When building microservices, you must solve for a number of critical functions, but the process can be incredibly complex and expensive to maintain. Christian Posta offers an overview of Envoy Proxy and Istio.io Service Mesh, explaining how they solve application networking problems more elegantly by pushing these concerns down to the infrastructure layer and demonstrating how it all works.
This document discusses Istio, an open-source service mesh that connects, secures, and manages microservices. Istio solves challenges of running hybrid cloud deployments by providing service communication and routing, observability through metric collection, and security through features like mTLS and workload identity. The document outlines Istio's capabilities and provides an architecture for running Istio across Kubernetes and virtual machine environments. A demo is presented to illustrate Istio's capabilities in hybrid deployments.
The document discusses Christian Posta's journey with microservices architectures. It begins by explaining why organizations are moving to microservices and defines microservices. It then covers related topics like cloud platforms, container technologies like Kubernetes and OpenShift, benefits and drawbacks of microservices, and tools for developing microservices like Docker, Kubernetes, OpenShift, and Camel.
The Hardest Part of Microservices: Your Data - Christian Posta, Red Hat
Christian Posta, principal architect at Red Hat discusses how to manage your data within a microservices architecture at the 2017 Microservices.com Practitioner Summit.
Microservices with Apache Camel, DDD, and Kubernetes
Building microservices requires more than just infrastructure, but infrastructure does have a role. In this talk we look at microservices from an enterprise perspective and talk about DDD, Docker, Kubernetes and how established open-source projects in the integration space fits a microservices architecture
Microservices and Integration: what's next with Istio service mesh
This document discusses microservices architectures and emerging technologies to support them. It introduces Envoy proxy as a sidecar proxy that implements common microservices patterns like circuit breaking and load balancing. It then introduces Istio as a control plane that manages Envoy proxies and provides higher-level capabilities like traffic management, security, and observability across microservices. The presentation argues that 2018 will be the year of service meshes, with Istio being a prominent example for managing microservices communication using Envoy proxies.
10 yrs ago, SOA promised a lot of the same things Microservices promise use today. So where did we go wrong? What makes microservices different? In this talk, we discussed from an architectural view how we went sideways with SOA, why we must embrace things like Domain Driven Design and scaled-out architectures, and how microservices can be built with enterprises in mind. We also cover a step-by-step, in-depth tutorial that covers these concepts.
Service-mesh technology promises to deliver a lot of value to a cloud-native application, but it doesn't come without some hype. In this talk, we'll look at what is a "service mesh", how it compares to similar technology (Netflix OSS, API Management, ESBs, etc) and what options for service mesh exist today.
The document discusses continuous delivery of integration applications using JBoss Fuse and OpenShift. It covers the cost of change in software development, how JBoss Fuse can help with integration challenges, and how OpenShift enables continuous delivery through automation and a developer self-service platform as a service model. The presentation demonstrates how to build a continuous delivery pipeline using tools like Git, Jenkins, Fabric8, and OpenShift to deploy and test applications.
The document discusses microservices and APIs. It covers how microservices optimize for speed by shedding dependencies and having dependencies on demand through services and APIs. It discusses consumer contracts for APIs and service versioning. It also discusses using an API gateway pattern for scalability, security, monitoring and more. It promotes API management for benefits like access control, analytics, and monetization of microservices.
Making sense of microservices, service mesh, and serverless
As companies move to become digital, we can get sidetracked and distracted by some of the changes in the technology landscape. Ideally we will be harnessing technology to solve the problems we have and leverage it to deliver software faster and safer. In this talk, I'll we'll take a look at some new technology trends in the open-source communities and when and how to use them.
This document discusses microservices with Docker, Kubernetes and Jenkins. It provides an overview of Kubernetes concepts like pods, replication controllers, services and labels. It also discusses how Kubernetes can help manage containers across multiple hosts and address challenges of scaling, avoiding port conflicts and keeping containers running. The document promotes using Jenkins and Kubernetes for continuous integration and delivery of containerized microservices applications. It recommends Fabric8 as a tool that can help create and deploy microservices on Kubernetes.
Real-world #microservices with Apache Camel, Fabric8, and OpenShift
What are and aren't microservices?
Microservices is a validation of the open-source approach to integration and service implementation and a rebuff of the committee-driven SOA approach. In this
Using apache camel for microservices and integration then deploying and managing on Docker and Kubernetes. When we need to make changes to our app, we can use Fabric8 continuous delivery built on top of Kubernetes and OpenShift.
Knative builds on Kubernetes and Istio to provide "PaaS-like abstractions" that raise the level of abstraction for specifying, running, and modifying applications. Knative includes building blocks like Knative Serving for autoscaling container workloads to zero, Knative Eventing for composing event-driven services, Knative Build for building containers from source, and Knative Pipelines for abstracting CI/CD pipelines. While Knative can run any type of container, its building blocks help enable serverless-style functions by allowing compute resources to scale to zero and be driven by event loads.
Topics covered:
1. Generating a new Remix project
2. Conventional files
3. Routes (including the nested variety)
4. Styling
5. Database interactions (via sqlite and prisma)
6. Mutations, Validation, and Authentication
7. Error handling
8. SEO with Meta Tags and much more
This document discusses integration in the age of DevOps. It describes how microservices help solve the problem of decoupling services and teams to move quickly at scale. Apache Camel is presented as a solution for integration that allows for reliable and distributed integration through mechanisms like messaging. Kubernetes and Docker are discussed as platforms that help develop and run microservices locally and at scale by providing automation, configuration, isolation and service discovery capabilities.
Service-mesh technology promises to deliver a lot of value to a cloud-native application, but it doesn't come without some hype. In this talk, we'll look at what is a "service mesh", how it compares to similar technology (Netflix OSS, API Management, ESBs, etc) and what options for service mesh exist today.
Evolution of integration and microservices patterns with service mesh
Cloud-native describes a way of building applications on a cloud platform to iteratively discover and deliver business value. We now have access to a lot of similar technology that the large internet companies pioneered and used to their advantage to dominate their respective markets. What challenges arise when we start building applications to take advantage of this new technology?
In this mini-conference, we'll cover what it means to build applications with microservices, how cloud-native integration and concepts like service mesh have evolved to solve some of those problems, and how the next iteration of application development with Functions as a Service (FaaS) and serverless computing fit into this landscape.
You'll hear from industry experts Burr Sutter and Christian Posta who recently authored a book Introducing Istio Service Mesh for Microservices about these topics.
Attendees should come away from this mini-conference with the following:
Understanding of what cloud-native means and how to use it to influence positive business outcomes
How integration has evolved to create, connect and manage cloud-native APIs
How service-mesh technology like Istio can solve the challenges introduced with cloud-native applications
How the next iteration of applications deliver with FaaS and serverless computing fits in with a world of monoliths, microservices, and APIs
These talks will be of value for developers, architects, operators, platform directors, and technology leaders.
After the presentations, please stay and join Christian, Burr and your peers for networking, food and drinks. All attendees will also receive a copy of Christian and Burr's new book: Introducing Istio Service Mesh for Microservices.
Role of Integration and Service Mesh in Cloud Native Architecture KubeCon 2108
Building useful services across our collection of existing applications, microservices, and now functions, we see a common theme: services must be able to communicate with each other, and solve problems like data mediation, routing, policy enforcement, security, and others. Service mesh is a technology that has emerged in container-based environments to help solve some of these problems; however, not all of them can be solved by pushing the problems to a different abstraction. Understanding the role and responsibility of service mesh and application-integration frameworks can help you successfully build useful business services on a cloud native platform. This talk will help you understand those roles and responsibilities and how service mesh and application integration co-exist to build cloud native applications.
Evolution of integration and microservices patterns with service mesh
The document discusses the evolution of integration and microservice patterns with service mesh technologies like Istio. It describes how service meshes provide decentralized application networking infrastructure between services through a data plane and control plane. This includes features like advanced load balancing, traffic control, observability, and policy enforcement that help improve resilience, security, and reliability of distributed applications.
