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In the “Sharing is caring” spirit, we came up with a series of internal talks called, By Showmaxers, for Showmaxers, and we recently started making them public. There are already talks about Networks, and Android app building, available. Our latest talk focuses on PostgreSQL Terminology, and is led by Angus Dippenaar. He worked on Showmax projects from South Africa, and moved to work with us in Prague, Czech Republic. The talk was meant to fill some holes in our knowledge of PostgreSQL. So, it guides you through the basic PostgreSQL terminology you need to understand when reading the official documentation and blogs. You may learn what all these POstgreSQL terms mean: Command, query, local or global object, non-schema local objects, relation, tablespace, database, database cluster, instance and its processes like postmaster or backend; session, connection, heap, file segment, table, TOAST, tuple, view, materialized (view), transaction, commit, rollback, index, write-ahead log, WAL record, WAL file, checkpoint, Multi-version concurrency control (MVCC), dead tuples (dead rows), or transaction exhaustion. The terminology is followed by a demonstration of transaction exhaustion. Get the complete explanation and see the demonstration of the transaction exhaustion and of tuple freezing in the talk on YouTube: https://youtu.be/E-RkI3Ws7gM.
PostgreSQL Terminology
PostgreSQL Terminology
Showmax Engineering
Analyzing sessions can bring a lot of useful feedback about what works and what does not. But implementing them is not easy because of data issues and operational costs that you will meet sooner or later. In this talk I will present 2 approaches to compute sessions with Apache Spark and AWS services. The first one will use batch and therefore, Spark SQL, whereas the second streaming and Structured Streaming module. During the talk I will cover different problems you may encounter when creating sessions, like late data, incomplete dataset, duplicated data, reprocessing or fault-tolerance aspects. I will try to solve them and show how Apache Spark features and AWS services (EMR, S3) can help to do that. After the talk you should be aware of the problems you may encounter with session pipelines and understand how to address them with Apache Spark features like watermarks, state store, checkpoints and how to integrate your code with a cloud provider.
Using Apache Spark to Solve Sessionization Problem in Batch and Streaming
Using Apache Spark to Solve Sessionization Problem in Batch and Streaming
Databricks
Speaker: Alexander Kukushkin Kubernetes is a solid leader among different cloud orchestration engines and its adoption rate is growing on a daily basis. Naturally people want to run both their applications and databases on the same infrastructure. There are a lot of ways to deploy and run PostgreSQL on Kubernetes, but most of them are not cloud-native. Around one year ago Zalando started to run HA setup of PostgreSQL on Kubernetes managed by Patroni. Those experiments were quite successful and produced a Helm chart for Patroni. That chart was useful, albeit a single problem: Patroni depended on Etcd, ZooKeeper or Consul. Few people look forward to deploy two applications instead of one and support them later on. In this talk I would like to introduce Kubernetes-native Patroni. I will explain how Patroni uses Kubernetes API to run a leader election and store the cluster state. I’m going to live-demo a deployment of HA PostgreSQL cluster on Minikube and share our own experience of running more than 130 clusters on Kubernetes. Patroni is a Python open-source project developed by Zalando in cooperation with other contributors on GitHub: https://github.com/zalando/patroni
PGConf APAC 2018 - Patroni: Kubernetes-native PostgreSQL companion
PGConf APAC 2018 - Patroni: Kubernetes-native PostgreSQL companion
PGConf APAC
Dry notes on our Sessionization implementation
Sessionization with Spark streaming
Sessionization with Spark streaming
Ramūnas Urbonas
Slides from Highload 2015 (Moscow, Russia).
Deep dive into PostgreSQL statistics.
Deep dive into PostgreSQL statistics.
Alexey Lesovsky
Jim Salter Openoid - System Administrator / Author Monday, Oct 19th 11:25 am - Operations
Move Over, Rsync
Move Over, Rsync
All Things Open
InfluxDB IOx Tech Talks: Intro to the InfluxDB IOx Read Buffer - A Read-Optimized In-Memory Query Execution Engine
InfluxDB IOx Tech Talks: Intro to the InfluxDB IOx Read Buffer - A Read-Optim...
InfluxDB IOx Tech Talks: Intro to the InfluxDB IOx Read Buffer - A Read-Optim...
InfluxData
Pgconf US 2016 slides
Deep dive into PostgreSQL statistics.
Deep dive into PostgreSQL statistics.
