Autoscaling in Kubernetes (K8s)
•
0 likes•36 views
Autoscaling in Kubernetes allows applications to automatically scale resources up or down based on metrics like CPU usage. It addresses challenges with traditional autoscaling approaches by being platform independent and scaling pods quickly using the Horizontal Pod Autoscaler. The document outlines an architecture that sets autoscaling to increase application pods when CPU usage crosses 50%, with a minimum of 1 and maximum of 3 pods. It then demonstrates this through scenarios of idle and heavy loads, ramping up users over 10 seconds to test the autoscaling capabilities.
Report
Share
Report
Share
Recommended
TechTalk_Cloud Performance Testing_0.6
The document provides an overview of a presentation on cloud performance testing. The presentation agenda includes cloud 101 concepts, cloud offerings and deployment models, challenges of cloud computing, and tools for cloud performance testing. It also summarizes a proof of concept that was conducted to compare the performance and costs of using a commercial tool versus an open source tool for load testing on cloud infrastructure. The results showed comparable response times between the tools and significantly lower costs when using the cloud versus maintaining physical infrastructure.
Jolt: Distributed, fault-tolerant test running at scale using Mesos
This document summarizes Yelp's new test parallelization system called Jolt. It discusses how Jolt bundles tests into groups to run in parallel on Mesos clusters. This improves upon their previous system called Seagull which had complex custom components. Jolt uses Task Processing to interface with Mesos in a composable way. The document also describes Yelp's autoscaling system called Clusterman which adjusts Mesos cluster sizes based on resource usage and spot instance pricing. It notes how these systems have significantly reduced Yelp's infrastructure costs while improving their ability to run tests and deploy code.
Kubernetes: Reducing Infrastructure Cost & Complexity
In this session, Kevin will dive into the unique challenges of keeping your Kubernetes workloads highly available while keeping costs low. You will learn about how to leverage cloud-native autoscaling, pod requirement right-sizing, resource buffer definition, cost allocation and more.
goto; London: Keeping your Cloud Footprint in Check
Presented on the "Lean" track at goto; London September 17th, 2015. Covers how Netflix manages cloud cost efficiency in light of innovation and reliability drivers.
Melbourne Big Data Meetup Talk: Scaling a Real-Time Anomaly Detection Applica...
Apache Kafka, Apache Cassandra and Kubernetes are open source big data technologies enabling applications and business operations to scale massively and rapidly. While Kafka and Cassandra underpins the data layer of the stack providing capability to stream, disseminate, store and retrieve data at very low latency, Kubernetes is a container orchestration technology that helps in automated application deployment and scaling of application clusters.
In this presentation, Paul will reveal how he architected a massive scale deployment of a streaming data pipeline with Kafka and Cassandra to cater to an example Anomaly detection application running on a Kubernetes cluster and generating and processing massive amount of events. Anomaly detection is a method used to detect unusual events in an event stream.
It is widely used in a range of applications such as financial fraud detection, security, threat detection, website user analytics, sensors, IoT, system health monitoring, etc. When such applications operate at massive scale generating millions or billions of events, they impose significant computational, performance and scalability challenges to anomaly detection algorithms and data layer technologies. Paul will demonstrate the scalability, performance and cost effectiveness of Apache Kafka, Cassandra and Kubernetes, with results from his experiments allowing the Anomaly detection application to scale to 19 Billion anomaly checks per day.
Melbourne Big Data Meetup, March 5 2020
https://www.eventbrite.com/e/melbourne-big-data-meetup-realtime-anomaly-detection-with-cassandra-kafka-tickets-93028445585
Scaling Open Source Big Data Cloud Applications is Easy/Hard
In the last decade, the development of modern horizontally scalable open-source Big Data technologies such as Apache Cassandra (for data storage), and Apache Kafka (for data streaming) enabled cost-effective, highly scalable, reliable, low-latency applications, and made these technologies increasingly ubiquitous. To enable reliable horizontal scalability, both Cassandra and Kafka utilize partitioning (for concurrency) and replication (for reliability and availability) across clustered servers. But building scalable applications isn’t as easy as just throwing more servers at the clusters, and unexpected speed humps are common. Consequently, you also need to understand the performance impact of partitions, replication, and clusters; monitor the correct metrics to have an end-to-end view of applications and clusters; conduct careful benchmarking, and scale and tune iteratively to take into account performance insights and optimizations. In this presentation, I will explore some of the performance goals, challenges, solutions, and results I discovered over the last 5 years building multiple realistic demonstration applications. The examples will include trade-offs with elastic Cassandra auto-scaling, scaling a Cassandra and Kafka anomaly detection application to 19 Billion checks per day, and building low-latency streaming data pipelines using Kafka Connect for multiple heterogeneous source and sink systems.
Invited keynote for 5th Workshop on Hot Topics in Cloud Computing Performance (HotCloudPerf 2022) https://hotcloudperf.spec.org/ at ICPE 2022 https://icpe2022.spec.org/
(SPOT302) Availability: The New Kind of Innovator’s Dilemma
Successful companies, while focusing on their current customers' needs, often fail to embrace disruptive technologies and business models. This phenomenon, known as the "Innovator's Dilemma," eventually leads to many companies' downfall and is especially relevant in the fast-paced world of online services. In order to protect its leading position and grow its share of the highly competitive global digital streaming market, Netflix has to continuously increase the pace of innovation by constantly refining recommendation algorithms and adding new product features, while maintaining a high level of service uptime. The Netflix streaming platform consists of hundreds of microservices that are constantly evolving, and even the smallest production change may cause a cascading failure that can bring the entire service down. We face a new kind of Innovator's Dilemma, where product changes may not only disrupt the business model but also cause production outages that deny customers service access. This talk will describe various architectural, operational and organizational changes adopted by Netflix in order to reconcile rapid innovation with service availability.
