InfoTrack: Creating a single source of truth with the Elastic StackElasticsearch
Ashim Joshi, Head of Innovation at InfoTrack, will discuss how the Elasticsearch Service helped tackle a variety of uses cases at Infotrack, like building a data-lake, and architecting a data-mart layer.
See the video: https://www.elastic.co/elasticon/tour/2019/sydney/infotrack-creating-a-single-source-of-truth-with-the-elastic-stack
Logging, Metrics, and APM: The Operations TrifectaElasticsearch
Learn how Elasticsearch efficiently combines logs, metrics, and APM data in a single store and see how Kibana is used to search logs, analyze metrics, and leverage APM features for better performance monitoring and faster troubleshooting.
Building a reliable and cost effect logging system at Box Elasticsearch
See how Box used learnings from building an auditing and reporting system on Elasticsearch to address the big challenge of developing a robust and reliable logging solution with cost efficiencies in mind.
Machine Learning for Anomaly Detection, Time Series Modeling, and MoreElasticsearch
Not a data scientist? You can still use Elastic machine learning to build real-time data models. See how time series modeling streamlines anomaly detection and forecasting, and preview future features.
How KeyBank Used Elastic to Build an Enterprise Monitoring SolutionElasticsearch
KeyBank is using an iterative design approach to scale their end-to-end enterprise monitoring system with Kafka and Elasticsearch at its core. See how they did it and the lessons learned along the way.
Hunting for Evil with the Elastic StackElasticsearch
Whether you are threat hunting or responding to a signature-based alert, learn how to use Elastic tools to tell the entire story and more efficiently root out adversaries in your environment.
See the video: https://www.elastic.co/elasticon/tour/2019/washington-dc/hunting-for-evil-with-the-elastic-stack
Kibana + timelion: time series with the elastic stackSylvain Wallez
The document discusses Kibana and Timelion, which are tools for visualizing and analyzing time series data in the Elastic Stack. It provides an overview of Kibana's evolution and capabilities for creating dashboards. Timelion is introduced as a scripting language that allows users to transform, aggregate, and calculate on time series data from multiple sources to create visualizations. The document demonstrates Timelion's expression language, which includes functions, combinations, filtering, and attributes to process and render time series graphs.
Security Events Logging at Bell with the Elastic StackElasticsearch
One of Canada’s largest telecommunications company is using Elastic to drive improved security analysis in their SOC. With a need to ingest all security logs, build threat detection models, and normalize many new types of logs, the Bell security team turned to Elastic. Learn how they’ve streamlined alerts, deepened log analysis, and addressed challenges unique to being an ISP.
InfoTrack: Creating a single source of truth with the Elastic StackElasticsearch
Ashim Joshi, Head of Innovation at InfoTrack, will discuss how the Elasticsearch Service helped tackle a variety of uses cases at Infotrack, like building a data-lake, and architecting a data-mart layer.
See the video: https://www.elastic.co/elasticon/tour/2019/sydney/infotrack-creating-a-single-source-of-truth-with-the-elastic-stack
Logging, Metrics, and APM: The Operations TrifectaElasticsearch
Learn how Elasticsearch efficiently combines logs, metrics, and APM data in a single store and see how Kibana is used to search logs, analyze metrics, and leverage APM features for better performance monitoring and faster troubleshooting.
Building a reliable and cost effect logging system at Box Elasticsearch
See how Box used learnings from building an auditing and reporting system on Elasticsearch to address the big challenge of developing a robust and reliable logging solution with cost efficiencies in mind.
Machine Learning for Anomaly Detection, Time Series Modeling, and MoreElasticsearch
Not a data scientist? You can still use Elastic machine learning to build real-time data models. See how time series modeling streamlines anomaly detection and forecasting, and preview future features.
How KeyBank Used Elastic to Build an Enterprise Monitoring SolutionElasticsearch
KeyBank is using an iterative design approach to scale their end-to-end enterprise monitoring system with Kafka and Elasticsearch at its core. See how they did it and the lessons learned along the way.
Hunting for Evil with the Elastic StackElasticsearch
Whether you are threat hunting or responding to a signature-based alert, learn how to use Elastic tools to tell the entire story and more efficiently root out adversaries in your environment.
See the video: https://www.elastic.co/elasticon/tour/2019/washington-dc/hunting-for-evil-with-the-elastic-stack
Kibana + timelion: time series with the elastic stackSylvain Wallez
The document discusses Kibana and Timelion, which are tools for visualizing and analyzing time series data in the Elastic Stack. It provides an overview of Kibana's evolution and capabilities for creating dashboards. Timelion is introduced as a scripting language that allows users to transform, aggregate, and calculate on time series data from multiple sources to create visualizations. The document demonstrates Timelion's expression language, which includes functions, combinations, filtering, and attributes to process and render time series graphs.
Security Events Logging at Bell with the Elastic StackElasticsearch
One of Canada’s largest telecommunications company is using Elastic to drive improved security analysis in their SOC. With a need to ingest all security logs, build threat detection models, and normalize many new types of logs, the Bell security team turned to Elastic. Learn how they’ve streamlined alerts, deepened log analysis, and addressed challenges unique to being an ISP.
