The agenda of this talk was to introduce MySQL Replication and then follow it up with Multi-threaded slaves(MTS) support. The presentation introduces Multi threading slaves by database which is a part of MySQL-5.6 as well as multi-threading policy introduced in MySQL-5.7.2. Finally there is a brief coverage of the new replication monitoring tables to monitor MySQL Replication. These tables are part of MySQL Performance Schema.
Navigating Transactions: ACID Complexity in Modern DatabasesShivji Kumar Jha
Transactions are anything but straightforward, with each database vendor offering its unique interpretation of the term. By scrutinising the internal architectures of these databases, engineers can gain valuable insights, enabling them to write more stable applications.This talk explores the intricacies of transactions, focusing on modern databases. Delving into distributed transactions, we discuss network challenges and cloud deployments in the contemporary era. The session provides a concise examination of the internal architectures of cloud-scale, multi-tenant databases such as Spanner, DynamoDB, and Amazon Aurora.
This document summarizes a presentation given at the London Open Source Meetup for RISC-V on April 19, 2021. The presentation introduced the RISC-V Online Tutor, an online course for learning RISC-V fundamentals from digital logic to C programming. It provided an overview of the course structure and lessons, which take students through RISC-V assembly, processor design, and application development. It also demonstrated the online learning platform and its ability to interact with remote FPGA hardware during lessons. The goal is to invite community participation and collaboration to further develop the Online Tutor.
The document summarizes a presentation on MySQL failover and orchestrator software. It discusses how orchestrator can help manage MySQL failover across servers to provide high availability and prevent downtime. Orchestrator automatically discovers MySQL topology, monitors servers, and can relocate masters and notify administrators of failures. It provides both a GUI and CLI to manage failover tasks and supports configurations from simple to complex multi-server setups.
This document provides a summary of a presentation on Amazon Aurora by Dickson Yue. It discusses Aurora fundamentals like its scale-out distributed architecture and 6 copies of data for fault tolerance. Recent improvements discussed include fast database cloning, backup and restore capabilities, and backtrack for point-in-time recovery. Coming soon features outlined are asynchronous key prefetch, batched scans, hash joins, and Aurora Serverless for automatic scaling.
A multi-signed kernel module can be loaded on kernels be trusted by different keys. Which means that one KMP can be deployed on different trust system.
This document provides tips for tuning a MySQL database to optimize performance. It discusses why tuning is important for cost effectiveness, performance, and competitive advantage. It outlines who should be involved in tuning including application designers, developers, DBAs and system administrators. The document covers what can be tuned such as applications, databases structures, and hardware. It provides best practices for when and how much to tune a database. Specific tuning techniques are discussed for various areas including application development, database design, server configuration, and storage engine optimizations.
Going Deep on Amazon Aurora Serverless (DAT427-R1) - AWS re:Invent 2018Amazon Web Services
Amazon Aurora Serverless is a configuration for Aurora (MySQL-compatible edition) where the database automatically starts up, shuts down, and scales capacity up or down based on your application's needs. In this session, we discuss how Aurora Serverless supports infrequent, intermittent, or unpredictable workloads, and we provide tips for building your next application on a serverless database.
Log Analytics with ELK Stack describes optimizing an ELK stack implementation for a mobile gaming company to reduce costs and scale data ingestion. Key optimizations included moving to spot instances, separating logs into different indexes based on type and retention needs, tuning Elasticsearch and Logstash configurations, and implementing a hot-warm architecture across different EBS volume types. These changes reduced overall costs by an estimated 80% while maintaining high availability and scalability.
The document discusses MongoDB backups and point-in-time recovery (PITR). It covers the reasons for backups including disaster recovery and high availability. It describes logical and physical backup types in MongoDB and tools like mongodump, mongoexport, and filesystem snapshots. It also explains how to perform PITR using incremental backups of the oplog and restoring from backups up to a chosen point-in-time.