Alexey Lesovsky
Recommandé
In the “Sharing is caring” spirit, we came up with a series of internal talks called, By Showmaxers, for Showmaxers, and we recently started making them public. There are already talks about Networks, and Android app building, available. Our latest talk focuses on PostgreSQL Terminology, and is led by Angus Dippenaar. He worked on Showmax projects from South Africa, and moved to work with us in Prague, Czech Republic. The talk was meant to fill some holes in our knowledge of PostgreSQL. So, it guides you through the basic PostgreSQL terminology you need to understand when reading the official documentation and blogs. You may learn what all these POstgreSQL terms mean: Command, query, local or global object, non-schema local objects, relation, tablespace, database, database cluster, instance and its processes like postmaster or backend; session, connection, heap, file segment, table, TOAST, tuple, view, materialized (view), transaction, commit, rollback, index, write-ahead log, WAL record, WAL file, checkpoint, Multi-version concurrency control (MVCC), dead tuples (dead rows), or transaction exhaustion. The terminology is followed by a demonstration of transaction exhaustion. Get the complete explanation and see the demonstration of the transaction exhaustion and of tuple freezing in the talk on YouTube: https://youtu.be/E-RkI3Ws7gM.
PostgreSQL Terminology
PostgreSQL Terminology
Showmax Engineering
Analyzing sessions can bring a lot of useful feedback about what works and what does not. But implementing them is not easy because of data issues and operational costs that you will meet sooner or later. In this talk I will present 2 approaches to compute sessions with Apache Spark and AWS services. The first one will use batch and therefore, Spark SQL, whereas the second streaming and Structured Streaming module. During the talk I will cover different problems you may encounter when creating sessions, like late data, incomplete dataset, duplicated data, reprocessing or fault-tolerance aspects. I will try to solve them and show how Apache Spark features and AWS services (EMR, S3) can help to do that. After the talk you should be aware of the problems you may encounter with session pipelines and understand how to address them with Apache Spark features like watermarks, state store, checkpoints and how to integrate your code with a cloud provider.
Using Apache Spark to Solve Sessionization Problem in Batch and Streaming
Using Apache Spark to Solve Sessionization Problem in Batch and Streaming
Databricks
Speaker: Alexander Kukushkin Kubernetes is a solid leader among different cloud orchestration engines and its adoption rate is growing on a daily basis. Naturally people want to run both their applications and databases on the same infrastructure. There are a lot of ways to deploy and run PostgreSQL on Kubernetes, but most of them are not cloud-native. Around one year ago Zalando started to run HA setup of PostgreSQL on Kubernetes managed by Patroni. Those experiments were quite successful and produced a Helm chart for Patroni. That chart was useful, albeit a single problem: Patroni depended on Etcd, ZooKeeper or Consul. Few people look forward to deploy two applications instead of one and support them later on. In this talk I would like to introduce Kubernetes-native Patroni. I will explain how Patroni uses Kubernetes API to run a leader election and store the cluster state. I’m going to live-demo a deployment of HA PostgreSQL cluster on Minikube and share our own experience of running more than 130 clusters on Kubernetes. Patroni is a Python open-source project developed by Zalando in cooperation with other contributors on GitHub: https://github.com/zalando/patroni
PGConf APAC 2018 - Patroni: Kubernetes-native PostgreSQL companion
PGConf APAC 2018 - Patroni: Kubernetes-native PostgreSQL companion
PGConf APAC
Dry notes on our Sessionization implementation
Sessionization with Spark streaming
Sessionization with Spark streaming
Ramūnas Urbonas
Slides from Highload 2015 (Moscow, Russia).
Deep dive into PostgreSQL statistics.
Deep dive into PostgreSQL statistics.
Alexey Lesovsky
Jim Salter Openoid - System Administrator / Author Monday, Oct 19th 11:25 am - Operations
Move Over, Rsync
Move Over, Rsync
All Things Open
InfluxDB IOx Tech Talks: Intro to the InfluxDB IOx Read Buffer - A Read-Optimized In-Memory Query Execution Engine
InfluxDB IOx Tech Talks: Intro to the InfluxDB IOx Read Buffer - A Read-Optim...
InfluxDB IOx Tech Talks: Intro to the InfluxDB IOx Read Buffer - A Read-Optim...
InfluxData
Pgconf US 2016 slides
Deep dive into PostgreSQL statistics.
Deep dive into PostgreSQL statistics.
