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.
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.
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.
Infrastructure monitoring made easy, from ingest to insightElasticsearch
Discover how simplified data onboarding with prebuilt integrations, automated insights with alerting and machine learning, and new visual tools are streamlining the infrastructure monitoring use case.
When T-mobile launched a mobile app that delivers personalized experiences and 1:1 customer care messaging, they turned to the Elastic Stack for help monitor speed, effectiveness, and user behavior.
Elastic on a Hyper-Converged Infrastructure for Operational Log AnalyticsElasticsearch
Learn how IHG runs Elastic on a hyper-converged infrastructure, processes more than 8 TB of data every day for operational log analytics, and maintains Kibana dashboards for more than 300 applications.
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.
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.
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.
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.
Infrastructure monitoring made easy, from ingest to insightElasticsearch
Discover how simplified data onboarding with prebuilt integrations, automated insights with alerting and machine learning, and new visual tools are streamlining the infrastructure monitoring use case.
When T-mobile launched a mobile app that delivers personalized experiences and 1:1 customer care messaging, they turned to the Elastic Stack for help monitor speed, effectiveness, and user behavior.
Elastic on a Hyper-Converged Infrastructure for Operational Log AnalyticsElasticsearch
Learn how IHG runs Elastic on a hyper-converged infrastructure, processes more than 8 TB of data every day for operational log analytics, and maintains Kibana dashboards for more than 300 applications.
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.
Divide & Conquer - Logging Architecture in Distributed Ecosystems with Elasti...Elasticsearch
See how the Otto.de team built a scalable and resilient logging solution and how they’re scaling Logstash, addressing housekeeping for Elasticsearch, and collecting usage metrics for analytics and billing.
Elastic Cloud Enterprise in Azure with DevonElasticsearch
Devon Energy is a leading independent oil and natural gas exploration and production company. Hear about their journey to augment and eventually replace their legacy SIEM solution with a homegrown analytics and automation platform. See the details of moving from using on-prem open source Elasticsearch to being the first ever user to run Elastic Cloud Enterprise in Azure. Plus, learn how the team uses Elasticsearch optimizations in their security telemetry pipeline, hear about cloud native deployment models, and see how the Logstash transform functions and using Kibana as frontend for security and operational logs have helped deliver big wins.
Log Monitoring and Anomaly Detection at Scale at ORNLElasticsearch
See how Oak Ridge National Laboratory transitioned from using COTS toolset to a more cost-effective and flexible open source model by employing NiFi, Kafka, and the Elastic Stack.
Improving search at Wellcome CollectionElasticsearch
Wellcome Collection is a free museum and library challenging how we think and feel about health. See how the Elasticsearch Service is used to aggregate descriptive data and provide unified search and discovery.
See the video: https://www.elastic.co/elasticon/tour/2019/london/improving-search-at-wellcome-collection
Hear directly from the creators of the Elastic Stack on the importance of our community, the future of Elasticsearch and Kibana, new features, expanding deployment options, and the evolving solutions landscape.
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.
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
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.
Zero Latency: Building a Telemetry Platform on the Elastic StackElasticsearch
Zero Latency is focused on creating the greatest free-roam, multiplayer, virtual reality experiences in the world. Zero Latency chose the Elastic Stack for their telemetry platform to reduce performance issues. Learn how they did it.
Better Search and Business Analytics at Southern Glazer’s Wine & SpiritsElasticsearch
See how Southern Glazer’s Wine & Spirits architected their system to deliver a better search and ordering experience, plus how they centrally manage all Elasticsearch deployments on Elastic Cloud Enterprise.
Industrial production process visualization with the Elastic Stack in real-ti...Elasticsearch
Learn how the Mayr-Melnhof Group implemented production process visualization in a highly automated and fragmented industrial, process-control environment with the Elastic Stack.
Protecting Your Cluster from Your HumansElasticsearch
Discover the safeguards Kroger uses to understand how to protect your cluster, improve performance, and provide a better end user experience that enables observability at scale.