This document provides an overview of microservices from Christian Posta, a chief architect at Red Hat. It discusses what microservices are, reasons for using them, common microservices patterns and frameworks, decomposing monolithic applications into microservices, and ensuring resilience between services. The presentation also covers using Kubernetes and OpenShift for microservices and demonstrates sample applications.
Most large-scale web companies have evolved their system architecture from a monolithic application and monolithic database to a set of loosely coupled micro-services. Using examples from Google, eBay, and KIXEYE, this talk outlines the pros and cons of these different stages of evolution, and makes practical suggestions about when and how other organizations should consider migrating to micro-services. It concludes with some more advanced implications of a micro-services architecture, including SLAs, cost-allocation, and vendor-customer relationships within the organization.
Early Draft: Service Mesh allows developers to focus on business logic while the crosscutting network data layer code is handled by the Service Mesh. This is a boon because this code can be tricky to implement and hard to test all of the edge cases. Service Mesh takes this a few steps further than AOP or Servlet Filters or custom language-specific frameworks because it works regardless of the underlying programming language being used which is great for polyglot development shops. Thus standardizing how these layers work, while allowing teams to pick the best tools or languages for the job at hand. Kubernetes and Istio Service Mesh automate best practices for DevSecOps needs like: failover, scale-out, scalability, health checks, circuit breakers, rate limiters, metrics, observability, avoiding cascading failure, disaster recovery, and traffic routing; supporting CI/CD and microservices architecture.
Istio’s ability to automate and maintaining zero trust networks is its most important feature. In the age of high-profile data breaches, security is paramount. Companies want to avoid major brand issues that impact the bottom line and shrink market capitalization in an instant. Istio allows a standard way to do mTLS and auto certificate rotation which helps prevent a breach and limits the blast radius if a breach occurs. Istio also takes the concern of mTLS from microservices deployments and makes it easy to use taking the burden off of application developers.
The evolution of micro services architecture. Mainframe, Midrange, Client Server, SOA. Best practices of microservices. Load balancing, BigData, design patterns. When and why to use microservices.
These are my summarized notes from all the microservices session I attended at QCon 2015. These sessions had tons of learning around how to scale microservices and avoid common pitfalls
The document discusses strategies for transitioning from monolithic architectures to microservice architectures. It outlines some of the challenges with maintaining large monolithic applications and reasons for modernizing, such as handling more data and needing faster changes. It then covers microservice design principles and best practices, including service decomposition, distributed systems strategies, and reactive design. Finally it introduces Lagom as a framework for building reactive microservices on the JVM and outlines its key components and development environment.
Bol.com Tech lab September 2017 - Microservices in action at the Dutch Nation...
3 DevOps teams are building high tech big data web applications in a private cloud environment to support police work. These teams use microservices architectures, with separate front-end and back-end components developed independently but integrated via service discovery. Testing includes unit, integration, and load testing across feature branches in a continuous integration environment before production deployment. Future work includes improving zero downtime deployments, modularizing the front-end, and automating security testing.
Cloud-native Data: Every Microservice Needs a Cache
Presented at the Pivotal Toronto Users Group, March 2017
Cloud-native applications form the foundation for modern, cloud-scale digital solutions, and the patterns and practices for cloud-native at the app tier are becoming widely understood – statelessness, service discovery, circuit breakers and more. But little has changed in the data tier. Our modern apps are often connected to monolithic shared databases that have monolithic practices wrapped around them. As a result, the autonomy promised by moving to a microservices application architecture is compromised.
With lessons from the application tier to guide us, the industry is now figuring out what the cloud-native architectural patterns are at the data tier. Join us to explore some of these with Cornelia Davis, a five year Cloud Foundry veteran who is now focused on cloud-native data. As it happens, every microservice needs a cache and this evening will drill deep on that topic. She’ll cover a variety of caching patterns and use cases, and demonstrate how their use helps preserve the autonomy that is driving agile software delivery practices today.
JavaZone 2017 - Microservices in action at the Dutch National Police
3 DevOps teams at the Dutch National Police are building big data applications in a private cloud using microservices architecture. They develop independently but coordinate planning. Testing includes unit, integration, end-to-end, load, and mutation tests. Features are developed on branches and deployed continuously to test and production after sprints. Challenges include balancing security and performance for stateless services and preventing monolithic frontends. They aim to improve with zero downtime deployments, product teams, and automated security testing.
Microservices in action at the Dutch National Police
3 DevOps teams at the Dutch National Police are building big data applications in a private cloud using microservices architecture. They develop using techniques like continuous delivery, short feedback loops, and embrace of change. Challenges include balancing performance and security with stateless services, minimizing dependencies between teams, and preventing monolithic frontends. Future plans include zero downtime deployments, cross-functional product teams, and a modular frontend.
OpenValue meetup October 2017 - Microservices in action at the Dutch National...
3 DevOps teams at the Dutch National Police are building big data applications in a private cloud using microservices architecture. They develop independently but coordinate planning. Testing includes unit, integration, end-to-end, load, and mutation tests. Features are developed on branches and merged/deployed continuously. Services register with Consul for service discovery. Challenges include balancing security and performance for stateless services and preventing monolithic frontends. Future plans include zero downtime deployments and cross-functional product teams.
From Monoliths to Services: Paying Your Technical Debt
This document discusses transitioning from monolithic applications to microservices and serverless architectures. It begins by defining technical debt and explaining how microservices can help pay it down incrementally. It then covers different architectural styles like monoliths and microservices. The rest of the document discusses moving to cloud infrastructure, breaking apart monolithic applications into independent services, communication between services, leveraging third-party services, and security considerations for microservices.
You know that adopting Continuous Delivery is key to a high-performance company. You’ve read the books and are ready to build microservices in the cloud. Great! Let’s go back to the principles and see how to apply them in a cloud native environment. What used to be about shipping code to static servers, is now about quickly creating decoupled pipelines for new services that are readily wired up into the platform, and everything is driven by code. This talk will give concrete guidance for a world where autonomous teams continuously deploy many independent services and containers into an infrastructure that is dynamically created via APIs. Release without staging environment, but with confidence.
Learn how to apply cloud native concepts to the delivery pipeline itself and how the concepts of continuous delivery need to be adjusted for microservices in the cloud. Hear real world examples, including how to QA in production.
Christian Posta is a principal middleware specialist and architect who has worked with large microservices architectures. He discusses why companies are moving to microservices and cloud platforms like Kubernetes and OpenShift. He covers characteristics of microservices like small autonomous teams and decentralized decision making. Posta also discusses breaking applications into independent services, shedding dependencies between teams, and using contracts and APIs for communication between services.
Dublin Microservice "Introduction to Service Meshes"
While service meshes may be the next "big thing" in microservices, the concept isn't new. Classical SOA attempted to implement similar technology for abstracting and managing all aspects of service-to-service communication, and this was often realized as the much-maligned Enterprise Service Bus (ESB). Several years ago similar technology emerged from the microservice innovators, including Airbnb (SmartStack for service discovery), Netflix (Prana integration sidecars), and Twitter (Finagle for extensible RPC), and these technologies have now converged into the service meshes we are currently seeing being deployed.
In this talk, Daniel Bryant will share with you what service meshes are, why they are (and sometimes are not) well-suited for microservice deployments, and how best to use a service mesh when you're deploying microservices. This presentation begins with a brief history of the development of service meshes, and the motivations of the unicorn organisations that developed them. From there, you'll learn about some of the currently available implementations that are targeting microservice deployments, such as Istio/Envoy, Linkerd, and NGINX Plus.
Microservices architecture is a very powerful way to build scalable systems optimized for speed of change. To do this, we need to build independent, autonomous services which by definition tend to minimize dependencies on other systems. One of the tenants of microservices, and a way to minimize dependencies, is “a service should own its own database”. Unfortunately this is a lot easier said than done. Why? Because: your data.
We’ve been dealing with data in information systems for 5 decades so isn’t this a solved problem? Yes and no. A lot of the lessons learned are still very relevant. Traditionally, we application developers have accepted the practice of using relational databases and relying on all of their safety guarantees without question. But as we build services architectures that span more than one database (by design, as with microservices), things get harder. If data about a customer changes in one database, how do we reconcile that with other databases (especially where the data storage may be heterogenous?).
