�ݺ�ߣshows by User: VadimSolovey

�ݺ�ߣshows by User: VadimSolovey / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: VadimSolovey / Tue, 14 Jan 2020 08:17:43 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: VadimSolovey Terraform Modules Restructured /slideshow/terraform-modules-restructured-220136382/220136382 terraformmodulesrestructured-200114081743
by Amos Mahloof, DoiT International]]>
by Amos Mahloof, DoiT International]]> Tue, 14 Jan 2020 08:17:43 GMT /slideshow/terraform-modules-restructured-220136382/220136382 VadimSolovey@slideshare.net(VadimSolovey) Terraform Modules Restructured VadimSolovey by Amos Mahloof, DoiT International <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/terraformmodulesrestructured-200114081743-thumbnail.jpg?width=120&height=120&fit=bounds" /> by Amos Mahloof, DoiT International

Terraform Modules Restructured from DoiT International

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0 GAN training with Tensorflow and Tensor Cores /slideshow/gan-training-with-tensorflow-and-tensor-cores/152176707 gantrainingusingtensorcoresandtensorflow-190627101844
Training Generative Adversarial Networks is a gentle process. Recent advances in GANs research resulted in incredible results of generated images. However, training GANs still remains tricky and slow. With TensorFlow and NVidia’s new Volta architecture it is possible to reduce training time by up to 50% using simplified code.]]>
Training Generative Adversarial Networks is a gentle process. Recent advances in GANs research resulted in incredible results of generated images. However, training GANs still remains tricky and slow. With TensorFlow and NVidia’s new Volta architecture it is possible to reduce training time by up to 50% using simplified code.]]> Thu, 27 Jun 2019 10:18:44 GMT /slideshow/gan-training-with-tensorflow-and-tensor-cores/152176707 VadimSolovey@slideshare.net(VadimSolovey) GAN training with Tensorflow and Tensor Cores VadimSolovey Training Generative Adversarial Networks is a gentle process. Recent advances in GANs research resulted in incredible results of generated images. However, training GANs still remains tricky and slow. With TensorFlow and NVidia’s new Volta architecture it is possible to reduce training time by up to 50% using simplified code. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/gantrainingusingtensorcoresandtensorflow-190627101844-thumbnail.jpg?width=120&height=120&fit=bounds" /> Training Generative Adversarial Networks is a gentle process. Recent advances in GANs research resulted in incredible results of generated images. However, training GANs still remains tricky and slow. With TensorFlow and NVidia’s new Volta architecture it is possible to reduce training time by up to 50% using simplified code.

GAN training with Tensorflow and Tensor Cores from DoiT International

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0 Orchestrating Redis & K8s Operators /slideshow/orchestrating-redis-k8s-operators/106414155 k8smeetup-redisoperators-180718100601
1. Double Orchestration of Redis Enterprise cluster on Kubernetes **** In this session we'll display how we deploy a highly available database on Kubernetes. The considerations we took when deploying a stateful application, and the challenges of answering different clients' demands for different k8s environments. 2. Operators to the rescue: stateful applications made easy with operators **** Kubernetes 1.7 introduced an import feature called custom controllers. This allows you to customise your Kubernetes installation and add your own resources to be managed in the native Kubernetes manner. The session will display the operator concept and cover our journey with developing the Redis Labs operator - why we chose it and how we use it.]]>
1. Double Orchestration of Redis Enterprise cluster on Kubernetes **** In this session we'll display how we deploy a highly available database on Kubernetes. The considerations we took when deploying a stateful application, and the challenges of answering different clients' demands for different k8s environments. 2. Operators to the rescue: stateful applications made easy with operators **** Kubernetes 1.7 introduced an import feature called custom controllers. This allows you to customise your Kubernetes installation and add your own resources to be managed in the native Kubernetes manner. The session will display the operator concept and cover our journey with developing the Redis Labs operator - why we chose it and how we use it.]]> Wed, 18 Jul 2018 10:06:01 GMT /slideshow/orchestrating-redis-k8s-operators/106414155 VadimSolovey@slideshare.net(VadimSolovey) Orchestrating Redis & K8s Operators VadimSolovey 1. Double Orchestration of Redis Enterprise cluster on Kubernetes **** In this session we'll display how we deploy a highly available database on Kubernetes. The considerations we took when deploying a stateful application, and the challenges of answering different clients' demands for different k8s environments. 2. Operators to the rescue: stateful applications made easy with operators **** Kubernetes 1.7 introduced an import feature called custom controllers. This allows you to customise your Kubernetes installation and add your own resources to be managed in the native Kubernetes manner. The session will display the operator concept and cover our journey with developing the Redis Labs operator - why we chose it and how we use it. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/k8smeetup-redisoperators-180718100601-thumbnail.jpg?width=120&height=120&fit=bounds" /> 1. Double Orchestration of Redis Enterprise cluster on Kubernetes **** In this session we'll display how we deploy a highly available database on Kubernetes. The considerations we took when deploying a stateful application, and the challenges of answering different clients' demands for different k8s environments. 2. Operators to the rescue: stateful applications made easy with operators **** Kubernetes 1.7 introduced an import feature called custom controllers. This allows you to customise your Kubernetes installation and add your own resources to be managed in the native Kubernetes manner. The session will display the operator concept and cover our journey with developing the Redis Labs operator - why we chose it and how we use it.