Accelerating Analytics for the Future of Genomics
Healthcare systems around the world are looking to Precision Medicine -- care decisions tailored for the individual patient -- as a means to drive better care outcomes at lower cost. Today, the most promising technology that has made this possible in certain diseases like cancer is sequencing a patient's genome. For infectious diseases, sequencing has revolutionized our understanding of outbreaks and how they spread. Genome sequencing has progressed significantly in the past decade to improve throughput and lower costs by 100X or more. It is a data and compute intensive endeavor, which most biomedical research and care delivery networks are not equipped to handle. This session features Dr. Swaine Chen from the Genome Institute of Singapore, and the Broad Institute Cromwell team, discussing the problem of dealing with the scale of genomic data, and how they solved these to deliver results.
Recommended
TechTalk_Cloud Performance Testing_0.6
The document provides an overview of a presentation on cloud performance testing. The presentation agenda includes cloud 101 concepts, cloud offerings and deployment models, challenges of cloud computing, and tools for cloud performance testing. It also summarizes a proof of concept that was conducted to compare the performance and costs of using a commercial tool versus an open source tool for load testing on cloud infrastructure. The results showed comparable response times between the tools and significantly lower costs when using the cloud versus maintaining physical infrastructure.
Jolt: Distributed, fault-tolerant test running at scale using Mesos
This document summarizes Yelp's new test parallelization system called Jolt. It discusses how Jolt bundles tests into groups to run in parallel on Mesos clusters. This improves upon their previous system called Seagull which had complex custom components. Jolt uses Task Processing to interface with Mesos in a composable way. The document also describes Yelp's autoscaling system called Clusterman which adjusts Mesos cluster sizes based on resource usage and spot instance pricing. It notes how these systems have significantly reduced Yelp's infrastructure costs while improving their ability to run tests and deploy code.
Kubernetes: Reducing Infrastructure Cost & Complexity
In this session, Kevin will dive into the unique challenges of keeping your Kubernetes workloads highly available while keeping costs low. You will learn about how to leverage cloud-native autoscaling, pod requirement right-sizing, resource buffer definition, cost allocation and more.
goto; London: Keeping your Cloud Footprint in Check
Presented on the "Lean" track at goto; London September 17th, 2015. Covers how Netflix manages cloud cost efficiency in light of innovation and reliability drivers.
Melbourne Big Data Meetup Talk: Scaling a Real-Time Anomaly Detection Applica...
Apache Kafka, Apache Cassandra and Kubernetes are open source big data technologies enabling applications and business operations to scale massively and rapidly. While Kafka and Cassandra underpins the data layer of the stack providing capability to stream, disseminate, store and retrieve data at very low latency, Kubernetes is a container orchestration technology that helps in automated application deployment and scaling of application clusters.
In this presentation, Paul will reveal how he architected a massive scale deployment of a streaming data pipeline with Kafka and Cassandra to cater to an example Anomaly detection application running on a Kubernetes cluster and generating and processing massive amount of events. Anomaly detection is a method used to detect unusual events in an event stream.
It is widely used in a range of applications such as financial fraud detection, security, threat detection, website user analytics, sensors, IoT, system health monitoring, etc. When such applications operate at massive scale generating millions or billions of events, they impose significant computational, performance and scalability challenges to anomaly detection algorithms and data layer technologies. Paul will demonstrate the scalability, performance and cost effectiveness of Apache Kafka, Cassandra and Kubernetes, with results from his experiments allowing the Anomaly detection application to scale to 19 Billion anomaly checks per day.
Melbourne Big Data Meetup, March 5 2020
https://www.eventbrite.com/e/melbourne-big-data-meetup-realtime-anomaly-detection-with-cassandra-kafka-tickets-93028445585
Scaling Open Source Big Data Cloud Applications is Easy/Hard
In the last decade, the development of modern horizontally scalable open-source Big Data technologies such as Apache Cassandra (for data storage), and Apache Kafka (for data streaming) enabled cost-effective, highly scalable, reliable, low-latency applications, and made these technologies increasingly ubiquitous. To enable reliable horizontal scalability, both Cassandra and Kafka utilize partitioning (for concurrency) and replication (for reliability and availability) across clustered servers. But building scalable applications isn’t as easy as just throwing more servers at the clusters, and unexpected speed humps are common. Consequently, you also need to understand the performance impact of partitions, replication, and clusters; monitor the correct metrics to have an end-to-end view of applications and clusters; conduct careful benchmarking, and scale and tune iteratively to take into account performance insights and optimizations. In this presentation, I will explore some of the performance goals, challenges, solutions, and results I discovered over the last 5 years building multiple realistic demonstration applications. The examples will include trade-offs with elastic Cassandra auto-scaling, scaling a Cassandra and Kafka anomaly detection application to 19 Billion checks per day, and building low-latency streaming data pipelines using Kafka Connect for multiple heterogeneous source and sink systems.