For developers focused on the traditional enterprise, not only do we have to try to build fast-changing systems that are surrounded by legacy systems, the domains (finance, insurance, retail, etc) are incredibly complicated. Just copying with Netflix does for microservices may or may not be useful. So how do we develop and reason about the boundaries in our system to reduce complexity in the domain?
In this talk, we’ll explore these problems and see how Domain Driven Design helps grapple with the domain complexity. We’ll see how DDD concepts like Entities and Aggregates help reason about boundaries based on use cases and how transactions are affected. Once we can identify our transactional boundaries we can more carefully adjust our needs from the CAP theorem to scale out and achieve truly autonomous systems with strictly ordered eventual consistency. We’ll see how technologies like Apache Kafka, Apache Camel and Debezium.io can help build the backbone for these types of systems. We’ll even explore the details of a working example that brings all of this together.
Developer's time is the most crucial resource in an enterprise IT organization. Too much time is spent on undifferentiated heavy lifting and in the world of APIs and microservices much of that is spent on non-functional, cross-cutting networking requirements like security, observability, and resilience.
As organizations reconcile their DevOps practices into Platform Engineering, tools like Istio help alleviate developer pain. In this talk we dig into what that pain looks like, how much it costs, and how Istio has solved these concerns by examining three real-life use cases. As this space continues to emerge, and innovation has not slowed, we will also discuss the recently announced Istio sidecar-less mode which significantly reduces the hurdles to adopt Istio within Kubernetes or outside Kubernetes.
Comparing Sidecar-less Service Mesh from Cilium and Istio
Service mesh is a powerful pattern for implementing strong zero-trust networking practices, introducing better network observability, and allowing for more fine-grained traffic control. Up until now, the sidecar pattern was used to implement service-mesh capability but as the technology matures, a new pattern has emerged: sidecarless service mesh. Two prominent open-source networking projects, Cilium and Istio, have implemented a sidecar-free approach to service mesh but they both make interesting design decisions and tradeoffs. In this talk we review the architecture of both, focusing on the pros and cons of implementations such as mutual authentication, ingress, and observability.
Understanding Wireguard, TLS and Workload Identity
Zero Trust Networking has become a standard marketing buzzword but the underlying principles are critical for modern microservice-style architectures. Authentication, authorizations, policy, etc. can be difficult to implement between services and do so in a maintainable way. Google invented their own transparent encryption and authorization protocol called "ALTS" back in 2007 to serve the application layer of Google's Borg workload scheduler, but we don't see others using it outside Google.
In this webinar we look at existing technology like TLS and newcomer Wireguard and see how these technologies come together to provide a secure foundation for workload identity and modern service-to-service networking.
Istio ambient mesh uses a sidecar-less data plane that focuses on ease of operations, incremental adoption, and separation of security boundaries for applications and mesh infrastructure.
In this webinar, we'll explore:
- The forces of modernization and compliance pressures,
- How Zero Trust Architecture (ZTA) can help, and
- How Istio ambient mesh lowers the barrier for establishing the properties necessary to achieve Zero Trust and compliance
The document discusses Cilium and Istio with Gloo Mesh. It provides an overview of Gloo Mesh, an enterprise service mesh for multi-cluster, cross-cluster and hybrid environments based on upstream Istio. Gloo Mesh focuses on ease of use, powerful best practices built in, security, and extensibility. It allows for consistent API for multi-cluster north-south and east-west policy, team tenancy with service mesh as a service, and driving everything through GitOps.
An eventful tour from enterprise integration to serverless and functionsChristian Posta
In this talk, Marius (@mariusbogoevici) and I (@christianposta) discuss the value of event-driven architectures (both business and technical merits) and how the landscape of integration, streaming, and messaging and now functions/lambdas have evolved to implement EDA while balancing agility, utilization, and simplicity.
KubeCon NA 2018: Evolution of Integration and Microservices with Service Mesh...Christian Posta
Cloud-native describes a way of building applications on a cloud platform to iteratively discover and deliver business value. We now have access to a lot of similar technology that the large internet companies pioneered and used to their advantage to dominate their respective markets. What challenges arise when we start building applications to take advantage of this new technology?
In this talk we'll explore the role of service meshes when building distributed systems, why they make sense, and where they don't make sense. We will look at a class of problem that crops up that service mesh cannot solve, but that frameworks and even new programming languages like Ballerina are aiming to solve
We consider a microservices architecture to achieve an end goal, not because it's "the cool thing to do". Every organization looking to adopt this architecture must realize (and adhere) to a set of foundational principles. Guided by those principles, we can correctly choose the technology to help support a microservices architecture and meet our end goals. This talk explains those core principles and gives you the tools needed for your microservices journey.
This document discusses Istio, an open-source service mesh that connects, secures, and manages microservices. Istio solves challenges of running hybrid cloud deployments by providing service communication and routing, observability through metric collection, and security through features like mTLS and workload identity. The document outlines Istio's capabilities and provides an architecture for running Istio across Kubernetes and virtual machine environments. A demo is presented to illustrate Istio's capabilities in hybrid deployments.
The document discusses Christian Posta's journey with microservices architectures. It begins by explaining why organizations are moving to microservices and defines microservices. It then covers related topics like cloud platforms, container technologies like Kubernetes and OpenShift, benefits and drawbacks of microservices, and tools for developing microservices like Docker, Kubernetes, OpenShift, and Camel.
The Hardest Part of Microservices: Your Data - Christian Posta, Red HatAmbassador Labs
Christian Posta, principal architect at Red Hat discusses how to manage your data within a microservices architecture at the 2017 Microservices.com Practitioner Summit.
Microservices with Apache Camel, DDD, and KubernetesChristian Posta
Building microservices requires more than just infrastructure, but infrastructure does have a role. In this talk we look at microservices from an enterprise perspective and talk about DDD, Docker, Kubernetes and how established open-source projects in the integration space fits a microservices architecture
Microservices and Integration: what's next with Istio service meshChristian Posta
This document discusses microservices architectures and emerging technologies to support them. It introduces Envoy proxy as a sidecar proxy that implements common microservices patterns like circuit breaking and load balancing. It then introduces Istio as a control plane that manages Envoy proxies and provides higher-level capabilities like traffic management, security, and observability across microservices. The presentation argues that 2018 will be the year of service meshes, with Istio being a prominent example for managing microservices communication using Envoy proxies.
10 yrs ago, SOA promised a lot of the same things Microservices promise use today. So where did we go wrong? What makes microservices different? In this talk, we discussed from an architectural view how we went sideways with SOA, why we must embrace things like Domain Driven Design and scaled-out architectures, and how microservices can be built with enterprises in mind. We also cover a step-by-step, in-depth tutorial that covers these concepts.
Service-mesh technology promises to deliver a lot of value to a cloud-native application, but it doesn't come without some hype. In this talk, we'll look at what is a "service mesh", how it compares to similar technology (Netflix OSS, API Management, ESBs, etc) and what options for service mesh exist today.
The document discusses continuous delivery of integration applications using JBoss Fuse and OpenShift. It covers the cost of change in software development, how JBoss Fuse can help with integration challenges, and how OpenShift enables continuous delivery through automation and a developer self-service platform as a service model. The presentation demonstrates how to build a continuous delivery pipeline using tools like Git, Jenkins, Fabric8, and OpenShift to deploy and test applications.
The document discusses microservices and APIs. It covers how microservices optimize for speed by shedding dependencies and having dependencies on demand through services and APIs. It discusses consumer contracts for APIs and service versioning. It also discusses using an API gateway pattern for scalability, security, monitoring and more. It promotes API management for benefits like access control, analytics, and monetization of microservices.
Making sense of microservices, service mesh, and serverlessChristian Posta
As companies move to become digital, we can get sidetracked and distracted by some of the changes in the technology landscape. Ideally we will be harnessing technology to solve the problems we have and leverage it to deliver software faster and safer. In this talk, I'll we'll take a look at some new technology trends in the open-source communities and when and how to use them.
