here's a proof-of-concept approach to process SQS messages with AWS Lambda and incorporate auto-scaling to elastically scale no. of instances of Lambda functions based on load
Serverless in production, an experience report (BuildStuff)Yan Cui
AWS Lambda has changed the way we deploy and run software, but the serverless paradigm has created new challenges to old problems: How do you test a cloud-hosted function locally? How do you monitor them? What about logging and config management? And how do we start migrating from existing architectures?
Yan Cui shares solutions to these challenges, drawing on his experience running Lambda in production and migrating from an existing monolithic architecture.
AWS Lambda from the trenches (Serverless London)Yan Cui
AWS Lambda has changed the way we deploy and run software, but this new serverless paradigm has created new challenges to old problems - how do you test a cloud-hosted function locally? How do you monitor them? What about logging and config management? And how do we start migrating from existing architectures?
In this talk Yan will discuss solutions to these challenges by drawing from real-world experience running Lambda in production and migrating from an existing monolithic architecture.
Serverless in production, an experience report (codemotion milan)Yan Cui
AWS Lambda has changed the way we deploy and run software, but the serverless paradigm has created new challenges to old problems: How do you test a cloud-hosted function locally? How do you monitor them? What about logging and config management? And how do we start migrating from existing architectures?
Yan Cui shares solutions to these challenges, drawing on his experience running Lambda in production and migrating from an existing monolithic architecture.
The Best and Worst of Cassandra-stress Tool (Christopher Batey, The Last Pick...DataStax
Making sure your Data Model will work on the production cluster after 6 months as well as it does on your laptop is an important skill. It's one that we use every day with our clients at The Last Pickle, and one that relies on tools like the cassandra-stress. Knowing how the data model will perform under stress once it has been loaded with data can prevent expensive re-writes late in the project.
In this talk Christopher Batey, Consultant at The Last Pickle, will shed some light on how to use the cassandra-stress tool to test your own schema, graph the results and even how to extend the tool for your own use cases. While this may be called premature optimisation for a RDBS, a successful Cassandra project depends on it's data model.
About the Speaker
Christopher Batey Consultant / Software Engineer, The Last Pickle
Christopher (@chbatey) is a part time consultant at The Last Pickle where he works with clients to help them succeed with Apache Cassandra as well as a freelance software engineer working in London. Likes: Scala, Haskell, Java, the JVM, Akka, distributed databases, XP, TDD, Pairing. Hates: Untested software, code ownership. You can checkout his blog at: http://www.batey.info
Clojure is a modern dynamically typed lisp. Dynamical typing is ofter associated with poor performance and runtime failures. In this talk, I'll present some of the lessons learned on building Clojure/Script systems that are both ridiculously fast and will fail fast on errors. Will compare the performance of mutable, persistent & zero-copy data structures and show how we can use interpreters and compilers to build beautiful and performant abstractions. A quick demo on how to build a simple non-blocking web server that runs idiomatic Clojure to serve millions of requests per sec.
Clojure is awesome, and it can be fast too.
Video: https://www.youtube.com/watch?v=3SSHjKT3ZmA
Serverless in production, an experience report (BuildStuff)Yan Cui
AWS Lambda has changed the way we deploy and run software, but the serverless paradigm has created new challenges to old problems: How do you test a cloud-hosted function locally? How do you monitor them? What about logging and config management? And how do we start migrating from existing architectures?
Yan Cui shares solutions to these challenges, drawing on his experience running Lambda in production and migrating from an existing monolithic architecture.
AWS Lambda from the trenches (Serverless London)Yan Cui
AWS Lambda has changed the way we deploy and run software, but this new serverless paradigm has created new challenges to old problems - how do you test a cloud-hosted function locally? How do you monitor them? What about logging and config management? And how do we start migrating from existing architectures?
In this talk Yan will discuss solutions to these challenges by drawing from real-world experience running Lambda in production and migrating from an existing monolithic architecture.
Serverless in production, an experience report (codemotion milan)Yan Cui
AWS Lambda has changed the way we deploy and run software, but the serverless paradigm has created new challenges to old problems: How do you test a cloud-hosted function locally? How do you monitor them? What about logging and config management? And how do we start migrating from existing architectures?
Yan Cui shares solutions to these challenges, drawing on his experience running Lambda in production and migrating from an existing monolithic architecture.
The Best and Worst of Cassandra-stress Tool (Christopher Batey, The Last Pick...DataStax
Making sure your Data Model will work on the production cluster after 6 months as well as it does on your laptop is an important skill. It's one that we use every day with our clients at The Last Pickle, and one that relies on tools like the cassandra-stress. Knowing how the data model will perform under stress once it has been loaded with data can prevent expensive re-writes late in the project.