The ELK stack is an open source toolset for data analysis that includes Logstash, Elasticsearch, and Kibana. Logstash collects and parses data from various sources, Elasticsearch stores and indexes the data for fast searching and analytics, and Kibana visualizes the data. The ELK stack can handle large volumes of time-series data in real-time and provides actionable insights. Commercial plugins are also available for additional functionality like monitoring, security, and support.
Architectural Best Practices to Master + Pitfalls to Avoid (P) Elasticsearch
This document provides an overview of Elasticsearch concepts and best practices. It discusses Elasticsearch documentation, cluster sizing recommendations from 3 nodes to 100s of nodes, default installations, monitoring capabilities, auto-generated mappings, template structures, dynamic settings, dedicated node types, shard sizing between 15-50GB, specific cluster sizing tools, indexing operations like rollover and split, search optimizations, and considerations for multi-cluster architectures. Customer stories from Elastic Support are recommended to learn lessons from real-world use cases.
- Elastic provides a search and analytics platform called the Elastic Stack that includes the Elastic Stack, Beats data shippers, and Kibana analytics and visualization tools.
- The presentation discussed updates to Elastic's products including performance improvements to search, new features for distributed search across data centers, and enhanced security options for authentication and authorization.
- Elastic aims to provide customizable and extensible solutions for users to ingest, store, search, analyze and visualize large volumes of data from various sources.
The document summarizes the new features and improvements in Elastic Stack v5.0.0, including updates to Kibana, Elasticsearch, Logstash, and Beats. Key highlights include a redesigned Kibana interface, improved indexing performance in Elasticsearch, easier plugin development in Logstash, new data shippers and filtering capabilities in Beats, and expanded subscription support offerings. The Elastic Stack aims to help users build distributed applications and solve real problems through its integrated search, analytics, and data pipeline capabilities.
Logging, Metrics, and APM: The Operations Trifecta (P)Elasticsearch
Take your operational visibility to the next level by bringing your logs, metrics, and now APM data under one roof. Learn how Elasticsearch efficiently combines these types of data in a single store and see how Kibana is used to search logs, analyze metrics, and leverage APM features for better performance monitoring and faster troubleshooting.
Keeping Up with the ELK Stack: Elasticsearch, Kibana, Beats, and LogstashAmazon Web Services
Version 7 of the Elastic Stack adds powerful new features to the popular open source platform for search, logging, and analytics. Come hear directly from Elastic engineers and architecture team members on powerful new additions like GIS functionality and frozen-tier search. Plus, hear about the full range of orchestration options for getting the most out of your deployments, however and wherever you choose to run them. This session is sponsored by Elastic.
Elastic at Procter & Gamble: A Network StoryElasticsearch
Learn how the Elastic Stack helped Procter & Gamble achieve a greater understanding of their data, as well as introducing observability to their toolkit to help them be more proactive and provide better services.
Replicate Elasticsearch Data with Cross-Cluster Replication (CCR)Elasticsearch
Launched in Elasticsearch version 6.5, cross-cluster replication (CCR) allows you to replicate an index from one Elasticsearch cluster to another. CCR is perfect for a number of use cases including cross data center replication, data locality (multiple copies of data closer to users), and creating a dedicated, centralized analytics cluster populated by multiple source clusters.
The document discusses Samsung ARTIK Cloud, an open data exchange platform for the Internet of Things (IoT). It allows users to easily create and connect IoT devices, collect and massage device data, and build new services and applications. The platform represents things in the cloud, facilitates interoperability across devices and clouds, and enables data to be transformed and accessed through APIs and SDKs. It also ensures user privacy by allowing users to control and grant access to their own data.
Combinación de logs, métricas y seguimiento para una visibilidad centralizadaElasticsearch
Descubre cómo Elasticsearch combina de forma eficiente los datos en un solo almacén y cómo los usa Kibana para analizarlos. Además, podrás comprobar la forma en la que los desarrollos más recientes facilitan la tarea de identificación, solución de problemas y resolución de incidencias operativas con mayor rapidez.
Video in french at https://www.youtube.com/watch?v=9LNnNh63rBI
Sizing an Elasticsearch cluster has to consider many dimensions. In this presentation we go through the different elements and features you should consider to handle big and varying loads of log data.
Bigger Faster Easier: LinkedIn Hadoop Summit 2015Shirshanka Das
We discuss LinkedIn's big data ecosystem and its evolution through the years. We introduce three open source projects, Gobblin for ingestion, Cubert for computation and Pinot for fast OLAP serving. We also showcase our in-house data discovery and lineage portal WhereHows.
This document discusses the partnership between Elastic and Microsoft Azure and highlights several products and services:
1. Elastic provides solutions for logs, metrics, application performance monitoring, uptime monitoring, security information and event management, and endpoints on the Elastic Stack that can be deployed on Azure in various ways.