Java one kubernetes, jenkins and microservicesChristian Posta
This document discusses microservices with Docker, Kubernetes and Jenkins. It provides an overview of Kubernetes concepts like pods, replication controllers, services and labels. It also discusses how Kubernetes can help manage containers across multiple hosts and address challenges of scaling, avoiding port conflicts and keeping containers running. The document promotes using Jenkins and Kubernetes for continuous integration and delivery of containerized microservices applications. It recommends Fabric8 as a tool that can help create and deploy microservices on Kubernetes.
Real-world #microservices with Apache Camel, Fabric8, and OpenShiftChristian Posta
What are and aren't microservices?
Microservices is a validation of the open-source approach to integration and service implementation and a rebuff of the committee-driven SOA approach. In this
Using apache camel for microservices and integration then deploying and managing on Docker and Kubernetes. When we need to make changes to our app, we can use Fabric8 continuous delivery built on top of Kubernetes and OpenShift.
Knative builds on Kubernetes and Istio to provide "PaaS-like abstractions" that raise the level of abstraction for specifying, running, and modifying applications. Knative includes building blocks like Knative Serving for autoscaling container workloads to zero, Knative Eventing for composing event-driven services, Knative Build for building containers from source, and Knative Pipelines for abstracting CI/CD pipelines. While Knative can run any type of container, its building blocks help enable serverless-style functions by allowing compute resources to scale to zero and be driven by event loads.
Topics covered:
1. Generating a new Remix project
2. Conventional files
3. Routes (including the nested variety)
4. Styling
5. Database interactions (via sqlite and prisma)
6. Mutations, Validation, and Authentication
7. Error handling
8. SEO with Meta Tags and much more
This document discusses integration in the age of DevOps. It describes how microservices help solve the problem of decoupling services and teams to move quickly at scale. Apache Camel is presented as a solution for integration that allows for reliable and distributed integration through mechanisms like messaging. Kubernetes and Docker are discussed as platforms that help develop and run microservices locally and at scale by providing automation, configuration, isolation and service discovery capabilities.
Service-mesh technology promises to deliver a lot of value to a cloud-native application, but it doesn't come without some hype. In this talk, we'll look at what is a "service mesh", how it compares to similar technology (Netflix OSS, API Management, ESBs, etc) and what options for service mesh exist today.
Evolution of integration and microservices patterns with service meshChristian Posta
Cloud-native describes a way of building applications on a cloud platform to iteratively discover and deliver business value. We now have access to a lot of similar technology that the large internet companies pioneered and used to their advantage to dominate their respective markets. What challenges arise when we start building applications to take advantage of this new technology?
In this mini-conference, we'll cover what it means to build applications with microservices, how cloud-native integration and concepts like service mesh have evolved to solve some of those problems, and how the next iteration of application development with Functions as a Service (FaaS) and serverless computing fit into this landscape.
You'll hear from industry experts Burr Sutter and Christian Posta who recently authored a book Introducing Istio Service Mesh for Microservices about these topics.
Attendees should come away from this mini-conference with the following:
Understanding of what cloud-native means and how to use it to influence positive business outcomes
How integration has evolved to create, connect and manage cloud-native APIs
How service-mesh technology like Istio can solve the challenges introduced with cloud-native applications
How the next iteration of applications deliver with FaaS and serverless computing fits in with a world of monoliths, microservices, and APIs
These talks will be of value for developers, architects, operators, platform directors, and technology leaders.
After the presentations, please stay and join Christian, Burr and your peers for networking, food and drinks. All attendees will also receive a copy of Christian and Burr's new book: Introducing Istio Service Mesh for Microservices.
Role of Integration and Service Mesh in Cloud Native Architecture KubeCon 2108Ballerina
Building useful services across our collection of existing applications, microservices, and now functions, we see a common theme: services must be able to communicate with each other, and solve problems like data mediation, routing, policy enforcement, security, and others. Service mesh is a technology that has emerged in container-based environments to help solve some of these problems; however, not all of them can be solved by pushing the problems to a different abstraction. Understanding the role and responsibility of service mesh and application-integration frameworks can help you successfully build useful business services on a cloud native platform. This talk will help you understand those roles and responsibilities and how service mesh and application integration co-exist to build cloud native applications.
Evolution of integration and microservices patterns with service meshJudy Breedlove
The document discusses the evolution of integration and microservice patterns with service mesh technologies like Istio. It describes how service meshes provide decentralized application networking infrastructure between services through a data plane and control plane. This includes features like advanced load balancing, traffic control, observability, and policy enforcement that help improve resilience, security, and reliability of distributed applications.
This document provides an overview of microservices from Christian Posta, a chief architect at Red Hat. It discusses what microservices are, reasons for using them, common microservices patterns and frameworks, decomposing monolithic applications into microservices, and ensuring resilience between services. The presentation also covers using Kubernetes and OpenShift for microservices and demonstrates sample applications.
Concurrency at Scale: Evolution to Micro-ServicesRandy Shoup
Most large-scale web companies have evolved their system architecture from a monolithic application and monolithic database to a set of loosely coupled micro-services. Using examples from Google, eBay, and KIXEYE, this talk outlines the pros and cons of these different stages of evolution, and makes practical suggestions about when and how other organizations should consider migrating to micro-services. It concludes with some more advanced implications of a micro-services architecture, including SLAs, cost-allocation, and vendor-customer relationships within the organization.
Early Draft: Service Mesh allows developers to focus on business logic while the crosscutting network data layer code is handled by the Service Mesh. This is a boon because this code can be tricky to implement and hard to test all of the edge cases. Service Mesh takes this a few steps further than AOP or Servlet Filters or custom language-specific frameworks because it works regardless of the underlying programming language being used which is great for polyglot development shops. Thus standardizing how these layers work, while allowing teams to pick the best tools or languages for the job at hand. Kubernetes and Istio Service Mesh automate best practices for DevSecOps needs like: failover, scale-out, scalability, health checks, circuit breakers, rate limiters, metrics, observability, avoiding cascading failure, disaster recovery, and traffic routing; supporting CI/CD and microservices architecture.
Istio’s ability to automate and maintaining zero trust networks is its most important feature. In the age of high-profile data breaches, security is paramount. Companies want to avoid major brand issues that impact the bottom line and shrink market capitalization in an instant. Istio allows a standard way to do mTLS and auto certificate rotation which helps prevent a breach and limits the blast radius if a breach occurs. Istio also takes the concern of mTLS from microservices deployments and makes it easy to use taking the burden off of application developers.
The evolution of micro services architecture. Mainframe, Midrange, Client Server, SOA. Best practices of microservices. Load balancing, BigData, design patterns. When and why to use microservices.
These are my summarized notes from all the microservices session I attended at QCon 2015. These sessions had tons of learning around how to scale microservices and avoid common pitfalls
The document discusses strategies for transitioning from monolithic architectures to microservice architectures. It outlines some of the challenges with maintaining large monolithic applications and reasons for modernizing, such as handling more data and needing faster changes. It then covers microservice design principles and best practices, including service decomposition, distributed systems strategies, and reactive design. Finally it introduces Lagom as a framework for building reactive microservices on the JVM and outlines its key components and development environment.
Bol.com Tech lab September 2017 - Microservices in action at the Dutch Nation...Bert Jan Schrijver
3 DevOps teams are building high tech big data web applications in a private cloud environment to support police work. These teams use microservices architectures, with separate front-end and back-end components developed independently but integrated via service discovery. Testing includes unit, integration, and load testing across feature branches in a continuous integration environment before production deployment. Future work includes improving zero downtime deployments, modularizing the front-end, and automating security testing.
Cloud-native Data: Every Microservice Needs a Cachecornelia davis
Presented at the Pivotal Toronto Users Group, March 2017
Cloud-native applications form the foundation for modern, cloud-scale digital solutions, and the patterns and practices for cloud-native at the app tier are becoming widely understood – statelessness, service discovery, circuit breakers and more. But little has changed in the data tier. Our modern apps are often connected to monolithic shared databases that have monolithic practices wrapped around them. As a result, the autonomy promised by moving to a microservices application architecture is compromised.