In this talk Christopher Batey, Consultant at The Last Pickle, will shed some light on how to use the cassandra-stress tool to test your own schema, graph the results and even how to extend the tool for your own use cases. While this may be called premature optimisation for a RDBS, a successful Cassandra project depends on it's data model.
About the Speaker
Christopher Batey Consultant / Software Engineer, The Last Pickle
Christopher (@chbatey) is a part time consultant at The Last Pickle where he works with clients to help them succeed with Apache Cassandra as well as a freelance software engineer working in London. Likes: Scala, Haskell, Java, the JVM, Akka, distributed databases, XP, TDD, Pairing. Hates: Untested software, code ownership. You can checkout his blog at: http://www.batey.info
Clojure is a modern dynamically typed lisp. Dynamical typing is ofter associated with poor performance and runtime failures. In this talk, I'll present some of the lessons learned on building Clojure/Script systems that are both ridiculously fast and will fail fast on errors. Will compare the performance of mutable, persistent & zero-copy data structures and show how we can use interpreters and compilers to build beautiful and performant abstractions. A quick demo on how to build a simple non-blocking web server that runs idiomatic Clojure to serve millions of requests per sec.
Clojure is awesome, and it can be fast too.
Video: https://www.youtube.com/watch?v=3SSHjKT3ZmA
PHP distribuído e paralelo: multithread + stream socketsDiana Ungaro Arnos
Todo mundo sabe que hoje em dia a distribuição de um sistema pode ser um fator chave de sucesso e escalabilidade. Nós falamos de micro-serviços, load balancers, assincronismo e por aí vai. Apesar de serem conceitos extremamente importantes, a idéia aqui é tentar algo diferente: vamos usar o php como uma linguagem multithread para paralelizar a execução e stream sockets para distribuir esse processamento. Por quê? Porque podemos, porque é divertido e porque é sempre bom saber maneiras diferentes de executar tarefas complexas.
Designing a reactive data platform: Challenges, patterns, and anti-patterns Alex Silva
Presentation given at the O'Reilly Software Architecture Conference in NYC, April 2016.
Covers the key architectural decisions made behind the design of a reactive self-service data ingestion analytics platform that is able to fulfill several business use cases at massive scale, both at real-time and batch scopes, while leveraging and integrating Kafka and Spark in an efficient, easy to use way.
The presentation describes a message-driven, reactive and distributed design that leverages REST and Hypermedia protocols, and several open source frameworks and platforms, including Akka, Kafka, Hadoop and Spark.
An overview of Cassandra drivers for Java, Ruby, Python with tips and tricks for getting the most performance from Cassandra. Tune your application for low latency or high throughput.
DIY: A distributed database cluster, or: MySQL ClusterUlf Wendel
Live from the International PHP Conference 2013: MySQL Cluster is a distributed, auto-sharding database offering 99,999% high availability. It runs on Rasperry PI as well as on a cluster of multi-core machines. A 30 node cluster was able to deliver 4.3 billion (not million) read transactions per second in 2012. Take a deeper look into the theory behind all the MySQL replication/clustering solutions (including 3rd party) and learn how they differ.
What are some of the performance implications of using lambdas and what strategies can be used to address these. When might be want an alternative to using a lambda and how can we design our APIs to be flexible in this regard. What are the principles of writing low latency code in Java? How do we tune and optimize our code for low latency? When don’t we optimize our code? Where does the JVM help and where does it get in our way? How does this apply to lambdas? How can we design our APIs to use lambdas and minimize garbage?
When it Absolutely, Positively, Has to be There: Reliability Guarantees in Ka...confluent
In the financial industry, losing data is unacceptable. Financial firms are adopting Kafka for their critical applications. Kafka provides the low latency, high throughput, high availability, and scale that these applications require. But can it also provide complete reliability? As a system architect, when asked “Can you guarantee that we will always get every transaction,” you want to be able to say “Yes” with total confidence.
In this session, we will go over everything that happens to a message – from producer to consumer, and pinpoint all the places where data can be lost – if you are not careful. You will learn how developers and operation teams can work together to build a bulletproof data pipeline with Kafka. And if you need proof that you built a reliable system – we’ll show you how you can build the system to prove this too.
Delivered at the Serverless Summit 2022. Learn how to design serverless systems and tip the balance of trade-offs in your favour.
To learn how to build production-grade serverless applications, check out my upcoming workshops at productionreadyserverless.com and get 15% off with the code "serverlesssummit22".