Uber’s blog post about migration from PostgreSQL to MySQL made a lot of buzz in PostgreSQL community. Many of Developers PostgreSQL community realized shortcoming of our table engine (which is the only one yet). As result, many of patches were developer in order to overcome the shortcomings mentioned by Uber. Some of those patches are overlapping, even some of them are in contradictory. Those patches include: indirect indexes (indexes which references primary key value), WARM (write-amplification reduction method), RDS (recently dead storage). Also there are discussions about pluggable table engines and undo log.
In this talk I’ll consider points of Uber’s blog post from PostgreSQL developer point of view. I’ll tell which points I agree, which points I disagree and which points I partially agree. Also I’ll consider developments of PostgreSQL community, and how them can overcome mentioned shortcomings from my point of view.
ClickHouse Monitoring 101: What to monitor and howAltinity Ltd
Webinar. Presented by Robert Hodges and Ned McClain, April 1, 2020
You are about to deploy ClickHouse into production. Congratulations! But what about monitoring? In this webinar we will introduce how to track the health of individual ClickHouse nodes as well as clusters. We'll describe available monitoring data, how to collect and store measurements, and graphical display using Grafana. We'll demo techniques and share sample Grafana dashboards that you can use for your own clusters.
Introducción al Stack Elastic y Machine Learning con ElasticsearchImma Valls Bernaus
Este documento presenta una introducción al Stack Elastic y sus capacidades de machine learning. Explica brevemente cada componente del stack, incluyendo Elasticsearch para almacenamiento y búsqueda de datos, Kibana para visualización, y Beats y Logstash para ingesta de datos. Luego se enfoca en las capacidades de machine learning de Elasticsearch, discutiendo detección de anomalías en series temporales y análisis con data frames para detección de valores atípicos y machine learning supervisado.
How to set up orchestrator to manage thousands of MySQL serversSimon J Mudd
This document discusses how to scale Orchestrator to manage thousands of MySQL servers. It describes how Booking.com uses Orchestrator to manage their thousands of MySQL servers. As the number of monitored servers increases, integration with internal infrastructure is needed, Orchestrator performance must be optimized, and high availability and wider user access features are added. The document provides examples of configuration settings and special considerations needed to effectively use Orchestrator at large scale.
Node.js and Oracle Database: New Development TechniquesChristopher Jones
These slides are from the AUSOUG webinar viewable at https://www.ausoug.org.au/event/node-js-and-oracle-database-new-development-techniques/
The session covered the best node-oracledb data access features for building great Node.js applications with Oracle Database. Spanning topics from the latest connection pooling advances, right through to efficient ways to access your data, all the best tips are demonstrated. After another busy year of node-oracledb releases, don’t miss the latest on this rapidly growing ecosystem.
This is a technical talk with code snippets demonstrating efficient use of the Node.js node-oracledb driver for Oracle DB. There have been several key releases of node-oracledb over the last year so there is plenty to talk about.
This document summarizes a presentation about Amazon Aurora. It discusses how Aurora provides the speed and availability of commercial databases at a lower cost than open source databases. Aurora is a MySQL and PostgreSQL compatible database that is managed as a service, automating administrative tasks. It utilizes a distributed, self-healing storage system to provide high availability and durability across availability zones.
The document discusses data loss and duplication in Apache Kafka. It begins with an overview of Kafka and how it works as a distributed commit log. It then covers sources of data loss, such as failures at the producer or cluster level. Data duplication can occur when producers retry messages or consumers restart from an unclean shutdown. The document provides configurations and techniques to minimize data loss and duplication, such as using producer acknowledgments and storing metadata to validate messages. It also discusses monitoring Kafka using JMX metrics to detect issues.
Venkatesh Duggirala from the MySQL Replication Team gave a presentation on Multi Source Replication. The presentation covered the background on why replication is used, an introduction to multi-source replication including how a slave can have multiple masters, use cases like data aggregation, and technical details on how channels and slave appliers work in multi-source replication. Monitoring of multi-source replication was also discussed.