Orchestrating Redis & K8s Operators from DoiT International

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0 K8s best practices from the field! /slideshow/k8s-best-practices-from-the-field/102706436 k8sbestpracticesfromthefield-180620111707
Learn from the dozens of large-scale deployments how to get the most out of your Kubernetes environment: - Container images optimization - Organizing namespaces - Readiness and Liveness probes - Resource requests and limits - Failing with grace - Mapping external services - Upgrading clusters with zero downtime]]>
Learn from the dozens of large-scale deployments how to get the most out of your Kubernetes environment: - Container images optimization - Organizing namespaces - Readiness and Liveness probes - Resource requests and limits - Failing with grace - Mapping external services - Upgrading clusters with zero downtime]]> Wed, 20 Jun 2018 11:17:07 GMT /slideshow/k8s-best-practices-from-the-field/102706436 VadimSolovey@slideshare.net(VadimSolovey) K8s best practices from the field! VadimSolovey Learn from the dozens of large-scale deployments how to get the most out of your Kubernetes environment: - Container images optimization - Organizing namespaces - Readiness and Liveness probes - Resource requests and limits - Failing with grace - Mapping external services - Upgrading clusters with zero downtime <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/k8sbestpracticesfromthefield-180620111707-thumbnail.jpg?width=120&height=120&fit=bounds" /> Learn from the dozens of large-scale deployments how to get the most out of your Kubernetes environment: - Container images optimization - Organizing namespaces - Readiness and Liveness probes - Resource requests and limits - Failing with grace - Mapping external services - Upgrading clusters with zero downtime

K8s best practices from the field! from DoiT International

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0 An Open-Source Platform to Connect, Manage, and Secure Microservices /slideshow/an-opensource-platform-to-connect-manage-and-secure-microservices/78619990 20170802meetup-istio-170807054153
Services are at the core of modern software architecture. Deploying a series of modular, small (micro-)services rather than big monoliths gives developers the flexibility to work in different languages, technologies and release cadence across the system; resulting in higher productivity and velocity, especially for larger teams. With the adoption of microservices, however, new problems emerge due to the sheer number of services that exist in a larger system. Problems that had to be solved once for a monolith, like security, load balancing, monitoring, and rate limiting need to be handled for each service. Istio, announced at GlueCon 2017, addresses these problems in a fundamental way through a service mesh framework. With Istio, developers can implement the core logic for the microservices, and let the framework take care of the rest – traffic management, discovery, service identity and security, and policy enforcement. Better yet, this can be also done for existing microservices without rewriting or recompiling any of their parts. Istio uses Envoy as its runtime proxy component and provides an extensible intermediation layer which allows global cross-cutting policy enforcement and telemetry collection. ]]>
Services are at the core of modern software architecture. Deploying a series of modular, small (micro-)services rather than big monoliths gives developers the flexibility to work in different languages, technologies and release cadence across the system; resulting in higher productivity and velocity, especially for larger teams. With the adoption of microservices, however, new problems emerge due to the sheer number of services that exist in a larger system. Problems that had to be solved once for a monolith, like security, load balancing, monitoring, and rate limiting need to be handled for each service. Istio, announced at GlueCon 2017, addresses these problems in a fundamental way through a service mesh framework. With Istio, developers can implement the core logic for the microservices, and let the framework take care of the rest – traffic management, discovery, service identity and security, and policy enforcement. Better yet, this can be also done for existing microservices without rewriting or recompiling any of their parts. Istio uses Envoy as its runtime proxy component and provides an extensible intermediation layer which allows global cross-cutting policy enforcement and telemetry collection. ]]> Mon, 07 Aug 2017 05:41:53 GMT /slideshow/an-opensource-platform-to-connect-manage-and-secure-microservices/78619990 VadimSolovey@slideshare.net(VadimSolovey) An Open-Source Platform to Connect, Manage, and Secure Microservices VadimSolovey Services are at the core of modern software architecture. Deploying a series of modular, small (micro-)services rather than big monoliths gives developers the flexibility to work in different languages, technologies and release cadence across the system; resulting in higher productivity and velocity, especially for larger teams. With the adoption of microservices, however, new problems emerge due to the sheer number of services that exist in a larger system. Problems that had to be solved once for a monolith, like security, load balancing, monitoring, and rate limiting need to be handled for each service. Istio, announced at GlueCon 2017, addresses these problems in a fundamental way through a service mesh framework. With Istio, developers can implement the core logic for the microservices, and let the framework take care of the rest – traffic management, discovery, service identity and security, and policy enforcement. Better yet, this can be also done for existing microservices without rewriting or recompiling any of their parts. Istio uses Envoy as its runtime proxy component and provides an extensible intermediation layer which allows global cross-cutting policy enforcement and telemetry collection. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/20170802meetup-istio-170807054153-thumbnail.jpg?width=120&height=120&fit=bounds" /> Services are at the core of modern software architecture. Deploying a series of modular, small (micro-)services rather than big monoliths gives developers the flexibility to work in different languages, technologies and release cadence across the system; resulting in higher productivity and velocity, especially for larger teams. With the adoption of microservices, however, new problems emerge due to the sheer number of services that exist in a larger system. Problems that had to be solved once for a monolith, like security, load balancing, monitoring, and rate limiting need to be handled for each service. Istio, announced at GlueCon 2017, addresses these problems in a fundamental way through a service mesh framework. With Istio, developers can implement the core logic for the microservices, and let the framework take care of the rest – traffic management, discovery, service identity and security, and policy enforcement. Better yet, this can be also done for existing microservices without rewriting or recompiling any of their parts. Istio uses Envoy as its runtime proxy component and provides an extensible intermediation layer which allows global cross-cutting policy enforcement and telemetry collection.