Alexey Lesovsky
June 24, 2014. At Velocity 2014, Fastly engineer Vladimir Vuksan gave an intro to Ganglia concepts (grid, clusters, hosts) as well as an installation of a sample monitoring grid. He also goes through the following commonly used visualization tools and how they may aid in detecting issues, identifying causes, and taking corrective action: - Cluster/Grid Views - Aggregate graphs - Compare Hosts - Custom graph functionality - Views - Interactive graphs - Trending - Nagios/Alerting system integration - How to add metrics to Ganglia - Different export formats such as JSON, CSV, and XML
Monitoring with Ganglia
Monitoring with Ganglia
Fastly
Talk for Kernel Recipes 2017 by Brendan Gregg. "Linux perf is a crucial performance analysis tool at Netflix, and is used by a self-service GUI for generating CPU flame graphs and other reports. This sounds like an easy task, however, getting perf to work properly in VM guests running Java, Node.js, containers, and other software, has been at times a challenge. This talk summarizes Linux perf, how we use it at Netflix, the various gotchas we have encountered, and a summary of advanced features."
Kernel Recipes 2017: Using Linux perf at Netflix
Kernel Recipes 2017: Using Linux perf at Netflix
Brendan Gregg
A monitoring system is arguably the most crucial system to have in place when administering and tweaking the performance of any database system. DBAs also find themselves with a variety of monitoring systems and plugins to use; ranging from small scripts in cron to complex data collection systems. In this talk, I’ll discuss how Box made a shift from the Cacti monitoring system and other various shell scripts to OpenTSDB and the changes made to our servers and daily interaction with monitoring to increase our agility in identifying and addressing changes in database behavior.
Monitoring MySQL with OpenTSDB
Monitoring MySQL with OpenTSDB
Geoffrey Anderson
Administer Apache Cassandra via JMX like a pro! Find hidden features, useful tricks and techniques to keep an eye on performance and efficiency.
Advanced Apache Cassandra Operations with JMX
Advanced Apache Cassandra Operations with JMX
zznate
Oracle database log writer I/O profiling
Profiling the logwriter and database writer
Profiling the logwriter and database writer
Kyle Hailey
How to find and eleminate performance issues with pgCenter
Troubleshooting PostgreSQL with pgCenter
Troubleshooting PostgreSQL with pgCenter
Alexey Lesovsky
setup opentsdb (based on hadoop and hbase) to collection servers' metrics collection.
opentsdb in a real enviroment
opentsdb in a real enviroment
Chen Robert
The slides I prepared for https://www.meetup.com/Paris-Apache-Kafka-Meetup/events/268164461/ about Apache Kafka integration in Apache Spark Structured Streaming.
Apache Spark Structured Streaming + Apache Kafka = ♡
Apache Spark Structured Streaming + Apache Kafka = ♡
Bartosz Konieczny
Presented by: Jonathan Creasy (Box) and Geoffrey Anderson (Box)
HBaseCon 2013: OpenTSDB at Box
HBaseCon 2013: OpenTSDB at Box
Cloudera, Inc.
Slides from Highload 2015 (Moscow, Russia).
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Deep dive into PostgreSQL statistics.
Alexey Lesovsky
Starting with the premise that "Performance is a Feature", this session will look at how to measure, what to measure and how get the best performance from your .NET code. We will look at real-world examples from the Roslyn code-base and StackOverflow (the product), including how the .NET Garbage Collector needs to be tamed!
Performance is a feature! - London .NET User Group
Performance is a feature! - London .NET User Group
Matt Warren
Learn how to customize Apache Spark through User Defined features and Spark Session extensions.
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Apache Spark in your likeness - low and high level customization
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Monitoring through Ganglia
Ganglia Monitoring Tool
Ganglia Monitoring Tool
sudhirpg
GC EASY
Am I reading GC logs Correctly?
Am I reading GC logs Correctly?
Tier1 App
This presentation introduces experimental interface to operate PostgreSQL replication protocol using the Python driver, psycopg2.
Adding replication protocol support for psycopg2
Adding replication protocol support for psycopg2
Alexander Shulgin
[Open Infrastructure & Cloud Native Days Korea 2019] 커뮤니티 버전의 OpenStack 과 Ceph를 활용하여 대고객서비스를 구축한 사례를 공유합니다. 유연성을 확보한 기업용 클라우드 서비스 구축 사례와 높은 수준의 보안을 요구하는 거래소 서비스를 구축, 운영한 사례를 소개합니다. 또한 이 프로젝트에 사용된 기술 스택 및 장애 해결사례와 최적화 방안을 소개합니다. 오픈스택은 역시 오픈소스컨설팅입니다. #openstack #ceph #openinfraday #cloudnative #opensourceconsulting
Ceph issue 해결 사례
Ceph issue 해결 사례
Open Source Consulting
Small presentation about monitoring stack performance (for example on linux) to see it`s behavior and troubleshoot operational issues.