2. The Elasticsearch Service on Azure is highlighted as the best way to deploy Elasticsearch, Kibana, and Elastic solutions on Azure with benefits like being hosted, secure, compliant, and always up-to-date.
3. Elastic Observability for Azure provides out-of-the-box support for Azure logs and metrics with integration for Azure Monitor and pre-built Kibana dashboards.
Leveraging Apache Spark and Delta Lake for Efficient Data Encryption at ScaleDatabricks
The increase in consumer data privacy laws brings continuing challenges to data teams all over the world which collect, store, and use data protected by these laws. The data engineering team at Mars Petcare is no exception, and in order to improve efficiency and accuracy in responding to these challenges they have built Gecko: an efficient, auditable, and simple CCPA compliance ecosystem designed for Spark and Delta Lake.
How to teach your data scientist to leverage an analytics cluster with Presto...Alluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
How to teach your data scientist to leverage an analytics cluster with Presto, Spark, and Alluxio
Katarzyna Orzechowska, Data Scientist (ING Tech)
Mariusz Derela, DevOps Engineer (ING Tech)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Nine Publishing: Building a modern infrastructure with the Elastic StackElasticsearch
Michael Lorant is a Principal Systems Engineer for Nine and is responsible for the infrastructure running some of the largest news publications in Australia. Michael has spent the last 5 years specialising in cloud infrastructure and has gained in-depth experience in the areas of containerisation and Kubernetes at scale.
See the video: https://www.elastic.co/elasticon/tour/2019/sydney/nine-publishing-building-a-modern-infrastructure-with-the-elastic-stack
Monitoring docker, k8s and your applications with the elastic stackSmartWave
This document discusses using the Elastic Stack, specifically Beats, to monitor Docker, Kubernetes, and applications. It provides an overview of the Beats family of lightweight data shippers, including Filebeat, Metricbeat, Packetbeat, Heartbeat, and Auditbeat. It then discusses how Metricbeat and metadata processors can be used to monitor Docker and Kubernetes by enriching events with metadata. It also covers autodiscover functionality where Metricbeat can dynamically start and stop modules based on Docker events. Lastly, it discusses different deployment strategies for the Elastic Stack with Docker and Kubernetes.
Extracting Value from IOT using Azure Cosmos DB, Azure Synapse Analytics and ...HostedbyConfluent
Due to explosion of IoT, we have streaming data that needs to be processed in real-time. This needs to be made available for applications as well as analytics scenarios such as anomaly detection. This workshop presents a solution using Confluent Cloud on Azure, Azure Cosmos DB and Azure Synapse Analytics which can be connected in a secure way within Azure VNET using Azure Private link configured on Kafka clusters.
Managing your Black Friday Logs - Antonio Bonuccelli - Codemotion Rome 2018Codemotion
Monitoring an entire application is not a simple task, but with the right tools it is not a hard task either. However, events like Black Friday can push your application to the limit, and even cause crashes. As the system is stressed, it generates a lot more logs, which may crash the monitoring system as well. In this talk I will walk through the best practices when using the Elastic Stack to centralize and monitor your logs. I will also share some tricks to help you with the huge increase of traffic typical in Black Fridays.
Scaling ingest pipelines with high performance computing principles - Rajiv K...SignalFx
By Rajiv Kurian, software engineer at SignalFx.
At SignalFx, we deal with high-volume high-resolution data from our users. This requires a high performance ingest pipeline. Over time we’ve found that we needed to adapt architectural principles from specialized fields such as HPC to get beyond performance plateaus encountered with more generic approaches. Some key examples include:
* Write very simple single threaded code, instead of complex algorithms
* Parallelize by running multiple copies of simple single threaded code, instead of using concurrent algorithms
* Separate the data plane from the control plane, instead of slowing data for control
* Write compact, array-based data structures with minimal indirection, instead of pointer-based data structures and uncontrolled allocation
The ELK stack is an open source toolset for data analysis that includes Logstash, Elasticsearch, and Kibana. Logstash collects and parses data from various sources, Elasticsearch stores and indexes the data for fast searching and analytics, and Kibana visualizes the data. The ELK stack can handle large volumes of time-series data in real-time and provides actionable insights. Commercial plugins are also available for additional functionality like monitoring, security, and support.
Architectural Best Practices to Master + Pitfalls to Avoid (P) Elasticsearch
This document provides an overview of Elasticsearch concepts and best practices. It discusses Elasticsearch documentation, cluster sizing recommendations from 3 nodes to 100s of nodes, default installations, monitoring capabilities, auto-generated mappings, template structures, dynamic settings, dedicated node types, shard sizing between 15-50GB, specific cluster sizing tools, indexing operations like rollover and split, search optimizations, and considerations for multi-cluster architectures. Customer stories from Elastic Support are recommended to learn lessons from real-world use cases.
- Elastic provides a search and analytics platform called the Elastic Stack that includes the Elastic Stack, Beats data shippers, and Kibana analytics and visualization tools.