With lessons from the application tier to guide us, the industry is now figuring out what the cloud-native architectural patterns are at the data tier. Join us to explore some of these with Cornelia Davis, a five year Cloud Foundry veteran who is now focused on cloud-native data. As it happens, every microservice needs a cache and this evening will drill deep on that topic. She’ll cover a variety of caching patterns and use cases, and demonstrate how their use helps preserve the autonomy that is driving agile software delivery practices today.
JavaZone 2017 - Microservices in action at the Dutch National PoliceBert Jan Schrijver
3 DevOps teams at the Dutch National Police are building big data applications in a private cloud using microservices architecture. They develop independently but coordinate planning. Testing includes unit, integration, end-to-end, load, and mutation tests. Features are developed on branches and deployed continuously to test and production after sprints. Challenges include balancing security and performance for stateless services and preventing monolithic frontends. They aim to improve with zero downtime deployments, product teams, and automated security testing.
3 DevOps teams at the Dutch National Police are building big data applications in a private cloud using microservices architecture. They develop using techniques like continuous delivery, short feedback loops, and embrace of change. Challenges include balancing performance and security with stateless services, minimizing dependencies between teams, and preventing monolithic frontends. Future plans include zero downtime deployments, cross-functional product teams, and a modular frontend.
OpenValue meetup October 2017 - Microservices in action at the Dutch National...Bert Jan Schrijver
3 DevOps teams at the Dutch National Police are building big data applications in a private cloud using microservices architecture. They develop independently but coordinate planning. Testing includes unit, integration, end-to-end, load, and mutation tests. Features are developed on branches and merged/deployed continuously. Services register with Consul for service discovery. Challenges include balancing security and performance for stateless services and preventing monolithic frontends. Future plans include zero downtime deployments and cross-functional product teams.
From Monoliths to Services: Paying Your Technical DebtTechWell
This document discusses transitioning from monolithic applications to microservices and serverless architectures. It begins by defining technical debt and explaining how microservices can help pay it down incrementally. It then covers different architectural styles like monoliths and microservices. The rest of the document discusses moving to cloud infrastructure, breaking apart monolithic applications into independent services, communication between services, leveraging third-party services, and security considerations for microservices.
You know that adopting Continuous Delivery is key to a high-performance company. You’ve read the books and are ready to build microservices in the cloud. Great! Let’s go back to the principles and see how to apply them in a cloud native environment. What used to be about shipping code to static servers, is now about quickly creating decoupled pipelines for new services that are readily wired up into the platform, and everything is driven by code. This talk will give concrete guidance for a world where autonomous teams continuously deploy many independent services and containers into an infrastructure that is dynamically created via APIs. Release without staging environment, but with confidence.
Learn how to apply cloud native concepts to the delivery pipeline itself and how the concepts of continuous delivery need to be adjusted for microservices in the cloud. Hear real world examples, including how to QA in production.
Christian Posta is a principal middleware specialist and architect who has worked with large microservices architectures. He discusses why companies are moving to microservices and cloud platforms like Kubernetes and OpenShift. He covers characteristics of microservices like small autonomous teams and decentralized decision making. Posta also discusses breaking applications into independent services, shedding dependencies between teams, and using contracts and APIs for communication between services.
Dublin Microservice "Introduction to Service Meshes"Daniel Bryant
While service meshes may be the next "big thing" in microservices, the concept isn't new. Classical SOA attempted to implement similar technology for abstracting and managing all aspects of service-to-service communication, and this was often realized as the much-maligned Enterprise Service Bus (ESB). Several years ago similar technology emerged from the microservice innovators, including Airbnb (SmartStack for service discovery), Netflix (Prana integration sidecars), and Twitter (Finagle for extensible RPC), and these technologies have now converged into the service meshes we are currently seeing being deployed.
In this talk, Daniel Bryant will share with you what service meshes are, why they are (and sometimes are not) well-suited for microservice deployments, and how best to use a service mesh when you're deploying microservices. This presentation begins with a brief history of the development of service meshes, and the motivations of the unicorn organisations that developed them. From there, you'll learn about some of the currently available implementations that are targeting microservice deployments, such as Istio/Envoy, Linkerd, and NGINX Plus.
Microservices architecture is a very powerful way to build scalable systems optimized for speed of change. To do this, we need to build independent, autonomous services which by definition tend to minimize dependencies on other systems. One of the tenants of microservices, and a way to minimize dependencies, is “a service should own its own database”. Unfortunately this is a lot easier said than done. Why? Because: your data.
We’ve been dealing with data in information systems for 5 decades so isn’t this a solved problem? Yes and no. A lot of the lessons learned are still very relevant. Traditionally, we application developers have accepted the practice of using relational databases and relying on all of their safety guarantees without question. But as we build services architectures that span more than one database (by design, as with microservices), things get harder. If data about a customer changes in one database, how do we reconcile that with other databases (especially where the data storage may be heterogenous?).
For developers focused on the traditional enterprise, not only do we have to try to build fast-changing systems that are surrounded by legacy systems, the domains (finance, insurance, retail, etc) are incredibly complicated. Just copying with Netflix does for microservices may or may not be useful. So how do we develop and reason about the boundaries in our system to reduce complexity in the domain?
In this talk, we’ll explore these problems and see how Domain Driven Design helps grapple with the domain complexity. We’ll see how DDD concepts like Entities and Aggregates help reason about boundaries based on use cases and how transactions are affected. Once we can identify our transactional boundaries we can more carefully adjust our needs from the CAP theorem to scale out and achieve truly autonomous systems with strictly ordered eventual consistency. We’ll see how technologies like Apache Kafka, Apache Camel and Debezium.io can help build the backbone for these types of systems. We’ll even explore the details of a working example that brings all of this together.
Similar to The Hardest Part of Microservices: Calling Your Services (20)
Move Auth, Policy, and Resilience to the PlatformChristian Posta
Developer's time is the most crucial resource in an enterprise IT organization. Too much time is spent on undifferentiated heavy lifting and in the world of APIs and microservices much of that is spent on non-functional, cross-cutting networking requirements like security, observability, and resilience.
As organizations reconcile their DevOps practices into Platform Engineering, tools like Istio help alleviate developer pain. In this talk we dig into what that pain looks like, how much it costs, and how Istio has solved these concerns by examining three real-life use cases. As this space continues to emerge, and innovation has not slowed, we will also discuss the recently announced Istio sidecar-less mode which significantly reduces the hurdles to adopt Istio within Kubernetes or outside Kubernetes.
Comparing Sidecar-less Service Mesh from Cilium and IstioChristian Posta
Service mesh is a powerful pattern for implementing strong zero-trust networking practices, introducing better network observability, and allowing for more fine-grained traffic control. Up until now, the sidecar pattern was used to implement service-mesh capability but as the technology matures, a new pattern has emerged: sidecarless service mesh. Two prominent open-source networking projects, Cilium and Istio, have implemented a sidecar-free approach to service mesh but they both make interesting design decisions and tradeoffs. In this talk we review the architecture of both, focusing on the pros and cons of implementations such as mutual authentication, ingress, and observability.
Understanding Wireguard, TLS and Workload IdentityChristian Posta
Zero Trust Networking has become a standard marketing buzzword but the underlying principles are critical for modern microservice-style architectures. Authentication, authorizations, policy, etc. can be difficult to implement between services and do so in a maintainable way. Google invented their own transparent encryption and authorization protocol called "ALTS" back in 2007 to serve the application layer of Google's Borg workload scheduler, but we don't see others using it outside Google.
In this webinar we look at existing technology like TLS and newcomer Wireguard and see how these technologies come together to provide a secure foundation for workload identity and modern service-to-service networking.
Istio ambient mesh uses a sidecar-less data plane that focuses on ease of operations, incremental adoption, and separation of security boundaries for applications and mesh infrastructure.
In this webinar, we'll explore:
- The forces of modernization and compliance pressures,
- How Zero Trust Architecture (ZTA) can help, and
- How Istio ambient mesh lowers the barrier for establishing the properties necessary to achieve Zero Trust and compliance
The document discusses Cilium and Istio with Gloo Mesh. It provides an overview of Gloo Mesh, an enterprise service mesh for multi-cluster, cross-cluster and hybrid environments based on upstream Istio. Gloo Mesh focuses on ease of use, powerful best practices built in, security, and extensibility. It allows for consistent API for multi-cluster north-south and east-west policy, team tenancy with service mesh as a service, and driving everything through GitOps.