An Open-Source Platform to Connect, Manage, and Secure Microservices from DoiT International

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0 Is your Elastic Cluster Stable and Production Ready? /slideshow/s-your-elastic-cluster-stable-and-production-ready/77971131 isyourelasticsearchclusterproductionready-170717203617
So you are deployed to production (or soon to be) with Elasticsearch running and powering important application features. Or maybe used for centralized logging for effective debugging. Was your Elastic cluster deployed correctly? Is it stable? Can it hold the throughput you expect it to? How did you do capacity planning? How to tell if the cluster is healthy and what to monitor? How to apply effective multi-tenancy? and what would be an ideal cluster topology and data ingestion architecture?]]>
So you are deployed to production (or soon to be) with Elasticsearch running and powering important application features. Or maybe used for centralized logging for effective debugging. Was your Elastic cluster deployed correctly? Is it stable? Can it hold the throughput you expect it to? How did you do capacity planning? How to tell if the cluster is healthy and what to monitor? How to apply effective multi-tenancy? and what would be an ideal cluster topology and data ingestion architecture?]]> Mon, 17 Jul 2017 20:36:17 GMT /slideshow/s-your-elastic-cluster-stable-and-production-ready/77971131 VadimSolovey@slideshare.net(VadimSolovey) Is your Elastic Cluster Stable and Production Ready? VadimSolovey So you are deployed to production (or soon to be) with Elasticsearch running and powering important application features. Or maybe used for centralized logging for effective debugging. Was your Elastic cluster deployed correctly? Is it stable? Can it hold the throughput you expect it to? How did you do capacity planning? How to tell if the cluster is healthy and what to monitor? How to apply effective multi-tenancy? and what would be an ideal cluster topology and data ingestion architecture? <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/isyourelasticsearchclusterproductionready-170717203617-thumbnail.jpg?width=120&height=120&fit=bounds" /> So you are deployed to production (or soon to be) with Elasticsearch running and powering important application features. Or maybe used for centralized logging for effective debugging. Was your Elastic cluster deployed correctly? Is it stable? Can it hold the throughput you expect it to? How did you do capacity planning? How to tell if the cluster is healthy and what to monitor? How to apply effective multi-tenancy? and what would be an ideal cluster topology and data ingestion architecture?

Is your Elastic Cluster Stable and Production Ready? from DoiT International

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0 Applying ML for Log Analysis /slideshow/applying-ml-for-log-analysis/77971111 doit-170717203538
We already trust artificial intelligence to drive our car, but we still configure thresholds and thrift through logs manually. In this talk, Ronny Lehmann, Loom CTO will discuss how he spent months analyzing modern-ops work, until he finally was able to extract the common-basis practices; and how we used this understanding to build a machine that complements ops teams, automating much of the work which is more suitable for machines - leaving for "humans" just the parts which require humans. What we built saves you time spent on parsers, on configuring and tuning rules and alerts, on conducting root-cause analysis and triage - and finally - on figuring out what to do.]]>
We already trust artificial intelligence to drive our car, but we still configure thresholds and thrift through logs manually. In this talk, Ronny Lehmann, Loom CTO will discuss how he spent months analyzing modern-ops work, until he finally was able to extract the common-basis practices; and how we used this understanding to build a machine that complements ops teams, automating much of the work which is more suitable for machines - leaving for "humans" just the parts which require humans. What we built saves you time spent on parsers, on configuring and tuning rules and alerts, on conducting root-cause analysis and triage - and finally - on figuring out what to do.]]> Mon, 17 Jul 2017 20:35:38 GMT /slideshow/applying-ml-for-log-analysis/77971111 VadimSolovey@slideshare.net(VadimSolovey) Applying ML for Log Analysis VadimSolovey We already trust artificial intelligence to drive our car, but we still configure thresholds and thrift through logs manually. In this talk, Ronny Lehmann, Loom CTO will discuss how he spent months analyzing modern-ops work, until he finally was able to extract the common-basis practices; and how we used this understanding to build a machine that complements ops teams, automating much of the work which is more suitable for machines - leaving for "humans" just the parts which require humans. What we built saves you time spent on parsers, on configuring and tuning rules and alerts, on conducting root-cause analysis and triage - and finally - on figuring out what to do. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/doit-170717203538-thumbnail.jpg?width=120&height=120&fit=bounds" /> We already trust artificial intelligence to drive our car, but we still configure thresholds and thrift through logs manually. In this talk, Ronny Lehmann, Loom CTO will discuss how he spent months analyzing modern-ops work, until he finally was able to extract the common-basis practices; and how we used this understanding to build a machine that complements ops teams, automating much of the work which is more suitable for machines - leaving for "humans" just the parts which require humans. What we built saves you time spent on parsers, on configuring and tuning rules and alerts, on conducting root-cause analysis and triage - and finally - on figuring out what to do.