This document discusses MySQL Fabric, which is a framework for managing a farm of MySQL servers to provide high availability and sharding capabilities. It describes how MySQL Fabric allows for easy management of MySQL servers, including load balancing, read/write splitting, distributed transactions, global updates, and sharding of tables. It also covers how application connectors can be made aware of MySQL Fabric to properly route queries and transactions to the backend MySQL servers.
NoSQL & SQL - Best of both worlds - BarCamp Berkshire 2013Andrew Morgan
The document discusses blending NoSQL and SQL databases by leveraging the strengths of both. It describes how MySQL Cluster provides massively scalable performance through its NoSQL-style data storage and replication abilities, while also supporting SQL queries, joins, and ACID transactions like a traditional relational database. This allows applications to use NoSQL for simple operations and scalability while still using SQL for complex queries and transactions as needed.
MySQL High Availability with Replication New FeaturesShivji Kumar Jha
The session was presented at open source India 2014 (http://osidays.com/osidays/) by Shivji (me) and Manish Kumar. It talks of the new features in MySQL-5.7 Replication. It covered work on
1) performance enhancements in MySQL Replication
2) Usability improvements
3) More flexibility to provide more options to our users so
they can chose what is best for their application.
4) Semisynchronous and MySQL Group Replication
At then end, there are a lot of links to the blogs written on these features by the MySQL Replication engineers.
This document discusses enhancements to MySQL database replication in versions 8 and 5.7. It covers new features for binary log metadata, multi-source replication with filtering, automatic protection of offline replicas, primary election weights, shutting down replicas that leave groups involuntarily, triggering primary elections and changing group modes online, and relaxed member eviction timeouts. It also discusses performance improvements to the replication applier thread through dependency tracking.
Using The Mysql Binary Log As A Change StreamLuís Soares
The binary log records all data modifications made to tables logged by MySQL. It provides a sequential record of statements and changes that can be used for point-in-time recovery or to replicate data. The binary log files are persisted on disk and contain control events, transaction events, and row events representing changes. Applications can inspect the contents of the binary log through SQL statements or the mysqlbinlog tool to understand the recorded changes.
MySQL Developer Day conference: MySQL Replication and ScalabilityShivji Kumar Jha
The slide deck contains the latest developments in MySQL Replication. It covers:
- An introduction to MySQL Replication
- Scaling with Multi-threaded slaves
- Data aggregation with Multi-source replication
- Lossless failover with semi-synchronous replication
- Replication Monitoring made easier
MySQL High Availability: Managing Farms of Distributed Servers (MySQL Fabric)Alfranio Júnior
This document provides an overview and introduction to MySQL Fabric, a new high availability and distributed database solution from Oracle. The summary includes:
- MySQL Fabric is a distributed framework that allows farms of MySQL servers to be managed as highly available groups. It uses extensions and connectors to provide fault tolerance.
- Failure detection and failover works by having MySQL Fabric monitor the servers in an availability group. If the master fails, it will trigger a failover to promote a slave to become the new master.
- MySQL Fabric-aware connectors are available for Python, Java, and PHP that can route transactions, cache information, and handle failures by retrying operations on a different server if needed.
Introduction to MySQL Enterprise MonitorMark Leith
The document is a presentation on MySQL Enterprise Monitor (MEM) by Mark Leith of Oracle. It introduces MEM as a distributed monitoring system for MySQL with a central Service Manager and agents installed on monitored hosts. The presentation includes sections on MEM architecture showing its core components, and a demo of features in the MEM UI like viewing instances, advisors, events, graphs, and query analysis.