Invited keynote for 5th Workshop on Hot Topics in Cloud Computing Performance (HotCloudPerf 2022) https://hotcloudperf.spec.org/ at ICPE 2022 https://icpe2022.spec.org/
(SPOT302) Availability: The New Kind of Innovator’s Dilemma
Successful companies, while focusing on their current customers' needs, often fail to embrace disruptive technologies and business models. This phenomenon, known as the "Innovator's Dilemma," eventually leads to many companies' downfall and is especially relevant in the fast-paced world of online services. In order to protect its leading position and grow its share of the highly competitive global digital streaming market, Netflix has to continuously increase the pace of innovation by constantly refining recommendation algorithms and adding new product features, while maintaining a high level of service uptime. The Netflix streaming platform consists of hundreds of microservices that are constantly evolving, and even the smallest production change may cause a cascading failure that can bring the entire service down. We face a new kind of Innovator's Dilemma, where product changes may not only disrupt the business model but also cause production outages that deny customers service access. This talk will describe various architectural, operational and organizational changes adopted by Netflix in order to reconcile rapid innovation with service availability.
Accelerating Analytics for the Future of Genomics
Healthcare systems around the world are looking to Precision Medicine -- care decisions tailored for the individual patient -- as a means to drive better care outcomes at lower cost. Today, the most promising technology that has made this possible in certain diseases like cancer is sequencing a patient's genome. For infectious diseases, sequencing has revolutionized our understanding of outbreaks and how they spread. Genome sequencing has progressed significantly in the past decade to improve throughput and lower costs by 100X or more. It is a data and compute intensive endeavor, which most biomedical research and care delivery networks are not equipped to handle. This session features Dr. Swaine Chen from the Genome Institute of Singapore, and the Broad Institute Cromwell team, discussing the problem of dealing with the scale of genomic data, and how they solved these to deliver results.
IEEE 2014 JAVA CLOUD COMPUTING PROJECTS Automatic scaling of internet applica...
IEEE 2014 JAVA CLOUD COMPUTING PROJECTS Automatic scaling of internet applica...IEEEGLOBALSOFTSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.orgCray HPC Environments for Leading Edge Simulations
This presentation is from the PBS User Group 2013, as presented by Greg Clifford.
"Cray scalable solutions are optimized for complex simulations, where parallel and massively concurrent applications need access to data, fast. This presentation will cover recent updates from Cray, showing how Cray continues to deliver the largest production supercomputers leveraging Altair PBS Works and HyperWorks software solutions."
Learn more: http://www.altairatc.com/page.aspx?region=na&name=agenda
Watch the presentation video: http://insidehpc.com/2013/10/04/cray-hpc-environments-leading-edge-simulation/
Ceilosca
See what happens when you overlay Ceilometer functionalities on top of a scalable solution like Monasca ... This is Ceilosca
Anton Boyko, "The evolution of microservices platform or marketing gibberish"
This document discusses Azure Functions and serverless computing. It provides an overview of serverless benefits like manage less, micro-pricing, and ease of scale. It also compares common serverless offerings from Microsoft Azure, AWS, and Google Cloud. The document demonstrates consumption scale, durable functions, and addressing issues like capacity planning, durability, and performance for serverless applications.
Anton Boyko "The future of serverless computing"
Are you still planning your servers capacity in CPU and RAM? Do you enjoy answering questions like “what amount of servers we need to buy to serve 10K and 10M users”? Do you enjoy paying for those servers while they are sitting idle?
In my session I will talk about the current state and the future of serverless computing. I will show several demos that show how to start using serverless computing, what are the application scenarios for it, how it can scale, what it will cost, etc.
This session will be useful for developers and architects who are seeking a way to create an app utilizing all your previous skills, but make it scalable, reliable, fast and cost efficient.
Robotics technical Presentation
HIGH PERFORMANCE EDGE DATA PROCESSING SOFTWARE FOR ROBOTIC APPLICATIONS
Robotic edge autonomous systems is a fast growing market with as fast growing challenges:
Sophisticated applications,
Increasing demand in complexity:
Communications with other systems,
Heavy algorithms: AI, vision navigation, etc. Hardware has improved substantially:
- Better embedded computers
- Improved sensors (more and faster data)
https://klepsydra.com/demos-media/#earth-observation-throughput
Surge 2013: Maximizing Scalability, Resiliency, and Engineering Velocity in t...
Surge 2013 presentation which covers how Netflix maximizes engineering velocity while keeping risks to scalability, reliability, and performance in check.
Kubernetes at NU.nl (Kubernetes meetup 2019-09-05)
Slides of the presentation about Kubernetes practices and learnings at NU.nl.
This presentation was the first of two at the Dutch Kubernetes meetup at the Sanoma Netherlands offices, that took place on Sept. 5th 2019
Intro to High Performance Computing in the AWS Cloud
Visit http:aws.amazon.com/hpc for more information about HPC on AWS.
High Performance Computing (HPC) allows scientists and engineers to solve complex science, engineering, and business problems using applications that require high bandwidth, low latency networking, and very high compute capabilities. AWS allows you to increase the speed of research by running high performance computing in the cloud and to reduce costs by providing Cluster Compute or Cluster GPU servers on-demand without large capital investments. You have access to a full-bisection, high bandwidth network for tightly-coupled, IO-intensive workloads, which enables you to scale out across thousands of cores for throughput-oriented applications.
More Nines for Your Dimes: Improving Availability and Lowering Costs using Au...
Running your Amazon EC2 instances in Auto Scaling groups allows you to improve your application's availability right out of the box. Auto Scaling replaces impaired or unhealthy instances automatically to maintain your desired number of instances (even if that number is one). You can also use Auto Scaling to automate the provisioning of new instances and software configurations as well as to track of usage and costs by app, project, or cost center. Of course, you can also use Auto Scaling to adjust capacity as needed - on demand, on a schedule, or dynamically based on demand. In this session, we show you a few of the tools you can use to enable Auto Scaling for the applications you run on Amazon EC2.