Applying ML for Log Analysis from DoiT International

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0 GCP for AWS Professionals /slideshow/gcp-for-aws-professionals/76965656 gcpforawsprofessionalsmeetup14-06-2017-170615084722
This meeting we'll host a discussion on Google Cloud Platform and Amazon Web Services to bring light to similarities and differences between platforms. If you have questions about how our platforms compare this is the meeting to attend! ]]>
This meeting we'll host a discussion on Google Cloud Platform and Amazon Web Services to bring light to similarities and differences between platforms. If you have questions about how our platforms compare this is the meeting to attend! ]]> Thu, 15 Jun 2017 08:47:22 GMT /slideshow/gcp-for-aws-professionals/76965656 VadimSolovey@slideshare.net(VadimSolovey) GCP for AWS Professionals VadimSolovey This meeting we'll host a discussion on Google Cloud Platform and Amazon Web Services to bring light to similarities and differences between platforms. If you have questions about how our platforms compare this is the meeting to attend! <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/gcpforawsprofessionalsmeetup14-06-2017-170615084722-thumbnail.jpg?width=120&height=120&fit=bounds" /> This meeting we'll host a discussion on Google Cloud Platform and Amazon Web Services to bring light to similarities and differences between platforms. If you have questions about how our platforms compare this is the meeting to attend!

GCP for AWS Professionals from DoiT International

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0 Cloud Dataflow - A Unified Model for Batch and Streaming Data Processing /slideshow/cloud-dataflow-a-unified-model-for-batch-and-streaming-data-processing/75418835 dataflow-aunifiedmodel2f2fmeetup-yoram-170426074023
Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.]]>
Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.]]> Wed, 26 Apr 2017 07:40:23 GMT /slideshow/cloud-dataflow-a-unified-model-for-batch-and-streaming-data-processing/75418835 VadimSolovey@slideshare.net(VadimSolovey) Cloud Dataflow - A Unified Model for Batch and Streaming Data Processing VadimSolovey Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dataflow-aunifiedmodel2f2fmeetup-yoram-170426074023-thumbnail.jpg?width=120&height=120&fit=bounds" /> Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.

Cloud Dataflow - A Unified Model for Batch and Streaming Data Processing from DoiT International

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0 AWS Cyber Security Best Practices /slideshow/aws-cyber-security-best-practices/73183383 awscybersecuritybestpractices-170315175249
We believe that security *IS* a shared responsibility, - when we give developers the power to create infrastructure, security became their responsibility, too. During this meetup, we'd like to share our experience with implementing security best practices, to be implemented directly by development teams to build more robust and secure cloud environments. Make cloud security your team's sport!]]>
We believe that security *IS* a shared responsibility, - when we give developers the power to create infrastructure, security became their responsibility, too. During this meetup, we'd like to share our experience with implementing security best practices, to be implemented directly by development teams to build more robust and secure cloud environments. Make cloud security your team's sport!]]> Wed, 15 Mar 2017 17:52:48 GMT /slideshow/aws-cyber-security-best-practices/73183383 VadimSolovey@slideshare.net(VadimSolovey) AWS Cyber Security Best Practices VadimSolovey We believe that security *IS* a shared responsibility, - when we give developers the power to create infrastructure, security became their responsibility, too. During this meetup, we'd like to share our experience with implementing security best practices, to be implemented directly by development teams to build more robust and secure cloud environments. Make cloud security your team's sport! <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/awscybersecuritybestpractices-170315175249-thumbnail.jpg?width=120&height=120&fit=bounds" /> We believe that security *IS* a shared responsibility, - when we give developers the power to create infrastructure, security became their responsibility, too. During this meetup, we'd like to share our experience with implementing security best practices, to be implemented directly by development teams to build more robust and secure cloud environments. Make cloud security your team's sport!