MySQL 8 High Availability with InnoDB ClustersMiguel Araújo
MySQL’s InnoDB cluster provides a high-level, easy-to-use solution for MySQL high availability. Combining MySQL Group Replication with MySQL Router and the MySQL Shell into an integrated solution, InnoDB clusters offer easy setup and management of MySQL instances into a fault-tolerant database service. In this session learn how to set up a basic InnoDB cluster, integrate it with applications, and recognize and react to common failure scenarios that would otherwise lead to a database outage.
- Workshop presentation
MySQL 20 años: pasado, presente y futuro; conoce las nuevas características d...GeneXus
The document is a safe harbor statement outlining Oracle's general product direction and disclaiming any commitments. It states that the information is intended for informational purposes only and should not be relied upon for purchasing decisions. It also notes that Oracle has sole discretion over releasing any product features or functionality mentioned. The document is copyrighted by Oracle in 2015.
Scaling MySQl 1 to N Servers -- Los Angelese MySQL User Group Feb 2014Dave Stokes
The document discusses various options for scaling MySQL databases to handle increasing load. It begins with simple options like upgrading MySQL versions, adding caching layers, and read/write splitting. More complex and reliable options include using MySQL replication, cloud hosting, MySQL Cluster, and columnar storage engines. Scaling to very large "big data" workloads may involve using NoSQL technologies, Hadoop, and data partitioning/sharding. The key challenges discussed are defining business and technical requirements, planning for high availability, and managing increased complexity.
MySQL InnoDB Cluster and Group Replication - OSI 2017 BangaloreSujatha Sivakumar
The document discusses MySQL InnoDB Cluster and Group Replication. It provides an introduction and overview of InnoDB Cluster, outlining the key features and how to get an InnoDB Cluster up and running in 3 steps: deploying instances, creating a cluster, and adding more instances. It also covers setting up and starting a router. For Group Replication, it discusses the concept of replicating writes across multiple servers for high availability and read scaling. It shows how Group Replication achieves consensus on membership, message delivery and state updates across the group.
MySQL Group Replication @osi days 2014Manish Kumar
MySQL Group Replication allows multiple MySQL servers to act as a single logical master by replicating transactions between them in parallel. It provides multi-master replication with automatic conflict detection and resolution. When a new server joins the replication group, it synchronizes by retrieving missing transactions from another member before participating.
The slde contains an introduction to the global transaction identifiers(GTIDs) in MySQL Replication. The new protocol at re-connect, skipping transactions with GTIDS, replication filters, purging logs, backup/restore ets are covered here.
The document provides an overview of new replication features in MySQL 5.7, including:
1. Online reconfiguration of global transaction identifiers and replication filters which allow changing replication settings without restarting servers or interrupting reads/writes.
2. Online reconfiguration of replication receivers and appliers which enables changing the replication topology during failover without stopping applier threads.
3. Improved replication monitoring through new performance schema tables that provide more accurate and extensive monitoring of replication components.
DataOps Barcelona - MySQL HA so easy... that's insane !Frederic Descamps
1. MySQL 8.0 InnoDB Cluster is a new high availability and scaling solution for MySQL that makes setup easy.
2. It uses Group Replication under the hood to allow writing to all nodes simultaneously while maintaining consistency.
3. Key components include MySQL Router for routing and load balancing, and MySQL Shell for administration.
MySQL Group Replication is a plugin that enables multi-master replication. It allows any server in the replication group to accept writes and provides automatic recovery from failures or new servers joining. It uses message passing and conflict detection to keep all servers in sync. The plugin manages the distributed transaction execution and recovery process.
Similar to MySQL User Camp: Multi-threaded Slaves (20)
Batch to near-realtime: inspired by a real production incidentShivji Kumar Jha
This slide deck was used for the platformatory streams meetup in Bengaluru on July 7, 2024.