At the heart of every event-driven architecture is a conduit for messages to flow through. AWS offers many services that can act as such conduit - EventBridge, SNS, SQS, Kinesis, DynamoDB streams, MSK, IOT Core and Amazon MQ just to name a few! These services have different characteristics and trade-offs around performance, scalability and cost. Picking the right service for your workload is not always easy. In this talk, let’s talk about how to pick the right messaging service to use in your event-driven architecture and play the game of trade-offs to your advantage.
PHP distribuído e paralelo: multithread + stream socketsDiana Ungaro Arnos
Todo mundo sabe que hoje em dia a distribuição de um sistema pode ser um fator chave de sucesso e escalabilidade. Nós falamos de micro-serviços, load balancers, assincronismo e por aí vai. Apesar de serem conceitos extremamente importantes, a idéia aqui é tentar algo diferente: vamos usar o php como uma linguagem multithread para paralelizar a execução e stream sockets para distribuir esse processamento. Por quê? Porque podemos, porque é divertido e porque é sempre bom saber maneiras diferentes de executar tarefas complexas.
Designing a reactive data platform: Challenges, patterns, and anti-patterns Alex Silva
Presentation given at the O'Reilly Software Architecture Conference in NYC, April 2016.
Covers the key architectural decisions made behind the design of a reactive self-service data ingestion analytics platform that is able to fulfill several business use cases at massive scale, both at real-time and batch scopes, while leveraging and integrating Kafka and Spark in an efficient, easy to use way.
The presentation describes a message-driven, reactive and distributed design that leverages REST and Hypermedia protocols, and several open source frameworks and platforms, including Akka, Kafka, Hadoop and Spark.
An overview of Cassandra drivers for Java, Ruby, Python with tips and tricks for getting the most performance from Cassandra. Tune your application for low latency or high throughput.
DIY: A distributed database cluster, or: MySQL ClusterUlf Wendel
Live from the International PHP Conference 2013: MySQL Cluster is a distributed, auto-sharding database offering 99,999% high availability. It runs on Rasperry PI as well as on a cluster of multi-core machines. A 30 node cluster was able to deliver 4.3 billion (not million) read transactions per second in 2012. Take a deeper look into the theory behind all the MySQL replication/clustering solutions (including 3rd party) and learn how they differ.
What are some of the performance implications of using lambdas and what strategies can be used to address these. When might be want an alternative to using a lambda and how can we design our APIs to be flexible in this regard. What are the principles of writing low latency code in Java? How do we tune and optimize our code for low latency? When don’t we optimize our code? Where does the JVM help and where does it get in our way? How does this apply to lambdas? How can we design our APIs to use lambdas and minimize garbage?
When it Absolutely, Positively, Has to be There: Reliability Guarantees in Ka...confluent
In the financial industry, losing data is unacceptable. Financial firms are adopting Kafka for their critical applications. Kafka provides the low latency, high throughput, high availability, and scale that these applications require. But can it also provide complete reliability? As a system architect, when asked “Can you guarantee that we will always get every transaction,” you want to be able to say “Yes” with total confidence.
In this session, we will go over everything that happens to a message – from producer to consumer, and pinpoint all the places where data can be lost – if you are not careful. You will learn how developers and operation teams can work together to build a bulletproof data pipeline with Kafka. And if you need proof that you built a reliable system – we’ll show you how you can build the system to prove this too.
Delivered at the Serverless Summit 2022. Learn how to design serverless systems and tip the balance of trade-offs in your favour.
To learn how to build production-grade serverless applications, check out my upcoming workshops at productionreadyserverless.com and get 15% off with the code "serverlesssummit22".
At the heart of every event-driven architecture is a conduit for messages to flow through. AWS offers many services that can act as such conduit - EventBridge, SNS, SQS, Kinesis, DynamoDB streams, MSK, IOT Core and Amazon MQ just to name a few! These services have different characteristics and trade-offs around performance, scalability and cost. Picking the right service for your workload is not always easy. In this talk, let’s talk about how to pick the right messaging service to use in your event-driven architecture and play the game of trade-offs to your advantage.
How to choose the right messaging service for your workloadYan Cui
At the heart of every event-driven architecture is a conduit for messages to flow through. AWS offers many services that can act as such conduit - EventBridge, SNS, SQS, Kinesis, DynamoDB streams, MSK, IOT Core and Amazon MQ just to name a few! These services have different characteristics and trade-offs around performance, scalability and cost. Picking the right service for your workload is not always easy. In this talk, let’s talk about how to pick the right messaging service to use in your event-driven architecture and play the game of trade-offs to your advantage.