AWS Cyber Security Best Practices from DoiT International

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0 Google Cloud Spanner Preview /slideshow/google-cloud-spanner-meetup-26022017/72595055 spannermeetup26-02-2017-170226182152
Cloud Spanner is the first and only relational database service that is both strongly consistent and horizontally scalable. With Cloud Spanner you enjoy all the traditional benefits of a relational database: ACID transactions, relational schemas (and schema changes without downtime), SQL queries, high performance, and high availability. But unlike any other relational database service, Cloud Spanner scales horizontally, to hundreds or thousands of servers, so it can handle the highest of transactional workloads. ]]>
Cloud Spanner is the first and only relational database service that is both strongly consistent and horizontally scalable. With Cloud Spanner you enjoy all the traditional benefits of a relational database: ACID transactions, relational schemas (and schema changes without downtime), SQL queries, high performance, and high availability. But unlike any other relational database service, Cloud Spanner scales horizontally, to hundreds or thousands of servers, so it can handle the highest of transactional workloads. ]]> Sun, 26 Feb 2017 18:21:52 GMT /slideshow/google-cloud-spanner-meetup-26022017/72595055 VadimSolovey@slideshare.net(VadimSolovey) Google Cloud Spanner Preview VadimSolovey Cloud Spanner is the first and only relational database service that is both strongly consistent and horizontally scalable. With Cloud Spanner you enjoy all the traditional benefits of a relational database: ACID transactions, relational schemas (and schema changes without downtime), SQL queries, high performance, and high availability. But unlike any other relational database service, Cloud Spanner scales horizontally, to hundreds or thousands of servers, so it can handle the highest of transactional workloads. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/spannermeetup26-02-2017-170226182152-thumbnail.jpg?width=120&height=120&fit=bounds" /> Cloud Spanner is the first and only relational database service that is both strongly consistent and horizontally scalable. With Cloud Spanner you enjoy all the traditional benefits of a relational database: ACID transactions, relational schemas (and schema changes without downtime), SQL queries, high performance, and high availability. But unlike any other relational database service, Cloud Spanner scales horizontally, to hundreds or thousands of servers, so it can handle the highest of transactional workloads.

Google Cloud Spanner Preview from DoiT International

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0 Amazon Athena Hands-On Workshop /slideshow/amazon-athena-handson-workshop/71426140 amazonathenaworkshop-170126163220
This 1-day course provides hands-on skills in ingesting, analyzing, transforming and visualizing data using AWS Athena and getting the best performance when using it at scale. Audience: This class is intended for data engineers, analysts and data scientists responsible for: analyzing and visualizing big data, implementing cloud-based big data solutions, deploying or migrating big data applications to the public cloud, implementing and maintaining large-scale data storage environments, and transforming/processing big data.]]>
This 1-day course provides hands-on skills in ingesting, analyzing, transforming and visualizing data using AWS Athena and getting the best performance when using it at scale. Audience: This class is intended for data engineers, analysts and data scientists responsible for: analyzing and visualizing big data, implementing cloud-based big data solutions, deploying or migrating big data applications to the public cloud, implementing and maintaining large-scale data storage environments, and transforming/processing big data.]]> Thu, 26 Jan 2017 16:32:19 GMT /slideshow/amazon-athena-handson-workshop/71426140 VadimSolovey@slideshare.net(VadimSolovey) Amazon Athena Hands-On Workshop VadimSolovey This 1-day course provides hands-on skills in ingesting, analyzing, transforming and visualizing data using AWS Athena and getting the best performance when using it at scale. Audience: This class is intended for data engineers, analysts and data scientists responsible for: analyzing and visualizing big data, implementing cloud-based big data solutions, deploying or migrating big data applications to the public cloud, implementing and maintaining large-scale data storage environments, and transforming/processing big data. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/amazonathenaworkshop-170126163220-thumbnail.jpg?width=120&height=120&fit=bounds" /> This 1-day course provides hands-on skills in ingesting, analyzing, transforming and visualizing data using AWS Athena and getting the best performance when using it at scale. Audience: This class is intended for data engineers, analysts and data scientists responsible for: analyzing and visualizing big data, implementing cloud-based big data solutions, deploying or migrating big data applications to the public cloud, implementing and maintaining large-scale data storage environments, and transforming/processing big data.