Join the creators of the Elastic Stack and Microsoft product experts to learn best practices around deployment, scaling, and security on hosted VMs and the fully managed Elasticsearch Service in this demo-heavy session.
Capgemini: Observability within the Dutch governmentElasticsearch
The digital landscape within Dutch government is a complex and heterogeneous mix of technologies. Within this scenario, Capgemini is tasked with continuous integration and maintenance of key infrastructure. The results connect major organizational parts of the country with a large volume of daily traffic. To keep the lights on in operation and allow for quick turn-around times, Elastic is the dominant choice for generating reliable insight. It facilitates a thorough insight into the inner workings of modern amalgamated java deployments, databases and legacy systems spanning a multitude of decades.
Grab: Building a Healthy Elasticsearch EcosystemElasticsearch
Grab began developing with Elasticsearch to help arrange team user access privileges. Discover how, through trial and error, Grab was able to go further to build a flexible and scalable Elasticsearch ecosystem.
Turning Evidence into Insights: How NCIS Leverages Elastic Elasticsearch
Learn how NCIS data analysis uses Elasticsearch to process evidence in the form of log files, its impact on efficient law enforcement, and some lessons learned along the way.
See the video: https://www.elastic.co/elasticon/tour/2019/washington-dc/turning-evidence-into-insights-how-ncis-leverages-elastic-
Empower Your Security Practitioners with Elastic SIEMElasticsearch
Learn how Elastic SIEM’s latest capabilities enable interactive exploration and automated analysis — all at the speed and scale your security practitioners need to defend your organization.
See the video: https://www.elastic.co/elasticon/tour/2019/washington-dc/empower-your-security-practitioners-with-elastic-siem
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.
Data Day Texas 2017: Scaling Data Science at Stitch FixStefan Krawczyk
At Stitch Fix we have a lot of Data Scientists. Around eighty at last count. One reason why I think we have so many, is that we do things differently. To get their work done, Data Scientists have access to whatever resources they need (within reason), because they’re end to end responsible for their work; they collaborate with their business partners on objectives and then prototype, iterate, productionize, monitor and debug everything and anything required to get the output desired. They’re full data-stack data scientists!
The teams in the organization do a variety of different tasks:
- Clothing recommendations for clients.
- Clothes reordering recommendations.
- Time series analysis & forecasting of inventory, client segments, etc.
- Warehouse worker path routing.
- NLP.
… and more!
They’re also quite prolific at what they do -- we are approaching 4500 job definitions at last count. So one might be wondering now, how have we enabled them to get their jobs done without getting in the way of each other?
This is where the Data Platform teams comes into play. With the goal of lowering the cognitive overhead and engineering effort required on part of the Data Scientist, the Data Platform team tries to provide abstractions and infrastructure to help the Data Scientists. The relationship is a collaborative partnership, where the Data Scientist is free to make their own decisions and thus choose they way they do their work, and the onus then falls on the Data Platform team to convince Data Scientists to use their tools; the easiest way to do that is by designing the tools well.
In regard to scaling Data Science, the Data Platform team has helped establish some patterns and infrastructure that help alleviate contention. Contention on:
Access to Data
Access to Compute Resources:
Ad-hoc compute (think prototype, iterate, workspace)
Production compute (think where things are executed once they’re needed regularly)
For the talk (and this post) I only focused on how we reduced contention on Access to Data, & Access to Ad-hoc Compute to enable Data Science to scale at Stitch Fix. With that I invite you to take a look through the slides.
Divide & Conquer - Logging Architecture in Distributed Ecosystems with Elasti...Elasticsearch
See how the Otto.de team built a scalable and resilient logging solution and how they’re scaling Logstash, addressing housekeeping for Elasticsearch, and collecting usage metrics for analytics and billing.