The Need of Cloud-Native Application
Where SOA and Monolitch EAR have failed. It's not simple to have your Apps scaling automagically without a very complex architecture. We're going to show pros and cons of so called Cloud-Native Applications based on Microservices, Caas, DevOps, Continuous Delivery....
Taming the cost of your first cloud - CCCEU 2014
Today everyone is talking about clouds, and a few are building them, but far fewer are operating successful clouds. In this session we'll examine a variety of paradigm shifts IT makes when moving from a traditional virtualization and management mindset to operating a successful cloud. For most organizations, without careful planning the hype of a cloud solution can quickly overcome its capabilities and pre-existing best practices can combine to create the worst possible cloud scenario -- a cloud which isn't economical to operate, and which is more cumbersome to manage than a traditional virtualization farm.
Key topics covered include:
- Successful transition of operational and management paradigm
- How the VM density of clouds change Ops
- What it means to monitor the network in a cloud environment, at hyper-dense virtualization levels
- Preventing storage costs from outpacing delivery costs
Building Reactive applications with Akka
The document discusses building reactive applications using Akka. Akka allows for building applications that are message-driven, elastic, resilient and able to handle failures. It enables building applications as systems of actors that communicate asynchronously by message passing. This model allows the applications to scale horizontally across clusters of machines and to recover from failures through supervision. The document provides examples of how to model parts of an application, such as a flight search service, as actor systems.
(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk
AWS Elastic Beanstalk provides an easy way for you to quickly deploy, manage, and scale applications in the AWS cloud. Through interactive demos and code samples, this session will teach you how to deploy your code to Elastic Beanstalk, provision and use additional AWS resources (for example, Amazon SNS, Amazon SQS, and Amazon DynamoDB), use your application’s health metrics to tune performance, scale your application to handle millions of requests, and perform zero-downtime deployments with traffic routing. Demos and code samples will be available to all session attendees.
Serverless on AWS : Understanding the hard parts at Froscon 2019
In unserem Vortrag tauchen wir tiefer in die Serverless-Welt ein und zeigen wie eine produktionsreife Serverless-Anwendung mithilfe von AWS-Cloud mit dem Technologie-Stack API Gateway, SNS, Lambda and DynamoDB aufgebaut werden kann. Dabei gehen wir auf die Herausforderungen der jeweiligen Services ein, wie "cold start" bei Lamda oder "provisioned throughput" und "adaptice capacity" bei DynamoDB. Dabei zeigen wir, welche Strategien und Wege es gibt, damit umzugehen. Außerdem behandeln wir solche Themen wie Implementierung von Aggregationslogik und (Scheduled) Auto Scaling bei DynamoDB. Am Ende werfen wir einen Blick in die Zukunft und sprechen über die erste relationale serverless Datenbank "Aurora Serverless"
Univa Presentation at DAC 2020
At this year’s annual Design Automation Conference (DAC 2020), Rob Lalonde and Bill Bryce of Univa partnered with representatives from Google and Synopsys to discuss EDA in the Cloud and share best practices related to cloud migration.
“Spikey Workloads” Emergency Management in the Cloud
“Spikey Workloads”:
Emergency Management in the Cloud
One of the best use cases for the cloud involves websites with surges in computing needs. This session will feature organizations that have leveraged the cloud to handle their unique burst workloads without breaking the bank:
Speaker: , Solutions Architect, Amazon Web Services
“Spikey Workloads” Emergency Management in the Cloud
One of the best use cases for the cloud involves websites with surges in computing needs. This session will feature organizations that have leveraged the cloud to handle their unique burst workloads without breaking the bank:
Speaker: Cameron Maxwell, Professional Services, Amazon Web Services
Intel Atom Processor Pre-Silicon Verification Experience
This document discusses the verification methodology and results for the Intel Atom processor. It describes the challenges of verifying a new microarchitecture with power management features on an aggressive schedule. The methodology involved cluster-level validation with functional coverage, architectural validation using an instruction set generator, and power management validation. Verification metrics like coverage and bug rates were tracked. The results included booting Windows and Linux 10 hours after receiving silicon, with few functional bugs found post-silicon that weren't corner cases. Debug and survivability features helped reduce escapes.
Intel open stack-summit-session-nov13-final
- Intel is a major contributor to OpenStack and open source projects, contributing across every layer of the OpenStack stack. As the #2 Linux kernel contributor, Intel helps improve performance, stability, and efficiency.
- Intel enables OpenStack cloud deployments through contributions to OpenStack projects, open source tools, and optimizations. Intel IT also uses OpenStack in their own private cloud.
- Intel is working on technologies to address challenges in datacenters, including security and compliance, cost reduction, and business uptime. Technologies include trusted compute pools, erasure coding, and enhanced platform awareness.
CloudOps_tool.pptx
CloudDBOps is Ashnik's automation focussed UI tool which can help you seamlessly install and configure multiple technologies like Postgres, MongoDB, Elastic(ELK), Monitoring
Webinar_CloudOps final.pptx
Database automation tools are needed to automate repetitive tasks, reduce risks from manual errors, improve alignment between business and IT, and allow organizations to move faster. They help keep systems running smoothly through monitoring, provisioning, backup/restore, maintenance, security, and more. When choosing a tool, organizations should consider ease of implementation, breadth of use cases covered, ability to work on-premises and in the cloud, long-term costs, customizability, learning curve, and do a trial run.
More Related Content
Similar to Autoscaling in Kubernetes (K8s)
IEEE 2014 JAVA CLOUD COMPUTING PROJECTS Automatic scaling of internet applica...