Amazon Athena Hands-On Workshop from DoiT International

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0 AWS Athena vs. Google BigQuery for interactive SQL Queries /slideshow/aws-athena-vs-google-bigquery-for-interactive-sql-queries/70034844 awsathenavsgooglebigqueryforinteractivesqlqueries-161211193543
During the re:Invent 2016, AWS has released the Amazon Athena - an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. We took a look on AWS Athena and compared it to the Google BigQuery - another player of serverless interactive data analysis. Would you like to know which one is the right tool for you? Join us for this meetup to learn AWS Athena and for the test drive of querying exactly the same dataset using AWS Athena and Google BigQuery to see where each one shines (or totally blows it).]]>
During the re:Invent 2016, AWS has released the Amazon Athena - an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. We took a look on AWS Athena and compared it to the Google BigQuery - another player of serverless interactive data analysis. Would you like to know which one is the right tool for you? Join us for this meetup to learn AWS Athena and for the test drive of querying exactly the same dataset using AWS Athena and Google BigQuery to see where each one shines (or totally blows it).]]> Sun, 11 Dec 2016 19:35:43 GMT /slideshow/aws-athena-vs-google-bigquery-for-interactive-sql-queries/70034844 VadimSolovey@slideshare.net(VadimSolovey) AWS Athena vs. Google BigQuery for interactive SQL Queries VadimSolovey During the re:Invent 2016, AWS has released the Amazon Athena - an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. We took a look on AWS Athena and compared it to the Google BigQuery - another player of serverless interactive data analysis. Would you like to know which one is the right tool for you? Join us for this meetup to learn AWS Athena and for the test drive of querying exactly the same dataset using AWS Athena and Google BigQuery to see where each one shines (or totally blows it). <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/awsathenavsgooglebigqueryforinteractivesqlqueries-161211193543-thumbnail.jpg?width=120&height=120&fit=bounds" /> During the re:Invent 2016, AWS has released the Amazon Athena - an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. We took a look on AWS Athena and compared it to the Google BigQuery - another player of serverless interactive data analysis. Would you like to know which one is the right tool for you? Join us for this meetup to learn AWS Athena and for the test drive of querying exactly the same dataset using AWS Athena and Google BigQuery to see where each one shines (or totally blows it).

AWS Athena vs. Google BigQuery for interactive SQL Queries from DoiT International

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0 Google BigQuery 101 & What’s New /slideshow/google-bigquery-101-whats-new/68548275 bigquery101whatsnew-161110064706
Vadim Solovey is a CTO of DoiT International has helped to implement Google BigQuery as a cloud data warehouse for many medium and large sized data and analytics initiatives. BigQuery’s serverless architecture had redefined what it means to be fully managed for hundreds of Israeli's startups. Recently, Google announced an update to BigQuery that dramatically advances cloud data analytics for large-scale businesses such as BigQuery now support Standard SQL, implementing the SQL 2011 standard as well as new ODBC drivers making it possible to use BigQuery with a number of tools ranging from Microsoft Excel to traditional business intelligence systems such as Microstrategy and Qlik. Agenda: • Partitioned tables • The ability to update, delete rows and columns using SQL • Integration with IAM for fine-grained security policies • Monitoring w/ StackDriver to track performance and usage • Query sharing via links, to foster knowledge within orgs • Cost optimisation strategies]]>
Vadim Solovey is a CTO of DoiT International has helped to implement Google BigQuery as a cloud data warehouse for many medium and large sized data and analytics initiatives. BigQuery’s serverless architecture had redefined what it means to be fully managed for hundreds of Israeli's startups. Recently, Google announced an update to BigQuery that dramatically advances cloud data analytics for large-scale businesses such as BigQuery now support Standard SQL, implementing the SQL 2011 standard as well as new ODBC drivers making it possible to use BigQuery with a number of tools ranging from Microsoft Excel to traditional business intelligence systems such as Microstrategy and Qlik. Agenda: • Partitioned tables • The ability to update, delete rows and columns using SQL • Integration with IAM for fine-grained security policies • Monitoring w/ StackDriver to track performance and usage • Query sharing via links, to foster knowledge within orgs • Cost optimisation strategies]]> Thu, 10 Nov 2016 06:47:06 GMT /slideshow/google-bigquery-101-whats-new/68548275 VadimSolovey@slideshare.net(VadimSolovey) Google BigQuery 101 & What’s New VadimSolovey Vadim Solovey is a CTO of DoiT International has helped to implement Google BigQuery as a cloud data warehouse for many medium and large sized data and analytics initiatives. BigQuery’s serverless architecture had redefined what it means to be fully managed for hundreds of Israeli's startups. Recently, Google announced an update to BigQuery that dramatically advances cloud data analytics for large-scale businesses such as BigQuery now support Standard SQL, implementing the SQL 2011 standard as well as new ODBC drivers making it possible to use BigQuery with a number of tools ranging from Microsoft Excel to traditional business intelligence systems such as Microstrategy and Qlik. Agenda: • Partitioned tables • The ability to update, delete rows and columns using SQL • Integration with IAM for fine-grained security policies • Monitoring w/ StackDriver to track performance and usage • Query sharing via links, to foster knowledge within orgs • Cost optimisation strategies <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/bigquery101whatsnew-161110064706-thumbnail.jpg?width=120&height=120&fit=bounds" /> Vadim Solovey is a CTO of DoiT International has helped to implement Google BigQuery as a cloud data warehouse for many medium and large sized data and analytics initiatives. BigQuery’s serverless architecture had redefined what it means to be fully managed for hundreds of Israeli's startups. Recently, Google announced an update to BigQuery that dramatically advances cloud data analytics for large-scale businesses such as BigQuery now support Standard SQL, implementing the SQL 2011 standard as well as new ODBC drivers making it possible to use BigQuery with a number of tools ranging from Microsoft Excel to traditional business intelligence systems such as Microstrategy and Qlik. Agenda: • Partitioned tables • The ability to update, delete rows and columns using SQL • Integration with IAM for fine-grained security policies • Monitoring w/ StackDriver to track performance and usage • Query sharing via links, to foster knowledge within orgs • Cost optimisation strategies