Elastic Cloud Enterprise in Azure with DevonElasticsearch
Devon Energy is a leading independent oil and natural gas exploration and production company. Hear about their journey to augment and eventually replace their legacy SIEM solution with a homegrown analytics and automation platform. See the details of moving from using on-prem open source Elasticsearch to being the first ever user to run Elastic Cloud Enterprise in Azure. Plus, learn how the team uses Elasticsearch optimizations in their security telemetry pipeline, hear about cloud native deployment models, and see how the Logstash transform functions and using Kibana as frontend for security and operational logs have helped deliver big wins.
Log Monitoring and Anomaly Detection at Scale at ORNLElasticsearch
See how Oak Ridge National Laboratory transitioned from using COTS toolset to a more cost-effective and flexible open source model by employing NiFi, Kafka, and the Elastic Stack.
Improving search at Wellcome CollectionElasticsearch
Wellcome Collection is a free museum and library challenging how we think and feel about health. See how the Elasticsearch Service is used to aggregate descriptive data and provide unified search and discovery.
See the video: https://www.elastic.co/elasticon/tour/2019/london/improving-search-at-wellcome-collection
Hear directly from the creators of the Elastic Stack on the importance of our community, the future of Elasticsearch and Kibana, new features, expanding deployment options, and the evolving solutions landscape.
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.
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
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.
Zero Latency: Building a Telemetry Platform on the Elastic StackElasticsearch
Zero Latency is focused on creating the greatest free-roam, multiplayer, virtual reality experiences in the world. Zero Latency chose the Elastic Stack for their telemetry platform to reduce performance issues. Learn how they did it.
Better Search and Business Analytics at Southern Glazer’s Wine & SpiritsElasticsearch
See how Southern Glazer’s Wine & Spirits architected their system to deliver a better search and ordering experience, plus how they centrally manage all Elasticsearch deployments on Elastic Cloud Enterprise.
Industrial production process visualization with the Elastic Stack in real-ti...Elasticsearch
Learn how the Mayr-Melnhof Group implemented production process visualization in a highly automated and fragmented industrial, process-control environment with the Elastic Stack.
Protecting Your Cluster from Your HumansElasticsearch
Discover the safeguards Kroger uses to understand how to protect your cluster, improve performance, and provide a better end user experience that enables observability at scale.
Join the creators of the Elastic Stack and Microsoft product experts to learn best practices around deployment, scaling, and security on hosted VMs and the fully managed Elasticsearch Service in this demo-heavy session.
Capgemini: Observability within the Dutch governmentElasticsearch
The digital landscape within Dutch government is a complex and heterogeneous mix of technologies. Within this scenario, Capgemini is tasked with continuous integration and maintenance of key infrastructure. The results connect major organizational parts of the country with a large volume of daily traffic. To keep the lights on in operation and allow for quick turn-around times, Elastic is the dominant choice for generating reliable insight. It facilitates a thorough insight into the inner workings of modern amalgamated java deployments, databases and legacy systems spanning a multitude of decades.
Grab: Building a Healthy Elasticsearch EcosystemElasticsearch
Grab began developing with Elasticsearch to help arrange team user access privileges. Discover how, through trial and error, Grab was able to go further to build a flexible and scalable Elasticsearch ecosystem.
Turning Evidence into Insights: How NCIS Leverages Elastic Elasticsearch
Learn how NCIS data analysis uses Elasticsearch to process evidence in the form of log files, its impact on efficient law enforcement, and some lessons learned along the way.
See the video: https://www.elastic.co/elasticon/tour/2019/washington-dc/turning-evidence-into-insights-how-ncis-leverages-elastic-
Empower Your Security Practitioners with Elastic SIEMElasticsearch
Learn how Elastic SIEM’s latest capabilities enable interactive exploration and automated analysis — all at the speed and scale your security practitioners need to defend your organization.
See the video: https://www.elastic.co/elasticon/tour/2019/washington-dc/empower-your-security-practitioners-with-elastic-siem
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.