Advanced troubleshooting linux performance
Advanced troubleshooting linux performance
Forthscale
This ppt was used by Devrim at pgDay Asia 2017. He talked about some important facts about WAL - Transaction Logs or xlogs in PostgreSQL. Some of these can really come handy on a bad day
PostgreSQL WAL for DBAs
PostgreSQL WAL for DBAs
PGConf APAC
Slides from my talk at PGConf.RU 2017 Moscow
Troubleshooting PostgreSQL Streaming Replication
Troubleshooting PostgreSQL Streaming Replication
Alexey Lesovsky
Managing PostgreSQL with PgCenter
Managing PostgreSQL with PgCenter
Managing PostgreSQL with PgCenter
Alexey Lesovsky
Hw09 Data Processing In The Enterprise
Hw09 Data Processing In The Enterprise
Cloudera, Inc.
Hw09 Hadoop Applications At Yahoo!
Hw09 Hadoop Applications At Yahoo!
Cloudera, Inc.
Contenu connexe
Tendances
June 24, 2014. At Velocity 2014, Fastly engineer Vladimir Vuksan gave an intro to Ganglia concepts (grid, clusters, hosts) as well as an installation of a sample monitoring grid. He also goes through the following commonly used visualization tools and how they may aid in detecting issues, identifying causes, and taking corrective action: - Cluster/Grid Views - Aggregate graphs - Compare Hosts - Custom graph functionality - Views - Interactive graphs - Trending - Nagios/Alerting system integration - How to add metrics to Ganglia - Different export formats such as JSON, CSV, and XML
Monitoring with Ganglia
Monitoring with Ganglia
Fastly
Talk for Kernel Recipes 2017 by Brendan Gregg. "Linux perf is a crucial performance analysis tool at Netflix, and is used by a self-service GUI for generating CPU flame graphs and other reports. This sounds like an easy task, however, getting perf to work properly in VM guests running Java, Node.js, containers, and other software, has been at times a challenge. This talk summarizes Linux perf, how we use it at Netflix, the various gotchas we have encountered, and a summary of advanced features."
Kernel Recipes 2017: Using Linux perf at Netflix
Kernel Recipes 2017: Using Linux perf at Netflix
Brendan Gregg
A monitoring system is arguably the most crucial system to have in place when administering and tweaking the performance of any database system. DBAs also find themselves with a variety of monitoring systems and plugins to use; ranging from small scripts in cron to complex data collection systems. In this talk, I’ll discuss how Box made a shift from the Cacti monitoring system and other various shell scripts to OpenTSDB and the changes made to our servers and daily interaction with monitoring to increase our agility in identifying and addressing changes in database behavior.
Monitoring MySQL with OpenTSDB
Monitoring MySQL with OpenTSDB
Geoffrey Anderson
Administer Apache Cassandra via JMX like a pro! Find hidden features, useful tricks and techniques to keep an eye on performance and efficiency.
Advanced Apache Cassandra Operations with JMX
Advanced Apache Cassandra Operations with JMX
zznate
Oracle database log writer I/O profiling
Profiling the logwriter and database writer
Profiling the logwriter and database writer
Kyle Hailey
How to find and eleminate performance issues with pgCenter
Troubleshooting PostgreSQL with pgCenter
Troubleshooting PostgreSQL with pgCenter
Alexey Lesovsky
setup opentsdb (based on hadoop and hbase) to collection servers' metrics collection.
opentsdb in a real enviroment
opentsdb in a real enviroment
Chen Robert
The slides I prepared for https://www.meetup.com/Paris-Apache-Kafka-Meetup/events/268164461/ about Apache Kafka integration in Apache Spark Structured Streaming.
Apache Spark Structured Streaming + Apache Kafka = ♡
Apache Spark Structured Streaming + Apache Kafka = ♡
Bartosz Konieczny
Presented by: Jonathan Creasy (Box) and Geoffrey Anderson (Box)
HBaseCon 2013: OpenTSDB at Box
HBaseCon 2013: OpenTSDB at Box
Cloudera, Inc.
Slides from Highload 2015 (Moscow, Russia).
Deep dive into PostgreSQL statistics.
Deep dive into PostgreSQL statistics.
Alexey Lesovsky
Starting with the premise that "Performance is a Feature", this session will look at how to measure, what to measure and how get the best performance from your .NET code. We will look at real-world examples from the Roslyn code-base and StackOverflow (the product), including how the .NET Garbage Collector needs to be tamed!