IEEE 2014 JAVA CLOUD COMPUTING PROJECTS Automatic scaling of internet applica...IEEEGLOBALSOFTSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.orgCray HPC Environments for Leading Edge Simulations
This presentation is from the PBS User Group 2013, as presented by Greg Clifford.
"Cray scalable solutions are optimized for complex simulations, where parallel and massively concurrent applications need access to data, fast. This presentation will cover recent updates from Cray, showing how Cray continues to deliver the largest production supercomputers leveraging Altair PBS Works and HyperWorks software solutions."
Learn more: http://www.altairatc.com/page.aspx?region=na&name=agenda
Watch the presentation video: http://insidehpc.com/2013/10/04/cray-hpc-environments-leading-edge-simulation/
Ceilosca
See what happens when you overlay Ceilometer functionalities on top of a scalable solution like Monasca ... This is Ceilosca
Anton Boyko, "The evolution of microservices platform or marketing gibberish"
This document discusses Azure Functions and serverless computing. It provides an overview of serverless benefits like manage less, micro-pricing, and ease of scale. It also compares common serverless offerings from Microsoft Azure, AWS, and Google Cloud. The document demonstrates consumption scale, durable functions, and addressing issues like capacity planning, durability, and performance for serverless applications.
Anton Boyko "The future of serverless computing"
Are you still planning your servers capacity in CPU and RAM? Do you enjoy answering questions like “what amount of servers we need to buy to serve 10K and 10M users”? Do you enjoy paying for those servers while they are sitting idle?
In my session I will talk about the current state and the future of serverless computing. I will show several demos that show how to start using serverless computing, what are the application scenarios for it, how it can scale, what it will cost, etc.
This session will be useful for developers and architects who are seeking a way to create an app utilizing all your previous skills, but make it scalable, reliable, fast and cost efficient.
Robotics technical Presentation
HIGH PERFORMANCE EDGE DATA PROCESSING SOFTWARE FOR ROBOTIC APPLICATIONS
Robotic edge autonomous systems is a fast growing market with as fast growing challenges:
Sophisticated applications,
Increasing demand in complexity:
Communications with other systems,
Heavy algorithms: AI, vision navigation, etc. Hardware has improved substantially:
- Better embedded computers
- Improved sensors (more and faster data)
https://klepsydra.com/demos-media/#earth-observation-throughput
Surge 2013: Maximizing Scalability, Resiliency, and Engineering Velocity in t...
Surge 2013 presentation which covers how Netflix maximizes engineering velocity while keeping risks to scalability, reliability, and performance in check.
Kubernetes at NU.nl (Kubernetes meetup 2019-09-05)
Slides of the presentation about Kubernetes practices and learnings at NU.nl.
This presentation was the first of two at the Dutch Kubernetes meetup at the Sanoma Netherlands offices, that took place on Sept. 5th 2019
Intro to High Performance Computing in the AWS Cloud
Visit http:aws.amazon.com/hpc for more information about HPC on AWS.
High Performance Computing (HPC) allows scientists and engineers to solve complex science, engineering, and business problems using applications that require high bandwidth, low latency networking, and very high compute capabilities. AWS allows you to increase the speed of research by running high performance computing in the cloud and to reduce costs by providing Cluster Compute or Cluster GPU servers on-demand without large capital investments. You have access to a full-bisection, high bandwidth network for tightly-coupled, IO-intensive workloads, which enables you to scale out across thousands of cores for throughput-oriented applications.
More Nines for Your Dimes: Improving Availability and Lowering Costs using Au...
Running your Amazon EC2 instances in Auto Scaling groups allows you to improve your application's availability right out of the box. Auto Scaling replaces impaired or unhealthy instances automatically to maintain your desired number of instances (even if that number is one). You can also use Auto Scaling to automate the provisioning of new instances and software configurations as well as to track of usage and costs by app, project, or cost center. Of course, you can also use Auto Scaling to adjust capacity as needed - on demand, on a schedule, or dynamically based on demand. In this session, we show you a few of the tools you can use to enable Auto Scaling for the applications you run on Amazon EC2.
The Need of Cloud-Native Application
Where SOA and Monolitch EAR have failed. It's not simple to have your Apps scaling automagically without a very complex architecture. We're going to show pros and cons of so called Cloud-Native Applications based on Microservices, Caas, DevOps, Continuous Delivery....
Taming the cost of your first cloud - CCCEU 2014
Today everyone is talking about clouds, and a few are building them, but far fewer are operating successful clouds. In this session we'll examine a variety of paradigm shifts IT makes when moving from a traditional virtualization and management mindset to operating a successful cloud. For most organizations, without careful planning the hype of a cloud solution can quickly overcome its capabilities and pre-existing best practices can combine to create the worst possible cloud scenario -- a cloud which isn't economical to operate, and which is more cumbersome to manage than a traditional virtualization farm.
Key topics covered include:
- Successful transition of operational and management paradigm
- How the VM density of clouds change Ops
- What it means to monitor the network in a cloud environment, at hyper-dense virtualization levels
- Preventing storage costs from outpacing delivery costs
Building Reactive applications with Akka
The document discusses building reactive applications using Akka. Akka allows for building applications that are message-driven, elastic, resilient and able to handle failures. It enables building applications as systems of actors that communicate asynchronously by message passing. This model allows the applications to scale horizontally across clusters of machines and to recover from failures through supervision. The document provides examples of how to model parts of an application, such as a flight search service, as actor systems.