- The presentation discussed updates to Elastic's products including performance improvements to search, new features for distributed search across data centers, and enhanced security options for authentication and authorization.
- Elastic aims to provide customizable and extensible solutions for users to ingest, store, search, analyze and visualize large volumes of data from various sources.
The document summarizes the new features and improvements in Elastic Stack v5.0.0, including updates to Kibana, Elasticsearch, Logstash, and Beats. Key highlights include a redesigned Kibana interface, improved indexing performance in Elasticsearch, easier plugin development in Logstash, new data shippers and filtering capabilities in Beats, and expanded subscription support offerings. The Elastic Stack aims to help users build distributed applications and solve real problems through its integrated search, analytics, and data pipeline capabilities.
Logging, Metrics, and APM: The Operations Trifecta (P)Elasticsearch
Take your operational visibility to the next level by bringing your logs, metrics, and now APM data under one roof. Learn how Elasticsearch efficiently combines these types of data in a single store and see how Kibana is used to search logs, analyze metrics, and leverage APM features for better performance monitoring and faster troubleshooting.
Keeping Up with the ELK Stack: Elasticsearch, Kibana, Beats, and LogstashAmazon Web Services
Version 7 of the Elastic Stack adds powerful new features to the popular open source platform for search, logging, and analytics. Come hear directly from Elastic engineers and architecture team members on powerful new additions like GIS functionality and frozen-tier search. Plus, hear about the full range of orchestration options for getting the most out of your deployments, however and wherever you choose to run them. This session is sponsored by Elastic.
Elastic at Procter & Gamble: A Network StoryElasticsearch
Learn how the Elastic Stack helped Procter & Gamble achieve a greater understanding of their data, as well as introducing observability to their toolkit to help them be more proactive and provide better services.
Replicate Elasticsearch Data with Cross-Cluster Replication (CCR)Elasticsearch
Launched in Elasticsearch version 6.5, cross-cluster replication (CCR) allows you to replicate an index from one Elasticsearch cluster to another. CCR is perfect for a number of use cases including cross data center replication, data locality (multiple copies of data closer to users), and creating a dedicated, centralized analytics cluster populated by multiple source clusters.
The document discusses Samsung ARTIK Cloud, an open data exchange platform for the Internet of Things (IoT). It allows users to easily create and connect IoT devices, collect and massage device data, and build new services and applications. The platform represents things in the cloud, facilitates interoperability across devices and clouds, and enables data to be transformed and accessed through APIs and SDKs. It also ensures user privacy by allowing users to control and grant access to their own data.
Combinación de logs, métricas y seguimiento para una visibilidad centralizadaElasticsearch
Descubre cómo Elasticsearch combina de forma eficiente los datos en un solo almacén y cómo los usa Kibana para analizarlos. Además, podrás comprobar la forma en la que los desarrollos más recientes facilitan la tarea de identificación, solución de problemas y resolución de incidencias operativas con mayor rapidez.
Video in french at https://www.youtube.com/watch?v=9LNnNh63rBI
Sizing an Elasticsearch cluster has to consider many dimensions. In this presentation we go through the different elements and features you should consider to handle big and varying loads of log data.
Bigger Faster Easier: LinkedIn Hadoop Summit 2015Shirshanka Das
We discuss LinkedIn's big data ecosystem and its evolution through the years. We introduce three open source projects, Gobblin for ingestion, Cubert for computation and Pinot for fast OLAP serving. We also showcase our in-house data discovery and lineage portal WhereHows.
This document discusses the partnership between Elastic and Microsoft Azure and highlights several products and services:
1. Elastic provides solutions for logs, metrics, application performance monitoring, uptime monitoring, security information and event management, and endpoints on the Elastic Stack that can be deployed on Azure in various ways.
2. The Elasticsearch Service on Azure is highlighted as the best way to deploy Elasticsearch, Kibana, and Elastic solutions on Azure with benefits like being hosted, secure, compliant, and always up-to-date.
3. Elastic Observability for Azure provides out-of-the-box support for Azure logs and metrics with integration for Azure Monitor and pre-built Kibana dashboards.
Leveraging Apache Spark and Delta Lake for Efficient Data Encryption at ScaleDatabricks
The increase in consumer data privacy laws brings continuing challenges to data teams all over the world which collect, store, and use data protected by these laws. The data engineering team at Mars Petcare is no exception, and in order to improve efficiency and accuracy in responding to these challenges they have built Gecko: an efficient, auditable, and simple CCPA compliance ecosystem designed for Spark and Delta Lake.
How to teach your data scientist to leverage an analytics cluster with Presto...Alluxio, Inc.
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
How to teach your data scientist to leverage an analytics cluster with Presto, Spark, and Alluxio
Katarzyna Orzechowska, Data Scientist (ING Tech)
Mariusz Derela, DevOps Engineer (ING Tech)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Nine Publishing: Building a modern infrastructure with the Elastic StackElasticsearch
Michael Lorant is a Principal Systems Engineer for Nine and is responsible for the infrastructure running some of the largest news publications in Australia. Michael has spent the last 5 years specialising in cloud infrastructure and has gained in-depth experience in the areas of containerisation and Kubernetes at scale.