Patterns and practices for building resilient serverless applications.pdfYan Cui
Lambda gives you multi-AZ out-of-the-box, but still, things can go wrong in production. There are region-wide outages, and performance degradation in services your function depends on can cause it to time out or error. And what if you're dealing with downstream systems that just aren't as scalable and can't handle the load you put on them? The bottom line is many things can go wrong and they often do at the worst of times. The goal of building resilient systems is not to prevent failures, but to build systems that can withstand these failures. In this talk, we will look at a number of practices and architectural patterns that can help you build more resilient serverless applications. Such as multi-region, active-active, employing DLQs and surge queues. We'll also see how we can use chaos experiments to help us identify failure modes before they manifest in production.
Serverless observability - a hero's perspectiveYan Cui
Yan Cui, an AWS Serverless Hero, will talk about the learnings from using serverless at scale.
He will cover the challenges for observability in serverless asynchronous workloads and the patterns to address those challenges, like using centralized logging, correlation IDs, tracing, lambda extensions.
How to ship customer value faster with step functionsYan Cui
Learn all about AWS Step Functions and how to use them to model business workflows and ship customer values quickly. In this session, we will talk about what is Step Functions, how to model business workflows as state machines, real-world case studies, and design patterns. By the end of this webinar, you should have a good idea of where Step Functions fit into your application and why you should use them (and why not!) to model workflows instead of building a custom solution yourself.
One of the key characteristics of serverless components is the pay-per-use pricing model. For example, with AWS Lambda, you don’t pay for the uptime of the underlying infrastructure but for the no. of invocations and how long your code actually runs for.
This important characteristic removes the need for many premature micro-optimizations as your cost is always tightly linked to usage and minimizes waste. As a result, many applications would run at a fraction of the cost if they were moved to serverless.
The pay-per-use pricing model also enables more accurate cost prediction and monitoring based on your application’s throughput. This gives rise to the notion of FinDev, where finance and development can intersect and allows optimization to be targeted to give the optimal return-on-invest on the engineering efforts.
And by building your application on serverless components, you can also leverage it as a business advantage and offer a more competitive, usage-based pricing to your customers. Which is going to be crucial at a time when businesses all around the world are affected by COVID and are looking for better efficiencies.
In this webinar, we will cover topics such as:
- How does the cost of serverless differ from serverful applications?
- How to predict and monitor cost in serverless applications?
- When should you optimize for cost?
- How can you leverage usage-based pricing as a business advantage?
Why your next serverless project should use AWS AppSyncYan Cui
In this webinar, Yan Cui and Lumigo Software Engineer Guy Moses will discuss some of the power of GraphQL and AppSync and why AppSync + Lambda + DynamoDB should be your stack of choice in 2021 and beyond!
Serverless technologies drastically simplify the task of building modern, scalable APIs in the cloud, and GraphQL makes it easy for frontend teams to consume these APIs and to iterate quickly on your product idea. Together, they are a perfect combination for a product-focused, full-stack team to deliver customer values quickly.
In this talk, see how we built a new social network mobile app in under 4 weeks using Lambda, AppSync, DynamoDB and Algolia. How we approached CI/CD, testing, authentication and lessons we learnt along the way.
Real-world serverless podcast: https://realworldserverless.com
Learn Lambda best practices: https://lambdabestpractice.com
Blog: https://theburningmonk.com
Consulting services: https://theburningmonk.com/hire-me
Production-Ready Serverless workshop: https://productionreadyserverless.com
Patterns and practices for building resilient serverless applicationsYan Cui
Lambda gives you multi-AZ out-of-the-box, but still, things can go wrong in production. There are region-wide outages, and performance degradation in services your function depends on can cause it to time out or error. And what if you're dealing with downstream systems that just aren't as scalable and can't handle the load you put on them? The bottom line is many things can go wrong and they often do at the worst of times. The goal of building resilient systems is not to prevent failures, but to build systems that can withstand these failures. In this talk, we will look at a number of practices and architectural patterns that can help you build more resilient serverless applications. Such as multi-region, active-active, employing DLQs and surge queues. We'll also see how we can use chaos experiments to help us identify failure modes before they manifest in production
How to bring chaos engineering to serverlessYan Cui
You might have heard about chaos engineering in the context of Netflix and Amazon, and how they kill EC2 servers in production at random to verify that their systems can stay up in the face of infrastructure failures. But did you know that the same ideas can be applied to serverless applications? Yes, despite not having access to the underlying servers, we can still apply principles of chaos engineering to uncover failure modes in our system (and there are plenty!) so we can build a defence against them and make our serverless applications more robust and more resilient!