(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk
AWS Elastic Beanstalk provides an easy way for you to quickly deploy, manage, and scale applications in the AWS cloud. Through interactive demos and code samples, this session will teach you how to deploy your code to Elastic Beanstalk, provision and use additional AWS resources (for example, Amazon SNS, Amazon SQS, and Amazon DynamoDB), use your application’s health metrics to tune performance, scale your application to handle millions of requests, and perform zero-downtime deployments with traffic routing. Demos and code samples will be available to all session attendees.
Serverless on AWS : Understanding the hard parts at Froscon 2019
In unserem Vortrag tauchen wir tiefer in die Serverless-Welt ein und zeigen wie eine produktionsreife Serverless-Anwendung mithilfe von AWS-Cloud mit dem Technologie-Stack API Gateway, SNS, Lambda and DynamoDB aufgebaut werden kann. Dabei gehen wir auf die Herausforderungen der jeweiligen Services ein, wie "cold start" bei Lamda oder "provisioned throughput" und "adaptice capacity" bei DynamoDB. Dabei zeigen wir, welche Strategien und Wege es gibt, damit umzugehen. Außerdem behandeln wir solche Themen wie Implementierung von Aggregationslogik und (Scheduled) Auto Scaling bei DynamoDB. Am Ende werfen wir einen Blick in die Zukunft und sprechen über die erste relationale serverless Datenbank "Aurora Serverless"
Univa Presentation at DAC 2020
At this year’s annual Design Automation Conference (DAC 2020), Rob Lalonde and Bill Bryce of Univa partnered with representatives from Google and Synopsys to discuss EDA in the Cloud and share best practices related to cloud migration.
“Spikey Workloads” Emergency Management in the Cloud
“Spikey Workloads”:
Emergency Management in the Cloud
One of the best use cases for the cloud involves websites with surges in computing needs. This session will feature organizations that have leveraged the cloud to handle their unique burst workloads without breaking the bank:
Speaker: , Solutions Architect, Amazon Web Services
“Spikey Workloads” Emergency Management in the Cloud
One of the best use cases for the cloud involves websites with surges in computing needs. This session will feature organizations that have leveraged the cloud to handle their unique burst workloads without breaking the bank:
Speaker: Cameron Maxwell, Professional Services, Amazon Web Services
Intel Atom Processor Pre-Silicon Verification Experience
This document discusses the verification methodology and results for the Intel Atom processor. It describes the challenges of verifying a new microarchitecture with power management features on an aggressive schedule. The methodology involved cluster-level validation with functional coverage, architectural validation using an instruction set generator, and power management validation. Verification metrics like coverage and bug rates were tracked. The results included booting Windows and Linux 10 hours after receiving silicon, with few functional bugs found post-silicon that weren't corner cases. Debug and survivability features helped reduce escapes.
Intel open stack-summit-session-nov13-final
- Intel is a major contributor to OpenStack and open source projects, contributing across every layer of the OpenStack stack. As the #2 Linux kernel contributor, Intel helps improve performance, stability, and efficiency.
- Intel enables OpenStack cloud deployments through contributions to OpenStack projects, open source tools, and optimizations. Intel IT also uses OpenStack in their own private cloud.
- Intel is working on technologies to address challenges in datacenters, including security and compliance, cost reduction, and business uptime. Technologies include trusted compute pools, erasure coding, and enhanced platform awareness.
Similar to Autoscaling in Kubernetes (K8s) (20)
IEEE 2014 JAVA CLOUD COMPUTING PROJECTS Automatic scaling of internet applica...
IEEE 2014 JAVA CLOUD COMPUTING PROJECTS Automatic scaling of internet applica...
Cray HPC Environments for Leading Edge Simulations
Cray HPC Environments for Leading Edge Simulations
Anton Boyko, "The evolution of microservices platform or marketing gibberish"
Anton Boyko, "The evolution of microservices platform or marketing gibberish"
Surge 2013: Maximizing Scalability, Resiliency, and Engineering Velocity in t...
Surge 2013: Maximizing Scalability, Resiliency, and Engineering Velocity in t...
Kubernetes at NU.nl (Kubernetes meetup 2019-09-05)
Kubernetes at NU.nl (Kubernetes meetup 2019-09-05)
Intro to High Performance Computing in the AWS Cloud
Intro to High Performance Computing in the AWS Cloud
More Nines for Your Dimes: Improving Availability and Lowering Costs using Au...
More Nines for Your Dimes: Improving Availability and Lowering Costs using Au...
(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk
(DVO201) Scaling Your Web Applications with AWS Elastic Beanstalk
Serverless on AWS : Understanding the hard parts at Froscon 2019
Serverless on AWS : Understanding the hard parts at Froscon 2019
“Spikey Workloads” Emergency Management in the Cloud
“Spikey Workloads” Emergency Management in the Cloud
“Spikey Workloads” Emergency Management in the Cloud
“Spikey Workloads” Emergency Management in the Cloud
Intel Atom Processor Pre-Silicon Verification Experience
Intel Atom Processor Pre-Silicon Verification Experience
More from Ashnikbiz
CloudOps_tool.pptx
CloudDBOps is Ashnik's automation focussed UI tool which can help you seamlessly install and configure multiple technologies like Postgres, MongoDB, Elastic(ELK), Monitoring
Webinar_CloudOps final.pptx
Database automation tools are needed to automate repetitive tasks, reduce risks from manual errors, improve alignment between business and IT, and allow organizations to move faster. They help keep systems running smoothly through monitoring, provisioning, backup/restore, maintenance, security, and more. When choosing a tool, organizations should consider ease of implementation, breadth of use cases covered, ability to work on-premises and in the cloud, long-term costs, customizability, learning curve, and do a trial run.
Why and how to use Kubernetes for scaling of your multi-tier (n-tier) appli...