See the video: https://www.elastic.co/elasticon/tour/2019/sydney/nine-publishing-building-a-modern-infrastructure-with-the-elastic-stack
Monitoring docker, k8s and your applications with the elastic stackSmartWave
This document discusses using the Elastic Stack, specifically Beats, to monitor Docker, Kubernetes, and applications. It provides an overview of the Beats family of lightweight data shippers, including Filebeat, Metricbeat, Packetbeat, Heartbeat, and Auditbeat. It then discusses how Metricbeat and metadata processors can be used to monitor Docker and Kubernetes by enriching events with metadata. It also covers autodiscover functionality where Metricbeat can dynamically start and stop modules based on Docker events. Lastly, it discusses different deployment strategies for the Elastic Stack with Docker and Kubernetes.
Extracting Value from IOT using Azure Cosmos DB, Azure Synapse Analytics and ...HostedbyConfluent
Due to explosion of IoT, we have streaming data that needs to be processed in real-time. This needs to be made available for applications as well as analytics scenarios such as anomaly detection. This workshop presents a solution using Confluent Cloud on Azure, Azure Cosmos DB and Azure Synapse Analytics which can be connected in a secure way within Azure VNET using Azure Private link configured on Kafka clusters.
Managing your Black Friday Logs - Antonio Bonuccelli - Codemotion Rome 2018Codemotion
Monitoring an entire application is not a simple task, but with the right tools it is not a hard task either. However, events like Black Friday can push your application to the limit, and even cause crashes. As the system is stressed, it generates a lot more logs, which may crash the monitoring system as well. In this talk I will walk through the best practices when using the Elastic Stack to centralize and monitor your logs. I will also share some tricks to help you with the huge increase of traffic typical in Black Fridays.
Scaling ingest pipelines with high performance computing principles - Rajiv K...SignalFx
By Rajiv Kurian, software engineer at SignalFx.
At SignalFx, we deal with high-volume high-resolution data from our users. This requires a high performance ingest pipeline. Over time we’ve found that we needed to adapt architectural principles from specialized fields such as HPC to get beyond performance plateaus encountered with more generic approaches. Some key examples include:
* Write very simple single threaded code, instead of complex algorithms
* Parallelize by running multiple copies of simple single threaded code, instead of using concurrent algorithms
* Separate the data plane from the control plane, instead of slowing data for control
* Write compact, array-based data structures with minimal indirection, instead of pointer-based data structures and uncontrolled allocation
Data warehousing is a critical component for analysing and extracting actionable insights from your data. Amazon Redshift allows you to deploy a scalable data warehouse in a matter of minutes and starts to analyse your data right away using your existing business intelligence tools.
Dissecting Open Source Cloud Evolution: An OpenStack Case StudySalman Baset
This document discusses methods for understanding the evolution of open source cloud systems like OpenStack. It presents the authors' solution of using tracing techniques to analyze OpenStack's data and message flows for logical operations such as creating and deleting VMs. Key findings from tracing OpenStack releases include significant behavioral changes between releases, hundreds of database queries and AMQP messages required for operations, and the involvement of components like Keystone, Glance, Nova, and Neutron. The authors propose using their techniques to inject faults and build a knowledge base to aid future problem diagnosis.
POLARDB: A database architecture for the cloudoysteing
PolarDB is a cloud-native database architecture developed by Alibaba for scalability, high availability, and integration with cloud services. It separates storage and computation to allow independent scaling. The storage component, PolarStore, is optimized for emerging hardware like NVMe and RDMA. It provides a distributed file system called PolarFS for low latency shared storage. PolarDB also supports read/write separation, parallel query processing, and hybrid transaction/analytical processing for high performance.
Descubre las características disponibles con demostraciones: la replicación entre clústeres, los índices bloqueados de Elasticsearch, los espacios de Kibana y los datos de integraciones en Beats y Logstash.
This document provides an introduction and overview of common methods for processing and analyzing next generation sequencing (NGS) data, including mapping NGS reads and de novo assembly of NGS reads. It discusses various NGS applications such as RNA-Seq, epigenetics, structural variation detection, and metagenomics. Key steps in read alignment such as choosing an alignment program and viewing alignments are outlined. Considerations for choosing an alignment program based on library type, read type, and platform are also reviewed. Popular alignment programs including Bowtie, BWA, TopHat, and Novoalign are mentioned.
POLARDB: A database architecture for the cloudoysteing
PolarDB is a cloud-native database architecture designed for the cloud. It separates storage and computation to independently scale each and provide high availability even across availability zones without data loss. PolarDB uses a shared storage architecture with PolarStore for storage and PolarProxy for intelligent routing. PolarStore is optimized for emerging hardware like NVMe and Optane and provides low latency access. PolarDB supports dynamic scaling, physical replication for high reliability, and read/write separation for session consistency.