Data Day Texas 2017: Scaling Data Science at Stitch FixStefan Krawczyk
At Stitch Fix we have a lot of Data Scientists. Around eighty at last count. One reason why I think we have so many, is that we do things differently. To get their work done, Data Scientists have access to whatever resources they need (within reason), because they’re end to end responsible for their work; they collaborate with their business partners on objectives and then prototype, iterate, productionize, monitor and debug everything and anything required to get the output desired. They’re full data-stack data scientists!
The teams in the organization do a variety of different tasks:
- Clothing recommendations for clients.
- Clothes reordering recommendations.
- Time series analysis & forecasting of inventory, client segments, etc.
- Warehouse worker path routing.
- NLP.
… and more!
They’re also quite prolific at what they do -- we are approaching 4500 job definitions at last count. So one might be wondering now, how have we enabled them to get their jobs done without getting in the way of each other?
This is where the Data Platform teams comes into play. With the goal of lowering the cognitive overhead and engineering effort required on part of the Data Scientist, the Data Platform team tries to provide abstractions and infrastructure to help the Data Scientists. The relationship is a collaborative partnership, where the Data Scientist is free to make their own decisions and thus choose they way they do their work, and the onus then falls on the Data Platform team to convince Data Scientists to use their tools; the easiest way to do that is by designing the tools well.
In regard to scaling Data Science, the Data Platform team has helped establish some patterns and infrastructure that help alleviate contention. Contention on:
Access to Data
Access to Compute Resources:
Ad-hoc compute (think prototype, iterate, workspace)
Production compute (think where things are executed once they’re needed regularly)
For the talk (and this post) I only focused on how we reduced contention on Access to Data, & Access to Ad-hoc Compute to enable Data Science to scale at Stitch Fix. With that I invite you to take a look through the slides.
Enterprise Data World 2018 - Building Cloud Self-Service Analytical SolutionDmitry Anoshin
This session will cover building the modern Data Warehouse by migration from the traditional DW platform into the cloud, using Amazon Redshift and Cloud ETL Matillion in order to provide Self-Service BI for the business audience. This topic will cover the technical migration path of DW with PL/SQL ETL to the Amazon Redshift via Matillion ETL, with a detailed comparison of modern ETL tools. Moreover, this talk will be focusing on working backward through the process, i.e. starting from the business audience and their needs that drive changes in the old DW. Finally, this talk will cover the idea of self-service BI, and the author will share a step-by-step plan for building an efficient self-service environment using modern BI platform Tableau.
Integrating ArchivesSpace and Archivematica at the Bentley Historical LibraryMax Eckard
Max Eckard, Lead Archivist for Digital Initiatives at the Bentley Historical Library, will cover the Bentley's integration of ArchivesSpace and Archivematica to streamline digital archiving workflows. He will highlight the decision-making process behind integrating both systems, things he wishes he’d known then that he knows now, goals for the future, and other tips and tricks. In his role at the Bentley Historical Library, Max oversees the digitization program, digital curation activities, web archives, and associated infrastructure.
Data Day Seattle 2017: Scaling Data Science at Stitch FixStefan Krawczyk
At Stitch Fix we have a lot of Data Scientists. Around eighty at last count. One reason why I think we have so many, is that we do things differently. To get their work done, Data Scientists have access to whatever resources they need (within reason), because they’re end to end responsible for their work; they collaborate with their business partners on objectives and then prototype, iterate, productionize, monitor and debug everything and anything required to get the output desired. They’re full data-stack data scientists!
The teams in the organization do a variety of different tasks:
- Clothing recommendations for clients.
- Clothes reordering recommendations.
- Time series analysis & forecasting of inventory, client segments, etc.
- Warehouse worker path routing.
- NLP.
… and more!
They’re also quite prolific at what they do -- we are approaching 4500 job definitions at last count. So one might be wondering now, how have we enabled them to get their jobs done without getting in the way of each other?