Kubernetes can be used to scale multi-tier applications by providing tools for container orchestration, including service discovery, load balancing, storage orchestration, and self-healing capabilities. It addresses challenges with traditional monolithic architectures by allowing microservices that are isolated, declarative, and can autoscale horizontally and vertically through features like horizontal pod autoscaling, vertical pod autoscaling, and cluster autoscaling. This allows applications to dynamically add or remove pods and nodes as needed to meet changing workload demands.
Zero trust in a multi tenant environment
Vault provides secure multi-tenancy by allowing the creation of namespaces that isolate "Vaults within a Vault". Each namespace can have independent authentication methods, secret engines, policies, identities and access management. Vault also enables API-driven encryption through secret engines like Transit and unified identities across multiple environments through its identity system. These capabilities allow Vault to securely store, restrict access to, and manage encryption of secrets and keys for multi-tenant infrastructure.
Deploy and automate ‘Secrets Management’ for a multi-cloud environment
Over the years, there has been a massive transition from on-premise environments to hybrid or multi-cloud, resulting in a significant increase in the adoption of cloud-native practices and technologies. However, while cloud-native methodologies offer growing benefits and are instrumental to digitalization, they can pose considerable challenges in managing secrets.
Secrets management aims to solve a lack of visibility and control on handling these highly-trusted credentials.
Deploy, move and manage Postgres across cloud platforms
Running applications in a hybrid set-up creates complexities that can increase downtime and maintenance. PostgreSQL runs across virtual, cloud, and container environments; minimizing complexity without sacrificing the performance, so you can take control. Being today’s undisputed leader of relational databases for new and modern applications, Postgres’ tools and features will enable you to swiftly deploy, move and manage your database across platforms.
Deploy, move and manage Postgres across cloud platforms
Running applications in a hybrid setup creates complexities that can increase downtime and maintenance. PostgreSQL runs across virtual, cloud, and container environments; minimizing complexity without sacrificing the performance, so you can take control. Being today’s undisputed leader of relational databases for new and modern applications, Postgres’ tools and features will enable you to swiftly deploy, move and manage your database across platforms.
Webinar Covers:
Multi-cloud strategy and trends
How EDB Postgres can pillar your cloud platform
Use cases: Postgres and its tools on-premises and multi-cloud platforms
Demo: Using Postgres tools on-premises and for diverse cloud platforms – handling back-up, monitoring, and ensuring Business Continuity Process (BCP)
The Best Approach For Multi-cloud Infrastructure Provisioning-2
The webinar covers the best approach for multi-cloud infrastructure provisioning. It discusses the complexities of multi-cloud environments and how Terraform can help with adoption. The webinar features a demo of provisioning cloud infrastructure with Terraform. It also addresses the business drivers for multi-cloud, including improving customer experience, and the challenges of multi-cloud such as the need for multiple skills and complex deployments.
The Best Approach For Multi-cloud Infrastructure Provisioning
This document discusses challenges of cloud computing and how HashiCorp's products address them. It introduces Cloud 2.0 as needing a unified control plane across networking, security, operations, and development to manage applications across private and public clouds. HashiCorp's products like Terraform for infrastructure as code, Vault for secrets management, and Consul for service discovery provide a full stack to operate in modern, dynamic cloud environments.
Which PostgreSQL is right for your multi cloud strategy? P2
The adoption of PostgreSQL in enterprises is becoming a strategic choice, more so with the adoption of Multi-Cloud now becoming a need for enterprise deployment. This availability creates multiple combinations of deployment options for you. So, it is important to identify the right strategy fitting into your organization’s needs.
Which PostgreSQL is right for your multi cloud strategy? P1
This webinar discusses strategies for using PostgreSQL in a multi-cloud environment. It will cover the different PostgreSQL deployment options for multi-cloud, including PostgreSQL-as-a-service, containerized PostgreSQL, and PostgreSQL on infrastructure-as-a-service. The webinar will also demonstrate how to automate deploying and scaling PostgreSQL. Key considerations for choosing a PostgreSQL option for multi-cloud include manageability, transportability, and automation.
Reduce the complexities of managing Kubernetes clusters anywhere 2
Learn how Kubernetes has become a critical component for deploying applications on multi-platform / multi-cloud environments and how to manage and monitor clusters running Mirantis Kubernetes Engine (formerly Docker Enterprise) using Mirantis Container Cloud, AWS, VMware and other providers.
Reduce the complexities of managing Kubernetes clusters anywhere
Learn how Kubernetes has become a critical component for deploying applications on multi-platform / multi-cloud environments and how to manage and monitor clusters running Mirantis Kubernetes Engine (formerly Docker Enterprise) using Mirantis Container Cloud, AWS, VMware and other providers.
Enhance your multi-cloud application performance using Redis Enterprise P2
This document provides an overview of Redis Enterprise. It discusses how Redis Enterprise is an in-memory multi-model database built on open source Redis that supports high-performance operational, analytics, and hybrid use cases. It offers deployment options including cloud, on-premises, and Kubernetes and supports a wide range of modern use cases including caching, transactions, streaming, messaging, and analytics workloads. Redis Enterprise provides features like high availability, security, and support for Redis modules to extend its capabilities.
Enhance your multi-cloud application performance using Redis Enterprise P1
Redis Enterprise can help enhance performance for multi-cloud applications. The webinar covered challenges of multi-cloud environments and how Redis is used, including a demo of setting up Redis across different platforms. It discussed how 72% of customers in Southeast Asia and India are adopting multi-cloud and the business benefits like improved experience, flexibility and reduced time to launch products. Challenges of multi-cloud like complex architecture and application performance were also reviewed.