Datasets and tools_from_ncbi_and_elsewhere_for_microbiome_research_v_62817Ben Busby
The document outlines Ben Busby's presentation on using NCBI tools and databases for metagenomics. It discusses searching databases like PubMed and SRA using tools like EDirect, BLAST, and taxonomy. It also covers computational resources at NCBI including sequence analysis, contig generation, and the EUtilities API. Finally, it advertises upcoming NCBI hackathons for hands-on training in using NCBI bioinformatics resources and tools.
Datadog: a Real-Time Metrics Database for One Quadrillion Points/DayC4Media
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/2mAKgJi.
Ian Nowland and Joel Barciauskas talk about the challenges Datadog faces as the company has grown its real-time metrics systems that collect, process, and visualize data to the point they now handle trillions of points per day. They also talk about how the architecture has evolved, and what they are looking to in the future as they architect for a quadrillion points per day. Filmed at qconnewyork.com.
Ian Nowland is the VP Engineering Metrics and Alerting at Datadog. Joel Barciauskas currently leads Datadog's distribution metrics team, providing accurate, low latency percentile measures for customers across their infrastructure.
MySQL Cluster Carrier Grade Edition is a real-time database designed for the telecom industry that provides the flexibility of a relational database with the cost savings of open source. It is suited for large carriers and operators and uses a distributed, synchronous storage architecture with automated failover capability. It offers high performance, scalability and availability across geographies through asynchronous data replication between clusters.
Descubre las mas recientes y futuras características del Stack: gestión del ciclo de vida de los datos para arquitecturas hot/warm/cold con DataStreams, mejoras en uso de memoria y disco, mejoras en el enrutado de las consultas; Analítica de datos multi lenguaje con query cDSL, SQL, KQL, PromQL y EQL; el nuevo sistema de Alertas y Acciones.
Scale confidently. From laptop to lots of nodes to multi-cluster, multi-use case deployments, Elastic experts are sharing best practices to master and pitfalls to avoid when it comes to scaling Elasticsearch.
'Scalable Logging and Analytics with LogStash'Cloud Elements
Rich Viet, Principal Engineer at Cloud Elements presents 'Scalable Logging and Analytics with LogStash' at All Things API meetup in Denver, CO.
Learn more about scalable logging and analytics using LogStash. This will be an overview of logstash components, including getting started, indexing, storing and getting information from logs.
Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching).
CouchDB at its Core: Global Data Storage and Rich Incremental Indexing at Clo...StampedeCon
At the StampedeCon 2013 Big Data conference in St. Louis, Adam Kocoloski, CoFounder & CTO of Cloudant, CouchDB Expert, discussed CouchDB at its Core: Global Data Storage and Rich Incremental Indexing at Cloudant - StampedeCon 2013. Cloudant operates database clusters comprising 100+ nodes based on BigCouch, the company’s fork of CouchDB. Key elements of CouchDB’s design have proven instrumental to success at this scale, including version histories, append-only storage, and multi-master replication. In this talk, Cloudant CoFounder and Apache CouchDB Committer Adam Kocoloski will discuss lessons learned from running production CouchDB clusters bigger than many wellpublicized Hadoop deployments, and how Cloudant’s experience at scale is informing development work on the next release of Apache CouchDB.
This document provides an overview of the ELK stack architecture and its components. It discusses Elasticsearch for search and analytics, Logstash for data processing, and Kibana for data visualization. Beats are lightweight data shippers that send data from sources to Logstash or Elasticsearch. The document then focuses on Logstash, explaining that it ingests data from various sources, transforms it through filters like grok and mutate, and outputs it to destinations like Elasticsearch. It provides examples of Logstash configuration with Beats as the input, grok and lowercase filters, and Elasticsearch as the output.
Apache Carbondata: An Indexed Columnar File Format for Interactive Query with...Spark Summit
Realtime analytics over large datasets has become an increasing wide-spread demand, over the past several years, Hadoop ecosystem has been continuously evolving, even complex queries over large datasets can be realized in an interactive fashion with distributed processing framework like Apache Spark, new paradigm of efficient storage were introduced as well to facilitate data processing framework, such as Apache Parquet, ORC provide fast scan over columnar data format, and Apache Hbase offers fast ingest and millisecond scale random access.
In this talk, we will outline Apache Carbondata, a new addition to open source Hadoop ecosystem which is an indexed columnar file format aimed for bridging the gap to fully enable real-time analytics abilities. It has been deeply integrated with Spark SQL and enables dramatic acceleration of query processing by leveraging efficient encoding/compression and effective predicate push down through Carbondata’s multi-level index technique.
KSQL is an open-source streaming SQL engine for Apache Kafka. It allows users to easily interact with and analyze streaming data in Kafka using SQL-like queries. KSQL builds upon Kafka Streams to provide stream processing capabilities with exactly-once processing semantics. It aims to expand access to stream processing beyond coding by providing an interactive SQL interface for tasks like streaming ETL, anomaly detection, real-time monitoring, and simple topic transformations. KSQL can be run in standalone, client-server, or application deployment modes.