Migrating existing monolith to serverless in 8 stepsYan Cui
Refactoring a monolith to serverless can be intimidating, but there are discrete steps that you can take to simplify the process. In this talk, AWS Serverless Hero Yan Cui outlines 8 steps to successfully refactor your monolith and highlight key decision points such as language and tooling choices.
Building a social network in under 4 weeks with Serverless and GraphQLYan Cui
Serverless technologies drastically simplify the task of building modern, scalable APIs in the cloud, and GraphQL makes it easy for frontend teams to consume these APIs and to iterate quickly on your product idea. Together, they are a perfect combination for a product-focused, full-stack team to deliver customer values quickly.
In this talk, see how we built a new social network mobile app in under 4 weeks using Lambda, AppSync, DynamoDB and Algolia. How we approached CI/CD, testing, authentication and lessons we learnt along the way.
Real-world serverless podcast: https://realworldserverless.com
Learn Lambda best practices: https://lambdabestpractice.com
Blog: https://theburningmonk.com
Consulting services: https://theburningmonk.com/hire-me
Production-Ready Serverless workshop: https://productionreadyserverless.com
FinDev as a business advantage in the post covid19 economyYan Cui
The impact COVID19 has had on consumer economy, ripples out to other service providers - analytics tools, etc because everyone is going to be squeezed. And the variable-cost (or pay-as-you-use) pricing model will be more appealing as companies tighten up their budgets for non-essential services/tools.
AWS has improved Lambda cold starts by leaps and bounds in the last year. But for performance-sensitive applications such as user-facing APIs, Lambda cold starts are still a thorn in one’s side, especially when working with languages such as Java and .Net Core.
In this webinar, we will dive into strategies for improving cold start latency and how to mitigate them altogether with Provisioned Concurrency, and how Lumigo helps you optimize your use of Provisioned Concurrency.
In this session, we will look at 10 common use cases for AWS Lambda such as REST APIs, WebSockets, IoT and building event-driven systems. We will also touch on some of the latest platform features such as Provisioned Concurrency, EFS integration and Lambda Destinations and when and where we should use them.
A chaos experiment a day, keeping the outage awayYan Cui
Presented at ServerlessDays Warsaw
Recording: https://youtu.be/21HprKZQczs
You might have heard about chaos engineering in the context of Netflix and Amazon, and how they kill EC2 servers in production at random to verify that their systems can stay up in the face of infrastructure failures. But did you know that the same ideas can be applied to serverless applications? Yes, despite not having access to the underlying servers, we can still apply principles of chaos engineering to uncover failure modes in our system (and there are plenty!) so we can build defence against them and make our serverless applications more robust and more resilient!
One of the most common performance issues in serverless architectures is elevated latencies from external services, such as DynamoDB, ElasticSearch or Stripe.
In this webinar, we will show you how to quickly identify and debug these problems, and some best practices for dealing with poor performing 3rd party services.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
12. retried 3 times
dead letter queue
one invocation per message
configurable
dead letter queue
no. of pollers
13. retried 3 times
dead letter queue
one invocation per message
highest parallelism!
configurable
dead letter queue
no. of pollers
14. retried 3 times
dead letter queue
one invocation per message
consider impact on
downstream systems
consider Lambda throttling
which is per region, so other
functions can get throttled too
configurable
dead letter queue
no. of pollers
19. retried until success/expiry
NO dead letter queue
one invocation per shard
charged by shard hour + reqs
configurable
dead letter queue
no. of pollers
charged by reqs
20. retried until success/expiry configurable
NO dead letter queue dead letter queue
one invocation per shard no. of pollers
charged by shard hour + reqs charged by reqs
high baseline cost (1 shard) but
order of magnitude cheaper at scale
21. 1 msg/s for a month
(1K msgs)
1 x 60s x 60m x 24hr x 30days @ $0.4 per mil
= $1.0368
1 x 60s x 60m x 24hr x 30days @ $0.014 per mil
+
24hrs x 30days x $0.015 per hr
= $10.836
22. 1000 msg/s for a month
(1K msgs)
1000 x 60s x 60m x 24hr x 30days @ $0.4 per mil
= $1036.80
1000 x 60s x 60m x 24hr x 30days @ $0.014 per mil
+
24hrs x 30days x $0.015 per hr
= $47.088
23. “none of them is the right choice
for every situation”
24. SQS is right choice sometimes, no?
“none of them is the right choice
for every situation”