Google BigQuery 101 & What’s New from DoiT International

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0 Running Production-Grade Kubernetes on AWS /slideshow/running-productiongrade-kubernetes-on-aws/64689031 productiongradekubernetesmeetup-160804090710
Kubernetes has been a key component for many companies to reduce technical debt in infrastructure by: • Fostering the Adoption of Docker • Simplifying Container Management • Onboarding Developers On Infrastructure • Unlocking Continuous Integration and Delivery During this meetup we are going to discuss the following topics and share some best practices • What's new with Kubernetes 1.3 • Generate Cluster Configuration using CloudFormation • Deploy Kubernetes Clusters on AWS • Scaling the Cluster • Integrating Ingress with Elastic Load Balancer • Using Internal ELB's as Kubernetes' Service • Using EBS for persistent volumes • Integrating Route53]]>
Kubernetes has been a key component for many companies to reduce technical debt in infrastructure by: • Fostering the Adoption of Docker • Simplifying Container Management • Onboarding Developers On Infrastructure • Unlocking Continuous Integration and Delivery During this meetup we are going to discuss the following topics and share some best practices • What's new with Kubernetes 1.3 • Generate Cluster Configuration using CloudFormation • Deploy Kubernetes Clusters on AWS • Scaling the Cluster • Integrating Ingress with Elastic Load Balancer • Using Internal ELB's as Kubernetes' Service • Using EBS for persistent volumes • Integrating Route53]]> Thu, 04 Aug 2016 09:07:10 GMT /slideshow/running-productiongrade-kubernetes-on-aws/64689031 VadimSolovey@slideshare.net(VadimSolovey) Running Production-Grade Kubernetes on AWS VadimSolovey Kubernetes has been a key component for many companies to reduce technical debt in infrastructure by: • Fostering the Adoption of Docker • Simplifying Container Management • Onboarding Developers On Infrastructure • Unlocking Continuous Integration and Delivery During this meetup we are going to discuss the following topics and share some best practices • What's new with Kubernetes 1.3 • Generate Cluster Configuration using CloudFormation • Deploy Kubernetes Clusters on AWS • Scaling the Cluster • Integrating Ingress with Elastic Load Balancer • Using Internal ELB's as Kubernetes' Service • Using EBS for persistent volumes • Integrating Route53 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/productiongradekubernetesmeetup-160804090710-thumbnail.jpg?width=120&height=120&fit=bounds" /> Kubernetes has been a key component for many companies to reduce technical debt in infrastructure by: • Fostering the Adoption of Docker • Simplifying Container Management • Onboarding Developers On Infrastructure • Unlocking Continuous Integration and Delivery During this meetup we are going to discuss the following topics and share some best practices • What's new with Kubernetes 1.3 • Generate Cluster Configuration using CloudFormation • Deploy Kubernetes Clusters on AWS • Scaling the Cluster • Integrating Ingress with Elastic Load Balancer • Using Internal ELB's as Kubernetes' Service • Using EBS for persistent volumes • Integrating Route53

Running Production-Grade Kubernetes on AWS from DoiT International

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0 Scaling Jenkins with Kubernetes by Ami Mahloof /slideshow/scaling-jenkins-with-kubernetes-by-ami-mahloof/61849770 scalingjenkinswithkubernetes-160510080342
Ami Mahloof from Glide explains how they are scaling and simplifying deployments with Kubernetes]]>
Ami Mahloof from Glide explains how they are scaling and simplifying deployments with Kubernetes]]> Tue, 10 May 2016 08:03:42 GMT /slideshow/scaling-jenkins-with-kubernetes-by-ami-mahloof/61849770 VadimSolovey@slideshare.net(VadimSolovey) Scaling Jenkins with Kubernetes by Ami Mahloof VadimSolovey Ami Mahloof from Glide explains how they are scaling and simplifying deployments with Kubernetes <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/scalingjenkinswithkubernetes-160510080342-thumbnail.jpg?width=120&height=120&fit=bounds" /> Ami Mahloof from Glide explains how they are scaling and simplifying deployments with Kubernetes

Scaling Jenkins with Kubernetes by Ami Mahloof from DoiT International

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0 CI Implementation with Kubernetes at LivePerson by Saar Demri /slideshow/ci-implementation-with-kubernetes-at-liveperson-by-saar-demri/61849545 lpk8s-160510075858
How LivePerson have built their Continuous Integration flow with Kubernetes to streamline development to production rollouts.]]>
How LivePerson have built their Continuous Integration flow with Kubernetes to streamline development to production rollouts.]]> Tue, 10 May 2016 07:58:58 GMT /slideshow/ci-implementation-with-kubernetes-at-liveperson-by-saar-demri/61849545 VadimSolovey@slideshare.net(VadimSolovey) CI Implementation with Kubernetes at LivePerson by Saar Demri VadimSolovey How LivePerson have built their Continuous Integration flow with Kubernetes to streamline development to production rollouts. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/lpk8s-160510075858-thumbnail.jpg?width=120&height=120&fit=bounds" /> How LivePerson have built their Continuous Integration flow with Kubernetes to streamline development to production rollouts.