Performance is a feature! - London .NET User Group
Performance is a feature! - London .NET User Group
Matt Warren
Learn how to customize Apache Spark through User Defined features and Spark Session extensions.
Apache Spark in your likeness - low and high level customization
Apache Spark in your likeness - low and high level customization
Bartosz Konieczny
Monitoring through Ganglia
Ganglia Monitoring Tool
Ganglia Monitoring Tool
sudhirpg
GC EASY
Am I reading GC logs Correctly?
Am I reading GC logs Correctly?
Tier1 App
This presentation introduces experimental interface to operate PostgreSQL replication protocol using the Python driver, psycopg2.
Adding replication protocol support for psycopg2
Adding replication protocol support for psycopg2
Alexander Shulgin
[Open Infrastructure & Cloud Native Days Korea 2019] 커뮤니티 버전의 OpenStack 과 Ceph를 활용하여 대고객서비스를 구축한 사례를 공유합니다. 유연성을 확보한 기업용 클라우드 서비스 구축 사례와 높은 수준의 보안을 요구하는 거래소 서비스를 구축, 운영한 사례를 소개합니다. 또한 이 프로젝트에 사용된 기술 스택 및 장애 해결사례와 최적화 방안을 소개합니다. 오픈스택은 역시 오픈소스컨설팅입니다. #openstack #ceph #openinfraday #cloudnative #opensourceconsulting
Ceph issue 해결 사례
Ceph issue 해결 사례
Open Source Consulting
Small presentation about monitoring stack performance (for example on linux) to see it`s behavior and troubleshoot operational issues.
Advanced troubleshooting linux performance
Advanced troubleshooting linux performance
Forthscale
This ppt was used by Devrim at pgDay Asia 2017. He talked about some important facts about WAL - Transaction Logs or xlogs in PostgreSQL. Some of these can really come handy on a bad day
PostgreSQL WAL for DBAs
PostgreSQL WAL for DBAs
PGConf APAC
Slides from my talk at PGConf.RU 2017 Moscow
Troubleshooting PostgreSQL Streaming Replication
Troubleshooting PostgreSQL Streaming Replication
Alexey Lesovsky
Managing PostgreSQL with PgCenter
Managing PostgreSQL with PgCenter
Managing PostgreSQL with PgCenter
Alexey Lesovsky
Tendances
(20)
Monitoring with Ganglia
Monitoring with Ganglia
Kernel Recipes 2017: Using Linux perf at Netflix
Kernel Recipes 2017: Using Linux perf at Netflix
Monitoring MySQL with OpenTSDB
Monitoring MySQL with OpenTSDB
Advanced Apache Cassandra Operations with JMX
Advanced Apache Cassandra Operations with JMX
Profiling the logwriter and database writer
Profiling the logwriter and database writer
Troubleshooting PostgreSQL with pgCenter
Troubleshooting PostgreSQL with pgCenter
opentsdb in a real enviroment
opentsdb in a real enviroment
Apache Spark Structured Streaming + Apache Kafka = ♡
Apache Spark Structured Streaming + Apache Kafka = ♡
HBaseCon 2013: OpenTSDB at Box
HBaseCon 2013: OpenTSDB at Box
Deep dive into PostgreSQL statistics.
Deep dive into PostgreSQL statistics.
Performance is a feature! - London .NET User Group
Performance is a feature! - London .NET User Group
Apache Spark in your likeness - low and high level customization
Apache Spark in your likeness - low and high level customization
Ganglia Monitoring Tool
Ganglia Monitoring Tool
Am I reading GC logs Correctly?
Am I reading GC logs Correctly?
Adding replication protocol support for psycopg2
Adding replication protocol support for psycopg2
Ceph issue 해결 사례
Ceph issue 해결 사례
Advanced troubleshooting linux performance
Advanced troubleshooting linux performance
PostgreSQL WAL for DBAs
PostgreSQL WAL for DBAs
Troubleshooting PostgreSQL Streaming Replication
Troubleshooting PostgreSQL Streaming Replication
Managing PostgreSQL with PgCenter
Managing PostgreSQL with PgCenter
En vedette
Hw09 Data Processing In The Enterprise
Hw09 Data Processing In The Enterprise
Cloudera, Inc.
Hw09 Hadoop Applications At Yahoo!
Hw09 Hadoop Applications At Yahoo!
Cloudera, Inc.
Hw09 Building Data Intensive Apps A Closer Look At Trending Topics.Org
Hw09 Building Data Intensive Apps A Closer Look At Trending Topics.Org
Cloudera, Inc.