This is where the Data Platform teams comes into play. With the goal of lowering the cognitive overhead and engineering effort required on part of the Data Scientist, the Data Platform team tries to provide abstractions and infrastructure to help the Data Scientists. The relationship is a collaborative partnership, where the Data Scientist is free to make their own decisions and thus choose they way they do their work, and the onus then falls on the Data Platform team to convince Data Scientists to use their tools; the easiest way to do that is by designing the tools well.
In regard to scaling Data Science, the Data Platform team has helped establish some patterns and infrastructure that help alleviate contention. Contention on:
Access to Data
Access to Compute Resources:
Ad-hoc compute (think prototype, iterate, workspace)
Production compute (think where things are executed once they’re needed regularly)
For the talk (and this post) I only focused on how we reduced contention on Access to Data, & Access to Ad-hoc Compute to enable Data Science to scale at Stitch Fix. With that I invite you to take a look through the slides.
What Is ELK Stack | ELK Tutorial For Beginners | Elasticsearch Kibana | ELK S...Edureka!
( ELK Stack Training - https://www.edureka.co/elk-stack-trai... )
This Edureka tutorial on What Is ELK Stack will help you in understanding the fundamentals of Elasticsearch, Logstash, and Kibana together and help you in building a strong foundation in ELK Stack. Below are the topics covered in this ELK tutorial for beginners:
1. Need for Log Analysis
2. Problems with Log Analysis
3. What is ELK Stack?
4. Features of ELK Stack
5. Companies Using ELK Stack
Log aggregation: using Elasticsearch, Fluentd/Fluentbit and Kibana (EFK)Lee Myring
A quick introduction to log aggregation in a local Docker development environment using Fluentd followed by a demonstration using a publicly available GitHub repo.
How to Develop and Operate Cloud First Data PlatformsAlluxio, Inc.
Alluxio Online Meetup
Feb 11, 2020
Speakers:
Du Li, Electronic Arts
Bin Fan, Alluxio
In cloud-based software stacks, there are varying degrees of automation across different layers: infrastructure, platform, and application. The mismatch in automation often breaks balance in devops, causing ops nightmares in platforms and applications. This talk will overview two projects at Electronic Arts (EA) that address the mismatch by data orchestration: One project automatically generates configurations for all components in a large monitoring system, which reduces the daily average number of alerts from ~1000 to ~20. The other project introduces Alluxio for caching and unifying address space across ETL and analytics workloads, which substantially simplifies architecture, improves performance, and reduces ops overheads.
Disenchantment: Netflix Titus, Its Feisty Team, and DaemonsC4Media
Video and slides synchronized, mp3 and slide download available at URL https://bit.ly/2Gmuwlg.
Andrew Spyker talks about Netflix's feisty team’s work across container runtimes, scheduling & control plane, and cloud infrastructure integration. He also talks about the demons they’ve found on this journey covering operability, security, reliability and performance. Filmed at qconsf.com.
Andrew Spyker worked to mature the technology base of Netflix Container Cloud (Project Titus) within the development team. Recently, he moved into a product management role collaborating with supporting Netflix infrastructure dependencies as well as supporting new container cloud usage scenarios including user on-boarding, feature prioritization/delivery and relationship management.
Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.[2] Though used sometimes loosely partly due to a lack of formal definition, the best interpretation is that it is a large body of information that cannot be comprehended when used in small amounts only.[Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.[2] Though used sometimes loosely partly due to a lack of formal definition, the best interpretation is that it is a large body of information that cannot be comprehended when used in small amounts only.[Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.[2] Though used sometimes loosely partly due to a lack of formal definition, the best interpretation is that it is a large body of information that cannot be comprehended when used in small amounts only.[Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.[2] Though used sometimes loosely partly due to a lack of formal definition, the best interpretation is that it is a large body of information that cannot be comprehended when used in small amounts only.[Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.[2] Though used sometimes loosely partly due to a lack of formal definition, the best interpretation is that it is a large body of information that cannot be comprehended when used in small amounts only.[Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.[2] Though used sometimes loosely partly due to a lack of formal definition, the best interpretation is that it is a large body of informa
Behind the Scenes at Coolblue - Feb 2017Pat Hermens
In this talk, Pat stepped us through how we integrate with the #elasticstack here at Coolblue, using tooling like #Log4Net, #Serilog, #Seq and #Redis. Along the way, we were introduced to the role of each of these technologies, and as an added bonus, Pat demo'd how we can set some of these tools up in Docker containers in order to aid our rapid development and testing feedback cycles.