This document discusses service mesh patterns for connecting microservices across multiple clusters. It describes using Envoy proxy to provide service discovery, load balancing, security and resiliency. Patterns are presented for connecting services across clusters with flat, controlled or separate networks. Managing connectivity across clusters can increase operator burden. Gloo Mesh is presented as a way to simplify management across multiple clusters with a centralized control plane.
Multicluster Kubernetes and Service Mesh PatternsChristian Posta
Building applications for cloud-native infrastructure that are resilient, scalable, secure, and meet compliance and IT objectives gets complicated. Another wrinkle for the organizations with which we work is the fact they need to run across a hybrid deployment footprint, not just Kubernetes. At Solo.io, we build application networking technology on Envoy Proxy that helps solve difficult multi-deployment, multi-cluster, and even multi-mesh problems.
In this webinar, we’re going to explore different options and patterns for building secure, scalable, resilient applications using technology like Kubernetes and Service Mesh without leaving behind existing IT investments. We’ll see why and when to use multi-cluster topologies, how to build for high availability and team autonomy, and solve for things like service discovery, identity federation, traffic routing, and access control.
Cloud-Native Application Debugging with Envoy and Service MeshChristian Posta
Microservices have been great for accelerating the software innovation and delivery, but they also present new challenges, especially as abstractions and automated orchestration at every layer make pinpointing the issue seem like walking around a maze with a blindfold. Existing tools weren’t designed for distributed environments, and the new tools need to consider how to leverage these abstraction layers to better observe, test, and troubleshoot issues.
Christian Posta walks you through Envoy Proxy and service mesh architecture for L7 data plane, the key features in Envoy that can help in debugging and troubleshooting, chaos engineering as a testing methodology for microservices, how to approach a testing and debugging framework for microservices, and new open source tools that address these areas. You’ll explore a workflow to discover and resolve microservices issues, including injecting experiments for stress testing the applications, gathering requests in flight, recording and replaying them, and debugging them step by step without affecting production traffic.
Kubernetes Ingress to Service Mesh (and beyond!)Christian Posta
Kubernetes users need to allow traffic to flow into and within the cluster. Treating the application traffic separately from the business logic allows presents new possibilities in how service to service traffic is served, controlled and observed — and provides a transition to intra cluster networking like Service Mesh. With microservices, there is a concept of both North / South traffic (incoming requests from end users to the cluster) and East / West (intra cluster) communication between the services. In this talk we will explain how Envoy Proxy works in Kubernetes as a proxy for both of these traffic directions and how it can be leveraged to do things like traffic shaping, security, and integrate the north/south to east/west behavior.
Christian Posta (@christianposta) is Global Field CTO at Solo.io, former Chief Architect at Red Hat, and well known in the community for being an author (Istio in Action, Manning, Istio Service Mesh, O'Reilly 2018, Microservices for Java Developers, O’Reilly 2016), frequent blogger, speaker, open-source enthusiast and committer on various open-source projects including Istio, Kubernetes, and many others. Christian has spent time at both enterprises as well as web-scale companies and now helps companies create and deploy large-scale, cloud-native resilient, distributed architectures. He enjoys mentoring, training and leading teams to be successful with distributed systems concepts, microservices, devops, and cloud-native application design.
The exploration of service mesh for any organization comes with some serious questions. What data plane should I use? How does this tie in with my existing API infrastructure? What kind of overhead do sidecar proxies demand? As I've seen in my work with various organizations over the years "if you have a successful microservices deployment, then you have a service mesh whether it’s explicitly optimized as one or not."
In this talk, we seek to understand the role of the data plane and how to pick the right component for the problem context. We start off by establishing the spectrum of data-plane components from shared gateways to in-code libraries with service proxies being along that spectrum. We clearly identify which scenarios would benefit from which part of the data-plane spectrum and show how modern service meshes including Istio, Linkerd, and Consul enable these optimizations.
Deep Dive: Building external auth plugins for Gloo EnterpriseChristian Posta
Using the plugin framework for Ext. Auth Service in Gloo Enterprise, we can build any custom AuthN/AuthZ plugins to handle security requirements not provided out of the box.
Role of edge gateways in relation to service mesh adoptionChristian Posta
API Gateways provide functionality like rate limiting, authentication, request routing, reporting, and more. If you’ve been following the rise in service-mesh technologies, you’ll notice there is a lot of overlap with API Gateways when solving some of the challenges of microservices. If service mesh can solve these same problems, you may wonder whether you really need a dedicated API Gateway solution?
The reality is there is some nuance in the problems solved at the edge (API Gateway) compared to service-to-service communication (service mesh) within a cluster. But with the evolution of cluster-deployment patterns, these nuances are becoming less important. What’s more important is that the API Gateway is evolving to live at a layer above service mesh and not directly overlapping with it. In other words, API Gateways are evolving to solve application-level concerns like aggregation, transformation, and deeper context and content-based routing as well as fitting into a more self-service, GitOps style workflow.
In this talk we put aside the “API Gateway” infrastructure as we know it today and go back to first principles with the “API Gateway pattern” and revisit the real problems we’re trying to solve. Then we’ll discuss pros and cons of alternative ways to implement the API Gateway pattern and finally look at open source projects like Envoy, Kubernetes, and GraphQL to see how the “API Gateway pattern” actually becomes the API for our applications while coexisting nicely with a service mesh (if you adopt a service mesh).
Navigating the service mesh landscape with Istio, Consul Connect, and LinkerdChristian Posta
The document discusses various service mesh options including Linkerd, Consul Connect, Istio, and AWS App Mesh. It provides an overview of each solution, describing their key features and strengths/opportunities. It emphasizes that the service mesh approach is useful for managing inter-service communication and that implementations are still evolving. It recommends starting simply and iteratively adopting capabilities to match needs.
Distributed microservices introduce new challenges: failure modes are harder to anticipate and resolve. In this session, we present a “Chaos Debugging” framework enabled by three open source projects: Gloo Shot, Squash, and Loop to help you increase your microservices’ “immunity” to issues.
Gloo Shot integrates with any service mesh to implement advanced, realistic chaos experiments. Squash connects powerful and mature debuggers (gdb, dlv, java debugging) to your microservices while they run in Kubernetes. Loop extends the capability of your service mesh to observe your application and record full transactions for sandboxed replay and debugging.
Come to this demo-heavy talk to see how together, Squash, Gloo Shot, and Loop allow you to trigger, replay, and investigate failure modes of your microservices in a language agnostic and efficient manner without requiring any changes to your code.
Leveraging Envoy Proxy and GraphQL to Lower the Risk of Monolith to Microserv...Christian Posta
If you have an existing Java monolith, you know you must take care making changes to it or altering it in any negative way. Often times these monoliths are very valuable to the business and generate a lot of revenue. At the same time, since it’s difficult to make changes to the monolith it’s desirable to move to a microservices architecture. Unfortunately you cannot just do a big-bang migration to a greenfield architecture and will have to incrementally adopt microservices. In this talk, we’ll look at using Gloo proxy which is based on Envoy Proxy and GraphQL to do surgical, function-level traffic control and API aggregation to safely migrate your monolith to microservices and serverless functions.
Service-mesh options with Linkerd, Consul, Istio and AWS AppMeshChristian Posta
Service mesh abstracts the network from developers to solve three main pain points:
How do services communicate securely with one another
How can services implement network resilience
When things go wrong, can we identify what and why
Service mesh implementations usually follow a similar architecture: traffic flows through control points between services (usually service proxies deployed as sidecar processes) while an out-of-band set of nodes is responsible for defining the behavior and management of the control points. This loosely breaks out into an architecture of a "data plane" through which requests flow and a "control plane" for managing a service mesh.