This is a real world account from an Apache Druid cluster in production. A story of 48 hours of debugging, learning and understanding batch vs stream better, filing a couple of issues in Druid open source projects and finally a stable production pipeline again thanks to the Druid community. We will discuss what parts of your design could be impacted, how you should change the related systems so the cascading failures don’t bring down your complete production availability. As an example, we will discuss the bottlenecks we had in overlord, slot issues for Peons in middle managers, coordinator bottlenecks, how to mitigated task and segment flooding, what configs we changed sprinkled with real world numbers and snapshots from our Grafana dashboards.
Finally we will list all the leanings and how we made sure we never repeat the same mistakes in production systems.
Druid Summit 2023 : Changing Druid Ingestion from 3 hours to 5 minutesShivji Kumar Jha
This is a real world account from a Druid cluster in production. A story of 48 hours of debugging, learning and understanding Druid better, filing a couple of issues in Druid github and finally a stable production pipeline again thanks to the Druid community.
We will discuss the bottlenecks we had in overlord, slot issues for Peons in middle managers, coordinator bottlenecks, how we mitigated task and segment flooding, what configs we changed sprinkled with real world numbers and snapshots from our grafana dashboards.
In this slide deck, we go exploring the database landscape today and the common lego blocks that are used to build these different falvours of databses. We will dive through internals of a database, explore some choices and towards the end also explore some real world database architectures in view of the concepts (legos) we explored earlier.
This document provides an overview of Apache Pulsar:
- It introduces Apache Pulsar and shares some stats on its adoption and contributors.
- It describes Pulsar's architecture including brokers, Zookeeper, BookKeeper, topics, and subscribers.
- It explains how Pulsar stores data across tenants, namespaces, bundles, ledgers and topics to enable features like multi-tenancy, load balancing, and geo-replication.
Pulsar Summit Asia 2022 - Streaming wars and How Apache Pulsar is acing the b...Shivji Kumar Jha
This presentation will cover why we prefer Apache Pulsar over other streaming solutions. Given the streaming requirements of near-realtime action, scalability, high availability, disaster recovery, load balancing, low cost of operations, multi-tenancy and flexibility to fit a variety of use cases, we have run kafka, kinesis and NATS Jetstream across different use cases. And we chose Apache Pulsar as our platform of choice for cloud-native messaging.
This talk presents the operational challenges we have faced running Pulsar for over 4 years and how Pulsar fit into different use cases given its multi-tenancy and configurability. We will also talk about how we have aced these challenges to stick to pulsar and even moved application from other messaging solutions to Pulsar. We will end with the challenges and learnings on moving to Pulsar from Kafka and Kinesis.
After this session, you will learn more on common messaging requirements, why you should also choose Apache Pulsar as your platform of choice and how you can safely transition to Pulsar if you have been running other messaging solutions.
Pulsar Summit Asia 2022 - Keeping on top of hybrid cloud usage with PulsarShivji Kumar Jha
This presentation will cover how we force controls on an application over a hybrid cloud infrastructure built from a combination of different clouds that could include private and public clouds. For instance, you could deploy your microservice in AWS but use BigTable as your data store.
Every cloud or on-premise infrastructure provider provides monitoring, alerting, metering, audit trail etc. In a hybrid cloud use case, the IT team needs a single view of the usage across the cloud providers. Such a platform needs to combine the data sourcing of these utilities from different infrastructure providers, parse them into a common format and build an integrated data sink. Adding to it the challenge of each data source evolving its data formats, volume, velocity, throughput, latency etc. You have a challenging task to understand data from varied sources and present it in one view.
We will present an architecture that has been battle-tested in production for over five years. The components include Pulsar, Flink, PostgreSQL, Redis, Neo4J DB, rule/ML engine etc., to name a few technologies.
