: “baz” }
Bitmaps
0011010101100111001010
Strings
"I'm a Plain Text String!”
Bit field
{23334}{112345569}{766538}
Key
9
2
”Retrieve the e-mail address of the user with the highest
bid in an auction that started on July 24th at 11:00pm PST” ZREVRANGE 07242015_2300 0 0=
Streams
{id1=time1.seq1(A:“xyz”, B:“cdf”),
d2=time2.seq2(D:“abc”, )}
Hyperloglog
00110101 11001110
Sorted Sets
{ A: 0.1, B: 0.3, C: 100 }
Sets
{ A , B , C , D , E }
Geospatial Indexes
{ A: (51.5, 0.12), B: (32.1, 34.7) }
10. • Add-ons that use a Redis API to seamlessly support additional
use cases and data structures.
• Enjoy Redis’ simplicity, super high performance, infinite
scalability and high availability.
Extensibility: Modules Extend Redis Infinitely
• Any C/C++/Go program can become a Module and run on Redis.
• Leverage existing data structures or introduce new ones.
• Can be used by anyone; Redis Enterprise Modules are tested and certified by Redis
Labs.
• Turn Redis into a Multi-Model database
10
3
13. Real Time
Analytics
User Session
Store
Real Time Data
Ingest
High Speed
Transactions
Job & Queue
Management
Time Series Data Complex
Statistical Analysis
Notifications Distributed Lock Caching
Geospatial Data Streaming Data Machine Learning
13
Very Large Data Sets Search
15. • An chunk of data that is connected to one “user” of a service
–”user” can be a simple visitor
–or proper user with an account
• Often persisted between client and server by a token in a cookie*
–Cookie is given by server, stored by browser
–Client sends that cookie back to the server on subsequent requests
–Server associates that token with data
• Often the most frequently used data by that user
–Data that is specific to the user
–Data that is required for rendering or common use
• Often ephemeral and duplicated
A user session store is…
16. Session Storage Uses Cases
Traditional
• Username
• Preferences
• Name
• “Stateful” data
Intelligent
• Traditional +
• Notifications
• Past behavior
–content surfacing
–analytical information
–personalization
25. User Session Store
• The Problem
• Maintain session state across
multiple servers
• Multiple session variables
• High speed/low latency required
Why Redis Rocks
• Hashes are perfect for this!
• HSET lets you save session
variables as key/value pairs
• HGET to retrieve values
• HINCRBY to increment any
field within the hash structure
26. Redis Hashes Example - https://redis.io/commands#hash
userid 8754
name dave
ip 10:20:104:31
hits 1
lastpage home
hash key: usersession:1
HMSET usersession:1 userid 8754 name dave ip 10:20:104:31 hits 1
HMGET usersession:1 userid name ip hits
HINCRBY usersession:1 hits 1
HSET usersession:1 lastpage “home”
HGET usersession:1 lastpage
HDEL usersession:1 lastpage
Hashes store a mapping of keys to values – like a dictionary or associative array – but faster
EXPIRE usersession:1 10
DEL usersession:1
or
28. Managing Queues of Work
• The Problem
• Tasks need to be worked on asynch
to reduce block/wait times
• Lots of items to be worked on
• Assign items to worker process and
remove from queue at the same time
• Similar to buffering high speed data-
ingestion
Why Redis Rocks
• Lists are perfect for this!
• LPUSH, RPUSH add values at
beginning or end of queue
• RPOPLPUSH – pops an item
from one queue and pushes it
to another queue
29. Redis Lists Example - https://redis.io/commands#list
LPUSH queue1 orange
LPUSH queue1 green
LPUSH queue1 blue
RPUSH queue1 red
LPUSH adds values to head of list
RPUSH adds value to tail of list
blue green orange .. .. red
30. Redis Lists Example - https://redis.io/commands#list
blue green orange .. ..
RPOPLPUSH queue1 queue2
red
LPUSH queue1 orange
LPUSH queue1 green
LPUSH queue1 blue
RPUSH queue1 red
RPOPLPUSH pops a value from one list and pushes it to another list
LLEN queue1
LINDEX queue1 0
LRANGE queue1 0 2
32. Managing Tags Example
• The Problem
• Loads of tags
• Find items with particular tags
• High speed/low latency required
Also used for:
• Recommending Similar Purchases
• Recommending Similar Posts
Why Redis Rocks
• Sets are unique collections of strings
• SADD to add tags to each article
• SISMEMBER to check if an article has
a given tag
• SMEMBERS to get all the tags for an
article
• SINTER to find which articles are
tagged with tag1, tag2 and tag77
35. Leaderboard with Sorted Sets Example
• The Problem
• MANY users playing a game or
collecting points
• Display real-time leaderboard.
• Who is your nearest competition
• Disk-based DB is too slow
Why Redis Rocks
• Sorted Sets are perfect!
• Automatically keeps list of
users sorted by score
• ZADD to add/update
• ZRANGE, ZREVRANGE to get
user
• ZRANK will get any users
rank instantaneously
38. Search within a Geographic Area Example
• The Problem
• MANY moving items within a
geographical area
• Display real-time locations.
• What is the nearest item NOW
• SQL Queries are too slow
Why Redis Rocks
• GEOADD to add an item
• Redis Geo uses Sorted Sets
so related Z-commands such
as ZRANGE & ZREM are
useful too
• GEODIST to find distance
between to points
• GEORADIUS to find all points
within an area
47. 47
Redis Data Structures
1. Strings - Cache SQL queries, pages, fast data
2. Bitmaps - Store 1s/0s (Online/Offline) like Pinterest
3. Bit Fields - Store arrays of complex numbers
4. Hashes - Store record-like info (user sessions, favorites, etc.)
5. Lists - Store ordered data (for ingesting data)
6. Sets - Store unique/unordered data (tags, unique IPs, etc.)
7. Sorted Sets - Store real-time sorted data like a MMPORG Leaderboard
8. Geospacial Indexes - Store real-time location (Uber, Lyft, etc.)
9. Hyperloglog - Store probabilistic data (Google Search count)
10. Streams - Store and share event data (similar to Kafka)
Lists
Hashes
Bitmaps
Strings
Bit fields
Streams
Hyperloglog
Sorted Sets
Sets
Geospatial Indexes
49. Redis Keys – Ground Rules
• It’s all about the keys
• No Querying
• No Indexes
• No Schemas
• Keys must be unique (like primary keys in an SQL database)