Similar to Migrating a legacy logging system: Etsy’s journey to Elastic Cloud (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
Al igual que la mayoría de las organizaciones modernas, tus equipos probablemente usan más de 10 aplicaciones basadas en la nube a diario, pero dedican demasiado tiempo a buscar la información que necesitan en todas estas. Gracias a las características integradas de Elastic Workplace Search, podrás comprobar lo sencillo que resulta poner el contenido relevante al alcance de tus equipos gracias a la búsqueda unificada para todas las aplicaciones que usan para llevar a cabo su trabajo.
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
Data is an increasingly valuable resource for delivering economic and social benefit. Heather will discuss the challenges and opportunities, and how communities at all levels of the public sector can play a part in leading the change.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
3. Etsy is the global
marketplace for
unique and
creative goods. It’s
home to a universe
of special,
extraordinary
items, from unique
handcrafted pieces
to vintage
treasures.
7. Why migrate Etsy’s
logging system? ● Etsy was migrating entirely to
Google Cloud
● Elasticsearch is a complex system
that requires specialized knowledge
(especially in a logging use case)
● Elasticsearch 2.4 old and
unmaintained (EOL date was
02/2018)
A few reasons...
8. Why migrate Etsy’s
logging system? ● Alert fatigue for the whole team
● Maintaining Elasticsearch infra is
NOT observability
● Data center shutdown
A few reasons...
9. Key considerations
Migration must not impact
developers’ day-to-day
work
Business as usual
Migration must be time
efficient (data center
shutdown)
Time
Migration must reduce
infrastructure
management from the
team
Reduce TOIL
10. Process Options
1. Move all logs to Elasticsearch
service on Elastic Cloud
2. Move only critical logs to
Elasticsearch service on Elastic
Cloud
3. Move to our Google Cloud
infrastructure using ECE (Elastic
Cloud Enterprise)
4. Move to our Google Cloud
infrastructure manually
11. Alternatives
● Splunk
● Stackdriver
● <name logging solution>
Considerations:
● Too many intrusive solutions for
developers
● We didn’t want to throw away the
Elasticsearch knowledge we built
over the year
● Not enough time to prototype and
roll out a change that big
12. Challenges
● Move stack from 2.4 to 7.x
○ Logstash 2.x can’t talk to
Elasticsearch > 6.x
○ Identify and replace
deprecated settings in
Elasticsearch
○ Learn new features
○ Deploy changes safely
● Keep two systems running in
parallel for some time
13. Migration Timeline
03/2018
Gathered cluster size
and wrote first options
draft
Prod data
migrated;
Beta testing
started!
10/2019
Users fully migrated to the
new setup
01/202012/2018
Finalized
options
Contract
signed!
03/201902/2019
Prepared
migration
plan
06/2019
Dev data
migrated
14. Migration Successes
● Met our deadline
● Elastic support and consultants are helpful
● Happy developers
● Returning teams
15. Migration Successes
● Better observability into the stack
● Easier and safer management of indices and logstash pipelines
● Create, grow and shrink clusters is way easier
● Better isolation of the stream of data
16. What we wished we knew?
● Sizing an ES cluster is an art
○ One needs to consider volume AND throughput
● Noisy neighbors
● Support SLAs are not ideal when developing
○ Initial response on SEV3 is 1 business day
● Elastic Cloud is not just an endpoint
○ We are still responsible for indices management
17. What’s next?
● Improvement on the logging pipeline
● Analyze use cases and recommend best practices in Etsy