Different service mesh implementations use different data planes depending on their use cases and familiarity with particular technology. The control plane implementations vary between service-mesh implementations as well. In this talk, we'll take a look at three different control plane implementations with Istio, Linkerd and Consul, their strengths, and their specific tradeoffs to see how they chose to solve each of the three pain points from above. We can use this information to make choices about a service mesh or to inform our journey if we choose to build a control plane ourselves.
The document summarizes the new features of Istio 1.1, an open-source service mesh. Some key highlights include improved performance and scalability, namespace isolation, multi-cluster capabilities, easier installation with Helm, and locality-aware load balancing. A new Sidecar resource was introduced to improve performance by configuring resources for individual proxies. The presentation demonstrates performance improvements with the Sidecar resource and highlights additional functionality in Istio like traffic control and metrics collection.
API Gateways are going through an identity crisisChristian Posta
API Gateways provide functionality like rate limiting, authentication, request routing, reporting, and more. If you've been following the rise in service-mesh technologies, you'll notice there is a lot of overlap with API Gateways when solving some of the challenges of microservices. If service mesh can solve these same problems, you may wonder whether you really need a dedicated API Gateway solution?
The reality is there is some nuance in the problems solved at the edge (API Gateway) compared to service-to-service communication (service mesh) within a cluster. But with the evolution of cluster-deployment patterns, these nuances are becoming less important. What's more important is that the API Gateway is evolving to live at a layer above service mesh and not directly overlapping with it. In other words, API Gateways are evolving to solve application-level concerns like aggregation, transformation, and deeper context and content-based routing as well as fitting into a more self-service, GitOps style workflow.
In this talk we put aside the "API Gateway" infrastructure as we know it today and go back to first principles with the "API Gateway pattern" and revisit the real problems we're trying to solve. Then we'll discuss pros and cons of alternative ways to implement the API Gateway pattern and finally look at open source projects like Envoy, Kubernetes, and GraphQL to see how the "API Gateway pattern" actually becomes the API for our applications while coexisting nicely with a service mesh (if you adopt a service mesh).
Responsibilities of Fleet Managers and How TrackoBit Can Assist.pdfTrackobit
What do fleet managers do? What are their duties, responsibilities, and challenges? And what makes a fleet manager effective and successful? This blog answers all these questions.
Lots of bloggers are using Google AdSense now. It’s getting really popular. With AdSense, bloggers can make money by showing ads on their websites. Read this important article written by the experienced designers of the best website designing company in Delhi –
React and Next.js are complementary tools in web development. React, a JavaScript library, specializes in building user interfaces with its component-based architecture and efficient state management. Next.js extends React by providing server-side rendering, routing, and other utilities, making it ideal for building SEO-friendly, high-performance web applications.
Sami provided a beginner-friendly introduction to Amazon Web Services (AWS), covering essential terms, products, and services for cloud deployment. Participants explored AWS' latest Gen AI offerings, making it accessible for those starting their cloud journey or integrating AI into coding practices.
Ansys Mechanical enables you to solve complex structural engineering problems and make better, faster design decisions. With the finite element analysis (FEA) solvers available in the suite, you can customize and automate solutions for your structural mechanics problems and parameterize them to analyze multiple design scenarios. Ansys Mechanical is a dynamic tool that has a complete range of analysis tools.
introduction of Ansys software and basic and advance knowledge of modelling s...sachin chaurasia
Ansys Mechanical enables you to solve complex structural engineering problems and make better, faster design decisions. With the finite element analysis (FEA) solvers available in the suite, you can customize and automate solutions for your structural mechanics problems and parameterize them to analyze multiple design scenarios. Ansys Mechanical is a dynamic tool that has a complete range of analysis tools.
In this talk, we will explore strategies to optimize the success rate of storing and retaining new information. We will discuss scientifically proven ideal learning intervals and content structures. Additionally, we will examine how to create an environment that improves our focus while you remain in the “flow”. Lastly we will also address the influence of AI on learning capabilities.
In the dynamic field of software development, this knowledge will empower you to accelerate your learning curve and support others in their learning journeys.
A captivating AI chatbot PowerPoint presentation is made with a striking backdrop in order to attract a wider audience. Select this template featuring several AI chatbot visuals to boost audience engagement and spontaneity. With the aid of this multi-colored template, you may make a compelling presentation and get extra bonuses. To easily elucidate your ideas, choose a typeface with vibrant colors. You can include your data regarding utilizing the chatbot methodology to the remaining half of the template.
Efficient hot work permit software for safe, streamlined work permit management and compliance. Enhance safety today. Contact us on +353 214536034.
https://sheqnetwork.com/work-permit/
Software development... for all? (keynote at ICSOFT'2024)miso_uam
Our world runs on software. It governs all major aspects of our life. It is an enabler for research and innovation, and is critical for business competitivity. Traditional software engineering techniques have achieved high effectiveness, but still may fall short on delivering software at the accelerated pace and with the increasing quality that future scenarios will require.
To attack this issue, some software paradigms raise the automation of software development via higher levels of abstraction through domain-specific languages (e.g., in model-driven engineering) and empowering non-professional developers with the possibility to build their own software (e.g., in low-code development approaches). In a software-demanding world, this is an attractive possibility, and perhaps -- paraphrasing Andy Warhol -- "in the future, everyone will be a developer for 15 minutes". However, to make this possible, methods are required to tweak languages to their context of use (crucial given the diversity of backgrounds and purposes), and the assistance to developers throughout the development process (especially critical for non-professionals).
In this keynote talk at ICSOFT'2024 I presented enabling techniques for this vision, supporting the creation of families of domain-specific languages, their adaptation to the usage context; and the augmentation of low-code environments with assistants and recommender systems to guide developers (professional or not) in the development process.
4. Christian Posta
Chief Architect, cloud application development
Twitter: @christianposta
Blog: http://blog.christianposta.com
Email: christian@redhat.com
Slides: http://slideshare.net/ceposta
• Author “Microservices for Java developers”
• Committer/contributor lots of open-source projects
• Worked with large Microservices, web-scale,
unicorn company
• Blogger, speaker
16. • Services shall be resilient when communicating
• Failures should not jump boundaries (no cascading failures)
• New releases should not impact production
• Mean time to recover should approach zero
• Security as a first-class citizen
• Policies to eliminate unexpected usage
Service principles
17. Have we had to solve for this in the past?
@christianposta
21. • Highly centralized == centralized governance
• Inadvertently scattered business logic away from business
apps/services
• Scalability issues?
• Not ideal for use in cloud environments
Some drawbacks to this approach?
25. • Require specific language to bring in new services
• A single language doesn’t fit for all use cases
• How do you patch/upgrade/manage lifecycle?
• Need strict control over application library choices
Some drawbacks to this approach?
27. But I’m using Vert.x!
• vertx-circuit-breaker
• vertx-service-discovery
• vertx-dropwizard-metrics
• vertx-zipkin?
• …..
• ......
@christianposta
28. Screw Java - I’m using NodeJS!
JavaScript is for rookies, I use Go!
But python is so pretty!
I prefer unreadability… Perl for me!
@christianposta
29. Things you must solve for because…
distributed systems
• Service discovery
• Retries
• Timeouts
• Load balancing
• Rate limiting
• Thread bulk heading
• Circuit breaking
@christianposta
30. …continued
• Routing between services (adaptive, zone-aware)
• Deadlines
• Back pressure
• Outlier detection
• Health checking
• Traffic shaping
• Request shadowing
@christianposta
33. Now we have …
• 30 different libraries for each of 5 languages, and each with 3
frameworks
• How do we maintain, upgrade, retire
• classpath/namespace pollution
• increases operational complexity
• force specific languages
• inconsistency
• correctness
34. These are all horizontal concerns
and apply to all services regardless
of implementation.
@christianposta
35. Let’s abstract this functionality to a single
binary and apply to all services.