After this presentation, you will learn more about
1. Combining infrastructure from multiple clouds and on-premise providers to build your application.
2. Appreciate the need for lambda architecture.
3. How to stream ever-evolving multi-schema data using pulsar
4. How to write custom rules over a stream analytics framework to make your application.
Event sourcing Live 2021: Streaming App Changes to Event StoreShivji Kumar Jha
This document discusses streaming app changes to event stores. It covers change data capture (CDC) which involves identifying, capturing, and delivering changes made to data. CDC can be done by capturing events from app code or by tailing database transaction logs. Capturing from app code provides flexibility but requires extra code, while capturing from databases is easier to control but depends on database log formats. The document also discusses using event stores for data warehouses, data lakes, CQRS patterns, and hybrid transactional/analytical processing (HTAP) databases.
Type safety is extremely important in any application built around a stream / queue. Type definition and evolution can either be built in the application or relied upon the data layer to support it out of the box allowing the application to only concentrate on business logic, not how of data store and evolution. It is this property of the good old relational databases (among others) that make them a favourite among all the modern NoSQL databases. Modern software architectures requires asynchronous communication (via stream / queue). While the data store and query design changes with asynchronous communication, type safety is still equally important.
In this slide deck, used for Apache Con 2021 talk, we will go over ways in which one can force structure (schema) over the streaming data. As an example, we will talk about Apache Pulsar. Apache pulsar offers server as well as client side support for the structured streaming. We have been using pulsar for asynchronous communication among microservices in our nutanix beam and flow security central apps for over 1.5 years in production. This deck presents the technical details on what is schema, how to represent schema, what is available in the apache pulsar server and client side, how we have used pulsar’s schema support to build our use cases and our learnings from them.
Apache Con 2021 : Apache Bookkeeper Key Value Store and use casesShivji Kumar Jha
In order to leverage the best performance characters of your data or stream backend, it is important to understand the nitty gritty details of how your backend store and compute works, how data is stored, how is it indexed and how the read path is. Understanding this empowers you to design your use case solutioning so as to make the best use of resources at hand as well as get the optimum amount of consistency, availability, latency and throughput for a given amount of resources at hand.
With this underlying philosophy, in this slide deck, we will get to the bottom of storage tier of pulsar (apache bookkeeper), the barebones of the bookkeeper storage semantics, how it is used in different use cases ( even other than pulsar), understand the object models of storage in pulsar, different kinds of data structures and algorithms pulsar uses therein and how that maps to the semantics of the storage class shipped with pulsar by default. Oh yes, you can change the storage backend too with some additional code!
The focus will be more on storage backend so as to not keep this tailored to pulsar specifically but to be able to apply it different data stores or streams.
Pulsar Summit Asia - Structured Data Stream with Apache PulsarShivji Kumar Jha
This document discusses Apache Pulsar schemas. It begins with background on Pulsar, serialization, and schema evolution. It then discusses the benefits of using schemas with Pulsar, including different schema types like primitive, JSON, and Avro schemas. It describes how Pulsar uses a schema registry to store schemas on the server side rather than client side. Key learnings are to use structured schemas like Avro to model domain objects, consider compatibility and ordering when designing topics, and manage schemas through a code review process. The document provides references for further reading on Pulsar schemas and schema evolution.
Pulsar Summit Asia - Running a secure pulsar clusterShivji Kumar Jha
This document provides an overview of securing Apache Pulsar. It discusses securing the different cluster components like Zookeeper, Bookkeeper and brokers. It describes how to enable TLS for securing communication between these components. It also covers setting up TLS, keystores and truststores for brokers and clients. The document references Pulsar and Zookeeper documentation for more details on configuring security.
Having used apache pulsar in production for an year for our pub sub use cases such as stream analytics, event sourcing etc, this slide deck presents the lesson learned per se understanding the architecture, tuning the cluster, managing to keep it highly available and fault tolerant and much more.
While the slides are presented in terms of apache pulsar, a lot of the concepts can be easily extended to a lot of distributed systems.
The views here are my own and do not represent the view of nutanix corporation.
Priyanka, a MySQL cluster developer, presented MySQL cluster in the MySQL User camp. The slide deck contains an introduction to the cluster module- the architecture,
auto-sharding, failover etc in the cluster module.