Similar to What’s Evolving in the Elastic Stack (20)
An introduction to Elasticsearch's advanced relevance ranking toolboxElasticsearch
The hallmark of a great search experience is always delivering the most relevant results, quickly, to every user. The difficulty lies behind the scenes in making that happen elegantly and at a scale. From App Search’s intuitive drag and drop interface to the advanced relevance capabilities built into the core of Elasticsearch — Elastic offers a range of tools for developers to tune relevance ranking and create incredible search experiences. In this session, we’ll explore some of Elasticsearch’s advanced relevance ranking features, such as dense vector fields, BM25F, ranking evaluation, and more. Plus we’ll give you some ideas for how these features are being used by other Elastic users to create world-class, category defining search experiences.
Eze Castle Integration is a managed service provider (MSP), cloud service provider (CSP), and internet service provider (ISP) that delivers services to more than 1,000 clients around the world. Different departments within Eze Castle have devised their own log aggregation solutions in order to provide visibility, meet regulatory compliance requirements, conduct cybersecurity investigations, and help engineers with troubleshooting infrastructure issues. In 2019, they partnered with Elastic to consolidate the data generated from different systems into a single pane of glass. And thanks to the ease of deployment on Elastic Cloud, professional consultation services from Elastic engineers, and on-demand training courses available on Elastic Learning, Eze Castle was able to go from proof-of-concept to a fully functioning ""Eze Managed SIEM"" product within a month!
Learn about Eze Castle's journey with Elastic and how they grew Eze Managed SIEM from zero to 100 customers In less than 14 months.
Cómo crear excelentes experiencias de búsqueda en sitios webElasticsearch
Descubre lo fácil que es crear búsquedas relevantes y enriquecidas en sitios web de cara al público para impulsar las conversiones, incrementar el consumo de contenido y ayudar a los visitantes a encontrar lo que necesitan. Realiza un recorrido por las herramientas de Elastic a las que puedes sacar partido para transformar con facilidad tu sitio web, lo que incluye nuestro nuevo y potente rastreador web.
Te damos la bienvenida a una nueva forma de realizar búsquedas Elasticsearch
1) The document introduces ElasticON Solution Series, which provides out-of-the-box personalized, centralized, and secure organizational search across internal and external sources.
2) It discusses how Elastic Enterprise Search can improve productivity, satisfaction, collaboration, and decision making by connecting all applications and content with a single scalable search platform.
3) The solution achieves this through intuitive search features, powerful analytics and visualization tools, simplified administration, and security certifications to ensure data protection.
Tirez pleinement parti d'Elastic grâce à Elastic CloudElasticsearch
Découvrez pourquoi Elastic Cloud est la solution idéale pour exploiter toutes les offres d'Elastic. Bénéficiez d'une flexibilité d'achat et de déploiement au sein de Google Cloud, de Microsoft Azure, d'Amazon Web Services ou des trois à la fois. Apprenez quels avantages vous apporte une offre de service géré et déterminez la solution qui vous permet de la gérer par vous-même grâce à des outils intégrés d'automatisation et d'orchestration. Et ce n'est pas tout ! Familiarisez-vous avec les fonctionnalités qui peuvent vous aider à scaler vos opérations au fur et à mesure de l'évolution de votre déploiement, à stocker vos données d'une manière rentable et à optimiser vos recherches. Ainsi, vous n'aurez plus à abandonner de données et obtiendrez les informations exploitables dont vous avez besoin pour assurer le fonctionnement de votre entreprise.
Comment transformer vos données en informations exploitablesElasticsearch
Découvrez des fonctionnalités stratégiques de la Suite Elastic, notamment Elasticsearch, un moteur de données incomparable, et Kibana, véritable fenêtre ouverte sur la Suite Elastic.
Dans cette session, vous apprendrez à :
injecter des données dans la Suite Elastic ;
stocker des données ;
analyser des données ;
exploiter des données.
Plongez au cœur de la recherche dans tous ses états.Elasticsearch
À l'instar de la plupart des entreprises modernes, vos équipes utilisent probablement plus de 10 applications hébergées dans le cloud chaque jour, mais passent aussi bien trop de temps à chercher les informations dont elles ont besoin dans ces outils. Grâce aux fonctionnalités prêtes à l'emploi d'Elastic Workplace Search, découvrez combien il est facile de mettre le contenu pertinent à portée de la main de vos équipes grâce à une recherche unifiée sur l'ensemble des applications qu'elles utilisent pour faire leur travail.
Modernising One Legal Se@rch with Elastic Enterprise Search [Customer Story]Elasticsearch
Knowledge management needs in the legal sector, why Linklaters decided to move away from its legacy KM search engine, Kin+Carta's management of the migration process, and how the switch revitalised a well-established system and opened up new possibilities for its future development.