Gain multi-cloud versatility with software load balancing designed for cloud-...
Over 50% organizations today are changing how they develop applications to support their digital transformation goals, and a multi-cloud strategy often plays a big role in that. For many organizations, it’s just not practical to be tied to one cloud anymore, given the flexibility of choosing the right cloud for each application.
Gain multi-cloud versatility with software load balancing designed for cloud-...
Over 50% organizations today are changing how they develop applications to support their digital transformation goals, and a multi-cloud strategy often plays a big role in that.
Enterprise-class security with PostgreSQL - 1
For businesses that handle personal data everyday, the security aspect of their database is of utmost importance.
With an increasing number of hack attacks and frauds, organizations want their open source databases to be fully equipped with the top security features.
Enterprise-class security with PostgreSQL - 2
For businesses that handle personal data everyday, the security aspect of their database is of utmost importance.
With an increasing number of hack attacks and frauds, organizations want their open source databases to be fully equipped with the top security features.
Securing Your CI Pipeline with HashiCorp Vault - P2
Today, CI/CD is becoming a practice for optimum software delivery in almost every organization. What is key is how you manage the secrets in your pipeline, especially in a large organization with multiple projects, across several teams.
Hashicorp Vault helps organizations to centrally manage secrets even in your CI/CD pipelines.
WEBINAR COVERS:
Why is it critical to secure your pipeline which needs to access a lot of important secrets in order to provision and deploy
How Vault provides a unified interface to any secret while providing tight access control and recording a detailed audit log
Customer use cases and scenarios
Demo: How to secure your CI pipeline with Vault
Watch on demand: https://bit.ly/35QCq0u
More from Ashnikbiz (20)
Why and how to use Kubernetes for scaling of your multi-tier (n-tier) appli...
Why and how to use Kubernetes for scaling of your multi-tier (n-tier) appli...
Deploy and automate ‘Secrets Management’ for a multi-cloud environment
Deploy and automate ‘Secrets Management’ for a multi-cloud environment
Deploy, move and manage Postgres across cloud platforms
Deploy, move and manage Postgres across cloud platforms
Deploy, move and manage Postgres across cloud platforms
Deploy, move and manage Postgres across cloud platforms
The Best Approach For Multi-cloud Infrastructure Provisioning-2
The Best Approach For Multi-cloud Infrastructure Provisioning-2
The Best Approach For Multi-cloud Infrastructure Provisioning
The Best Approach For Multi-cloud Infrastructure Provisioning
Which PostgreSQL is right for your multi cloud strategy? P2
Which PostgreSQL is right for your multi cloud strategy? P2
Which PostgreSQL is right for your multi cloud strategy? P1
Which PostgreSQL is right for your multi cloud strategy? P1
Reduce the complexities of managing Kubernetes clusters anywhere 2
Reduce the complexities of managing Kubernetes clusters anywhere 2
Reduce the complexities of managing Kubernetes clusters anywhere
Reduce the complexities of managing Kubernetes clusters anywhere
Enhance your multi-cloud application performance using Redis Enterprise P2
Enhance your multi-cloud application performance using Redis Enterprise P2
Enhance your multi-cloud application performance using Redis Enterprise P1
Enhance your multi-cloud application performance using Redis Enterprise P1
Gain multi-cloud versatility with software load balancing designed for cloud-...
Gain multi-cloud versatility with software load balancing designed for cloud-...
Gain multi-cloud versatility with software load balancing designed for cloud-...
Gain multi-cloud versatility with software load balancing designed for cloud-...
Securing Your CI Pipeline with HashiCorp Vault - P2
Securing Your CI Pipeline with HashiCorp Vault - P2
Recently uploaded
Generating privacy-protected synthetic data using Secludy and Milvus
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Project Management Semester Long Project - Acuity
Acuity is an innovative learning app designed to transform the way you engage with knowledge. Powered by AI technology, Acuity takes complex topics and distills them into concise, interactive summaries that are easy to read & understand. Whether you're exploring the depths of quantum mechanics or seeking insight into historical events, Acuity provides the key information you need without the burden of lengthy texts.
Choosing The Best AWS Service For Your Website + API.pptx
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
June Patch Tuesday
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
National Security Agency - NSA mobile device best practices
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Best 20 SEO Techniques To Improve Website Visibility In SERP
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
OpenID AuthZEN Interop Read Out - Authorization
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
Recently uploaded (20)
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
National Security Agency - NSA mobile device best practices
National Security Agency - NSA mobile device best practices
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
Autoscaling in Kubernetes (K8s)
- 1. Autoscaling in Kubernetes (K8s)
- 2. Autoscaling – Challenges & Advantages • Why? • Traditional autoscaling in cloud • Challenges with this approach • Autoscaling in K8s • Advantages of this approach - • Auto-scales and provides results quicker • Platform independent, HPA is a core component of any K8s distribution and will work out of the box without any changes to code
- 3. Architecture
- 4. Architecture under idle load
- 5. Architecture under heavy load
- 6. For testing purposes, we set autoscaling to increase application pod replicas when they cross over 50% of their allotted CPU usage. We have a minimum replica count of 1, and a maximum of 3. Scenario 1: Idle load • Number of users: 100 • Requests per user: 10 • Ramp up time: 10s A total of 1000 requests, by 100 users, within 10 seconds Test Scenarios Scenario 2: Heavy load • Number of users: 1000 • Requests per user: 10 • Ramp up time: 10s A total of 10000 requests, by 100 users, within 10 seconds
- 7. Demo
- 8. THANK YOU FOR ATTENDING THE WEBINAR