Garbage In, Garbage Out: Why poor data curation is killing your AI models (an...Zilliz
Enterprises have traditionally prioritized data quantity, assuming more is better for AI performance. However, a new reality is setting in: high-quality data, not just volume, is the key. This shift exposes a critical gap – many organizations struggle to understand their existing data and lack effective curation strategies and tools. This talk dives into these data challenges and explores the methods of automating data curation.
"Hands-on development experience using wasm Blazor", Furdak Vladyslav.pptxFwdays
I will share my personal experience of full-time development on wasm Blazor
What difficulties our team faced: life hacks with Blazor app routing, whether it is necessary to write JavaScript, which technology stack and architectural patterns we chose
What conclusions we made and what mistakes we committed
Top 12 AI Technology Trends For 2024.pdfMarrie Morris
Technology has become an irreplaceable component of our daily lives. The role of AI in technology revolutionizes our lives for the betterment of the future. In this article, we will learn about the top 12 AI technology trends for 2024.
The Challenge of Interpretability in Generative AI Models.pdfSara Kroft
Navigating the intricacies of generative AI models reveals a pressing challenge: interpretability. Our blog delves into the complexities of understanding how these advanced models make decisions, shedding light on the mechanisms behind their outputs. Explore the latest research, practical implications, and ethical considerations, as we unravel the opaque processes that drive generative AI. Join us in this insightful journey to demystify the black box of artificial intelligence.
Dive into the complexities of generative AI with our blog on interpretability. Find out why making AI models understandable is key to trust and ethical use and discover current efforts to tackle this big challenge.
The Zaitechno Handheld Raman Spectrometer is a powerful and portable tool for rapid, non-destructive chemical analysis. It utilizes Raman spectroscopy, a technique that analyzes the vibrational fingerprint of molecules to identify their chemical composition. This handheld instrument allows for on-site analysis of materials, making it ideal for a variety of applications, including:
Material identification: Identify unknown materials, minerals, and contaminants.
Quality control: Ensure the quality and consistency of raw materials and finished products.
Pharmaceutical analysis: Verify the identity and purity of pharmaceutical compounds.
Food safety testing: Detect contaminants and adulterants in food products.
Field analysis: Analyze materials in the field, such as during environmental monitoring or forensic investigations.
The Zaitechno Handheld Raman Spectrometer is easy to use and features a user-friendly interface. It is compact and lightweight, making it ideal for field applications. With its rapid analysis capabilities, the Zaitechno Handheld Raman Spectrometer can help you improve efficiency and productivity in your research or quality control workflows.
This PDF delves into the aspects of information security from a forensic perspective, focusing on privacy leaks. It provides insights into the methods and tools used in forensic investigations to uncover and mitigate privacy breaches in mobile and cloud environments.
The History of Embeddings & Multimodal EmbeddingsZilliz
Frank Liu will walk through the history of embeddings and how we got to the cool embedding models used today. He'll end with a demo on how multimodal RAG is used.
Self-Healing Test Automation Framework - HealeniumKnoldus Inc.
Revolutionize your test automation with Healenium's self-healing framework. Automate test maintenance, reduce flakes, and increase efficiency. Learn how to build a robust test automation foundation. Discover the power of self-healing tests. Transform your testing experience.
Demystifying Neural Networks And Building Cybersecurity ApplicationsPriyanka Aash
In today's rapidly evolving technological landscape, Artificial Neural Networks (ANNs) have emerged as a cornerstone of artificial intelligence, revolutionizing various fields including cybersecurity. Inspired by the intricacies of the human brain, ANNs have a rich history and a complex structure that enables them to learn and make decisions. This blog aims to unravel the mysteries of neural networks, explore their mathematical foundations, and demonstrate their practical applications, particularly in building robust malware detection systems using Convolutional Neural Networks (CNNs).