• Allow heterogeneous architectures
• Remove application-specific implementations of this
functionality
• Consistently enforce these properties
• Correctly enforce these properties
• Opt-in as well as safety nets
@christianposta
39. Envoy is…
• service proxy
• written in C++, highly parallel, non-blocking
• L3/4 network filter
• out of the box L7 filters
• HTTP 2, including gRPC
• baked in service discovery/health checking
• advanced load balancing
• stats, metrics, tracing
• dynamic configuration through xDS
48. “2018 is the year of the service mesh”
Clayton Coleman (@smarterclayton)
Red Hat OpenShift Platform Architect
@christianposta
49. How do we reason about a fleet of
these service proxies in a large cluster?
@christianposta
50. A service mesh is decentralized application-
networking infrastructure between your services
that provides resiliency, security, observability,
and routing control.
A service mesh is comprised of a data plane
and control plane.
@christianposta
Time for definitions:
51. All traffic between our applications flows
through these proxies. The proxies make
up the “data plane”
@christianposta
58. Thanks!
BTW: Hand drawn diagrams made with Paper by FiftyThree.com
Twitter: @christianposta
Blog: http://blog.christianposta.com
Email: christian@redhat.com
Slides: http://slideshare.net/cepostaFollow up links:
• http://envoyproxy.io
• http://istio.io
• http://blog.christianposta.com/istio-workshop/slides/
• http://launch.openshift.io
• http://blog.openshift.com
• http://developers.redhat.com/blog
• https://www.redhat.com/en/open-innovation-labs
Editor's Notes
One large database!
We should focus on how we design our data models so that they can be sharded and distributed…. Focus on transactions, etc not 2PC
One large database!
We should focus on how we design our data models so that they can be sharded and distributed…. Focus on transactions, etc not 2PC
One large database!
We should focus on how we design our data models so that they can be sharded and distributed…. Focus on transactions, etc not 2PC
One large database!
We should focus on how we design our data models so that they can be sharded and distributed…. Focus on transactions, etc not 2PC
One large database!
We should focus on how we design our data models so that they can be sharded and distributed…. Focus on transactions, etc not 2PC
One large database!
We should focus on how we design our data models so that they can be sharded and distributed…. Focus on transactions, etc not 2PC
One large database!
We should focus on how we design our data models so that they can be sharded and distributed…. Focus on transactions, etc not 2PC
https://en.wikipedia.org/wiki/Fallacies_of_distributed_computing
The network is reliable.
Latency is zero.
Bandwidth is infinite.
The network is secure.
Topology doesn't change.
There is one administrator.
Transport cost is zero.
The network is homogeneous.
This concept of defining language, developing models to describe a domain, implementing those models, enforcing assertions, etc all happen within a certain context, and that context is vitally important in software. In common language, we are smart enough to resolve these types of language conflicts within a sentence because of its context. The computer doesn’t have this context. We have to make it explicit. And any context needs to have explicit boundaries.
This model needs to be “useful” ie, it should be able to be implemented. Try to establish a model that’s both useful for discussion with the domain experts and is implementable. There are infinite ways to model/think about something. Balance both masters with the model you choose.
Large complex domains may need multiple models. And really the only way to understand a language and model is within a certain context. That context should have boundaries so it doesn’t bleed or force others to bleed definitions and semantics.
Bounded context: within this space, this is the context of the language. This is what it means and it’s not ambiguous.
Central thing about a model is the language you create to express the prblem and solution very crisply. Need clear language and need boundaries.
Anti corruption layers are translations between the different models that may exist in multiple bounded contexts. They keep an internal model consistent and pure without bleeding across the boundaries.
Bounded contexts tend to be “self contained systems” themselves with a complete vertical stack of the software including UI, business logic, data models, and database. They tend to not share databases across multiple models.
This concept of defining language, developing models to describe a domain, implementing those models, enforcing assertions, etc all happen within a certain context, and that context is vitally important in software. In common language, we are smart enough to resolve these types of language conflicts within a sentence because of its context. The computer doesn’t have this context. We have to make it explicit. And any context needs to have explicit boundaries.
This model needs to be “useful” ie, it should be able to be implemented. Try to establish a model that’s both useful for discussion with the domain experts and is implementable. There are infinite ways to model/think about something. Balance both masters with the model you choose.
Large complex domains may need multiple models. And really the only way to understand a language and model is within a certain context. That context should have boundaries so it doesn’t bleed or force others to bleed definitions and semantics.
Bounded context: within this space, this is the context of the language. This is what it means and it’s not ambiguous.
Central thing about a model is the language you create to express the prblem and solution very crisply. Need clear language and need boundaries.
Anti corruption layers are translations between the different models that may exist in multiple bounded contexts. They keep an internal model consistent and pure without bleeding across the boundaries.
Bounded contexts tend to be “self contained systems” themselves with a complete vertical stack of the software including UI, business logic, data models, and database. They tend to not share databases across multiple models.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
This concept of defining language, developing models to describe a domain, implementing those models, enforcing assertions, etc all happen within a certain context, and that context is vitally important in software. In common language, we are smart enough to resolve these types of language conflicts within a sentence because of its context. The computer doesn’t have this context. We have to make it explicit. And any context needs to have explicit boundaries.
This model needs to be “useful” ie, it should be able to be implemented. Try to establish a model that’s both useful for discussion with the domain experts and is implementable. There are infinite ways to model/think about something. Balance both masters with the model you choose.
Large complex domains may need multiple models. And really the only way to understand a language and model is within a certain context. That context should have boundaries so it doesn’t bleed or force others to bleed definitions and semantics.
Bounded context: within this space, this is the context of the language. This is what it means and it’s not ambiguous.
Central thing about a model is the language you create to express the prblem and solution very crisply. Need clear language and need boundaries.
Anti corruption layers are translations between the different models that may exist in multiple bounded contexts. They keep an internal model consistent and pure without bleeding across the boundaries.
Bounded contexts tend to be “self contained systems” themselves with a complete vertical stack of the software including UI, business logic, data models, and database. They tend to not share databases across multiple models.
This concept of defining language, developing models to describe a domain, implementing those models, enforcing assertions, etc all happen within a certain context, and that context is vitally important in software. In common language, we are smart enough to resolve these types of language conflicts within a sentence because of its context. The computer doesn’t have this context. We have to make it explicit. And any context needs to have explicit boundaries.
This model needs to be “useful” ie, it should be able to be implemented. Try to establish a model that’s both useful for discussion with the domain experts and is implementable. There are infinite ways to model/think about something. Balance both masters with the model you choose.
Large complex domains may need multiple models. And really the only way to understand a language and model is within a certain context. That context should have boundaries so it doesn’t bleed or force others to bleed definitions and semantics.
Bounded context: within this space, this is the context of the language. This is what it means and it’s not ambiguous.
Central thing about a model is the language you create to express the prblem and solution very crisply. Need clear language and need boundaries.
Anti corruption layers are translations between the different models that may exist in multiple bounded contexts. They keep an internal model consistent and pure without bleeding across the boundaries.
Bounded contexts tend to be “self contained systems” themselves with a complete vertical stack of the software including UI, business logic, data models, and database. They tend to not share databases across multiple models.
This concept of defining language, developing models to describe a domain, implementing those models, enforcing assertions, etc all happen within a certain context, and that context is vitally important in software. In common language, we are smart enough to resolve these types of language conflicts within a sentence because of its context. The computer doesn’t have this context. We have to make it explicit. And any context needs to have explicit boundaries.
This model needs to be “useful” ie, it should be able to be implemented. Try to establish a model that’s both useful for discussion with the domain experts and is implementable. There are infinite ways to model/think about something. Balance both masters with the model you choose.
Large complex domains may need multiple models. And really the only way to understand a language and model is within a certain context. That context should have boundaries so it doesn’t bleed or force others to bleed definitions and semantics.
Bounded context: within this space, this is the context of the language. This is what it means and it’s not ambiguous.
Central thing about a model is the language you create to express the prblem and solution very crisply. Need clear language and need boundaries.
Anti corruption layers are translations between the different models that may exist in multiple bounded contexts. They keep an internal model consistent and pure without bleeding across the boundaries.
Bounded contexts tend to be “self contained systems” themselves with a complete vertical stack of the software including UI, business logic, data models, and database. They tend to not share databases across multiple models.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.
Get back to first principles.
Focus on principles, patterns, methodologies.
Tools will help, but you cannot start with tools.