Hw09 Large Scale Transaction Analysis
Hw09 Large Scale Transaction Analysis
Cloudera, Inc.
Presented at the post-ApacheCon Hadoop meetup in Oakland on November 5th, 2009.
ZooKeeper Futures
ZooKeeper Futures
Cloudera, Inc.
Hw09 Optimizing Hadoop Deployments
Hw09 Optimizing Hadoop Deployments
Cloudera, Inc.
This webinar discusses how you can use Navigator capabilities such as Encrypt and Key Trustee to secure data and enable compliance. Additionally, we will discuss our joint work with Intel on Project Rhino (an initiative to improve data security in Hadoop). We also hear from a security architect at a financial services company that is using encryption and key management to meet financial regulatory requirements.
Comprehensive Security for the Enterprise III: Protecting Data at Rest and In...
Comprehensive Security for the Enterprise III: Protecting Data at Rest and In...
Cloudera, Inc.
En vedette
(7)
Hw09 Data Processing In The Enterprise
Hw09 Data Processing In The Enterprise
Hw09 Hadoop Applications At Yahoo!
Hw09 Hadoop Applications At Yahoo!
Hw09 Building Data Intensive Apps A Closer Look At Trending Topics.Org
Hw09 Building Data Intensive Apps A Closer Look At Trending Topics.Org
Hw09 Large Scale Transaction Analysis
Hw09 Large Scale Transaction Analysis
ZooKeeper Futures
ZooKeeper Futures
Hw09 Optimizing Hadoop Deployments
Hw09 Optimizing Hadoop Deployments
Comprehensive Security for the Enterprise III: Protecting Data at Rest and In...
Comprehensive Security for the Enterprise III: Protecting Data at Rest and In...
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This presentation was given at the Boston Django meetup on November 16, and surveyed several leading PaaS providers including Stackato, Dotcloud, OpenShift and Heroku. For each PaaS provider, I documented the steps necessary to deploy Mezzanine, a popular Django-based CMS and blogging platform. At the end of the presentation, I do a wrap-up of the different providers and provide a comparison matrix showing which providers have which features. This matrix is likely to go out-of-date quickly because these providers are adding new features all the time.
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Caching has been a 'hot' topic for a few years. But caching takes more than merely taking data and putting it in a cache : the right caching techniques can improve performance and reduce load significantly. But we'll also look at some major pitfalls, showing that caching the wrong way can bring down your site. If you're looking for a clear explanation about various caching techniques and tools like Memcached, Nginx and Varnish, as well as ways to deploy them in an efficient way, this talk is for you.
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Django deployment with PaaS
Hw09 Production Deep Dive With High Availability
Hw09 Production Deep Dive With High Availability
Eagle from eBay at China Hadoop Summit 2015
Eagle from eBay at China Hadoop Summit 2015
Planning for-high-performance-web-application
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Osd ctw spark
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Into The Box 2018 Going live with commandbox and docker
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Going live with BommandBox and docker Into The Box 2018
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FP - Découverte de Play Framework Scala
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Monitoring MySQL with DTrace/SystemTap
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DrupalCampLA 2011: Drupal backend-performance
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Deep learning - the conf br 2018
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Introduction to Stacki at Atlanta Meetup February 2016
Introduction to Stacki at Atlanta Meetup February 2016
Beyond Cookies, Persistent Storage For Web Applications Web Directions North ...
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Partner Webinar for updates and news January 25th 2022
Partner Briefing_January 25 (FINAL).pptx
Partner Briefing_January 25 (FINAL).pptx
Cloudera, Inc.
This annual program recognizes organizations who are moving swiftly towards the future and building innovative solutions by making what was impossible yesterday, possible today. The winning organizations' implementations demonstrate outstanding achievements in fulfilling their mission, technical advancement, and overall impact. The 2021 Data Impact Awards recognize organizations' achievements with the Cloudera Data Platform in seven categories: Data Lifecycle Connection Data for Enterprise AI Cloud Innovation Security & Governance Leadership People First Data for Good Industry Transformation
Cloudera Data Impact Awards 2021 - Finalists
Cloudera Data Impact Awards 2021 - Finalists
Cloudera, Inc.
Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.
2020 Cloudera Data Impact Awards Finalists
2020 Cloudera Data Impact Awards Finalists
Cloudera, Inc.
Cloudera Enterprise Data Cloud Event Vienna 1 Oct. 2019
Edc event vienna presentation 1 oct 2019
Edc event vienna presentation 1 oct 2019
Cloudera, Inc.