CI Implementation with Kubernetes at LivePerson by Saar Demri from DoiT International

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0 Kubernetes @ Nanit by Chen Fisher /slideshow/kubernetes-nanit-by-chen-fisher/61849460 kubernetesnanitpublic-160510075626
How Nanit are using Kubernetes to simplify development, streamline staging and scale production.]]>
How Nanit are using Kubernetes to simplify development, streamline staging and scale production.]]> Tue, 10 May 2016 07:56:25 GMT /slideshow/kubernetes-nanit-by-chen-fisher/61849460 VadimSolovey@slideshare.net(VadimSolovey) Kubernetes @ Nanit by Chen Fisher VadimSolovey How Nanit are using Kubernetes to simplify development, streamline staging and scale production. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/kubernetesnanitpublic-160510075626-thumbnail.jpg?width=120&height=120&fit=bounds" /> How Nanit are using Kubernetes to simplify development, streamline staging and scale production.

Kubernetes @ Nanit by Chen Fisher from DoiT International

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0 Dataflow - A Unified Model for Batch and Streaming Data Processing /slideshow/dataflow-a-unified-model-for-batch-and-streaming-data-processing/61074485 dataflow-aunifiedmodel-meetup-160419051609
Batch and Streaming Data Processing and Vizualize 300Tb in 5 Seconds meetup on April 18th, 2016 (http://www.meetup.com/Big-things-are-happening-here/events/229532500)]]>
Batch and Streaming Data Processing and Vizualize 300Tb in 5 Seconds meetup on April 18th, 2016 (http://www.meetup.com/Big-things-are-happening-here/events/229532500)]]> Tue, 19 Apr 2016 05:16:09 GMT /slideshow/dataflow-a-unified-model-for-batch-and-streaming-data-processing/61074485 VadimSolovey@slideshare.net(VadimSolovey) Dataflow - A Unified Model for Batch and Streaming Data Processing VadimSolovey Batch and Streaming Data Processing and Vizualize 300Tb in 5 Seconds meetup on April 18th, 2016 (http://www.meetup.com/Big-things-are-happening-here/events/229532500) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dataflow-aunifiedmodel-meetup-160419051609-thumbnail.jpg?width=120&height=120&fit=bounds" /> Batch and Streaming Data Processing and Vizualize 300Tb in 5 Seconds meetup on April 18th, 2016 (http://www.meetup.com/Big-things-are-happening-here/events/229532500)

Dataflow - A Unified Model for Batch and Streaming Data Processing from DoiT International

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0 Kubernetes - State of the Union (Q1-2016) /slideshow/kubernetes-state-of-the-union-q12016-56977150/56977150 kubernetesroadmap2016-160112211804
Kubernetes is making the promise of changing the datacenter from being a group of computer to "a computer" itself. This presentation outlines the new features in K8S with 1.1 and 1.2 release.]]>
Kubernetes is making the promise of changing the datacenter from being a group of computer to "a computer" itself. This presentation outlines the new features in K8S with 1.1 and 1.2 release.]]> Tue, 12 Jan 2016 21:18:04 GMT /slideshow/kubernetes-state-of-the-union-q12016-56977150/56977150 VadimSolovey@slideshare.net(VadimSolovey) Kubernetes - State of the Union (Q1-2016) VadimSolovey Kubernetes is making the promise of changing the datacenter from being a group of computer to "a computer" itself. This presentation outlines the new features in K8S with 1.1 and 1.2 release. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/kubernetesroadmap2016-160112211804-thumbnail.jpg?width=120&height=120&fit=bounds" /> Kubernetes is making the promise of changing the datacenter from being a group of computer to "a computer" itself. This presentation outlines the new features in K8S with 1.1 and 1.2 release.

Kubernetes - State of the Union (Q1-2016) from DoiT International

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0 https://cdn.slidesharecdn.com/profile-photo-VadimSolovey-48x48.jpg?cb=1578981498 As a CTO and co-founder of one of the best cloud consultancy companies in the world, I help startups to architect, build, manage and secure their products using Google Cloud Platform and Amazon Web Services platforms. I am also a business expert with hands-on experience in many aspects such as partnerships, sales, marketing, mergers and acquisition with proven track record. www.doit-intl.com https://cdn.slidesharecdn.com/ss_thumbnails/terraformmodulesrestructured-200114081743-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/terraform-modules-restructured-220136382/220136382 Terraform Modules Rest... https://cdn.slidesharecdn.com/ss_thumbnails/gantrainingusingtensorcoresandtensorflow-190627101844-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/gan-training-with-tensorflow-and-tensor-cores/152176707 GAN training with Tens... https://cdn.slidesharecdn.com/ss_thumbnails/k8smeetup-redisoperators-180718100601-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/orchestrating-redis-k8s-operators/106414155 Orchestrating Redis & ...