An introduction to Elasticsearch's advanced relevance ranking toolboxElasticsearch
The hallmark of a great search experience is always delivering the most relevant results, quickly, to every user. The difficulty lies behind the scenes in making that happen elegantly and at a scale. From App Search’s intuitive drag and drop interface to the advanced relevance capabilities built into the core of Elasticsearch — Elastic offers a range of tools for developers to tune relevance ranking and create incredible search experiences. In this session, we’ll explore some of Elasticsearch’s advanced relevance ranking features, such as dense vector fields, BM25F, ranking evaluation, and more. Plus we’ll give you some ideas for how these features are being used by other Elastic users to create world-class, category defining search experiences.
Like most modern organizations, your teams are likely using upwards of 10 cloud-based applications on a daily basis, but spending far too many hours a day searching for the information they need across all of them. With the out-of-the-box capabilities of Elastic Workplace Search, see how easy it is to put relevant content right at your teams’ fingertips with unified search across all the apps they rely on to get work done.
Building great website search experiencesElasticsearch
Discover how easy it is to create rich, relevant search on public facing websites that drives conversion, increases content consumption, and helps visitors find what they need. Get a tour of the Elastic tools you can leverage to easily transform your website, including our powerful new web crawler.
Keynote: Harnessing the power of Elasticsearch for simplified searchElasticsearch
Get an overview of the innovation Elastic is bringing to the Enterprise Search landscape, and learn how you can harness these capabilities across your technology landscape to make the power of search work for you.
Cómo transformar los datos en análisis con los que tomar decisionesElasticsearch
Descubre las áreas de características estratégicas de Elastic Stack: Elasticsearch, un motor de datos inigualable y Kibana, la ventana que da acceso a Elastic Stack.
En la sesión hablaremos sobre:
Cómo incorporar datos a Elastic Stack
Almacenamiento de datos
Análisis de los datos
Actuar en función de los datos
Explore relève les défis Big Data avec Elastic Cloud Elasticsearch
Spécialisée dans le développement et la gestion de solutions de veille documentaire et commerciale, Explore offre à ses clients une lecture précise et organisée de l’actualités des marchés et projets sur leurs territoires d'intervention. Afin de rendre leur offre plus agile et performante, Explore a choisi l’offre Elastic Cloud hébergée sur Microsoft Azure. Découvrez comment les équipes de production et de développement sont désormais en mesure de mieux exploiter les données pour les clients d’Explore et gagnent du temps sur la gestion de leur infrastructure.
Comment transformer vos données en informations exploitablesElasticsearch
Découvrez des fonctionnalités stratégiques de la Suite Elastic, notamment Elasticsearch, un moteur de données incomparable, et Kibana, véritable fenêtre ouverte sur la Suite Elastic.
Dans cette session, vous apprendrez à :
injecter des données dans la Suite Elastic ;
stocker des données ;
analyser des données ;
exploiter des données.
Transforming data into actionable insightsElasticsearch
Learn about the strategic feature areas of the Elastic Stack—Elasticsearch, a data engine like no other, and Kibana, the window into the Elastic Stack.
The session will cover:
Bringing data into the Elastic Stack
Storing data
Analyzing data
Acting on data
"Elastic enables the world’s leading organization to exceed their business objectives and power their mission-critical systems by eliminating data silos, connecting the dots, and transforming data of all types into actionable insights.
Come learn how the power of search can help you quickly surface relevant insights at scale. Whether you are an executive looking to reduce operational costs, a department head striving to do more with fewer tools, or engineer monitoring and protecting your IT environment, this session is for you. "
Empowering agencies using Elastic as a Service inside GovernmentElasticsearch
It has now been four years since the beta release of Elastic Cloud Enterprise which kicked off a wave of the Elastic public sector community running Elastic as a service within Government rather than utilizing purely hosted solutions. Fast forward to 2021 and we have multiple options for multiple mission needs. Learn top tips from Elastic architects and their experience enabling their teams with the automation and provisioning of Elastic tech to change the game in how government delivers solutions.
The opportunities and challenges of data for public goodElasticsearch
The document discusses data for public good and the opportunities and challenges involved. It notes that data infrastructure is needed to deliver public good through data. There are almost endless opportunities to use data for public services, policy, and citizen benefits. However, challenges include legacy systems, data silos, unclear governance, and risk aversion. As a case study, it outlines how the UK Census 2021 addressed index faced challenges but showed progress on using data better, with lessons for continued public sector transformation.
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...Fwdays
Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...DanBrown980551
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
13. Auditbeat
File Integrity Monitoring and Linux Kernel Auditing
• Watches for file changes on Linux, macOS, Windows
• Detects short lived processes and connections
• Indexes directly into Elasticsearch
• Correlates kernel audit events
• Resolves user IDs to user names
30. Data Rollups
Flexible bucketing and filtering by time, histograms, and terms
prod-1.myco.com
prod-2.myco.com
prod-3.myco.com
prod-4.myco.com
prod-5.myco.com
Date Histogram Histogram Terms
78. Frozen Indices
• For storing and searching old data
• Low heap usage
• Frozen indices opened and searched sequentially
• Replicated - no data loss
Trade disk storage for search latency