Cloudera Fast Forward Labs’ latest research report and prototype explore learning with limited labeled data. This capability relaxes the stringent labeled data requirement in supervised machine learning and opens up new product possibilities. It is industry invariant, addresses the labeling pain point and enables applications to be built faster and more efficiently.
Machine Learning with Limited Labeled Data 4/3/19
Machine Learning with Limited Labeled Data 4/3/19
Cloudera, Inc.
In this session, we will cover how to move beyond structured, curated reports based on known questions on known data, to an ad-hoc exploration of all data to optimize business processes and into the unknown questions on unknown data, where machine learning and statistically motivated predictive analytics are shaping business strategy.
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Cloudera, Inc.
Watch this webinar to understand how Hortonworks DataFlow (HDF) has evolved into the new Cloudera DataFlow (CDF). Learn about key capabilities that CDF delivers such as - -Powerful data ingestion powered by Apache NiFi -Edge data collection by Apache MiNiFi -IoT-scale streaming data processing with Apache Kafka -Enterprise services to offer unified security and governance from edge-to-enterprise
Introducing Cloudera DataFlow (CDF) 2.13.19
Introducing Cloudera DataFlow (CDF) 2.13.19
Cloudera, Inc.
Cloudera’s Data Science Workbench (CDSW) is available for Hortonworks Data Platform (HDP) clusters for secure, collaborative data science at scale. During this webinar, we provide an introductory tour of CDSW and a demonstration of a machine learning workflow using CDSW on HDP.
Introducing Cloudera Data Science Workbench for HDP 2.12.19
Introducing Cloudera Data Science Workbench for HDP 2.12.19
Cloudera, Inc.
Join Cloudera as we outline how we use Cloudera technology to strengthen sales engagement, minimize marketing waste, and empower line of business leaders to drive successful outcomes.
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on Azure. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Leveraging the cloud for analytics and machine learning 1.29.19
Leveraging the cloud for analytics and machine learning 1.29.19
Cloudera, Inc.
Join us to learn about the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on AWS. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Leveraging the Cloud for Big Data Analytics 12.11.18
Leveraging the Cloud for Big Data Analytics 12.11.18
Cloudera, Inc.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Modern Data Warehouse Fundamentals Part 3
Modern Data Warehouse Fundamentals Part 3
Cloudera, Inc.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Modern Data Warehouse Fundamentals Part 2
Modern Data Warehouse Fundamentals Part 2
Cloudera, Inc.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Modern Data Warehouse Fundamentals Part 1
Modern Data Warehouse Fundamentals Part 1
Cloudera, Inc.
Cloudera SDX is by no means no restricted to just the platform; it extends well beyond. In this webinar, we show you how Bardess Group’s Zero2Hero solution leverages the shared data experience to coordinate Cloudera, Trifacta, and Qlik to deliver complete customer insight.
Extending Cloudera SDX beyond the Platform
Extending Cloudera SDX beyond the Platform
Cloudera, Inc.
Join Cloudera Fast Forward Labs Research Engineer, Mike Lee Williams, to hear about their latest research report and prototype on Federated Learning. Learn more about what it is, when it’s applicable, how it works, and the current landscape of tools and libraries.
Federated Learning: ML with Privacy on the Edge 11.15.18
Federated Learning: ML with Privacy on the Edge 11.15.18
Cloudera, Inc.
451 Research Analyst Sheryl Kingstone, and Cloudera’s Steve Totman recently discussed how a growing number of organizations are replacing legacy Customer 360 systems with Customer Insights Platforms.
Analyst Webinar: Doing a 180 on Customer 360
Analyst Webinar: Doing a 180 on Customer 360
Cloudera, Inc.
In this webinar, you will learn how Cloudera and BAH riskCanvas can help you build a modern AML platform that reduces false positive rates, investigation costs, technology sprawl, and regulatory risk.
Build a modern platform for anti-money laundering 9.19.18
Build a modern platform for anti-money laundering 9.19.18
Cloudera, Inc.
How can companies integrate data science into their businesses more effectively? Watch this recorded webinar and demonstration to hear more about operationalizing data science with Cloudera Data Science Workbench on Cazena’s fully-managed cloud platform.
Introducing the data science sandbox as a service 8.30.18
Introducing the data science sandbox as a service 8.30.18
Cloudera, Inc.
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Partner Briefing_January 25 (FINAL).pptx
Partner Briefing_January 25 (FINAL).pptx
Cloudera Data Impact Awards 2021 - Finalists
Cloudera Data Impact Awards 2021 - Finalists
2020 Cloudera Data Impact Awards Finalists
2020 Cloudera Data Impact Awards Finalists
Edc event vienna presentation 1 oct 2019
Edc event vienna presentation 1 oct 2019
Machine Learning with Limited Labeled Data 4/3/19
Machine Learning with Limited Labeled Data 4/3/19
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Data Driven With the Cloudera Modern Data Warehouse 3.19.19
Introducing Cloudera DataFlow (CDF) 2.13.19
Introducing Cloudera DataFlow (CDF) 2.13.19
Introducing Cloudera Data Science Workbench for HDP 2.12.19
Introducing Cloudera Data Science Workbench for HDP 2.12.19
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19
Leveraging the cloud for analytics and machine learning 1.29.19
Leveraging the cloud for analytics and machine learning 1.29.19
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19
Leveraging the Cloud for Big Data Analytics 12.11.18
Leveraging the Cloud for Big Data Analytics 12.11.18
Modern Data Warehouse Fundamentals Part 3
Modern Data Warehouse Fundamentals Part 3
Modern Data Warehouse Fundamentals Part 2
Modern Data Warehouse Fundamentals Part 2
Modern Data Warehouse Fundamentals Part 1
Modern Data Warehouse Fundamentals Part 1
Extending Cloudera SDX beyond the Platform
Extending Cloudera SDX beyond the Platform
Federated Learning: ML with Privacy on the Edge 11.15.18
Federated Learning: ML with Privacy on the Edge 11.15.18
Analyst Webinar: Doing a 180 on Customer 360
Analyst Webinar: Doing a 180 on Customer 360
Build a modern platform for anti-money laundering 9.19.18
Build a modern platform for anti-money laundering 9.19.18
Introducing the data science sandbox as a service 8.30.18
Introducing the data science sandbox as a service 8.30.18
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Manulife - Insurer Innovation Award 2024
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Abhishek Deb(1), Mr Abdul Kalam(2) M. Des (UX) , School of Design, DIT University , Dehradun. This paper explores the future potential of AI-enabled smartphone processors, aiming to investigate the advancements, capabilities, and implications of integrating artificial intelligence (AI) into smartphone technology. The research study goals consist of evaluating the development of AI in mobile phone processors, analyzing the existing state as well as abilities of AI-enabled cpus determining future patterns as well as chances together with reviewing obstacles as well as factors to consider for more growth.
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Explore the top 10 most downloaded games on the Play Store in 2024, reflecting the latest gaming trends. As a premier game development company in India, we're committed to crafting innovative and engaging gaming experiences. Partner with us to bring your game ideas to life and captivate audiences worldwide. Visit here:- https://www.synarionit.com/game-development-company-in-india.html
Top 10 Most Downloaded Games on Play Store in 2024
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Imagine a world where information flows as swiftly as thought itself, making decision-making as fluid as the data driving it. Every moment is critical, and the right tools can significantly boost your organization’s performance. The power of real-time data automation through FME can turn this vision into reality. Aimed at professionals eager to leverage real-time data for enhanced decision-making and efficiency, this webinar will cover the essentials of real-time data and its significance. We’ll explore: FME’s role in real-time event processing, from data intake and analysis to transformation and reporting An overview of leveraging streams vs. automations FME’s impact across various industries highlighted by real-life case studies Live demonstrations on setting up FME workflows for real-time data Practical advice on getting started, best practices, and tips for effective implementation Join us to enhance your skills in real-time data automation with FME, and take your operational capabilities to the next level.
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This presentations targets students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many developer tools, platforms & APIs? This comprehensive yet still high-level overview outlines the most impactful tools for where to run your code, store & analyze your data. It will also inspire you as to what's possible. This talk is 50 minutes in length.
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wesley chun
Building Digital Trust in a Digital Economy Veronica Tan, Director - Cyber Security Agency of Singapore Apidays Singapore 2024: Connecting Customers, Business and Technology (April 17 & 18, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
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apidays
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If you are a Domino Administrator in any size company you already have a range of skills that make you an expert administrator across many platforms and technologies. In this session Gab explains how to apply those skills and that knowledge to take your career wherever you want to go.
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A Domino Admins Adventures (Engage 2024)
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I've been in the field of "Cyber Security" in its many incarnations for about 25 years. In that time I've learned some lessons, some the hard way. Here are my slides presented at BSides New Orleans in April 2024.
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With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.
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Boost PC performance: How more available memory can improve productivity
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Hw09 Monitoring Best Practices
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the $H!T out of Hadoop Developing a comprehensive open approach to monitoring hadoop clusters
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Extend for NameNode
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